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Risk factors for mortality in patients undergoing hemodialysis: A systematic review and meta-analysis
Risk factors for mortality in patients undergoing hemodialysis: A systematic review and meta-analysis Lijie Ma, Sumei Zhao PII: DOI: Reference:
S0167-5273(17)31125-7 doi:10.1016/j.ijcard.2017.02.095 IJCA 24621
To appear in:
International Journal of Cardiology
Received date: Revised date: Accepted date:
17 August 2016 6 January 2017 20 February 2017
Please cite this article as: Ma Lijie, Zhao Sumei, Risk factors for mortality in patients undergoing hemodialysis: A systematic review and meta-analysis, International Journal of Cardiology (2017), doi:10.1016/j.ijcard.2017.02.095
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ACCEPTED MANUSCRIPT Risk factors for mortality in patients undergoing hemodialysis: a systematic review and meta-analysis
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Lijie Ma, Sumei Zhao*
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Department of Nephrology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China *Corresponding author
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Sumei Zhao
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Department of Nephrology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
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Tel: +86-13681468505
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Grant support: None
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Email: [email protected]
Conflict of interest: All authors declared that they have no conflict of interest.
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Key words: Cardiac death; hemodialysis; meta-analysis; mortality; risk
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Abstract
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Background: No consensus exists regarding the factors influencing mortality in
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patients undergoing hemodialysis(HD). This meta-analysis aimed to evaluate the impact of various patient characteristics on the risk of mortality in such patients. Methods: PubMed, Embase, and Cochrane Central were searched for studies
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evaluating the risk factors for mortality in patients undergoing HD. The factors
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included age, gender, diabetes mellitus(DM), body mass index (BMI), previous cardiovascular disease (CVD), HD duration, hemoglobin, albumin, white blood cell,
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C-reactive protein (CRP), parathyroid hormone, total iron binding capacity (TIBC),
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iron, ln ferritin, adiponectin, apolipoprotein A1 (ApoA1), ApoA2, ApoA3,
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high-density lipoprotein (HDL), total cholesterol, hemoglobin A1c (HbA1c), serum phosphate, troponin T (TnT), and B-type natriuretic peptide (BNP). Relative risks
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with 95% confidence intervals were derived. Data were synthesized using the random-effects model. Results: Age (per 1-year increment), DM, previous CVD, CRP (higher versus lower), ln ferritin, adiponectin (per 10.0 µg/mL increment), HbA1c (higher versus lower), TnT, and BNP were associated with an increased risk of all-cause mortality. BMI (per 1 kg/m2 increment), hemoglobin (per 1 d/dL increment), albumin (higher versus lower), TIBC, iron, ApoA2, and ApoA3 were associated with reduced risk of all-cause mortality. Age (per 1-year increment), gender (women versus men), DM, previous CVD, HD duration, ln ferritin, HDL, and HbA1c (higher versus lower) significantly 2
ACCEPTED MANUSCRIPT increased the risk of cardiac death. Albumin (higher versus lower), TIBC, and ApoA2 had a beneficial impact on the risk of cardiac death.
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Conclusions: Multiple markers and factors influence the risk of mortality and cardiac
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death in patients undergoing HD.
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ACCEPTED MANUSCRIPT 1. Introduction Cardiovascular disease (CVD) is the most common cause of death in patients
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undergoing hemodialysis (HD), and vascular calcification is a proven risk factor [1].
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The risk of vascular calcification corresponds with the deterioration of renal function and is highest in end-stage renal disease (ESRD) [2]. Despite the continuing progress in hemodialysis therapy, the mortality rate of patients undergoing maintenance
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dialysis is unacceptably high. The reason for this could be a disturbance in mineral
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metabolism, calcium-based therapies, or chronic inflammation in a uremic milieu. Also, the active process of osteogenesis in vascular smooth muscle cells might
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influence the risk of vascular calcification [3, 4]. Previous studies suggested the use of
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serum albumin, serum creatinine, body mass index (BMI), and normalized protein
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catabolic rate (nPCR) to assess the nutritional status of patients with chronic kidney diseases [5-7]. Furthermore, several studies indicated that these factors were
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associated with the risk of mortality in patients undergoing HD [8-10]. However, data on the effect of several patient characteristics on subsequent all-cause mortality and cardiac death are both limited and inconclusive. Several studies have indicated that hematologic indexes may influence the risk of mortality. Ishii et al indicated that per 1 d/dL increment in hemoglobin was associated with a reduced risk of all-cause mortality [8], whereas Park et al showed no association between hemoglobin and the risk of mortality [9]. The risk factors for mortality in patients undergoing HD have not been definitively determined. This
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ACCEPTED MANUSCRIPT meta-analysis attempted a large-scale examination of the available studies to
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determine the risk factors for mortality in patients undergoing HD.
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2. Methods
A meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement [11].
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2.1 Search strategy
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Any study that examined the risk factors for mortality or cardiac death in patients undergoing HD was eligible for inclusion in the present meta-analysis. No restrictions
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were placed on language or publication status (published, in press, or in progress).
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PubMed, Embase, and Cochrane Central electronic databases were searched for
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articles published through July 2016, using ((("Renal Dialysis"[Mesh] OR "Dialysis"[Mesh] OR "Peritoneal Dialysis"[Mesh] OR "Kidneys, Artificial"[Mesh] "Hemodialysis,
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((("Calcium"[Mesh]
Home"[Mesh])
OR
AND
"Phosphates"[Mesh]
Clinical OR
Trial[ptyp]))
"Phosphorus"[Mesh]
AND OR
"Prealbumin"[Mesh] OR "Creatinine"[Mesh] OR "Albumins"[Mesh] OR "Serum Albumin"[Mesh] OR "Parathyroid Hormone"[Mesh] OR "Hemoglobins"[Mesh] OR "Triglycerides"[Mesh] OR "Cholesterol"[Mesh] OR "Cholesterol, LDL"[Mesh] OR "Cholesterol, HDL"[Mesh] OR "Body Mass Index"[Mesh] OR "C-Reactive Protein"[Mesh])) AND Clinical Trial[ptyp])as the search terms. Manual searches of reference lists from all the relevant original and review articles were also conducted to identify additional eligible studies. The medical subject heading, methods, patient 5
ACCEPTED MANUSCRIPT population, design, factors, and outcome variables of these articles were used to identify the relevant studies.
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2.2 Selection Criteria
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The literature search was independently undertaken by two authors using a standardized approach. Any inconsistencies between these two authors were settled by the primary author until a consensus was reached. The study was eligible for
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inclusion if the following criteria were met: (1) the study included patients undergoing
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HD; (2) the study included at least one of the following factors: age, gender, diabetes mellitus (DM), BMI, previous cardiovascular disease (CVD), duration of HD,
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hemoglobin, albumin, white blood cell (WBC), C-reaction protein (CRP), parathyroid
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hormone (PTH), total iron binding capacity (TIBC), iron, ln ferritin, adiponectin,
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apolipoprotein A1 (ApoA1), ApoA2, ApoA3, HDL, total cholesterol (TC), hemoglobin A1c (HbA1c), serum phosphate, troponin T (TnT), and B-type natriuretic
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peptide (BNP); and (3) the study compared these factors with corresponding controls (the lowest indexes or per unit increment of indexes). Additionally, reviews, editorials, nonhuman studies, letters, and conference papers were excluded because of insufficient data. 2.3 Data Collection and Quality Assessment The data included the first author name, publication year, country, sample size, mean age at baseline, percentage of male patients, previous coronary artery disease (PCAD), BMI, duration of HD, percentage of smokers, follow-up duration, reported endpoints, and covariates in the fully adjusted model. For studies that reported several 6
ACCEPTED MANUSCRIPT multivariable adjusted relative risks (RRs), the effect estimate that was maximally adjusted for potential confounders was selected.
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The NewcastleOttawa Scale (NOS) [12], which is quite comprehensive and has been
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partially validated for evaluating the quality of observational studies in meta-analyses, was used to evaluate methodological quality. The NOS is based on the following three subscales: selection (four items), comparability (one item), and outcome (three items).
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A “star system” (range, 0–9) was developed for assessment (Table S1). The data
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extraction and quality assessment were conducted independently by two authors. Information was examined and adjudicated independently by an additional author
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2.4 Statistical analysis
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referring to the original studies.
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The risk factors were examined on the basis of the effect estimate (odds ratio, RR, or hazard ratio) and its 95% confidence interval (CI) published in each study. The
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random-effects model [13] was used to calculate summary RRs and 95% CIs for the higher versus lower factor levels. Heterogeneity between studies was investigated using the Q statistic, and P values <0.10 were considered as indicative of significant heterogeneity [14]. A sensitivity analysis was also performed by removing each individual study from the meta-analysis. At the stages of planning, we intended to conduct a stratified analysis for cardiac death in different countries whereas few studies have reported the risk factors for cardiac death in HD patients. Therefore, we just conducted a subgroup analysis for total mortality based on country (Western Countries and Eastern Countries) if the results included 6 or more subsets. All 7
ACCEPTED MANUSCRIPT reported P values were two-sided, and P values <0.05 were considered statistically significant for all included studies. Statistical analyses were performed using STATA
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software (version 12.0; Stata Corporation, TX, USA).
3. Results 3.1 Literature search
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In this study, 1789 articles were retrieved from PubMed, 3330 from Embase, and 994
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from the Cochrane Central. After removing duplicates, 47 articles were identified for inclusion in the meta-analysis. A total of 6066 articles were excluded because they
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were determined not relevant after scanning titles and abstracts. Furthermore, articles
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found to be unrelated based on full-text assessment (4), affiliate studies (9), and
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undesired outcome studies (11) were also excluded. Finally, 23 studies assessing 86,915 patients undergoing HD were included in the present systematic review (Fig. 1)
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[8-10, 15-34].
3.2 Study characteristics Of the 23 included studies, the follow-up duration for patients undergoing HD was 1.310.0 years, while 5035, 655 patients were included in each study. Eleven studies were conducted in Asia [8, 9, 15, 18, 21-26, 33], four in the USA or Australia [10, 19, 32, 34], seven in Europe [16, 20, 27-31], and the remaining one in
other countries.
All included studies reported all-cause mortality, and nine studies reported cardiac death. Study quality was assessed using the NOS (Table 1). A study with a score ≥7 was considered as being of high quality. Overall, 6 studies had a score of 8 [8, 16, 18, 8
ACCEPTED MANUSCRIPT 21, 23, 26], 10 studies had a score of 7 [9, 10, 17, 20, 22, 24, 29, 31, 32, 34], and the remaining 7 studies had a score of 6 [15, 19, 25, 27, 28, 30, 33].
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3.3 Risk factors for all-cause mortality in patients undergoing HD
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As shown in Figure 2, the summary RR showed that age (per 1-year increment) (RR: 1.05; 95% CI: 1.041.07; P< 0.001), DM (RR: 2.00; 95% CI: 1.692.35; P< 0.001), previous CVD (RR: 1.41; 95% CI: 1.131.76; P = 0.002), higher levels of CRP (RR:
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1.37; 95% CI: 1.181.59; P< 0.001), ln ferritin (RR: 1.67; 95% CI: 1.172.38; P =
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0.005), adiponectin (per 10.0 µg/mL increment) (RR: 1.23; 95% CI: 1.081.41; P = 0.002), higher levels of HbA1c (RR: 3.60; 95% CI: 1.578.27; P = 0.003), TnT (RR:
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3.57; 95% CI: 2.245.69; P< 0.001), BNP (RR: 1.99; 95% CI: 1.352.94; P = 0.001)
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were associated with a statistically significant increase in the risk of mortality in
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patients undergoing HD compared with controls. Although substantial heterogeneity was found in age, DM, previous CVD, CRP, and ln ferritin, sensitivity analyses were
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conducted and the conclusion was not affected by the exclusion of any specific study. The pooled RR suggested that BMI (per 1 kg/m2 increment) (RR: 0.95; 95% CI: 0.910.99; P = 0.007), hemoglobin (per 1 d/dL increment) (RR: 0.95; 95% CI: 0.900.99; P = 0.012), higher levels of albumin (RR: 0.52; 95% CI: 0.410.67; P< 0.001), TIBC (RR: 0.99; 95% CI: 0.991.00; P = 0.001), iron (RR: 0.99; 95% CI: 0.991.00; P = 0.013), ApoA2 (RR: 0.63; 95% CI: 0.490.80; P< 0.001), and ApoA3 (RR: 0.78; 95% CI: 0.610.98; P = 0.040) were associated with a lower risk of all-cause mortality in patients undergoing HD. Although substantial heterogeneity was observed in the magnitude of effect across the studies for BMI and albumin, the 9
ACCEPTED MANUSCRIPT conclusion was not affected by the exclusion of any specific study from the pooled analysis. Finally, gender (women versus men), duration of hemodialysis, WBC, PTH,
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ApoA1, HDL, TC, and serum phosphate had no significant impact on all-cause
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mortality.
3.4 Risk factors for cardiac death in patients undergoing HD As shown in Figure 3, the pooled analysis results for cardiac death indicated that age
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(per 1-year increment) (RR: 1.04; 95% CI: 1.021.06; P< 0.001), gender (women
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versus men) (RR: 1.41; 95% CI: 1.111.80; P = 0.005), DM (RR: 2.11; 95% CI: 1.552.86; P< 0.001), previous CVD (RR: 2.53; 95% CI: 1.165.55; P = 0.020),
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duration of hemodialysis (RR: 5.77; 95% CI: 1.9414.37; P = 0.001), higher levels of
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ln ferritin (RR: 1.34; 95% CI: 1.041.72; P = 0.025), HDL (RR: 1.08; 95% CI:
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1.001.16; P = 0.043), and HbA1c (RR: 6.66; 95% CI: 1.5129.40; P = 0.012) exerted a harmful effect. Heterogeneity was observed in the magnitude of effect
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across the trials for age and previous CVD. However, after sequential exclusion of each study from the pooled analyses, the conclusion was not affected. In addition, higher levels of albumin (RR: 0.43; 95% CI: 0.340.55; P< 0.001), TIBC (RR: 0.99; 95% CI: 0.991.00; P = 0.009), and ApoA2 (RR: 0.64; 95% CI: 0.450.93; P = 0.016) were associated with reduced risk of cardiac death compared with the lowest categories, and no significant heterogeneity was observed. Finally, BMI, hemoglobin, WBC, CRP, PTH, iron, ApoA1, ApoA3, and TC had no significant impact on the risk of cardiac death in patients undergoing HD. 3.5 Subgroup analysis for total mortality 10
ACCEPTED MANUSCRIPT The results of subgroup analyses for total mortality in Western and Eastern Counties are presented in Table 2. We noted most results were consistent with overall analysis,
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whereas the following outcomes reported significant differences between Western and
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Eastern Countries. First, patients with CVD previously in Western Countries was not associated with the risk of total mortality (RR: 1.22; 95%CI: 0.92-1.63; P=0.166), whereas increased the risk of total mortality in Eastern Countries (RR: 1.62; 95%CI:
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1.14-2.30; P=0.007). Second, hemoglobin (per 1 d/dL increment) in Western
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Countries was associated with a lower risk of total mortality (RR: 0.93; 95%CI: 0.89-0.98; P=0.004), but without significant impact in Eastern countries (RR: 0.95;
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95%CI: 0.89-1.02; P=0.148). Finally, according to the P value between subgroups, we
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noted patients in different countries might affected the risk of total mortality for age
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4. Discussion
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(per 1 year increment), BMI (per 1 kg/m2 increment), and CRP (high versus low).
The present study was based on observational studies and explored the risk factors for all-cause mortality or cardiac death in patients undergoing HD. This large quantitative study included 86,915 individuals from 23 studies. The findings suggested that age (per 1-year increment), DM, previous CVD, ln ferritin, and HbA1c (higher versus lower) had a significant harmful impact on the risk of all-cause mortality and cardiac death. Furthermore, CRP (higher versus lower), adiponectin (per 10.0 µg/mL increment), TnT, and BNP significantly increased the risk of all-cause mortality whereas they had no significant impact on the risk of cardiac death. Similarly, gender 11
ACCEPTED MANUSCRIPT (women versus men), duration of HD, and level of HDL were associated with an increased risk of cardiac death, but they had no effect on the risk of all-cause mortality.
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Conversely, albumin (higher versus lower), TIBC, and ApoA2 significantly reduced
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the risk of all-cause mortality and cardiac death. Furthermore, BMI (per 1 kg/m 2 increment), hemoglobin (per 1 d/dL increment), iron, and ApoA3 were associated with a lower risk of all-cause mortality, but they had little or no effect on the risk of
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cardiac death.
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Previous meta-analyses have illustrated several factors influencing mortality in patients undergoing HD. Palmer et al suggested that depression in patients undergoing
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HD was associated with an increased risk of all-cause mortality, whereas it had
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minimal effects on cardiac death [35]. Fabrizi et al indicated that anti-HCV-positive
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patients on dialysis had an increased risk of either liver or cardiac mortality compared with anti-HCV-negative patients [36]. Pilz et al suggested that increased 25(OH)D
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levels were associated with significantly improved survival in patients with chronic kidney disease [37]. However, previous studies have not investigated several important characteristics of patients undergoing HD. Therefore, this comprehensive systematic review and meta-analysis was conducted to evaluate the risk factors for mortality and cardiac death in patients undergoing HD. In this study, age (per 1-year increment), patients with DM, previous CVD, higher levels of ln ferritin, and HbA1c were regarded as the risk factors in patients undergoing HD. Patients with DM, previous CVD, or higher HbA1c were associated with an increased risk of cardiovascular events and all-cause mortality or cardiac 12
ACCEPTED MANUSCRIPT death. Serum ferritin is widely accepted as a marker of iron storage in patients with chronic kidney disease [38]. Although a significant association between ferritin and
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the risk of mortality in patients undergoing HD was observed, whether this
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relationship was attributed to systemic inflammation and nutritional factors needed further investigation. Furthermore, varying dialysis vintage in patients undergoing HD might affect this correlation. The aforementioned factors influenced the risk of
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mortality in patients undergoing HD. Although CRP, adiponectin, TnT, and BNP were
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also detected and considered as risk factors for all-cause mortality, these conclusions might be unreliable because a small number of studies reported such indexes. In
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addition, the duration of HD and HDL level might influence cardiac death, since these
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factors were associated with the risk of cardiovascular disease. Finally, potential
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gender-based differences in cardiac death were found among patients undergoing HD. Female patients undergoing HD had a higher risk of cardiac death compared with
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male patients undergoing HD. Further large-scale studies are required to verify this gender-based difference. In this study, higher levels of albumin, TIBC, and ApoA2 were considered as protective factors that reduced the risk of all-cause mortality and cardiac death. The level of albumin was regarded as a cardiovascular biomarker significantly associated with all-cause mortality and cardiac death. Furthermore, although significant differences were detected for TIBC and ApoA2, these conclusions might vary because a few studies reported such indexes. Furthermore, increased BMI, hemoglobin, iron, and ApoA3 were associated with a reduced risk of all-cause mortality, but they did not 13
ACCEPTED MANUSCRIPT affect cardiac death. This might be because higher BMI and hemoglobin might serve as risk factors for cardiovascular disease, balancing the potential beneficial impact on
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cardiac death.
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Subgroup analysis was conducted aiming at the total mortality in different countries. We have noted significant heterogeneity between subgroups with the indexes of age (per 1 year increment), BMI (per 1 kg/m2 increment), and CRP (high versus low).
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Further, patients with CVD previously was not affected total mortality in Western
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Countries, and per 1 d/dL increment in hemoglobin has no significant effect on total mortality in Eastern countries. Due to the higher contribution in total mortality of
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CVD [1], and prevalence of CVD might be various in different races and ethnicities
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[39], which might affected the incidence of total mortality in patients indirectly in
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different countries. Furthermore, the conclusions may be variable since smaller number of studies were included in such subsets. Therefore, the risk factors for total
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mortality in HD patients in these subsets should be verified in future larger scale prospective studies. Two strengths of this study should be highlighted. First, the large sample size allowed us to quantitatively assess the risk factors for mortality in patients undergoing HD. Thus, the present findings were potentially more robust compared with those of any individual study. Second, most factors investigated in this study were not explored in previous meta-analyses. The limitations of this study were as follows: (1) the adjusted models were different across the included studies, and these factors might influence the risk of mortality; (2) 14
ACCEPTED MANUSCRIPT At the stages of planning, stratified analysis for cardiac death in different countries should be conducted, whereas few studies reported the risk factors on cardiac death in
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HD patients; (3) data on different races and ethnicities were not available, we
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therefore conducted subgroup analysis in different countries to provide relative results; (4) different disease statuses might affect the incidence of total mortality and cardiac death; (5) in a meta-analysis of published studies, publication bias was an inevitable
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problem; and (6) the meta-analysis used pooled data (individual data were not
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available), which restricted the authors from performing a more detailed relevant analysis and obtaining more comprehensive results.
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In conclusion, this study indicated that multiple factors affected the mortality in
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patients undergoing HD. However, data supporting this conclusion for several indexes
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are insufficient. Furthermore, race and ethnicity difference on the risk of cardiac death in HD patients should be conducted. Hence, further large-scale studies are needed to
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verify the findings.
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Acknowledgement
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None
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Author contribution
Lijie Ma contributed to study concept, manuscript preparation and drafting the manuscript.Sumei Zhao contributed to data collection, data analysis and revising the
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approval of the version to be published.
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manuscript critically for important intellectual content.All authors have given final
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References
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[1] Verbeke F, Van Biesen W, Honkanen E, et al. Prognostic value of aortic stiffness
SC R
and calcification for cardiovascular events and mortality in dialysis patients: outcome of the calcification outcome in renal disease (CORD) study. Clin J Am Soc Nephrol. 2011;6:153-9.
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[2] Temmar M, Liabeuf S, Renard C, et al. Pulse wave velocity and vascular
MA
calcification at different stages of chronic kidney disease. J Hypertens. 2010;28:163-9.
D
[3] Owen WF, Jr., Lew NL, Liu Y, Lowrie EG, Lazarus JM. The urea reduction ratio
TE
and serum albumin concentration as predictors of mortality in patients undergoing
CE P
hemodialysis. N Engl J Med. 1993;329:1001-6. [4] Combe C, Chauveau P, Laville M, et al. Influence of nutritional factors and
AC
hemodialysis adequacy on the survival of 1,610 French patients. Am J Kidney Dis. 2001;37:S81-8.
[5] Lowrie EG, Huang WH, Lew NL. Death risk predictors among peritoneal dialysis and hemodialysis patients: a preliminary comparison. Am J Kidney Dis. 1995;26:220-8. [6] Kalantar-Zadeh K, Kopple JD. Relative contributions of nutrition and inflammation to clinical outcome in dialysis patients. Am J Kidney Dis. 2001;38:1343-50. [7] Pifer TB, McCullough KP, Port FK, et al. Mortality risk in hemodialysis patients 17
ACCEPTED MANUSCRIPT and changes in nutritional indicators: DOPPS. Kidney Int. 2002;62:2238-45. [8] Ishii J, Takahashi H, Kitagawa F, et al. Multimarker approach to risk stratification
IP
T
for long-term mortality in patients on chronic hemodialysis. Circ J. 2015;79:656-63.
SC R
[9] Park KS, Ryu GW, Jhee JH, et al. Serum Ferritin Predicts Mortality Regardless of Inflammatory and Nutritional Status in Patients Starting Dialysis: A Prospective Cohort Study. Blood Purif. 2015;40:209-17.
NU
[10] Rhee CM, Nguyen DV, Moradi H, et al. Association of Adiponectin With Body
MA
Composition and Mortality in Hemodialysis Patients. Am J Kidney Dis. 2015;66:313-21.
D
[11] Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items
CE P
2010;8:336-41.
TE
for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg.
[12] Wells G, Shea B, O'Connell D. The Newcastle-Ottawa Scale (NOS) for assessing
AC
the quality of nonrandomised studies in meta-analyses. [13] Ades AE, Lu G, Higgins JP. The interpretation of random-effects meta-analysis in decision models. Med Decis Making. 2005;25:646-54. [14] Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557-60. [15] Mathew S, Abraham G, Vijayan M, et al. Body composition monitoring and nutrition in maintenance hemodialysis and CAPD patients--a multicenter longitudinal study. Ren Fail. 2015;37:66-72. [16] Silbernagel G, Genser B, Drechsler C, et al. HDL cholesterol, apolipoproteins, 18
ACCEPTED MANUSCRIPT and cardiovascular risk in hemodialysis patients. J Am Soc Nephrol. 2015;26:484-92. [17] Tentori F, Wang M, Bieber BA, et al. Recent changes in therapeutic approaches
IP
T
and association with outcomes among patients with secondary hyperparathyroidism
SC R
on chronic hemodialysis: the DOPPS study. Clin J Am Soc Nephrol. 2015;10:98-109. [18] Chen HY, Chiu YL, Chuang YF, et al. Visceral adiposity index and risks of cardiovascular events and mortality in prevalent hemodialysis patients. Cardiovasc
NU
Diabetol. 2014;13:136.
MA
[19] Moradi H, Streja E, Kashyap ML, Vaziri ND, Fonarow GC, Kalantar-Zadeh K. Elevated high-density lipoprotein cholesterol and cardiovascular mortality in
D
maintenance hemodialysis patients. Nephrol Dial Transplant. 2014;29:1554-62.
TE
[20] Joao Matias P, Azevedo A, Laranjinha I, et al. Lower serum magnesium is
CE P
associated with cardiovascular risk factors and mortality in haemodialysis patients. Blood Purif. 2014;38:244-52.
AC
[21] Kim CH, Kim SJ, Lee MJ, et al. LDL cholesterol affects clinical outcomes in incident hemodialysis patients during the early stages of dialysis. Blood Purif. 2014;38:131-9.
[22] Kuragano T, Matsumura O, Matsuda A, et al. Association between hemoglobin variability, serum ferritin levels, and adverse events/mortality in maintenance hemodialysis patients. Kidney Int. 2014;86:845-54. [23] Ok ES, Asci G, Toz H, et al. Glycated hemoglobin predicts overall and cardiovascular mortality in non-diabetic hemodialysis patients. Clin Nephrol. 2014;82:173-80. 19
ACCEPTED MANUSCRIPT [24] Prasad N, Sinha A, Gupta A, et al. Effect of body mass index on outcomes of peritoneal dialysis patients in India. Perit Dial Int. 2014;34:399-408.
IP
T
[25] Turkmen K, Guney I, Yazici R, Arslan S, Altintepe L, Yeksan M. Health-related
SC R
quality of life, depression and mortality in peritoneal dialysis patients in Turkey: seven-year experience of a center. Ren Fail. 2014;36:859-64.
[26] Chang TI, Oh HJ, Kang EW, et al. A low serum bicarbonate concentration as a
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risk factor for mortality in peritoneal dialysis patients. PLoS One. 2013;8:e82912.
MA
[27] Cuevas X, Garcia F, Martin-Malo A, et al. Risk factors associated with cardiovascular morbidity and mortality in Spanish incident hemodialysis patients:
D
two-year results from the ANSWER study. Blood Purif. 2012;33:21-9.
TE
[28] Yoo HH, Martin LC, Kochi AC, et al. Could albumin level explain the higher
2012;13:80.
CE P
mortality in hemodialysis patients with pulmonary hypertension? BMC Nephrol.
AC
[29] Wagner M, Ansell D, Kent DM, et al. Predicting mortality in incident dialysis patients: an analysis of the United Kingdom Renal Registry. Am J Kidney Dis. 2011;57:894-902.
[30] Antunes AA, Delatim Vannini F, de Arruda Silveira LV, Martin LC, Barretti P, Caramori JC. Influence of protein intake and muscle mass on survival in chronic dialysis patients. Ren Fail. 2010;32:1055-9. [31] de Mutsert R, Grootendorst DC, Indemans F, et al. Association between serum albumin and mortality in dialysis patients is partly explained by inflammation, and not by malnutrition. J Ren Nutr. 2009;19:127-35. 20
ACCEPTED MANUSCRIPT [32] Habib AN, Baird BC, Leypoldt JK, Cheung AK, Goldfarb-Rumyantzev AS. The association of lipid levels with mortality in patients on chronic peritoneal dialysis.
IP
T
Nephrol Dial Transplant. 2006;21:2881-92.
SC R
[33] Iseki K, Yamazato M, Tozawa M, Takishita S. Hypocholesterolemia is a significant predictor of death in a cohort of chronic hemodialysis patients. Kidney Int. 2002;61:1887-93.
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[34] Herzig KA, Purdie DM, Chang W, et al. Is C-reactive protein a useful predictor
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of outcome in peritoneal dialysis patients? J Am Soc Nephrol. 2001;12:814-21. [35] Palmer SC, Vecchio M, Craig JC, et al. Association between depression and
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2013;62:493-505.
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death in people with CKD: a meta-analysis of cohort studies. Am J Kidney Dis.
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[36] Fabrizi F, Dixit V, Messa P. Impact of hepatitis C on survival in dialysis patients: a link with cardiovascular mortality? J Viral Hepat. 2012;19:601-7.
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[37] Pilz S, Iodice S, Zittermann A, Grant WB, Gandini S. Vitamin D status and mortality risk in CKD: a meta-analysis of prospective studies. Am J Kidney Dis. 2011;58:374-82.
[38] Fernandez-Rodriguez AM, Guindeo-Casasus MC, Molero-Labarta T, et al. Diagnosis of iron deficiency in chronic renal failure. Am J Kidney Dis. 1999;34:508-13. [39] Liu L. Using Multivariate Quantile Regression Analysis to Explore Cardiovascular Risk Differences in Subjects with Chronic Kidney Disease by Race and Ethnicity: Findings from the U.S. Chronic Renal Insufficiency Cohort Study// 21
ACCEPTED MANUSCRIPT Formulation and Analytical Development for Low-Dose Oral Drug Products. John
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Country
Sample size
Mean age
Percentage male (%)
PCAD (%)
BMI
Duration of Smoking hemodialysis (%) (year)
Follow-up duration (year)
Reported outcomes
Adjusted factors
NOS score
Ishii 2015[8]
Japan
516
60.0
59.9
33.3
20.6
5.5
28.8
10.0
All-cause mortality and cardiac death
Age, diabetes, BMI, PCAD, hemoglobin, and albumin
8
Mathew 2015 [15]
India
99
55.3
78.8
NA
22.2
NA
NA
2.0
All-cause mortality
BMI, overhydration, and fat tissue index
6
Park 2015[9]
Korea
946
60.0
61.4
13.7
23.2
NA
NA
3.3
All-cause mortality and cardiac death
Age, sex, DM, BMI, albumin, TIBC, and iron
7
Rhee 2015[10]
USA
501
55.1
56.5
26.4
3.5
36.1
1.3
All-cause mortality
Age, sex, race, ethnicity, dialysis vintage, diabetes, serum albumin level, total iron-binding capacity, serum creatinine level, white blood cell count, phosphorus
7
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Table 1. Baseline characteristics of studies included in the systematic review and meta-analysis
NA
23
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Germany
1255
66.3
53.9
29.4
28.0
Tentori 2014[17]
Multicenter
35655
62.8
58.3
42.6
25.2
Chen 2014[18]
China
464
60.0
49.0
8.3
40.4
3.9
All-cause mortality and cardiac death
Multivariate Andersen–Gill model
8
2.7
NA
1.6
All-cause mortality
Patient age, sex, BMI, time on dialysis, catheter use, comorbidities, albumin, hemoglobin, creatinine, facility percentage of patients with catheter use, percentage of patients having albumin 3.5 g/dL, and mean hemoglobin
7
3.6
NA
4.2
All-cause mortality
Gender, age, HD vintage, presence of DM, HTN and
8
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US
Silbernagel 2015[16]
CR
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level, hemoglobin level, and normalized protein catabolic rate
23.0
22.7
24
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US
33109
60.0
55.0
7.0
27.5
Matias 2014[20]
Portugal
206
63.6
55.0
28.0
Kim 2014[21]
Korea
867
57.6
59.5
Kuragano 2014 [22]
Japan
1095
61.8
60.3
Ok 2014[23]
Turkey
489
57.6
NA
NA
3.0
All-cause mortality and cardiac death
Gender, age, HD vintage, presence of DM, race, primary insurance, and comorbidities
6
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Moradi 2014[19]
US
CR
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concurrent CV disease, hemoglobin, iPTH, hs-CRP, calcium phosphate product, and GNRI levels
3.5
NA
2.0
All-cause mortality and cardiac death
Age, DM, time on HD, CRP, PP, LVMI, and SVCS
7
13.7
23.3
NA
43.2
1.9
All-cause mortality
Age, gender, DM, and pre-existing CVD
8
NA
21.7
8.8
NA
2.0
All-cause mortality
Sex, age, etiology, and albumin, CRP, and intact parathyroid hormone levels.
7
19.0
23.2
4.0
NA
3.0
All-cause mortality
Age, history of CVD, BMI, albumin,
8
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NA
53.3
25
India
328
52.6
73.8
15.9
21.9
Turkmen 2014 [25]
Turkey
63
52.9
67.4
NA
26.7
Chang 2013 [26]
Korea
441
59.2
54.4
15.9
Cuevas 2012 [27]
Spain
2310
NA
NA
NA
and cardiac death
hemoglobin, fasting blood glucose, hs-CRP, and ESA dose
NA
1.7
All-cause mortality
Age, subjective global assessment, comorbidities, albumin, diabetes, and residual glomerular filtration rate
7
1.7
NA
7.0
All-cause mortality
NA
6
22.8
NA
NA
2.9
All-cause mortality and cardiac death
Age, diabetes, CAD, serum albumin, ferritin, CRP, residual glomerular filtration rate, peritoneal Kt/V urea, nPCR, and percentage of lean body mass
8
NA
NA
NA
2.0
All-cause mortality and cardiac
Alcohol consumption; chronic kidney disease etiology,
6
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US
Prasad 2014[24]
CR
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NA
26
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dyslipidemia, previous cardiac arrhythmia, left ventricular hypertrophy, systolic blood pressure before HD session; hemodialysis technique, dialysis time, glucose, potassium, iPTH, phosphorus-binding drugs, cardiovascular drugs, and hypolipidemic drugs
Brazil
75
56.2
60.0
Wagner 2011[29]
UK
5447
64.0
61.4
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Yoo 2012[28]
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MA N
US
CR
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death
NA
24.6
NA
NA
6.0
All-cause mortality
Crude
6
33.1
25.0
NA
NA
3.0
All-cause mortality
Start-year of dialysis, Townsend score, change in treatment modality within the first 3 months of dialysis treatment, phosphate, and ferritin
7
27
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Brazil
79
60.0
60.7
NA
24.1
4.8
NA
3.2
All-cause mortality
Age, gender, time on dialysis, diabetes, dialysis modality, and CRP
6
Mutsert 2009[31]
The Netherlands
700
59.1
60.5
NA
24.7
NA
NA
2.0
All-cause mortality
SGA, subjective global assessment of nutritional status
7
Habib 2006[32]
US
1053
57.2
52.0
35.0
25.5
NA
NA
2.0
All-cause mortality and cardiac death
Age, gender, race, weight, height, primary cause of ESRD, hemoglobin, serum albumin, serum calcium phosphate product, serum bicarbonate, residual kidney creatinine clearance, pharmacodynamic parameters, use of lipid-modifying medications, and comorbidity characteristics
7
Iseki 2002[33]
Japan
1167
52.6
58.3
NA
NA
5.2
NA
10.0
All-cause mortality
Baseline characteristics
6
Herzig
Australia
50
58.6
30.0
30.0
25.4
2.1
34.0
3.0
All-cause
DM, previous CVD,
7
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US
CR
IP
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Antunes 2010 [30]
28
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mortality
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US
CR
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2001[34]
29
CCr, previous smoking, residual renal function, Kt/V, pre-albumin, and albumin
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Age (per 1 year Country increment) Western Countries
1.05 (1.03-1.07)
<0.001
1.06 (1.04-1.08)
<0.001
<0.001
0.012
Western Countries
2.08 (1.36-3.20)
0.001
0.024
Eastern Countries
2.00 (1.68-2.40)
<0.001
0.083
0.65 (0.54-0.79)
<0.001
0.347
0.040
0.108
0.97 (0.74-1.27) 0.92 (0.74-1.14)
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Eastern Countries
0.827 0.444
0.090
Western Countries
1.22 (0.92-1.63)
0.166
0.020
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Country
0.97 (0.95-1.00)
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Eastern Countries
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Country
BMI (per 1 Country kg/m2 increment) Western Countries
Previous CVD
P value for P value between heterogeneity subgroups
0.010
Gender (women Country vs men) Western Countries
DM vs non-DM
P value
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Eastern Countries
RR and 95%CI
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Factors
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Table 2. Subgroup analysis based on country for total mortality
1.62 (1.14-2.30)
0.007
0.017
0.93 (0.89-0.98)
0.004
0.594
Eastern Countries
0.95 (0.89-1.02)
0.148
0.156
0.52 (0.35-0.76)
0.001
<0.001
0.52 (0.38-0.72)
<0.001
<0.001
1.68 (1.33-2.11)
<0.001
0.746
1.25 (1.06-1.46)
0.006
<0.001
Eastern Countries
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Hemoglobin (per Country 1 d/dl increment) Western Countries
Albumin (high Country versus low) Western Countries Eastern Countries CRP (high versus Country low) Western Countries Eastern Countries
30
0.022
0.422
0.545
<0.001
0.056
0.523
0.456
<0.001
ACCEPTED MANUSCRIPT Figure legends Figure 1.Flow diagram of the literature search and trial selection process.
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Figure 2. Factors influencing the risk of all-cause mortality in patients undergoing
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HD.
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Figure 3. Factors influencing the risk of cardiac death in patients undergoing HD.
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Fig. 1
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S0167-5273(17)31125-7 doi:10.1016/j.ijcard.2017.02.095 IJCA 24621
To appear in:
International Journal of Cardiology
Received date: Revised date: Accepted date:
17 August 2016 6 January 2017 20 February 2017
Please cite this article as: Ma Lijie, Zhao Sumei, Risk factors for mortality in patients undergoing hemodialysis: A systematic review and meta-analysis, International Journal of Cardiology (2017), doi:10.1016/j.ijcard.2017.02.095
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Risk factors for mortality in patients undergoing hemodialysis: a systematic review and meta-analysis
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Lijie Ma, Sumei Zhao*
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Department of Nephrology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China *Corresponding author
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Sumei Zhao
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Department of Nephrology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
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Tel: +86-13681468505
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Grant support: None
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Email: [email protected]
Conflict of interest: All authors declared that they have no conflict of interest.
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Key words: Cardiac death; hemodialysis; meta-analysis; mortality; risk
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Abstract
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Background: No consensus exists regarding the factors influencing mortality in
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patients undergoing hemodialysis(HD). This meta-analysis aimed to evaluate the impact of various patient characteristics on the risk of mortality in such patients. Methods: PubMed, Embase, and Cochrane Central were searched for studies
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evaluating the risk factors for mortality in patients undergoing HD. The factors
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included age, gender, diabetes mellitus(DM), body mass index (BMI), previous cardiovascular disease (CVD), HD duration, hemoglobin, albumin, white blood cell,
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C-reactive protein (CRP), parathyroid hormone, total iron binding capacity (TIBC),
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iron, ln ferritin, adiponectin, apolipoprotein A1 (ApoA1), ApoA2, ApoA3,
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high-density lipoprotein (HDL), total cholesterol, hemoglobin A1c (HbA1c), serum phosphate, troponin T (TnT), and B-type natriuretic peptide (BNP). Relative risks
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with 95% confidence intervals were derived. Data were synthesized using the random-effects model. Results: Age (per 1-year increment), DM, previous CVD, CRP (higher versus lower), ln ferritin, adiponectin (per 10.0 µg/mL increment), HbA1c (higher versus lower), TnT, and BNP were associated with an increased risk of all-cause mortality. BMI (per 1 kg/m2 increment), hemoglobin (per 1 d/dL increment), albumin (higher versus lower), TIBC, iron, ApoA2, and ApoA3 were associated with reduced risk of all-cause mortality. Age (per 1-year increment), gender (women versus men), DM, previous CVD, HD duration, ln ferritin, HDL, and HbA1c (higher versus lower) significantly 2
ACCEPTED MANUSCRIPT increased the risk of cardiac death. Albumin (higher versus lower), TIBC, and ApoA2 had a beneficial impact on the risk of cardiac death.
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Conclusions: Multiple markers and factors influence the risk of mortality and cardiac
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death in patients undergoing HD.
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ACCEPTED MANUSCRIPT 1. Introduction Cardiovascular disease (CVD) is the most common cause of death in patients
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undergoing hemodialysis (HD), and vascular calcification is a proven risk factor [1].
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The risk of vascular calcification corresponds with the deterioration of renal function and is highest in end-stage renal disease (ESRD) [2]. Despite the continuing progress in hemodialysis therapy, the mortality rate of patients undergoing maintenance
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dialysis is unacceptably high. The reason for this could be a disturbance in mineral
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metabolism, calcium-based therapies, or chronic inflammation in a uremic milieu. Also, the active process of osteogenesis in vascular smooth muscle cells might
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influence the risk of vascular calcification [3, 4]. Previous studies suggested the use of
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serum albumin, serum creatinine, body mass index (BMI), and normalized protein
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catabolic rate (nPCR) to assess the nutritional status of patients with chronic kidney diseases [5-7]. Furthermore, several studies indicated that these factors were
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associated with the risk of mortality in patients undergoing HD [8-10]. However, data on the effect of several patient characteristics on subsequent all-cause mortality and cardiac death are both limited and inconclusive. Several studies have indicated that hematologic indexes may influence the risk of mortality. Ishii et al indicated that per 1 d/dL increment in hemoglobin was associated with a reduced risk of all-cause mortality [8], whereas Park et al showed no association between hemoglobin and the risk of mortality [9]. The risk factors for mortality in patients undergoing HD have not been definitively determined. This
4
ACCEPTED MANUSCRIPT meta-analysis attempted a large-scale examination of the available studies to
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determine the risk factors for mortality in patients undergoing HD.
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2. Methods
A meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement [11].
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2.1 Search strategy
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Any study that examined the risk factors for mortality or cardiac death in patients undergoing HD was eligible for inclusion in the present meta-analysis. No restrictions
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were placed on language or publication status (published, in press, or in progress).
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PubMed, Embase, and Cochrane Central electronic databases were searched for
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articles published through July 2016, using ((("Renal Dialysis"[Mesh] OR "Dialysis"[Mesh] OR "Peritoneal Dialysis"[Mesh] OR "Kidneys, Artificial"[Mesh] "Hemodialysis,
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OR
((("Calcium"[Mesh]
Home"[Mesh])
OR
AND
"Phosphates"[Mesh]
Clinical OR
Trial[ptyp]))
"Phosphorus"[Mesh]
AND OR
"Prealbumin"[Mesh] OR "Creatinine"[Mesh] OR "Albumins"[Mesh] OR "Serum Albumin"[Mesh] OR "Parathyroid Hormone"[Mesh] OR "Hemoglobins"[Mesh] OR "Triglycerides"[Mesh] OR "Cholesterol"[Mesh] OR "Cholesterol, LDL"[Mesh] OR "Cholesterol, HDL"[Mesh] OR "Body Mass Index"[Mesh] OR "C-Reactive Protein"[Mesh])) AND Clinical Trial[ptyp])as the search terms. Manual searches of reference lists from all the relevant original and review articles were also conducted to identify additional eligible studies. The medical subject heading, methods, patient 5
ACCEPTED MANUSCRIPT population, design, factors, and outcome variables of these articles were used to identify the relevant studies.
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2.2 Selection Criteria
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The literature search was independently undertaken by two authors using a standardized approach. Any inconsistencies between these two authors were settled by the primary author until a consensus was reached. The study was eligible for
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inclusion if the following criteria were met: (1) the study included patients undergoing
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HD; (2) the study included at least one of the following factors: age, gender, diabetes mellitus (DM), BMI, previous cardiovascular disease (CVD), duration of HD,
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hemoglobin, albumin, white blood cell (WBC), C-reaction protein (CRP), parathyroid
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hormone (PTH), total iron binding capacity (TIBC), iron, ln ferritin, adiponectin,
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apolipoprotein A1 (ApoA1), ApoA2, ApoA3, HDL, total cholesterol (TC), hemoglobin A1c (HbA1c), serum phosphate, troponin T (TnT), and B-type natriuretic
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peptide (BNP); and (3) the study compared these factors with corresponding controls (the lowest indexes or per unit increment of indexes). Additionally, reviews, editorials, nonhuman studies, letters, and conference papers were excluded because of insufficient data. 2.3 Data Collection and Quality Assessment The data included the first author name, publication year, country, sample size, mean age at baseline, percentage of male patients, previous coronary artery disease (PCAD), BMI, duration of HD, percentage of smokers, follow-up duration, reported endpoints, and covariates in the fully adjusted model. For studies that reported several 6
ACCEPTED MANUSCRIPT multivariable adjusted relative risks (RRs), the effect estimate that was maximally adjusted for potential confounders was selected.
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The NewcastleOttawa Scale (NOS) [12], which is quite comprehensive and has been
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partially validated for evaluating the quality of observational studies in meta-analyses, was used to evaluate methodological quality. The NOS is based on the following three subscales: selection (four items), comparability (one item), and outcome (three items).
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A “star system” (range, 0–9) was developed for assessment (Table S1). The data
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extraction and quality assessment were conducted independently by two authors. Information was examined and adjudicated independently by an additional author
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2.4 Statistical analysis
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referring to the original studies.
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The risk factors were examined on the basis of the effect estimate (odds ratio, RR, or hazard ratio) and its 95% confidence interval (CI) published in each study. The
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random-effects model [13] was used to calculate summary RRs and 95% CIs for the higher versus lower factor levels. Heterogeneity between studies was investigated using the Q statistic, and P values <0.10 were considered as indicative of significant heterogeneity [14]. A sensitivity analysis was also performed by removing each individual study from the meta-analysis. At the stages of planning, we intended to conduct a stratified analysis for cardiac death in different countries whereas few studies have reported the risk factors for cardiac death in HD patients. Therefore, we just conducted a subgroup analysis for total mortality based on country (Western Countries and Eastern Countries) if the results included 6 or more subsets. All 7
ACCEPTED MANUSCRIPT reported P values were two-sided, and P values <0.05 were considered statistically significant for all included studies. Statistical analyses were performed using STATA
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software (version 12.0; Stata Corporation, TX, USA).
3. Results 3.1 Literature search
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In this study, 1789 articles were retrieved from PubMed, 3330 from Embase, and 994
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from the Cochrane Central. After removing duplicates, 47 articles were identified for inclusion in the meta-analysis. A total of 6066 articles were excluded because they
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were determined not relevant after scanning titles and abstracts. Furthermore, articles
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found to be unrelated based on full-text assessment (4), affiliate studies (9), and
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undesired outcome studies (11) were also excluded. Finally, 23 studies assessing 86,915 patients undergoing HD were included in the present systematic review (Fig. 1)
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[8-10, 15-34].
3.2 Study characteristics Of the 23 included studies, the follow-up duration for patients undergoing HD was 1.310.0 years, while 5035, 655 patients were included in each study. Eleven studies were conducted in Asia [8, 9, 15, 18, 21-26, 33], four in the USA or Australia [10, 19, 32, 34], seven in Europe [16, 20, 27-31], and the remaining one in
other countries.
All included studies reported all-cause mortality, and nine studies reported cardiac death. Study quality was assessed using the NOS (Table 1). A study with a score ≥7 was considered as being of high quality. Overall, 6 studies had a score of 8 [8, 16, 18, 8
ACCEPTED MANUSCRIPT 21, 23, 26], 10 studies had a score of 7 [9, 10, 17, 20, 22, 24, 29, 31, 32, 34], and the remaining 7 studies had a score of 6 [15, 19, 25, 27, 28, 30, 33].
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3.3 Risk factors for all-cause mortality in patients undergoing HD
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As shown in Figure 2, the summary RR showed that age (per 1-year increment) (RR: 1.05; 95% CI: 1.041.07; P< 0.001), DM (RR: 2.00; 95% CI: 1.692.35; P< 0.001), previous CVD (RR: 1.41; 95% CI: 1.131.76; P = 0.002), higher levels of CRP (RR:
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1.37; 95% CI: 1.181.59; P< 0.001), ln ferritin (RR: 1.67; 95% CI: 1.172.38; P =
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0.005), adiponectin (per 10.0 µg/mL increment) (RR: 1.23; 95% CI: 1.081.41; P = 0.002), higher levels of HbA1c (RR: 3.60; 95% CI: 1.578.27; P = 0.003), TnT (RR:
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3.57; 95% CI: 2.245.69; P< 0.001), BNP (RR: 1.99; 95% CI: 1.352.94; P = 0.001)
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were associated with a statistically significant increase in the risk of mortality in
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patients undergoing HD compared with controls. Although substantial heterogeneity was found in age, DM, previous CVD, CRP, and ln ferritin, sensitivity analyses were
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conducted and the conclusion was not affected by the exclusion of any specific study. The pooled RR suggested that BMI (per 1 kg/m2 increment) (RR: 0.95; 95% CI: 0.910.99; P = 0.007), hemoglobin (per 1 d/dL increment) (RR: 0.95; 95% CI: 0.900.99; P = 0.012), higher levels of albumin (RR: 0.52; 95% CI: 0.410.67; P< 0.001), TIBC (RR: 0.99; 95% CI: 0.991.00; P = 0.001), iron (RR: 0.99; 95% CI: 0.991.00; P = 0.013), ApoA2 (RR: 0.63; 95% CI: 0.490.80; P< 0.001), and ApoA3 (RR: 0.78; 95% CI: 0.610.98; P = 0.040) were associated with a lower risk of all-cause mortality in patients undergoing HD. Although substantial heterogeneity was observed in the magnitude of effect across the studies for BMI and albumin, the 9
ACCEPTED MANUSCRIPT conclusion was not affected by the exclusion of any specific study from the pooled analysis. Finally, gender (women versus men), duration of hemodialysis, WBC, PTH,
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ApoA1, HDL, TC, and serum phosphate had no significant impact on all-cause
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mortality.
3.4 Risk factors for cardiac death in patients undergoing HD As shown in Figure 3, the pooled analysis results for cardiac death indicated that age
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(per 1-year increment) (RR: 1.04; 95% CI: 1.021.06; P< 0.001), gender (women
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versus men) (RR: 1.41; 95% CI: 1.111.80; P = 0.005), DM (RR: 2.11; 95% CI: 1.552.86; P< 0.001), previous CVD (RR: 2.53; 95% CI: 1.165.55; P = 0.020),
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duration of hemodialysis (RR: 5.77; 95% CI: 1.9414.37; P = 0.001), higher levels of
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ln ferritin (RR: 1.34; 95% CI: 1.041.72; P = 0.025), HDL (RR: 1.08; 95% CI:
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1.001.16; P = 0.043), and HbA1c (RR: 6.66; 95% CI: 1.5129.40; P = 0.012) exerted a harmful effect. Heterogeneity was observed in the magnitude of effect
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across the trials for age and previous CVD. However, after sequential exclusion of each study from the pooled analyses, the conclusion was not affected. In addition, higher levels of albumin (RR: 0.43; 95% CI: 0.340.55; P< 0.001), TIBC (RR: 0.99; 95% CI: 0.991.00; P = 0.009), and ApoA2 (RR: 0.64; 95% CI: 0.450.93; P = 0.016) were associated with reduced risk of cardiac death compared with the lowest categories, and no significant heterogeneity was observed. Finally, BMI, hemoglobin, WBC, CRP, PTH, iron, ApoA1, ApoA3, and TC had no significant impact on the risk of cardiac death in patients undergoing HD. 3.5 Subgroup analysis for total mortality 10
ACCEPTED MANUSCRIPT The results of subgroup analyses for total mortality in Western and Eastern Counties are presented in Table 2. We noted most results were consistent with overall analysis,
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whereas the following outcomes reported significant differences between Western and
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Eastern Countries. First, patients with CVD previously in Western Countries was not associated with the risk of total mortality (RR: 1.22; 95%CI: 0.92-1.63; P=0.166), whereas increased the risk of total mortality in Eastern Countries (RR: 1.62; 95%CI:
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1.14-2.30; P=0.007). Second, hemoglobin (per 1 d/dL increment) in Western
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Countries was associated with a lower risk of total mortality (RR: 0.93; 95%CI: 0.89-0.98; P=0.004), but without significant impact in Eastern countries (RR: 0.95;
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95%CI: 0.89-1.02; P=0.148). Finally, according to the P value between subgroups, we
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noted patients in different countries might affected the risk of total mortality for age
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4. Discussion
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(per 1 year increment), BMI (per 1 kg/m2 increment), and CRP (high versus low).
The present study was based on observational studies and explored the risk factors for all-cause mortality or cardiac death in patients undergoing HD. This large quantitative study included 86,915 individuals from 23 studies. The findings suggested that age (per 1-year increment), DM, previous CVD, ln ferritin, and HbA1c (higher versus lower) had a significant harmful impact on the risk of all-cause mortality and cardiac death. Furthermore, CRP (higher versus lower), adiponectin (per 10.0 µg/mL increment), TnT, and BNP significantly increased the risk of all-cause mortality whereas they had no significant impact on the risk of cardiac death. Similarly, gender 11
ACCEPTED MANUSCRIPT (women versus men), duration of HD, and level of HDL were associated with an increased risk of cardiac death, but they had no effect on the risk of all-cause mortality.
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Conversely, albumin (higher versus lower), TIBC, and ApoA2 significantly reduced
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the risk of all-cause mortality and cardiac death. Furthermore, BMI (per 1 kg/m 2 increment), hemoglobin (per 1 d/dL increment), iron, and ApoA3 were associated with a lower risk of all-cause mortality, but they had little or no effect on the risk of
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cardiac death.
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Previous meta-analyses have illustrated several factors influencing mortality in patients undergoing HD. Palmer et al suggested that depression in patients undergoing
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HD was associated with an increased risk of all-cause mortality, whereas it had
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minimal effects on cardiac death [35]. Fabrizi et al indicated that anti-HCV-positive
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patients on dialysis had an increased risk of either liver or cardiac mortality compared with anti-HCV-negative patients [36]. Pilz et al suggested that increased 25(OH)D
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levels were associated with significantly improved survival in patients with chronic kidney disease [37]. However, previous studies have not investigated several important characteristics of patients undergoing HD. Therefore, this comprehensive systematic review and meta-analysis was conducted to evaluate the risk factors for mortality and cardiac death in patients undergoing HD. In this study, age (per 1-year increment), patients with DM, previous CVD, higher levels of ln ferritin, and HbA1c were regarded as the risk factors in patients undergoing HD. Patients with DM, previous CVD, or higher HbA1c were associated with an increased risk of cardiovascular events and all-cause mortality or cardiac 12
ACCEPTED MANUSCRIPT death. Serum ferritin is widely accepted as a marker of iron storage in patients with chronic kidney disease [38]. Although a significant association between ferritin and
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the risk of mortality in patients undergoing HD was observed, whether this
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relationship was attributed to systemic inflammation and nutritional factors needed further investigation. Furthermore, varying dialysis vintage in patients undergoing HD might affect this correlation. The aforementioned factors influenced the risk of
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mortality in patients undergoing HD. Although CRP, adiponectin, TnT, and BNP were
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also detected and considered as risk factors for all-cause mortality, these conclusions might be unreliable because a small number of studies reported such indexes. In
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addition, the duration of HD and HDL level might influence cardiac death, since these
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factors were associated with the risk of cardiovascular disease. Finally, potential
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gender-based differences in cardiac death were found among patients undergoing HD. Female patients undergoing HD had a higher risk of cardiac death compared with
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male patients undergoing HD. Further large-scale studies are required to verify this gender-based difference. In this study, higher levels of albumin, TIBC, and ApoA2 were considered as protective factors that reduced the risk of all-cause mortality and cardiac death. The level of albumin was regarded as a cardiovascular biomarker significantly associated with all-cause mortality and cardiac death. Furthermore, although significant differences were detected for TIBC and ApoA2, these conclusions might vary because a few studies reported such indexes. Furthermore, increased BMI, hemoglobin, iron, and ApoA3 were associated with a reduced risk of all-cause mortality, but they did not 13
ACCEPTED MANUSCRIPT affect cardiac death. This might be because higher BMI and hemoglobin might serve as risk factors for cardiovascular disease, balancing the potential beneficial impact on
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cardiac death.
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Subgroup analysis was conducted aiming at the total mortality in different countries. We have noted significant heterogeneity between subgroups with the indexes of age (per 1 year increment), BMI (per 1 kg/m2 increment), and CRP (high versus low).
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Further, patients with CVD previously was not affected total mortality in Western
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Countries, and per 1 d/dL increment in hemoglobin has no significant effect on total mortality in Eastern countries. Due to the higher contribution in total mortality of
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CVD [1], and prevalence of CVD might be various in different races and ethnicities
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[39], which might affected the incidence of total mortality in patients indirectly in
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different countries. Furthermore, the conclusions may be variable since smaller number of studies were included in such subsets. Therefore, the risk factors for total
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mortality in HD patients in these subsets should be verified in future larger scale prospective studies. Two strengths of this study should be highlighted. First, the large sample size allowed us to quantitatively assess the risk factors for mortality in patients undergoing HD. Thus, the present findings were potentially more robust compared with those of any individual study. Second, most factors investigated in this study were not explored in previous meta-analyses. The limitations of this study were as follows: (1) the adjusted models were different across the included studies, and these factors might influence the risk of mortality; (2) 14
ACCEPTED MANUSCRIPT At the stages of planning, stratified analysis for cardiac death in different countries should be conducted, whereas few studies reported the risk factors on cardiac death in
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HD patients; (3) data on different races and ethnicities were not available, we
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therefore conducted subgroup analysis in different countries to provide relative results; (4) different disease statuses might affect the incidence of total mortality and cardiac death; (5) in a meta-analysis of published studies, publication bias was an inevitable
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problem; and (6) the meta-analysis used pooled data (individual data were not
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available), which restricted the authors from performing a more detailed relevant analysis and obtaining more comprehensive results.
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In conclusion, this study indicated that multiple factors affected the mortality in
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patients undergoing HD. However, data supporting this conclusion for several indexes
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are insufficient. Furthermore, race and ethnicity difference on the risk of cardiac death in HD patients should be conducted. Hence, further large-scale studies are needed to
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verify the findings.
15
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Acknowledgement
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None
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Author contribution
Lijie Ma contributed to study concept, manuscript preparation and drafting the manuscript.Sumei Zhao contributed to data collection, data analysis and revising the
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approval of the version to be published.
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manuscript critically for important intellectual content.All authors have given final
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References
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[1] Verbeke F, Van Biesen W, Honkanen E, et al. Prognostic value of aortic stiffness
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and calcification for cardiovascular events and mortality in dialysis patients: outcome of the calcification outcome in renal disease (CORD) study. Clin J Am Soc Nephrol. 2011;6:153-9.
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[2] Temmar M, Liabeuf S, Renard C, et al. Pulse wave velocity and vascular
MA
calcification at different stages of chronic kidney disease. J Hypertens. 2010;28:163-9.
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[3] Owen WF, Jr., Lew NL, Liu Y, Lowrie EG, Lazarus JM. The urea reduction ratio
TE
and serum albumin concentration as predictors of mortality in patients undergoing
CE P
hemodialysis. N Engl J Med. 1993;329:1001-6. [4] Combe C, Chauveau P, Laville M, et al. Influence of nutritional factors and
AC
hemodialysis adequacy on the survival of 1,610 French patients. Am J Kidney Dis. 2001;37:S81-8.
[5] Lowrie EG, Huang WH, Lew NL. Death risk predictors among peritoneal dialysis and hemodialysis patients: a preliminary comparison. Am J Kidney Dis. 1995;26:220-8. [6] Kalantar-Zadeh K, Kopple JD. Relative contributions of nutrition and inflammation to clinical outcome in dialysis patients. Am J Kidney Dis. 2001;38:1343-50. [7] Pifer TB, McCullough KP, Port FK, et al. Mortality risk in hemodialysis patients 17
ACCEPTED MANUSCRIPT and changes in nutritional indicators: DOPPS. Kidney Int. 2002;62:2238-45. [8] Ishii J, Takahashi H, Kitagawa F, et al. Multimarker approach to risk stratification
IP
T
for long-term mortality in patients on chronic hemodialysis. Circ J. 2015;79:656-63.
SC R
[9] Park KS, Ryu GW, Jhee JH, et al. Serum Ferritin Predicts Mortality Regardless of Inflammatory and Nutritional Status in Patients Starting Dialysis: A Prospective Cohort Study. Blood Purif. 2015;40:209-17.
NU
[10] Rhee CM, Nguyen DV, Moradi H, et al. Association of Adiponectin With Body
MA
Composition and Mortality in Hemodialysis Patients. Am J Kidney Dis. 2015;66:313-21.
D
[11] Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items
CE P
2010;8:336-41.
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for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg.
[12] Wells G, Shea B, O'Connell D. The Newcastle-Ottawa Scale (NOS) for assessing
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the quality of nonrandomised studies in meta-analyses. [13] Ades AE, Lu G, Higgins JP. The interpretation of random-effects meta-analysis in decision models. Med Decis Making. 2005;25:646-54. [14] Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557-60. [15] Mathew S, Abraham G, Vijayan M, et al. Body composition monitoring and nutrition in maintenance hemodialysis and CAPD patients--a multicenter longitudinal study. Ren Fail. 2015;37:66-72. [16] Silbernagel G, Genser B, Drechsler C, et al. HDL cholesterol, apolipoproteins, 18
ACCEPTED MANUSCRIPT and cardiovascular risk in hemodialysis patients. J Am Soc Nephrol. 2015;26:484-92. [17] Tentori F, Wang M, Bieber BA, et al. Recent changes in therapeutic approaches
IP
T
and association with outcomes among patients with secondary hyperparathyroidism
SC R
on chronic hemodialysis: the DOPPS study. Clin J Am Soc Nephrol. 2015;10:98-109. [18] Chen HY, Chiu YL, Chuang YF, et al. Visceral adiposity index and risks of cardiovascular events and mortality in prevalent hemodialysis patients. Cardiovasc
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Diabetol. 2014;13:136.
MA
[19] Moradi H, Streja E, Kashyap ML, Vaziri ND, Fonarow GC, Kalantar-Zadeh K. Elevated high-density lipoprotein cholesterol and cardiovascular mortality in
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maintenance hemodialysis patients. Nephrol Dial Transplant. 2014;29:1554-62.
TE
[20] Joao Matias P, Azevedo A, Laranjinha I, et al. Lower serum magnesium is
CE P
associated with cardiovascular risk factors and mortality in haemodialysis patients. Blood Purif. 2014;38:244-52.
AC
[21] Kim CH, Kim SJ, Lee MJ, et al. LDL cholesterol affects clinical outcomes in incident hemodialysis patients during the early stages of dialysis. Blood Purif. 2014;38:131-9.
[22] Kuragano T, Matsumura O, Matsuda A, et al. Association between hemoglobin variability, serum ferritin levels, and adverse events/mortality in maintenance hemodialysis patients. Kidney Int. 2014;86:845-54. [23] Ok ES, Asci G, Toz H, et al. Glycated hemoglobin predicts overall and cardiovascular mortality in non-diabetic hemodialysis patients. Clin Nephrol. 2014;82:173-80. 19
ACCEPTED MANUSCRIPT [24] Prasad N, Sinha A, Gupta A, et al. Effect of body mass index on outcomes of peritoneal dialysis patients in India. Perit Dial Int. 2014;34:399-408.
IP
T
[25] Turkmen K, Guney I, Yazici R, Arslan S, Altintepe L, Yeksan M. Health-related
SC R
quality of life, depression and mortality in peritoneal dialysis patients in Turkey: seven-year experience of a center. Ren Fail. 2014;36:859-64.
[26] Chang TI, Oh HJ, Kang EW, et al. A low serum bicarbonate concentration as a
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risk factor for mortality in peritoneal dialysis patients. PLoS One. 2013;8:e82912.
MA
[27] Cuevas X, Garcia F, Martin-Malo A, et al. Risk factors associated with cardiovascular morbidity and mortality in Spanish incident hemodialysis patients:
D
two-year results from the ANSWER study. Blood Purif. 2012;33:21-9.
TE
[28] Yoo HH, Martin LC, Kochi AC, et al. Could albumin level explain the higher
2012;13:80.
CE P
mortality in hemodialysis patients with pulmonary hypertension? BMC Nephrol.
AC
[29] Wagner M, Ansell D, Kent DM, et al. Predicting mortality in incident dialysis patients: an analysis of the United Kingdom Renal Registry. Am J Kidney Dis. 2011;57:894-902.
[30] Antunes AA, Delatim Vannini F, de Arruda Silveira LV, Martin LC, Barretti P, Caramori JC. Influence of protein intake and muscle mass on survival in chronic dialysis patients. Ren Fail. 2010;32:1055-9. [31] de Mutsert R, Grootendorst DC, Indemans F, et al. Association between serum albumin and mortality in dialysis patients is partly explained by inflammation, and not by malnutrition. J Ren Nutr. 2009;19:127-35. 20
ACCEPTED MANUSCRIPT [32] Habib AN, Baird BC, Leypoldt JK, Cheung AK, Goldfarb-Rumyantzev AS. The association of lipid levels with mortality in patients on chronic peritoneal dialysis.
IP
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Nephrol Dial Transplant. 2006;21:2881-92.
SC R
[33] Iseki K, Yamazato M, Tozawa M, Takishita S. Hypocholesterolemia is a significant predictor of death in a cohort of chronic hemodialysis patients. Kidney Int. 2002;61:1887-93.
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[34] Herzig KA, Purdie DM, Chang W, et al. Is C-reactive protein a useful predictor
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of outcome in peritoneal dialysis patients? J Am Soc Nephrol. 2001;12:814-21. [35] Palmer SC, Vecchio M, Craig JC, et al. Association between depression and
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2013;62:493-505.
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death in people with CKD: a meta-analysis of cohort studies. Am J Kidney Dis.
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[36] Fabrizi F, Dixit V, Messa P. Impact of hepatitis C on survival in dialysis patients: a link with cardiovascular mortality? J Viral Hepat. 2012;19:601-7.
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[37] Pilz S, Iodice S, Zittermann A, Grant WB, Gandini S. Vitamin D status and mortality risk in CKD: a meta-analysis of prospective studies. Am J Kidney Dis. 2011;58:374-82.
[38] Fernandez-Rodriguez AM, Guindeo-Casasus MC, Molero-Labarta T, et al. Diagnosis of iron deficiency in chronic renal failure. Am J Kidney Dis. 1999;34:508-13. [39] Liu L. Using Multivariate Quantile Regression Analysis to Explore Cardiovascular Risk Differences in Subjects with Chronic Kidney Disease by Race and Ethnicity: Findings from the U.S. Chronic Renal Insufficiency Cohort Study// 21
ACCEPTED MANUSCRIPT Formulation and Analytical Development for Low-Dose Oral Drug Products. John
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Wiley & Sons, Inc. 2015:405-428.
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Country
Sample size
Mean age
Percentage male (%)
PCAD (%)
BMI
Duration of Smoking hemodialysis (%) (year)
Follow-up duration (year)
Reported outcomes
Adjusted factors
NOS score
Ishii 2015[8]
Japan
516
60.0
59.9
33.3
20.6
5.5
28.8
10.0
All-cause mortality and cardiac death
Age, diabetes, BMI, PCAD, hemoglobin, and albumin
8
Mathew 2015 [15]
India
99
55.3
78.8
NA
22.2
NA
NA
2.0
All-cause mortality
BMI, overhydration, and fat tissue index
6
Park 2015[9]
Korea
946
60.0
61.4
13.7
23.2
NA
NA
3.3
All-cause mortality and cardiac death
Age, sex, DM, BMI, albumin, TIBC, and iron
7
Rhee 2015[10]
USA
501
55.1
56.5
26.4
3.5
36.1
1.3
All-cause mortality
Age, sex, race, ethnicity, dialysis vintage, diabetes, serum albumin level, total iron-binding capacity, serum creatinine level, white blood cell count, phosphorus
7
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MA N
US
CR
Study
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Table 1. Baseline characteristics of studies included in the systematic review and meta-analysis
NA
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Germany
1255
66.3
53.9
29.4
28.0
Tentori 2014[17]
Multicenter
35655
62.8
58.3
42.6
25.2
Chen 2014[18]
China
464
60.0
49.0
8.3
40.4
3.9
All-cause mortality and cardiac death
Multivariate Andersen–Gill model
8
2.7
NA
1.6
All-cause mortality
Patient age, sex, BMI, time on dialysis, catheter use, comorbidities, albumin, hemoglobin, creatinine, facility percentage of patients with catheter use, percentage of patients having albumin 3.5 g/dL, and mean hemoglobin
7
3.6
NA
4.2
All-cause mortality
Gender, age, HD vintage, presence of DM, HTN and
8
AC
CE P
TE D
MA N
US
Silbernagel 2015[16]
CR
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level, hemoglobin level, and normalized protein catabolic rate
23.0
22.7
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US
33109
60.0
55.0
7.0
27.5
Matias 2014[20]
Portugal
206
63.6
55.0
28.0
Kim 2014[21]
Korea
867
57.6
59.5
Kuragano 2014 [22]
Japan
1095
61.8
60.3
Ok 2014[23]
Turkey
489
57.6
NA
NA
3.0
All-cause mortality and cardiac death
Gender, age, HD vintage, presence of DM, race, primary insurance, and comorbidities
6
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MA N
Moradi 2014[19]
US
CR
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concurrent CV disease, hemoglobin, iPTH, hs-CRP, calcium phosphate product, and GNRI levels
3.5
NA
2.0
All-cause mortality and cardiac death
Age, DM, time on HD, CRP, PP, LVMI, and SVCS
7
13.7
23.3
NA
43.2
1.9
All-cause mortality
Age, gender, DM, and pre-existing CVD
8
NA
21.7
8.8
NA
2.0
All-cause mortality
Sex, age, etiology, and albumin, CRP, and intact parathyroid hormone levels.
7
19.0
23.2
4.0
NA
3.0
All-cause mortality
Age, history of CVD, BMI, albumin,
8
AC
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NA
53.3
25
India
328
52.6
73.8
15.9
21.9
Turkmen 2014 [25]
Turkey
63
52.9
67.4
NA
26.7
Chang 2013 [26]
Korea
441
59.2
54.4
15.9
Cuevas 2012 [27]
Spain
2310
NA
NA
NA
and cardiac death
hemoglobin, fasting blood glucose, hs-CRP, and ESA dose
NA
1.7
All-cause mortality
Age, subjective global assessment, comorbidities, albumin, diabetes, and residual glomerular filtration rate
7
1.7
NA
7.0
All-cause mortality
NA
6
22.8
NA
NA
2.9
All-cause mortality and cardiac death
Age, diabetes, CAD, serum albumin, ferritin, CRP, residual glomerular filtration rate, peritoneal Kt/V urea, nPCR, and percentage of lean body mass
8
NA
NA
NA
2.0
All-cause mortality and cardiac
Alcohol consumption; chronic kidney disease etiology,
6
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MA N
US
Prasad 2014[24]
CR
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NA
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dyslipidemia, previous cardiac arrhythmia, left ventricular hypertrophy, systolic blood pressure before HD session; hemodialysis technique, dialysis time, glucose, potassium, iPTH, phosphorus-binding drugs, cardiovascular drugs, and hypolipidemic drugs
Brazil
75
56.2
60.0
Wagner 2011[29]
UK
5447
64.0
61.4
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Yoo 2012[28]
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MA N
US
CR
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death
NA
24.6
NA
NA
6.0
All-cause mortality
Crude
6
33.1
25.0
NA
NA
3.0
All-cause mortality
Start-year of dialysis, Townsend score, change in treatment modality within the first 3 months of dialysis treatment, phosphate, and ferritin
7
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Brazil
79
60.0
60.7
NA
24.1
4.8
NA
3.2
All-cause mortality
Age, gender, time on dialysis, diabetes, dialysis modality, and CRP
6
Mutsert 2009[31]
The Netherlands
700
59.1
60.5
NA
24.7
NA
NA
2.0
All-cause mortality
SGA, subjective global assessment of nutritional status
7
Habib 2006[32]
US
1053
57.2
52.0
35.0
25.5
NA
NA
2.0
All-cause mortality and cardiac death
Age, gender, race, weight, height, primary cause of ESRD, hemoglobin, serum albumin, serum calcium phosphate product, serum bicarbonate, residual kidney creatinine clearance, pharmacodynamic parameters, use of lipid-modifying medications, and comorbidity characteristics
7
Iseki 2002[33]
Japan
1167
52.6
58.3
NA
NA
5.2
NA
10.0
All-cause mortality
Baseline characteristics
6
Herzig
Australia
50
58.6
30.0
30.0
25.4
2.1
34.0
3.0
All-cause
DM, previous CVD,
7
AC
CE P
TE D
MA N
US
CR
IP
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Antunes 2010 [30]
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mortality
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MA N
US
CR
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2001[34]
29
CCr, previous smoking, residual renal function, Kt/V, pre-albumin, and albumin
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Age (per 1 year Country increment) Western Countries
1.05 (1.03-1.07)
<0.001
1.06 (1.04-1.08)
<0.001
<0.001
0.012
Western Countries
2.08 (1.36-3.20)
0.001
0.024
Eastern Countries
2.00 (1.68-2.40)
<0.001
0.083
0.65 (0.54-0.79)
<0.001
0.347
0.040
0.108
0.97 (0.74-1.27) 0.92 (0.74-1.14)
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Eastern Countries
0.827 0.444
0.090
Western Countries
1.22 (0.92-1.63)
0.166
0.020
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Country
0.97 (0.95-1.00)
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Eastern Countries
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Country
BMI (per 1 Country kg/m2 increment) Western Countries
Previous CVD
P value for P value between heterogeneity subgroups
0.010
Gender (women Country vs men) Western Countries
DM vs non-DM
P value
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Eastern Countries
RR and 95%CI
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Factors
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Table 2. Subgroup analysis based on country for total mortality
1.62 (1.14-2.30)
0.007
0.017
0.93 (0.89-0.98)
0.004
0.594
Eastern Countries
0.95 (0.89-1.02)
0.148
0.156
0.52 (0.35-0.76)
0.001
<0.001
0.52 (0.38-0.72)
<0.001
<0.001
1.68 (1.33-2.11)
<0.001
0.746
1.25 (1.06-1.46)
0.006
<0.001
Eastern Countries
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Hemoglobin (per Country 1 d/dl increment) Western Countries
Albumin (high Country versus low) Western Countries Eastern Countries CRP (high versus Country low) Western Countries Eastern Countries
30
0.022
0.422
0.545
<0.001
0.056
0.523
0.456
<0.001
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Figure 2. Factors influencing the risk of all-cause mortality in patients undergoing
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Figure 3. Factors influencing the risk of cardiac death in patients undergoing HD.
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