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Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension
HLC 2466 1–7
Heart, Lung and Circulation (2017) xx, 1–7 1443-9506/04/$36.00 http://dx.doi.org/10.1016/j.hlc.2017.08.007
Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension
1 2 3 4 5 6
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Q1
8 9 10 11 12 13 14 15
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ORIGINAL ARTICLE
Q2 Q3
[TD$FIRSNAME]Anna[TD$FIRSNAME.] [TD$SURNAME]Smukowska-Gorynia[TD$SURNAME.] a*, [TD$FIRSNAME]Iga[TD$FIRSNAME.] [TD$SURNAME]Tomaszewska[TD$SURNAME.] a, ska-Rajpold[TD$SURNAME.] a, [TD$FIRSNAME]Justyna[TD$FIRSNAME.] [TD$SURNAME]Marcinkowska[TD$SURNAME.] b, [TD$FIRSNAME]Katarzyna[TD$FIRSNAME.] [TD$SURNAME]Maaczyn [TD$FIRSNAME]Anna[TD$FIRSNAME.] [TD$SURNAME]Komosa[TD$SURNAME.] a, [TD$FIRSNAME]Magdalena[TD$FIRSNAME.] [TD$SURNAME]Janus[TD$SURNAME.] a, [TD$FIRSNAME]Anna[TD$FIRSNAME.] [TD$SURNAME]Olasi nska-Wisniewska[TD$SURNAME.] a, [TD$FIRSNAME]Sylwia[TD$FIRSNAME.] [TD$SURNAME]Sawek[TD$SURNAME.] a, [TD$FIRSNAME]Aleksander[TD$FIRSNAME.] [TD$SURNAME]Araszkiewicz[TD$SURNAME.] a, [TD$FIRSNAME]Stanisaw[TD$FIRSNAME.] [TD$SURNAME]Jankiewicz[TD$SURNAME.] a, [TD$FIRSNAME]Tatiana[TD$FIRSNAME.] [TD$SURNAME]Mularek-Kubzdela[TD$SURNAME.] a a
1st Department of Cardiology, University of Medical Sciences, Poznan, Poland Department of Computer Science and Statistics, University of Medical Sciences, Poznan, Poland
b
Received 2 March 2017; received in revised form 17 July 2017; accepted 4 August 2017; online published-ahead-of-print xxx
Background
Red blood cells distribution width (RDW) predicts survival in cardiovascular diseases. Little is known about the variability of RDW level over time among patients with pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH). To our knowledge, RDW has never been analysed as a marker of response to specific treatment.
Materials and Methods
We retrospectively analysed 77 patients for: i) RDW measured during the last hospitalisation before death or during the last follow-up (RDWlast); ii) mean RDW from all hospitalisations during the entire follow-up of the patient (RDWmean); iii) maximum RDW of all hospitalisations of each patient (RDWmax). In order to assess response to specific treatment and association with prognosis, we compared RDW levels (obtained from 56 patients) before and three to six months after introduction or intensification of treatment in both the alive and deceased group.
Results
Twenty-eight of 77 patients died, whereas in specific drugs treatment response analysis, 22 of 56 patients died during follow-up. The cut-off values derived from the ROC analysis and assessed using the log-rank test were significant for RDWlast (p < 0.0001), RDWmean (p < 0.001) and RDWmax (p = 0.02). A decrease in RDW levels after introduction or intensification of specific treatment was significant (p = 0.015) in survivors, whereas there was no significance (p = 0.29) in decrease in RDW levels in non-survivors after change of therapy.
Conclusions
Red blood cells distribution width might be a potential prognostic biomarker in patients with PAH and inoperable CTEPH. The decrease in RDW level after introduction or escalation of PAH-targeted and CTEPH-targeted drugs is associated with a good treatment response and better prognosis.
Keywords
Red blood cell distribution width Pulmonary arterial hypertension Chronic thromboembolic pulmonary hypertension Treatment Prognosis
Q5 Q4 *Corresponding author at: 1st Department of Cardiology, University of Medical Sciences, Szpital Kliniczny Przemienienia Panskiego, Dluga 1/2 , 61-848, Poznan, Poland., Email: [email protected] © 2017 Published by Elsevier B.V. on behalf of Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ).
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
HLC 2466 1–7
2
Q6
20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
20% with PAH CTD, 2% with PAH PoP, and 12% with CTEPH. The PAPm was 53 mmHg, the mean 6-minute walking test (6-MWT) was 303 metres and 64% of the patients were in WHO functional class III. The median follow-up was 57 months (Table 1). The secondary endpoint was response to treatment with specific drugs. The diagnosis of pulmonary hypertension was made based on right heart catheterisation (RHC). The PAH-targeted drugs were as follows: sildenafil, bosentan, ambrisentan, macitentan, treprostinil, iloprost, and the CTEPH-targeted drug was riociguat. The first-line treatment was oral monotherapy (sildenafil or bosentan in PAH CHD, and riociguat or sildenafil in CTEPH). When disease worsening occurred or a patient was in WHO functional class IV at the time of diagnosis, dual therapy was introduced (sildenafil with one of the PAH-targeted drugs mentioned above). Follow-up data were collected during scheduled visits every three to six months and during unscheduled hospitalisations due to all-cause sudden clinical worsening/deterioration. The time period of follow-up visits was
Introduction
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A. Smukowska-Gorynia et al.
Q7
Red blood cells distribution width (RDW), a laboratory biomarker routinely measured in standard blood analyses, predicts survival in cardiovascular diseases, such as chronic heart failure [1], coronary artery disease [2], acute pulmonary embolism [3], and many more. In addition, RDW is associated with morbidity in a wide range of cardiovascular and pulmonary diseases: it predicts adverse clinical outcomes in patients with paroxysmal atrial fibrillation [4], acute decompensated heart failure [5], coronary artery disease [6], community-acquired pneumonia [7], and many more. Previously, RDW has been identified as an independent prognostic marker in patients with pulmonary hypertension (PH) of mixed aetiology [8], idiopathic arterial pulmonary hypertension [9] as well as Eisenmenger syndrome [10]. However, little is still known about variability of RDW level over time among patients with pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH). In addition, to the best of our knowledge, RDW has never been analysed as a marker of a response to a specific treatment. Therefore, we aimed to investigate the predictive value of RDW in patients with PAH and CTEPH and to examine whether the introduction or intensification of specific pulmonary hypertension treatment is associated with a decrease in RDW.
Q1
Table 1 Patient demographics. Characteristics
Analysis of RDW as a prognostic
Analysis of RDW as a marker of
marker
response to specific treatment
Total number
77
56
of patients
44
Subjects and Methods
45
Study Subjects
F
54 (70%)
43 (77%)
46
We retrospectively collected RDW results from 77 patients (70% of whom were females) with PAH and inoperable CTEPH, treated in the 1st Department of Cardiology, Poznan, Poland, between October 2008 and October 2016. The mean age was 52.15 [1_TD$IF]217.49 years. Forty-five per cent of the patients were diagnosed with idiopathic pulmonary arterial hypertension (IPAH), 25% with pulmonary arterial hypertension associated with congenital heart defect (PAH CHD), 16% with pulmonary arterial hypertension associated with connective tissue disease (PAH CTD), 1% with portopulmonary arterial hypertension (PAH PoP), and 13% with CTEPH. The mean pulmonary arterial pressure (PAPm) was 53 millimetres of mercury (mmHg), the mean 6-minute walking test was 305 metres and 67% of the patients were in World Health Organization Functional Class (WHO FC) III (Table 1). The median follow-up was 65 months. The primary endpoint was all-cause death. For further analysis we took RDW measurements from 56 patients of the whole cohort of 77 patients who had complete data to evaluate the response to the treatment (77% of whom were females). Blood samples to assess the RDW level were obtained at two time points: before and three to six months after introduction or intensification of specific drug treatment. The mean age of this group was 54.45 15.18 years. Forty-one per cent of the patients were diagnosed with IPAH, 25% with PAH CHD,
M
23 (30%)
13 (23%)
52.15 17.49
54.45 15.18
35 (45%) 19 (25%)
23 (41%) 14 (25%)
Gender
47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
Age (years) Aetiology: IPAH PAH CHD PAH CTD
12 (16%)
11 (20%)
PAH PoP
1 (1%)
1 (2%)
CTEPH
10 (13%)
7 (12%)
WHO FC I
2 (3%)
0
II III
12 (16%) 52 (67%)
9 (16%) 36 (64%)
11 (14%)
11 (20%)
PAPm (mmHg)
IV
53
53
6MWT (meters)
305
303
Patient age, PAPm, 6MWT are presented as mean. Abbreviations: IPAH: idiopathic pulmonary arterial hypertension, PAH CHD pulmonary arterial hypertension associated with congestive heart defect, pulmonary arterial hypertension associated with connective tissue disease, PAH PoP: portopulmonary arterial hypertension, CTEPH: chronic thrombembolic pulmonary hypertension, WHO FC: World Health Organization Functional Class, PAPm: mean pressure in pulmonary artery, 6MWT: 6-minute walking test.
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89
HLC 2466 1–7
3
Red Blood Cells Distribution
90 91 92 93 94 95 96
97 98 99 100 101 102 103 104 105 106 107 108
indicated by guidelines for the diagnosis and treatment of pulmonary hypertension of European Society of Cardiology [11]. In addition, a 6-minute walking test (6-MWT), cardiopulmonary exercise test and echocardiography were performed, and N-terminal pro-brain natriuretic peptide (NT-proBNP) was measured during follow-up visits.
Materials and Methods We analysed: i) RDW measured during the last hospitalisation before death or during the last follow-up (RDWlast); ii) mean RDW from all hospitalisations during the entire follow-up of the patient (RDWmean); iii) maximum RDW of all hospitalisations of each patient (RDWmax). In addition, we assessed 6-MWT, World Health Organization Functional Class (WHO FC) and mean pressure in pulmonary artery (mPAP). In order to assess response to specific treatment and association with prognosis, we compared RDW levels before and three to six months after introduction or intensification of treatment in both the alive and deceased group.
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Statistical Analysis
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Data are presented as absolute numbers, percentages and mean standard deviation (SD). Receiver operating
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characteristic (ROC) curves were used to determine cut-off points associated with a higher probability of death. ROC curves for the prognostic variable of RDW (RDWlast, RDWmean and RDWmax, respectively) allowed classification of patients into groups with high and low risk of death. Survival curves were plotted as estimated by the KaplanMeier method and compared with others using the log-rank test. We studied the impact of the level of RDW, 6-MWT, WHO FC and mPAP on survival time by creating Cox proportional hazard models. The normality distributions of RDW were tested using the Shapiro-Wilk test as well as the skewness and kurtosis coefficients. Red blood cells distribution width levels before and three to six months after introduction or intensification of specific treatment were assessed using the t-student test. The statistical analysis was performed using the PQStat version 1.6.2.
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Results
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Twenty-eight of 77 (36%) patients died during follow-up. From the ROC analysis, cut-off points were derived to predict mortality for RDWlast (16.2%), RDW mean (15.65%) and RDWmax (17.7%); and their area under the curve was above 0.5: RDWlast (p < 0.001, AUC 0.73), RDWmean (p < 0.01, AUC 0.70) and RDWmax (p = 0.02, AUC 0.70), respectively. The cut-off values derived from the ROC analysis and assessed using the log-rank test were significant for RDWlast
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Figure 1 Kaplan-Meier survival curves showing survival estimates in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension, graded by red cells distribution width: RDWlast (A), RDWmean (B) and RDWmax (C) levels below and above receiver operating characteristic-derived values.
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
130 131 132 133 134 135 136
4 HLC 2466 1–7
Cox proportional
[5_TD$IF]Multivariate
Univariate
hazard models 6-MWT
mPAP
WHO FC/NYHA
p-value AIC – Akaikeg criterion
RDW
RDW
RDW
+RDW
+RDW
+RDW
+RDW
+RDW
+RDW
+RDW
+RDW
+RDW
[4_TD$IF]mean
max
last
mean
max
last
mean
max
last
mean
max
last
0.001
0.048
0.01
0.001
0.01
0.01
0.02
0.12
0.19
0.001
0.01
0.01
199.0498
206.6315
203.0587
184.4218
187.6654
186.2565
168.5909
172.1004
173.0225
194.9176
199.0359
198.2023
R2 (Nagelkerke) R2 (Cox-Snell)
0.337211 0.337014
0.130915 0.130839
0.235097 0.23496
0.404749 0.404447
0.328671 0.328426
0.362844 0.362573
0.257383 0.257042
0.14987 0.149672
0.119133 0.118975
0.435648 0.435379
0.346129 0.345916
0.365325 0.365099
p-value Wald test
0.000405
0.043708
0.004591
0.028865
0.270341
0.100996
0.008893
0.083354
0.153519
0.01266
0.192323
0.109897
Hazard ratio*
1.47
1.14
1.21
1.31
1.08
1.13
1.35
1.14
1.11
1.35
1.09
1.13
95% CI*
1.19
1.00
1.06
1.03
0.94
0.98
1.08
0.98
0.96
1.07
0.95
0.97
+95% CI*
1.82
1.29
1.39
1.67
1.25
1.32
1.68
1.32
1.27
1.70
1.25
1.31
0.04
0.28
0.11
0.01
0.08
0.15
0.02
0.20
0.12
p-value Chi^2
Abbreviations: 6-MWT: 6-minute walking test; mPAP: mean pulmonary arterial pressure; WHO FC: World Health Organization Functional Class; NYHA: New York Heart Association. *
Hazard ratio and 95% CI are given for RDW.
A. Smukowska-Gorynia et al.
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
Table 2 Univariate Cox proportional hazard model shows statistical significance of RDWmean, RDWmax and RDWlast (p-value). Multivariate proportional hazard models show statistical significance of adding RDWmean to 6-MWT, mPAP and WFO FC (p-value Chi^2).
HLC 2466 1–7
5
Red Blood Cells Distribution
Figure 2 The diagram presents significant difference in RDW levels before and 3–6 months after specific drugs introduction/escalation in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension in alive group.
137 138 139 140 141 142 143 144 145 146 147 148 149 150
(p < 0.0001), RDWmean (p < 0.001) and RDWmax (p = 0.02) (Figure 1). On Cox regression analysis, RDW predicted death: RDWlast (p < 0.01; HR 1.21; 95% CI 1.06–1.39), RDWmean (p < 0.001; HR 1.47; 95% CI 1.19–1.82) and RDWmax (p = 0.04; HR 1.14; 95% CI 1.00–1.29), respectively (Table 2). The WHO FC and 6MWT also were significant in prediction of death (p < 0.001; HR 3.03; 95% CI 1.49–6.13 and p < 0.01; HR 0.995; 95% CI 0.992–0.998. respectively), while the mPAP was not significant (p = 0.27; HR 0.98; 95% CI 0.95– 1.01) on univariate Cox regression analysis. On multivariate Cox regression analysis adding the RDWmean to the WHO FC (p = 0.02), 6-MWT (p = 0.04) and mPAP (p = 0.01) increased the prognostic value of these parameters, whereas adding the RDWlast and RDWmax did not improve the
Figure 3 The diagram presents no significant difference in RDW levels before and 3–6 months after specific drugs introduction/escalation in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension in deceased group.
Figure 4 The diagram presents significant difference in RDW levels after 3–6 months’ treatment introduction/ escalation of specific drugs in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension between alive and deceased group.
prognostic value of the WHO FC (p = 0.12, p = 0.20), 6MWT (p = 0.11, p = 0.28) and mPAP (p = 0.15, p = 0.08) (Table 2). In specific drugs treatment response analysis, 22 of 56 (39%) patients died during follow-up. A decrease in RDW levels after introduction or intensification of specific treatment was statistically significant (p = 0.015) in survivors (Figure 2), whereas there was no statistical significance (p = 0.29) in decrease in RDW levels in non-survivors after change of therapy (Figure 3). Moreover, RDW levels after introduction or escalation of specific treatment were significantly lower (p = 0.01) in the alive group when compared to patients who died (Figure 4).
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Discussion
164
The explanation why RDW is a good predictor of mortality in cardiovascular diseases [12], pulmonary diseases, cancer, sepsis [13], renal disease [14], and many more is associated with the fact that RDW reflects many different pathophysiologic mechanisms (inflammation, impaired iron metabolism, renal dysfunction, nutritional state, oxidative stress) and these processes result in decreased erythropoietic output. Analysis of direct cause of rising RDW in many diseases was performed by Patel et al. [15] using a mechanistic model of in vivo red blood cells (RBC) population. They investigated possible causes of elevated RDW in this model: i) decreased mean cell volume; ii) increased reticulocyte volume variance; iii) increased heterogeneity in the rate of RBC volume reduction occurring in the peripheral circulation; iv) delayed RBC clearance. The result of this interesting analysis was that the last cause, delay in clearance of RBCs is the crucial mechanism, leading to increase in RDW, as an adaptation to reduction in erythropoietic output, to maintain
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Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
152 153 154 155 156 157 158 159 160 161 162 163
167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182
HLC 2466 1–7
6
183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239
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peripheral cell mass. A greater number of older and smaller RBCs in blood circulation (RBCs become smaller and haemoglobin mass drops as they age) results in elevated RDW. Previously, studies have shown that increase in RDW of every 1% is associated with an increase in all-cause mortality risk of 22% [16]. Therefore, the authors suggest that slight changes in erythropoiesis such as reticulocytes decrease of 3% and decreased RBC clearance do not significantly affect standard blood analysis results, which are maintained within normal range, but may reflect latent pathology [15]. Other authors found that poor stem cell mobilisation is associated with increased RDW in patients with advanced chronic heart failure [17]. A wide range of different clinical variables should be assessed during follow-up visits in patients with PAH and CTEPH [11]. Clinical status evaluation includes: WHO FC, progression of symptoms, clinical signs of right heart failure, history of syncope, 6MWD, cardiopulmonary exercise test (peak oxygen consumption and ventilatory equivalents for carbon dioxide), echocardiography (right atrium area, pericardial effusion) and RHC (right atrial pressure, cardiac index and mixed venous oxygen saturation). However, only one biomarker, plasma level of NT-proBNP, is recommended for disease monitoring and prognostication. In our study, RDW (last, mean and max), as well as the established prognostic parameters, such as WHO FC and 6-MWT confirmed the prognostic value in predicting death, opposite to the mPAP which is not proved to be a predicting factor. Interestingly, only RDWmean added to the WHO FC, 6-MWT and mPAP improved the prognostic significance of the model, which means that constantly high levels of RDW (RDWmean 15.65% in our study) is the important determinant of death. The cut-off value of RDWmean presented in our study (15.65%) was similar to the cut-off value of baseline RDW (15.7%) predicting death, analysed by Rhodes et al. in patients with IPAH. However, in our study the baseline RDW was not significant in predicting death (p = 0.66, HR 0.96, 95% CI 0.81–1.14). The higher cut-off value of RDWlast (16.2%) in our study may reflect the increasing trend of RDW directly before death, and gradually increasing RDW is associated with poor prognosis. The highest cut-off value of RDWmax (17.7%) characterises the significantly higher risk of mortality as well. To our knowledge, RDW has never been examined as a marker of response to treatment with specific drugs in the PAH and CTEPH populations. In our study, RDW significantly decreased in alive patients who had received a PAHor CTEPH-targeted drug, in opposition to patients who died. Thus, a good clinical response to specific drug introduction or intensification measured by RDW lowering is associated with good prognosis. In addition, RDW levels after specific drug treatment were significantly lower in the alive group when compared to the deceased group, which indicates that a change in RDW (decrease, no change or even increase) after introduction/escalation of specific treatment is more important than one occasional RDW measurement. Therefore, RDWmax (p = 0.02) was less significant than RDWlast
(p < 0.001) and RDWmean (p < 0.01) because our data suggest that there is a crucial influence of response to treatment which can modify the course of disease and prognosis. Therefore, elevated RDW levels, despite specific treatment therapy, indicate poor prognosis. Thus, according to our results, RDW may have the potential to be added to the currently used functional, haemodynamic and echocardiographic parameters and NT-proBNP for better risk stratification and treatment monitoring in patients with PAH and CTEPH. Moreover, Hampole and Rhodes proved [8,9] that RDW outperformed NT-proBNP as a prognostic marker in patients with pulmonary hypertension. Finally, we decided not to evaluate other red blood cell parameters measured in standard blood analysis because, in prior studies, the prognostic value of RDW was independent of haemoglobin and mean cell volume (MCV) in patients with pulmonary hypertension [9]. The limitations of the study are the retrospective design and the cohort size, which indicate the necessity of further validation RDW levels as a prognostic marker in patients with PAH and inoperable CTEPH.
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Conclusions
261
Our data suggest that RDW may be a potential prognostic biomarker in patients with PAH and inoperable CTEPH. The decrease in RDW levels after introduction or escalation of PAH-targeted and CTEPH-targeted drugs is associated with a good treatment response and better prognosis. However, prospective validation in another independent cohort is needed to demonstrate the utility of RDW as a biomarker in precapillary PH. Moreover, there is a need for a new widely available sensitive test to detect abnormalities in erythropoiesis in its early stage.
262
Disclosures
272
Authors declare no conflict of interests. Authors declare no external financial support.
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HLC 2466 1–7
7
Red Blood Cells Distribution
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[12] Anderson JL, Ronnow BS, Horne BD, et al. Usefulness of a complete Q9 316 blood count-derived risk score to predict incident mortality in 317 patients with suspected cardiovascular disease. Am J Cardiol 318 2007;99:169–74. 319 [13] Perlstein TS, Weuve J, Pfeffer MA, et al. Red blood cell distribution width 320 and mortality risk in a community-based prospective cohort. Arch Intern 321 Med 2009;169:588–94. 322 [14] Vashistha T, Streja E, Molnar MZ, Rhee CM, Moradi H, Soohoo M, et al. 323 Red Cell Distribution Width and Mortality in Hemodialysis Patients. Am 324 J Kidney Dis 2016;68(Jul (1)):110–21. 325 [15] Patel HH, Patel HR, Higgins JM. Modulation of red blood cell population 326 dynamics is a fundamental homeostatic response to disease. Am J Hem327 atol 2015;90(May (5)):422–8. 328 [16] Patel KV, Ferrucci L, Ershler WB, et al. Red blood cell distribution width 329 and the risk of death in middle-aged and older adults. Arch Intern Med 330 2009;169:515–23. 331 [17] Poglajen G, Sever M, Cernel9 c P, Haddad F, Vrtovec B. Increased red cell 332 distribution width is associated with poor stem cell mobilization 333 in patients with advanced chronic heart failure. Biomarkers 2015;20 Q10 334 (6–7):365–70. 335
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
Heart, Lung and Circulation (2017) xx, 1–7 1443-9506/04/$36.00 http://dx.doi.org/10.1016/j.hlc.2017.08.007
Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension
1 2 3 4 5 6
7
Q1
8 9 10 11 12 13 14 15
16 17
ORIGINAL ARTICLE
Q2 Q3
[TD$FIRSNAME]Anna[TD$FIRSNAME.] [TD$SURNAME]Smukowska-Gorynia[TD$SURNAME.] a*, [TD$FIRSNAME]Iga[TD$FIRSNAME.] [TD$SURNAME]Tomaszewska[TD$SURNAME.] a, ska-Rajpold[TD$SURNAME.] a, [TD$FIRSNAME]Justyna[TD$FIRSNAME.] [TD$SURNAME]Marcinkowska[TD$SURNAME.] b, [TD$FIRSNAME]Katarzyna[TD$FIRSNAME.] [TD$SURNAME]Maaczyn [TD$FIRSNAME]Anna[TD$FIRSNAME.] [TD$SURNAME]Komosa[TD$SURNAME.] a, [TD$FIRSNAME]Magdalena[TD$FIRSNAME.] [TD$SURNAME]Janus[TD$SURNAME.] a, [TD$FIRSNAME]Anna[TD$FIRSNAME.] [TD$SURNAME]Olasi nska-Wisniewska[TD$SURNAME.] a, [TD$FIRSNAME]Sylwia[TD$FIRSNAME.] [TD$SURNAME]Sawek[TD$SURNAME.] a, [TD$FIRSNAME]Aleksander[TD$FIRSNAME.] [TD$SURNAME]Araszkiewicz[TD$SURNAME.] a, [TD$FIRSNAME]Stanisaw[TD$FIRSNAME.] [TD$SURNAME]Jankiewicz[TD$SURNAME.] a, [TD$FIRSNAME]Tatiana[TD$FIRSNAME.] [TD$SURNAME]Mularek-Kubzdela[TD$SURNAME.] a a
1st Department of Cardiology, University of Medical Sciences, Poznan, Poland Department of Computer Science and Statistics, University of Medical Sciences, Poznan, Poland
b
Received 2 March 2017; received in revised form 17 July 2017; accepted 4 August 2017; online published-ahead-of-print xxx
Background
Red blood cells distribution width (RDW) predicts survival in cardiovascular diseases. Little is known about the variability of RDW level over time among patients with pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH). To our knowledge, RDW has never been analysed as a marker of response to specific treatment.
Materials and Methods
We retrospectively analysed 77 patients for: i) RDW measured during the last hospitalisation before death or during the last follow-up (RDWlast); ii) mean RDW from all hospitalisations during the entire follow-up of the patient (RDWmean); iii) maximum RDW of all hospitalisations of each patient (RDWmax). In order to assess response to specific treatment and association with prognosis, we compared RDW levels (obtained from 56 patients) before and three to six months after introduction or intensification of treatment in both the alive and deceased group.
Results
Twenty-eight of 77 patients died, whereas in specific drugs treatment response analysis, 22 of 56 patients died during follow-up. The cut-off values derived from the ROC analysis and assessed using the log-rank test were significant for RDWlast (p < 0.0001), RDWmean (p < 0.001) and RDWmax (p = 0.02). A decrease in RDW levels after introduction or intensification of specific treatment was significant (p = 0.015) in survivors, whereas there was no significance (p = 0.29) in decrease in RDW levels in non-survivors after change of therapy.
Conclusions
Red blood cells distribution width might be a potential prognostic biomarker in patients with PAH and inoperable CTEPH. The decrease in RDW level after introduction or escalation of PAH-targeted and CTEPH-targeted drugs is associated with a good treatment response and better prognosis.
Keywords
Red blood cell distribution width Pulmonary arterial hypertension Chronic thromboembolic pulmonary hypertension Treatment Prognosis
Q5 Q4 *Corresponding author at: 1st Department of Cardiology, University of Medical Sciences, Szpital Kliniczny Przemienienia Panskiego, Dluga 1/2 , 61-848, Poznan, Poland., Email: [email protected] © 2017 Published by Elsevier B.V. on behalf of Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ).
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
HLC 2466 1–7
2
Q6
20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
20% with PAH CTD, 2% with PAH PoP, and 12% with CTEPH. The PAPm was 53 mmHg, the mean 6-minute walking test (6-MWT) was 303 metres and 64% of the patients were in WHO functional class III. The median follow-up was 57 months (Table 1). The secondary endpoint was response to treatment with specific drugs. The diagnosis of pulmonary hypertension was made based on right heart catheterisation (RHC). The PAH-targeted drugs were as follows: sildenafil, bosentan, ambrisentan, macitentan, treprostinil, iloprost, and the CTEPH-targeted drug was riociguat. The first-line treatment was oral monotherapy (sildenafil or bosentan in PAH CHD, and riociguat or sildenafil in CTEPH). When disease worsening occurred or a patient was in WHO functional class IV at the time of diagnosis, dual therapy was introduced (sildenafil with one of the PAH-targeted drugs mentioned above). Follow-up data were collected during scheduled visits every three to six months and during unscheduled hospitalisations due to all-cause sudden clinical worsening/deterioration. The time period of follow-up visits was
Introduction
18 19
A. Smukowska-Gorynia et al.
Q7
Red blood cells distribution width (RDW), a laboratory biomarker routinely measured in standard blood analyses, predicts survival in cardiovascular diseases, such as chronic heart failure [1], coronary artery disease [2], acute pulmonary embolism [3], and many more. In addition, RDW is associated with morbidity in a wide range of cardiovascular and pulmonary diseases: it predicts adverse clinical outcomes in patients with paroxysmal atrial fibrillation [4], acute decompensated heart failure [5], coronary artery disease [6], community-acquired pneumonia [7], and many more. Previously, RDW has been identified as an independent prognostic marker in patients with pulmonary hypertension (PH) of mixed aetiology [8], idiopathic arterial pulmonary hypertension [9] as well as Eisenmenger syndrome [10]. However, little is still known about variability of RDW level over time among patients with pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH). In addition, to the best of our knowledge, RDW has never been analysed as a marker of a response to a specific treatment. Therefore, we aimed to investigate the predictive value of RDW in patients with PAH and CTEPH and to examine whether the introduction or intensification of specific pulmonary hypertension treatment is associated with a decrease in RDW.
Q1
Table 1 Patient demographics. Characteristics
Analysis of RDW as a prognostic
Analysis of RDW as a marker of
marker
response to specific treatment
Total number
77
56
of patients
44
Subjects and Methods
45
Study Subjects
F
54 (70%)
43 (77%)
46
We retrospectively collected RDW results from 77 patients (70% of whom were females) with PAH and inoperable CTEPH, treated in the 1st Department of Cardiology, Poznan, Poland, between October 2008 and October 2016. The mean age was 52.15 [1_TD$IF]217.49 years. Forty-five per cent of the patients were diagnosed with idiopathic pulmonary arterial hypertension (IPAH), 25% with pulmonary arterial hypertension associated with congenital heart defect (PAH CHD), 16% with pulmonary arterial hypertension associated with connective tissue disease (PAH CTD), 1% with portopulmonary arterial hypertension (PAH PoP), and 13% with CTEPH. The mean pulmonary arterial pressure (PAPm) was 53 millimetres of mercury (mmHg), the mean 6-minute walking test was 305 metres and 67% of the patients were in World Health Organization Functional Class (WHO FC) III (Table 1). The median follow-up was 65 months. The primary endpoint was all-cause death. For further analysis we took RDW measurements from 56 patients of the whole cohort of 77 patients who had complete data to evaluate the response to the treatment (77% of whom were females). Blood samples to assess the RDW level were obtained at two time points: before and three to six months after introduction or intensification of specific drug treatment. The mean age of this group was 54.45 15.18 years. Forty-one per cent of the patients were diagnosed with IPAH, 25% with PAH CHD,
M
23 (30%)
13 (23%)
52.15 17.49
54.45 15.18
35 (45%) 19 (25%)
23 (41%) 14 (25%)
Gender
47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
Age (years) Aetiology: IPAH PAH CHD PAH CTD
12 (16%)
11 (20%)
PAH PoP
1 (1%)
1 (2%)
CTEPH
10 (13%)
7 (12%)
WHO FC I
2 (3%)
0
II III
12 (16%) 52 (67%)
9 (16%) 36 (64%)
11 (14%)
11 (20%)
PAPm (mmHg)
IV
53
53
6MWT (meters)
305
303
Patient age, PAPm, 6MWT are presented as mean. Abbreviations: IPAH: idiopathic pulmonary arterial hypertension, PAH CHD pulmonary arterial hypertension associated with congestive heart defect, pulmonary arterial hypertension associated with connective tissue disease, PAH PoP: portopulmonary arterial hypertension, CTEPH: chronic thrombembolic pulmonary hypertension, WHO FC: World Health Organization Functional Class, PAPm: mean pressure in pulmonary artery, 6MWT: 6-minute walking test.
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89
HLC 2466 1–7
3
Red Blood Cells Distribution
90 91 92 93 94 95 96
97 98 99 100 101 102 103 104 105 106 107 108
indicated by guidelines for the diagnosis and treatment of pulmonary hypertension of European Society of Cardiology [11]. In addition, a 6-minute walking test (6-MWT), cardiopulmonary exercise test and echocardiography were performed, and N-terminal pro-brain natriuretic peptide (NT-proBNP) was measured during follow-up visits.
Materials and Methods We analysed: i) RDW measured during the last hospitalisation before death or during the last follow-up (RDWlast); ii) mean RDW from all hospitalisations during the entire follow-up of the patient (RDWmean); iii) maximum RDW of all hospitalisations of each patient (RDWmax). In addition, we assessed 6-MWT, World Health Organization Functional Class (WHO FC) and mean pressure in pulmonary artery (mPAP). In order to assess response to specific treatment and association with prognosis, we compared RDW levels before and three to six months after introduction or intensification of treatment in both the alive and deceased group.
109
Statistical Analysis
110
Data are presented as absolute numbers, percentages and mean standard deviation (SD). Receiver operating
111
characteristic (ROC) curves were used to determine cut-off points associated with a higher probability of death. ROC curves for the prognostic variable of RDW (RDWlast, RDWmean and RDWmax, respectively) allowed classification of patients into groups with high and low risk of death. Survival curves were plotted as estimated by the KaplanMeier method and compared with others using the log-rank test. We studied the impact of the level of RDW, 6-MWT, WHO FC and mPAP on survival time by creating Cox proportional hazard models. The normality distributions of RDW were tested using the Shapiro-Wilk test as well as the skewness and kurtosis coefficients. Red blood cells distribution width levels before and three to six months after introduction or intensification of specific treatment were assessed using the t-student test. The statistical analysis was performed using the PQStat version 1.6.2.
112
Results
128
Twenty-eight of 77 (36%) patients died during follow-up. From the ROC analysis, cut-off points were derived to predict mortality for RDWlast (16.2%), RDW mean (15.65%) and RDWmax (17.7%); and their area under the curve was above 0.5: RDWlast (p < 0.001, AUC 0.73), RDWmean (p < 0.01, AUC 0.70) and RDWmax (p = 0.02, AUC 0.70), respectively. The cut-off values derived from the ROC analysis and assessed using the log-rank test were significant for RDWlast
129
Figure 1 Kaplan-Meier survival curves showing survival estimates in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension, graded by red cells distribution width: RDWlast (A), RDWmean (B) and RDWmax (C) levels below and above receiver operating characteristic-derived values.
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
130 131 132 133 134 135 136
4 HLC 2466 1–7
Cox proportional
[5_TD$IF]Multivariate
Univariate
hazard models 6-MWT
mPAP
WHO FC/NYHA
p-value AIC – Akaikeg criterion
RDW
RDW
RDW
+RDW
+RDW
+RDW
+RDW
+RDW
+RDW
+RDW
+RDW
+RDW
[4_TD$IF]mean
max
last
mean
max
last
mean
max
last
mean
max
last
0.001
0.048
0.01
0.001
0.01
0.01
0.02
0.12
0.19
0.001
0.01
0.01
199.0498
206.6315
203.0587
184.4218
187.6654
186.2565
168.5909
172.1004
173.0225
194.9176
199.0359
198.2023
R2 (Nagelkerke) R2 (Cox-Snell)
0.337211 0.337014
0.130915 0.130839
0.235097 0.23496
0.404749 0.404447
0.328671 0.328426
0.362844 0.362573
0.257383 0.257042
0.14987 0.149672
0.119133 0.118975
0.435648 0.435379
0.346129 0.345916
0.365325 0.365099
p-value Wald test
0.000405
0.043708
0.004591
0.028865
0.270341
0.100996
0.008893
0.083354
0.153519
0.01266
0.192323
0.109897
Hazard ratio*
1.47
1.14
1.21
1.31
1.08
1.13
1.35
1.14
1.11
1.35
1.09
1.13
95% CI*
1.19
1.00
1.06
1.03
0.94
0.98
1.08
0.98
0.96
1.07
0.95
0.97
+95% CI*
1.82
1.29
1.39
1.67
1.25
1.32
1.68
1.32
1.27
1.70
1.25
1.31
0.04
0.28
0.11
0.01
0.08
0.15
0.02
0.20
0.12
p-value Chi^2
Abbreviations: 6-MWT: 6-minute walking test; mPAP: mean pulmonary arterial pressure; WHO FC: World Health Organization Functional Class; NYHA: New York Heart Association. *
Hazard ratio and 95% CI are given for RDW.
A. Smukowska-Gorynia et al.
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
Table 2 Univariate Cox proportional hazard model shows statistical significance of RDWmean, RDWmax and RDWlast (p-value). Multivariate proportional hazard models show statistical significance of adding RDWmean to 6-MWT, mPAP and WFO FC (p-value Chi^2).
HLC 2466 1–7
5
Red Blood Cells Distribution
Figure 2 The diagram presents significant difference in RDW levels before and 3–6 months after specific drugs introduction/escalation in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension in alive group.
137 138 139 140 141 142 143 144 145 146 147 148 149 150
(p < 0.0001), RDWmean (p < 0.001) and RDWmax (p = 0.02) (Figure 1). On Cox regression analysis, RDW predicted death: RDWlast (p < 0.01; HR 1.21; 95% CI 1.06–1.39), RDWmean (p < 0.001; HR 1.47; 95% CI 1.19–1.82) and RDWmax (p = 0.04; HR 1.14; 95% CI 1.00–1.29), respectively (Table 2). The WHO FC and 6MWT also were significant in prediction of death (p < 0.001; HR 3.03; 95% CI 1.49–6.13 and p < 0.01; HR 0.995; 95% CI 0.992–0.998. respectively), while the mPAP was not significant (p = 0.27; HR 0.98; 95% CI 0.95– 1.01) on univariate Cox regression analysis. On multivariate Cox regression analysis adding the RDWmean to the WHO FC (p = 0.02), 6-MWT (p = 0.04) and mPAP (p = 0.01) increased the prognostic value of these parameters, whereas adding the RDWlast and RDWmax did not improve the
Figure 3 The diagram presents no significant difference in RDW levels before and 3–6 months after specific drugs introduction/escalation in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension in deceased group.
Figure 4 The diagram presents significant difference in RDW levels after 3–6 months’ treatment introduction/ escalation of specific drugs in patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension between alive and deceased group.
prognostic value of the WHO FC (p = 0.12, p = 0.20), 6MWT (p = 0.11, p = 0.28) and mPAP (p = 0.15, p = 0.08) (Table 2). In specific drugs treatment response analysis, 22 of 56 (39%) patients died during follow-up. A decrease in RDW levels after introduction or intensification of specific treatment was statistically significant (p = 0.015) in survivors (Figure 2), whereas there was no statistical significance (p = 0.29) in decrease in RDW levels in non-survivors after change of therapy (Figure 3). Moreover, RDW levels after introduction or escalation of specific treatment were significantly lower (p = 0.01) in the alive group when compared to patients who died (Figure 4).
151
Discussion
164
The explanation why RDW is a good predictor of mortality in cardiovascular diseases [12], pulmonary diseases, cancer, sepsis [13], renal disease [14], and many more is associated with the fact that RDW reflects many different pathophysiologic mechanisms (inflammation, impaired iron metabolism, renal dysfunction, nutritional state, oxidative stress) and these processes result in decreased erythropoietic output. Analysis of direct cause of rising RDW in many diseases was performed by Patel et al. [15] using a mechanistic model of in vivo red blood cells (RBC) population. They investigated possible causes of elevated RDW in this model: i) decreased mean cell volume; ii) increased reticulocyte volume variance; iii) increased heterogeneity in the rate of RBC volume reduction occurring in the peripheral circulation; iv) delayed RBC clearance. The result of this interesting analysis was that the last cause, delay in clearance of RBCs is the crucial mechanism, leading to increase in RDW, as an adaptation to reduction in erythropoietic output, to maintain
165 166
Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007
152 153 154 155 156 157 158 159 160 161 162 163
167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182
HLC 2466 1–7
6
183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239
A. Smukowska-Gorynia et al.
peripheral cell mass. A greater number of older and smaller RBCs in blood circulation (RBCs become smaller and haemoglobin mass drops as they age) results in elevated RDW. Previously, studies have shown that increase in RDW of every 1% is associated with an increase in all-cause mortality risk of 22% [16]. Therefore, the authors suggest that slight changes in erythropoiesis such as reticulocytes decrease of 3% and decreased RBC clearance do not significantly affect standard blood analysis results, which are maintained within normal range, but may reflect latent pathology [15]. Other authors found that poor stem cell mobilisation is associated with increased RDW in patients with advanced chronic heart failure [17]. A wide range of different clinical variables should be assessed during follow-up visits in patients with PAH and CTEPH [11]. Clinical status evaluation includes: WHO FC, progression of symptoms, clinical signs of right heart failure, history of syncope, 6MWD, cardiopulmonary exercise test (peak oxygen consumption and ventilatory equivalents for carbon dioxide), echocardiography (right atrium area, pericardial effusion) and RHC (right atrial pressure, cardiac index and mixed venous oxygen saturation). However, only one biomarker, plasma level of NT-proBNP, is recommended for disease monitoring and prognostication. In our study, RDW (last, mean and max), as well as the established prognostic parameters, such as WHO FC and 6-MWT confirmed the prognostic value in predicting death, opposite to the mPAP which is not proved to be a predicting factor. Interestingly, only RDWmean added to the WHO FC, 6-MWT and mPAP improved the prognostic significance of the model, which means that constantly high levels of RDW (RDWmean 15.65% in our study) is the important determinant of death. The cut-off value of RDWmean presented in our study (15.65%) was similar to the cut-off value of baseline RDW (15.7%) predicting death, analysed by Rhodes et al. in patients with IPAH. However, in our study the baseline RDW was not significant in predicting death (p = 0.66, HR 0.96, 95% CI 0.81–1.14). The higher cut-off value of RDWlast (16.2%) in our study may reflect the increasing trend of RDW directly before death, and gradually increasing RDW is associated with poor prognosis. The highest cut-off value of RDWmax (17.7%) characterises the significantly higher risk of mortality as well. To our knowledge, RDW has never been examined as a marker of response to treatment with specific drugs in the PAH and CTEPH populations. In our study, RDW significantly decreased in alive patients who had received a PAHor CTEPH-targeted drug, in opposition to patients who died. Thus, a good clinical response to specific drug introduction or intensification measured by RDW lowering is associated with good prognosis. In addition, RDW levels after specific drug treatment were significantly lower in the alive group when compared to the deceased group, which indicates that a change in RDW (decrease, no change or even increase) after introduction/escalation of specific treatment is more important than one occasional RDW measurement. Therefore, RDWmax (p = 0.02) was less significant than RDWlast
(p < 0.001) and RDWmean (p < 0.01) because our data suggest that there is a crucial influence of response to treatment which can modify the course of disease and prognosis. Therefore, elevated RDW levels, despite specific treatment therapy, indicate poor prognosis. Thus, according to our results, RDW may have the potential to be added to the currently used functional, haemodynamic and echocardiographic parameters and NT-proBNP for better risk stratification and treatment monitoring in patients with PAH and CTEPH. Moreover, Hampole and Rhodes proved [8,9] that RDW outperformed NT-proBNP as a prognostic marker in patients with pulmonary hypertension. Finally, we decided not to evaluate other red blood cell parameters measured in standard blood analysis because, in prior studies, the prognostic value of RDW was independent of haemoglobin and mean cell volume (MCV) in patients with pulmonary hypertension [9]. The limitations of the study are the retrospective design and the cohort size, which indicate the necessity of further validation RDW levels as a prognostic marker in patients with PAH and inoperable CTEPH.
240
Conclusions
261
Our data suggest that RDW may be a potential prognostic biomarker in patients with PAH and inoperable CTEPH. The decrease in RDW levels after introduction or escalation of PAH-targeted and CTEPH-targeted drugs is associated with a good treatment response and better prognosis. However, prospective validation in another independent cohort is needed to demonstrate the utility of RDW as a biomarker in precapillary PH. Moreover, there is a need for a new widely available sensitive test to detect abnormalities in erythropoiesis in its early stage.
262
Disclosures
272
Authors declare no conflict of interests. Authors declare no external financial support.
273
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275
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263 264 265 266 267 268 269 270 271
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276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291
HLC 2466 1–7
7
Red Blood Cells Distribution
292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315
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Please cite this article in press as: Smukowska-Gorynia A, et al. Red Blood Cells Distribution Width as a Potential Prognostic Biomarker in Patients With Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension. Heart, Lung and Circulation (2017), http://dx.doi.org/10.1016/j.hlc.2017.08.007