Preoperative predictors for mortality following hip fracture surgery: A systematic review and meta-analysis

Injury, Int. J. Care Injured 43 (2012) 676–685

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Review

Preoperative predictors for mortality following hip fracture surgery: A systematic review and meta-analysis Fangke Hu a,c, Chengying Jiang a,c, Jing Shen b, Peifu Tang b, Yan Wang b,* a b

Medical College, Nankai University, 94 Weijin Road, Tianjin 300071, China Orthopedic Department, Chinese PLA General Hospital, 28 Fuxing Road, Beijing 100853, China

A R T I C L E I N F O

A B S T R A C T

Article history: Accepted 16 May 2011

Background: Hip fractures are always associated with a high postoperative mortality, the preoperative predictors for mortality have neither been well identified or summarised. This systematic review and meta-analysis was performed to identify the preoperative non-interventional predictors for mortality in hip fracture patients, especially focused on 1 year mortality. Methods: Non-interventional studies were searched in Pubmed, Embase, Cochrane central database (all to February 26th, 2011). Only prospective studies and retrospective studies with prospective collected data were included. Qualities of included studies were assessed by a standardised scale previous reported for observational studies. The effects of individual studies were combined with the study quality score using a previous reported model of best-evidence synthesis. The hazard ratios of strong evidence predictors were combined only by high quality studies. Results: 75 included studies with 94 publications involving 64,316 patients were included and the available observations was a heterogeneous group. The overall inpatient or 1 month mortality was 13.3%, 3–6 months was 15.8%, 1 year 24.5% and 2 years 34.5%. There were strong evidence for 12 predictors, including advanced age, male gender, nursing home or facility residence, poor preoperative walking capacity, poor activities of daily living, higher ASA grading, poor mental state, multiple comorbidities, dementia or cognitive impairment, diabetes, cancer and cardiac disease. We also identified 7 moderate evidence and 12 limited evidence mortality predictors, and only the race was identified as the conflicting evidence predictor. Conclusion: Whilst there is no conclusive evidence of the preoperative predictors for mortality following hip fractures, special attention should be paid to the above 12 strong evidence predictors. Future researches were still needed to evaluate the effects of these predictors. ß 2011 Elsevier Ltd. All rights reserved.

Keywords: Hip fracture Predictor Mortality Systematic review Meta-analysis Multivariate analysis

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Search strategy . . . . . . . . . . . . . . . . . . . . . . . Screening on inclusion/exclusion criteria . . Data extraction . . . . . . . . . . . . . . . . . . . . . . . Quality of included studies. . . . . . . . . . . . . . Data analyses and best-evidence synthesis . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Characteristics of the included studies . . . . Quality of included studies. . . . . . . . . . . . . . Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . Evidence level of identified predictors. . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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* Corresponding author. Tel.: +86 01066939439; fax: +86 01088219862. E-mail address: [email protected] (Y. Wang). c The first two authors contributed equally to this work. 0020–1383/$ – see front matter ß 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.injury.2011.05.017

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F. Hu et al. / Injury, Int. J. Care Injured 43 (2012) 676–685

Introduction As an ageing population generally faced, hip fracture is an international public health problem. Worldwide, approximately 1.5 million hip fractures occur each year and is expected to increase to 2.6 million by 2025 and 4.5 million by 2050.1,90 An increased risk of death after hip fracture has been well documented, with 1 year mortality ranging from 8.4% to 36%1 and the risk may persist for several years and even as long as 10 years.1,90 As most of the mortality could be resulted from comorbidities and complications but not fracture itself, it highlights the need to identify those patients who are candidates for interventions in order to reduce their risk for mortality.36,90 Intense controversies are still undergoing about these preoperative risk factors for the high mortality.38,50,69 The presence of concomitant medical illness11,44,49,82 and poor health status24,44,53,71 as negative predictors were reported by numerous studies, advanced age,45,71,75 male gender,3,44,49 poor pre-fracture functional abilities,56,67,71 low preoperative haemoglobin level,38,69 diabetes,67,71 dementia45,96 were also suggested as the predictor of the excess mortality. However, the most predominant of these predictors have not been identified, and whether other factors could be considered as predictors are still unknown, such as fracture type,20,67 low serum albumin11,78 and pre-fracture living residence.15,44 To the best of our knowledge, there has been no systematic evaluation of these preoperative factors to predict the excess mortality. We therefore performed the systematic review of the literature to identify the non-interventional predictors in patients following hip fracture surgery, especially focused on 1 year mortality. This will provide an evidence base from which orthopaedic surgeons could assess the mortality risk for each hip fracture and develop a better intervention strategy.

677

withheld after criteria application. There were 19 multiple publications and eventually 75 studies were included (shown in Fig. 1). Data extraction The two independent reviewers extracted the 94 publications to a standard form. In case of discrepancies, the third reviewer would be involved. We extracted the study characteristics, quality of the study and outcome effects. The outcome effects of particular interest were unadjusted mortality (the absolute, observed mortality rate within a defined study population) and hazard ratio (HR) for specified preoperative exposure calculated by univariate analysis or multivariable Cox proportional hazards model or logistic regression analysis adjusted for other risk factors. Only factors identified by more than one study were included in the final analysis. Preoperative walking capacity, activities of daily living, mental state and cognitive impairment could be judged either by standard grading forms or by patient-reported questionnaires. Quality of included studies Quality of included studies was independently assessed by the two reviewers using a standardised scale. Presented in Table 1, these criteria were designed for quality assessment of observational studies and were used to assess the same components of methodological quality in previous observational systematic reviews.5,22,33,61,97 We modified these criteria to a full score of 9 points to cover the topic of our review. Studies were ranked according to their methodological quality score and high quality studies were judged by multivariate analysis with a quality rank percentage above 70%, presented in Table 2.

Methods

Data analyses and best-evidence synthesis

Search strategy

Given the heterogeneity across the studies with regards to study populations, study design and analytical techniques, we judged it inappropriate to perform a direct meta-analysis. We combined the effects of individual studies with the study characteristics and the study quality score, and summarised the results following the model of ‘‘best-evidence synthesis’’.33,61,97 This is a less common approach but is increasingly recognised as pertinent because it provides a conclusion that incorporates both outcomes and quality of studies.5,33,61,97 Suggested by the US Agency for Healthcare Research and Quality,102 this synthesis enabled the evidence to be rated according to five levels: no, conflicting, limited, moderate or strong evidence,33,61,97 as presented in Table 2. The effects of strong evidence predictors were pooled by high quality studies in which significant differences were reported. Review Manager software (version 5.0.25, Thomson Research Soft, Carlsbad, CA, USA) was used with generic inverse variance of HR (hazard ratio) on log scale (if Odds Ratio was provided instead of HR, we still combined the effects even though we might had overestimated the exposure effect). Random-effects model was used whilst we consider the significant heterogeneity exist in the study population and interventions.

We searched the Pubmed, Embase, Cochrane central database (all to February 26th, 2011) for non-interventional studies exploring the preoperative risk factors. The main key words were ‘‘mortality’’ or ‘‘death’’ or ‘‘survival’’ or ‘‘factor’’ or ‘‘predict’’ or ‘‘risk’’ or ‘‘multivariate’’ or ‘‘regression’’ AND ‘‘hip’’ or ‘‘intertrochanteric’’ or ‘‘femoral neck’’ AND ‘‘fracture’’ or ‘‘surgery’’ or ‘‘operation’’. Screening on inclusion/exclusion criteria To be included, studies had to explore the preoperative predictors for mortality following hip fracture surgery. Noninterventional studies such as cohorts, case-control studies and cross-sectional studies were all eligible for inclusion and the predictors could be identified by controlled groups, univariate analysis or multivariate analysis. Only prospective observational studies and studies with prospectively collected data were included. Exclusion criteria were interventional studies, studies controlled to patients without fractures, sample size < 50 and studies with insufficient outcome data. Only articles published in English (or translation available) were included. Two independent reviewers (F.H. and C.J.) screened the titles and abstracts to determine the relevance to this review. 2076 citations were identified after duplications were excluded. Based on the titles and abstracts, 1837 publications were excluded (if relevance was unclear, a publication was included). Remaining 239 publications were screened by full text. If relevance was unclear, the third reviewer would be involved (J.S.). 145 publications were

Results Characteristics of the included studies A total of 75 studies were included involving 64,316 patients. There were 16 cohorts (involving 12,698 patients), 54 crosssectional studies (50,521 patients) and 5 case-control studies

F. Hu et al. / Injury, Int. J. Care Injured 43 (2012) 676–685

678

Fig. 1. Stepwise literature review procedure.

Table 1 Criteria for assessment of the methodological quality for observational studies.50,22,61,97 Item

Criterion

Points

Study population

Sample size  200 and participation rate  80% For cohort studies: cases and controls drawn from the same population; for case-control and cross-sectional studies: selected group was representative of the general hip fracture population Cohort design Prospective design (not a retrospective study with prospective collected data) Follow-up 1 year Withdrawals and conservative treatment patients 10% Frequencies of most important outcomes were given Multivariate analysis performed, or cohort studies adjusted for at least age and gender Appropriate analysis techniques were used

1 1

Study design

Analysis and data presentation

1 1 1 1 1 1 1

Table 2 Criteria for quality of included studies and best-evidence synthesis.33,61,97 Item

Level

Criteria for inclusion

Level of studies

High quality studies Moderate quality studies

Multivariate analysis performed and had a quality score rank 70% Multivariate analysis performed but a quality score rank <70% or no multivariate analysis performed but a quality score rank 60% No multivariate analysis performed and had a quality score rank <60% Minimum of three high quality studies with generally consistent findings Minimum of three moderate quality studies with generally consistent findings Minimum of two low quality studies with generally consistent findings Converse findings in >25% of the studies No studies could be found

Level of evidence

Low quality studies Strong evidence Moderate evidence Limited evidence Conflicting evidence No evidence

Table 3 Characteristics of the included studies (HF: hip fracture; DB: database; *retrospective study with prospective collected data). N

Setting

Year

Multicenter

Design

Prospective

Study quality (score)

Population: age

Sample (female percent)

Mean age

Follow–up: months (mortality)

Trombetti (2002)96 Wehren (2003),101 et al19,65 Alegre-Lopez (2005)3 Bellelli (2008)7 Carpintero (2005)11 Davis (1987)15

Switzerland American Spain Italy Spain New Zealand

1992–1994 1990–1991 1998 2002–2006 1998–2000 1982–1984

1 8 1 1 1 DB

Cohort Cohort Cross-sectional Cohort Cohort Cross-sectional

Yes Yes Yes Yes Yes Yes

High High High High High High

(9) (9) (8) (8) (8) (8)

HF  55y HF  65y HF  50y HF  65y HF  65y HF  55y

370 804 218 370 165 538

81 81 81.8 80.8 79.3 79

7 8 9 10 11 12 13 14 15 16 17 18

Dolk (1989)20 Elliott (2003)24 Hershkovitz (2010)41 Holvik (2010)44 Hommel (2008)45 Jamal Sepah (2010)49 Kalra (2010)53 Kopp (2009)56 Muraki (2006)67 Paksima (2008),71 et al2,21,26,46,86 Pereira (2010)75 Pioli (2006)78

Sweden Ireland Israel Norway Sweden Pakistan Britain Czech Japan American Brazil Italy

1973–1974 1997–1999 2006–2007 2007–2008 2003–2004 2003–2006 2006–2007 2003–2005 1991–1996 1987–2003 2001 2000–2001

1 2 1 1 1 1 1 1 1 1 4 1

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cohort Cross-sectional Cross-sectional Cross-sectional Case-control Cross-sectional

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

High High High High High High High High High High High High

(8) (8) (8) (8) (8) (8) (8) (8) (8) (8) (8) (8)

HF HF HF HF  65y HF HF  50y HF  60y HF  70y HF HF  65y HF  60y HF  70y

282 (72%) 1780 (76.7%) 376 (75.3%) 567 (77.6%) 420 (68.6%) 366 (61%) 131 (76.3%) 269 (81.4%) 480 (82.7%) 1109 (78.8%) 246 (72.8%) 243 (87.2%)

82.3 85.1 81 67.1 82 81 82.3 80 79.4 83.6

12 (24.3%) 12 (18.7%); 24 (27.1%) 12 (22.5%) 12 (8.1%) 3 (16.4%); 12 (30.3%) Discharge (6.1%);12 (20.4%) 8 (20.6%) 12 (22.0%) 24 (20.8%) 18 (23.5%) 4 (14.7%); 12 (26.4%) 12 (7.8%) 12 (27.0%)

19

Roche (2005),82 et al59,91

Britain

1999–2003

1

Cross-sectional

Yes

High (8)

HF  60y

2448 (79.9%)

82

20

Rosencher (2005)83

France

2002

Cohort

Yes

High (8)

HF

6860 (75.6%)

82

1990–1991

DB: 531 1

12 (11.5%) 12 (11.9%) 12 (35.0%) Discharge (4.9%);12 (25.9%) 1 (9.4%);12 (30.5%); 60 (25.3%) 6 (14.7%)

Cohort

Yes

High (8)

309 (100%)

83

12 (29.5%)

3

Cross-sectional

Yes

High (8)

492 (78.7%)

80

12 (27.2%)

495 288 238 600 103

(73%) (72%) (72.3%) (74.8%) (82.5%)

85 75 81 83 81

(81.4%) (82.4%) (75.8%) (74.9%)

82 82.1 83.4 79.01

12 (26.0%) 6 (16.0%) Discharge (4.6%) 1 (13.5%) Discharge (6.9%); 40 (50.6%) 6 (13.5%) 6 (26.7%) 21 (28.6%) 12 (15.7%); 60 (43.9%) 12 (26.0%) 42 (28.2%) 12 (20.3%)

1 2 3 4 5 6

87

(71.4%) (78.5%) (76.1%) (50%) (51.5%)

Smith (1996)

Britain

22

Withey (1995)103

Britain

23 24 25 26 27

Bentler (2009)8 Elmerson (1988)25 Fisher (2007)27 Foss (2006)30 Furlaneto (2007)31,32

American Sweden Australia Denmark Brazil

1993–2005 1975–1976 2004–2005 2002–2004 2001–2002

DB 2 1 1 1

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cohort

No* Yes Yes Yes Yes

Moderate Moderate Moderate Moderate Moderate

(7) (7) (7) (7) (7)

Female HF  65y Femoral neck  60y HF  80y HF HF  70y HF HF  65y

28 29 30 31

Hannan (2001),38 et al12,23,37 Holmes (2000),68 et al42 Juliebo (2010)51,52 Karagiannis (2006)54

American Britain Norway Greece

1997–1998 1995–1997 2005–2006 1989–1992

4 2 3 1

Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Yes Yes Yes Yes

Moderate Moderate Moderate Moderate

(7) (7) (7) (7)

HF  50y HF  65y HF  65y HF  60y

571 731 364 499

32 33 34

Kreutzfeldt (1984)58 Meyer (2000)63 Ozturk (2010)69

Denmark Norway Turkey

1978 1992–1993 2006

1 2 1

Cross-sectional Cross-sectional Cross-sectional

Yes Yes Yes

Moderate (7) Moderate (7) Moderate (7)

117 (74.8%) 248 74 (70.3%)

79

35 36 37

Peterson (2008)76 Sernbo (1993),85 et al100 Soderqvist (2009),88 et al84

American Sweden Sweden

1982–1985 2003

1 1 4

Cohort Cross-sectional Cross-sectional

Yes Yes No*

Moderate (7) Moderate (7) Moderate (7)

HF  60y HF HF:hemiarthroplasty  65y HF  65y HF HF  65y

105 (79%) 1429 (74.2%) 2134 (72.6%)

79 78 81.4

38 39

Talsnes (2010)93 Tjiang (2003)94

Norway Netherlands

2005–2009 1996–1998

2 1

Case-control Cross-sectional

Yes Yes

Moderate (7) Moderate (7)

302 (75.8%) 146 (77.4%)

84 82

40 41 42 43 44

Todd (1995)95 Vaseenon (2010)99 Bjorkelund (2009)10 Cree (2000)13 da Costa (2009)14

Britain Thailand Sweden Canada Portugal

1998–2003 1999–2001 1996–1997 2007

8 1 1 2 1

Cross-sectional Cross-sectional Cross-sectional Cross-sectional Cross-sectional

Yes Yes No* Yes Yes

Moderate Moderate Moderate Moderate Moderate

HF  75y Femoral neck: hemiarthroplasty HF  65y HF  50y HF  65y HF  64y HF  65y

580 367 428 558 184

80.3 74.6 82.5 81

(7) (7) (6) (6) (6)

(76.9%) (83.1%) (72.9%) (73.8%) (82.3%)

77.9

36 (29.5%) 12 (20.1%) 4 (15.8%); 24 (37.0%) 3 (19.5%) 36 (57.5%) 3 (18.2%) 54 (49.9%) 4 (15.9%) 3 (7.9%) 12 (26.8%)

679

21

F. Hu et al. / Injury, Int. J. Care Injured 43 (2012) 676–685

Study

680

Table 3 (Continued ) Study

Setting

45

Dawson-Bowling (2008)16

Britain

46

de Luise (2008)17,18

Denmark

47 48

Hasegawa (2007)40 Holt (1994)43,55

49 50 51 52

Johansen (2010)50 Maggi (2010)62 Penrod (2008)74 Ristic (2006)81

Year

Multicenter

Design

Prospective

Study quality (score)

Population: age

Sample (female percent)

1

Cohort

Yes

Moderate (6)

108

1998–2003

DB

Cross-sectional

No*

Moderate (6)

Femoral neck  65y HF  40

11,985 (71.4%)

80

Japan Britain

2000 1989–1992

4 2

Cross-sectional Cross-sectional

Yes Yes

Moderate (6) Moderate (6)

HF  50y HF

845 (64.6%) 972 (81%)

80 79

2003–2004 2003–2005 1997–1999

DB 6 13 1

Cross-sectional Cross-sectional Cross-sectional Cross-sectional

No* Yes No* Yes

Moderate Moderate Moderate Moderate

HF HF  50y HF  50y HF  65y

916 (74.1%) 3707 (78.5%) 2692 (79%) 132 (68.9%)

81.3 81.6 76.9

1 (17.6%); 12 (28.3%) 4 (9.0%) Discharge (12.6%); 12 (34.5%) 60 (66.4%) 6 (18.7%) 6 (12.0%) 6 (27.3%)

1989–1990

1 2

Case-control Cross-sectional

Yes Yes

Moderate (5) Moderate (5)

HF  70y Femoral neck  55y Male HF  50y HF  65y Female HF  50y HF  65y HF  65y HF  60y HF  65y HF  60y HF  65y Intertrochanteric  60y HF  55y HF  50y HF  65y Intertrochanteric  60y HF  65y HF HF > 64y HF  70y Femoral neck HF HF  90y

171 (87.7%) 158 (75.9%)

82.4 76.8

Discharge (12.3%) 6 (9.6%)

100 395 (78.2%) 170 (100%)

79.9

24 (58.0%) 12 (8.9%) 12 (18.8%)

53 54

Incalzi (1994) Ions (1987)48

Britain Italy American Serbia and Montenegro Italy Britain

55 56 57

Pande (2006)72 Gruson (2002)34 Haentjens (2007)35

Britain American Belgium

1995–1997 1991–1997 1995–1996

1 DB 4

Cross-sectional Cohort Cohort

Yes No* Yes

Moderate (5) Low (7) Low (7)

Australia Israel American Switzerland Britain Britain Germany

2003–2006 1996–2003 1981–? 2007–2008 2003–2005

1 1 2 1 1 1 1

Cohort Cohort Cross-sectional Case-control Cross-sectional Cohort Cross-sectional

Yes Yes Yes Yes Yes Yes Yes

Low Low Low Low Low Low Low

(7) (7) (7) (7) (6) (6) (6)

Canada Norway American Tunisia

2007–2008 1984–1986 1988–1995

17 DB DB 1

Cross-sectional Cross-sectional Cross-sectional Cross-sectional

No* Yes No* Yes

Low Low Low Low

(5) (5) (5) (5)

Spain American Sweden Netherlands Britain France Spain

1992–1993

1 1 1 1 1 DB: 34 2

Cross-sectional Cohort Cross-sectional Cross-sectional Cross-sectional Cross-sectional Case-control

Yes Yes Yes Yes Yes No* Yes

Low Low Low Low Low Low Low

(5) (5) (5) (5) (5) (4) (4)

58 59 60 61 62 63 64

47

39

Harris (2010) Lieberman (2007)60 Mullen (1992)66 Pretto (2010)80 Bhaskar (2010)9 Pillai (2010)77 Pitto (1994)79 4

65 66 67 68

Alzahrani (2010) Forsen (1999)29 Koval (1999)57 Mnif (2009)64

69 70 71 72 73 74 75

Pages (1998)70 Patterson (1992)73 Svensson (1996)92 van der Veer (1990)98 Wood (1992)104 Baudoin (1996)6 Formiga (2003)28

1985–1987

1991–1992 1982–1985 1992 2000

(6) (6) (6) (6)

666 962 (65.1%) 400 (0%) 272 (77.6%) 791 (81.2%) 1117 (84.6%) 143 (87.4%)

Mean age

Follow–up: months (mortality) Discharge (8.3%)

79

78.4 84

81

2178 (72%) 1825 (73.3%) 490 100 (40%)

79

459 (79.1%) 63 (79.4%) 232 (77.2%) 767 531 (80.8%) 1459 (75.6%) 106 (70.8%)

80.8 73 81

76

77.5 80.6 92.4

12 (24.8%) Discharge (1.2%) 12 (15.0%) 12 (22.0%) 12 (26.4%) 4 (15.1%) 6 (23.1%) Discharge (5.0%) 12 (20.7%) 12 (12.2%) 24 (28.0%) Discharge (6.1%) 12 (24.2%) 12 (12.9%) 3 (24.0%) 6 (22.6%) 24 (38.9%) 3 (19.8%)

F. Hu et al. / Injury, Int. J. Care Injured 43 (2012) 676–685

N

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Table 4 Distribution of the quality of included studies and involved patients. Study quality

Study number (%) Total studies (%) Total patients (%)

High quality

Moderate quality

Low quality

9 points

8 points

7 points

6 points

5 points

7 points

6 points

5 points

4 points

2 (2.7%) 22 (29.3%) 18,843 (29.3%)

20 (26.7%)

19 (25.3%)

11 (14.7%) 33 (44.0%) 32,176 (50.3%)

3 (4.0%)

6 (8.0%)

3 (4.0%) 20 (26.7%) 13,297 (20.4%)

9 (12.0%)

2 (2.7%)

(1097 patients). 65 studies based on prospective design and 10 retrospective studies using prospectively collected data. Presented in Table 3, there were 14 studies undertaken in Britain, 10 in American, 7 in Sweden, 5 in Norway, 4 respectively in Italy and Spain, 3 in Denmark, 2 respectively in Australia, Brazil, Canada, France, Israel, Japan, Netherlands, Switzerland. The sample size ranged from 6373 to 11,98518 patients, and 31 studies based on multi-centre design. For the population characteristics, 68 studies were taken amongst hip fractures, 5 amongst femoral neck frac-

tures16,48,94,103,104 and two amongst intertrochanteric fractures.64,79 Most patients were female, and the female percentage was 61%49– 87.7%47 with a total of 75.3% after gender selected studies were excluded. Average age ranged from 67.149 to 85.144 with a mean of 80.6 after age selected studies were excluded. Quality of included studies According to our methodological quality assessment criteria for observational studies, 2 (2.4%) studies scored 9 points, 20 (23.8%)

Table 5 Strong evidence predictive factors associated with the excess mortality following senile hip fractures (HR: hazard ratio; CI: confidence interval; ASA: American Anaesthetists Society score). Factors related to excess mortality

Patient number of high quality studies

Patient number of moderate quality studies

Patient number of low quality studies

Advanced aged

1 year: 849715,24,45,49,56,67,71,75,82,96,103 3 months: 714220,83 Pooled HR by per year: 1.05, 95% CI: (1.03, 1.08): 11,01924,45,67,71,83,96 Pooled HR by >80 controlled to <80: 2.15, 95% CI: (1.65, 2.80): 318675,82,103 1 year: 84403,24,44,45,49,56,67,71,82,101 3 months: 714220,83 Pooled HR controlled to female: 1.70, 95% CI: (1.42, 2.04): 60463,44,45,67,71,82,101 1 year: 110515,44

16,7508,10,13,14,25,30,40,42,43,48,50,52,54,58,62,74,76,85,88,93–95,99

61596,28,29,43,47,64,66,72,73,77,79,80,104

16,1778,10,11,13,25,40,42,43,50,52,54,58,62,69,74,81,85,88,93,95,99

255414,28,29,70

13,87225,30,38,40,42,44,48,50,82,83

52364,13,39,52,72,80,98,104

2 years: 264082 1 year: 503145,56,67,71,82,87

15,33610,13,30,38,40,41,43,52,58,62,63,81,83,94,101

240428,43,66,72,73,76,80,104

3 months: 28220 1 year: 27363,24,75,103

311010,38,48,85,95

122563,70,72,80,94

1 year: 358724,44,53,71

525510,30,40,50,69,76,88,93,94

202539,52,66,98

3 months: 686083 2 years: 804101 Pooled HR for 3–4 grades controlled to 1–2 grades: 1.73, 95% CI: (1.53, 1.96): 823144,83,101 1 year: 79923,11,44,49,56,78,82,87,103

131713,40

391210,48,66,70,79,88,104

2 years: 804101 Pooled HR: 1.78, 95% CI: (1.45, 2.20): 350744,82,103 1 year: 452911,44,49,56,78,82,103

49828,38,42,71,81,88

405813,28,62,64,69,72,79,80,92

2 years: 804101 1 year: 180815,45,67,96

18,5198,18,30,32,41,42,44,81,87,88,101

120910,28,80,104

Male gender

Nursing home or facility living residence Poor preoperative walking capacity Poor activities of daily living Higher ASA grading

Poor mental state

Multiple comorbidities Dementia or cognitive impairment

Diabetes

Cancer Cardiac disease

3 months: 686083 2 years: 37641 Pooled HR: 1.89, 95% CI: (1.51, 2.37): 850641,45,67,83,96 1 year: 403767,71,82 Pooled HR: 1.44, 95% CI: (1.13, 1.82): 403767,71,82 1 year: 355771,82 3 months: 686083 1 year: 199215,49,71 3 months: 686083

24675

16,04818,44,74,101

93848,66,104

14,12718,52,54,95,101

40066

F. Hu et al. / Injury, Int. J. Care Injured 43 (2012) 676–685

682

Fig. 2. Combined effect of advanced age on the excess mortality pooled by hazard ratio using random-effects model (subgroup: hazard ratio by per year and by >80 years controlled to <80 years).

studies scored 8 points, 25 (29.8%) studies 7 points, 14 (16.7%) studies 6 points, 12 (14.3%) studies 5 points and 2 (2.4%) studies 4 points. As presented in Table 4, according to the quality assessment criteria, 22 (29.3%) were deemed as high quality studies involving 18,843 (29.3%) patients, 33 (44.0%) as moderate quality studies involving 32,176 (50.3%) patients, and 20 (26.7%) as low quality studies involving 13,297 (20.4%) patients. Mortality The follow-up period varied from discharge4,16,27,47,60,70 to 5 years54,82,99 and 48% of the included studies were 12 months. The inpatient or 1 month mortality was 13.3% (calculated by a total of 20,988 patients, 1.2%60–16.3%47), 3–6 months 15.8% (total 21,823 patients, 7.9%13–26.7%42), 1 year 24.5% (total 31,895 patients, 7.8%49–35%75), 2 years 34.5% (total 5075 patients, 20.8%41– 58.0%72), 3–5 years 38.1% (total 4987 patients, 25.3%82–66.4%50). Evidence level of identified predictors There were 31 potential risk factors identified by more than one study and were included in the final analysis. As shown in Table 5, 12 were identified as strong evidence predictors. Advanced age was presented as a mortality predictor in 13 high quality studies involving 15,639 patients, and the pooled HR was 1.05 (95% CI: 1.03–1.08) per year24,45,67,71,83,96 and 2.15 (95% CI: 1.65–2.80) for aged >80 years controlled to <80 years75,82,103 (presented in

Fig. 2). Male gender as a mortality predictor was supported in 12 high quality studies involving 15,582 patients, and the pooled HR was 1.70 (95% CI: 1.42–2.04) 3,44,45,67,71,82,101 controlled to female patients (presented in Fig. 3). Nursing home or facility residence was supported by 3 high quality studies involving 3745 patients. Poor preoperative walking capacity was identified in 7 high quality studies involving 5313 patients, and poor activities of daily living was identified in 4 high quality studies involving 2736 patients. Higher ASA (American Anaesthetists Society score) grading was presented as a mortality predictor in 6 high quality studies involving 11,251 patients, and the pooled HR was 1.73 (95% CI: 1.53–1.96)44,83,101 for 3–4 grades controlled to 1–2 grades. Poor mental state was supported in 10 high quality studies involving 8796 patients, and the pooled HR was 1.78 (95% CI: 1.45– 2.20).44,82,103 Multiple comorbidities was supported in 8 high quality studies involving 5333 patients. Dementia or cognitive impairment was identified in 6 high quality studies involving 9044 patients, and the pooled HR was 1.89 (95% CI: 1.51– 2.3741,45,67,83,96). Diabetes as a mortality predictor in 3 high quality studies (4073 patients, pooled HR: 1.44, 95% CI: 1.13– 1.8267,71,82). Cancer was supported in 3 high quality studies (10,417 patients) and cardiac disease in 4 high quality studies (8852 patients). Presented in Table 6, there were 7 moderate evidence mortality predictors identified, including intertrochanteric fracture (versus femoral neck fracture), low body mass index, low serum albumin or malnutrition, low haemoglobin, high serum creatinine, chronic

Fig. 3. Combined effect of male gender on the excess mortality pooled by hazard ratio using random-effects model.

F. Hu et al. / Injury, Int. J. Care Injured 43 (2012) 676–685

683

Table 6 Moderate, limited and conflicting evidence predictive factors associated with the excess mortality following senile hip fractures. Evidence level

Factors related to excess mortality

Moderate evidence

Intertrochanteric fracture (versus femoral neck) Low body mass index Low serum albumin or mulnutrition Low haemoglobin High serum creatinine Chronic renal disease Chronic pulmonary disease Living alone Previous year hospital admission Poor social function Smokers Low blood lymphocyte count High serum potassium High serum troponin T High heart rate at admittance Cerebrovascular disease Digestive disease Delirium Depression Race: whites or not

Limited evidence

Conflicting evidence

Patient number of high quality studies 56220,67 720549,83 40811,78

244882 244882

Patient number of moderate quality studies 154338,43 105140,52 187941,69,85 107310,38,69 973610,82,83 15,56618,32,74,101 15,38118,74,101

42045

Patient number of low quality studies 17035

157547,52,57,63,66,73 16509,34,47,52 40066 69552,104 14596

41214,63

244882

53815

804101 16511 23911,69

14379 12669,57

244882 34616,27 29252

29252

105075,101

90147,66,104 40066 10628

48067 73142 2117

renal disease and chronic pulmonary disease. 12 limited evidence mortality predictors were identified, including living alone, previous year hospital admission, poor social function, smokers, low blood lymphocyte count, high serum potassium, high serum troponin T, high heart rate at admittance, cerebrovascular disease, digestive disease, delirium and depression. Only the race was identified as the conflicting evidence predictor. Discussion Most cases of hip fractures arise because of low-enegry trauma in individuals with bone fragility. The goal of the treatment is to return patients to their prefracture functional levels without mortality and long-term disability. The frail old people with a number of underlying medical conditions might not withstand the acute complications associated with fracture thus may die rapidly after surgery.1,90 Of the 75 included studies involving 64,316 patients, the overall inpatient or 1 month mortality was 13.3%, 3– 6 months was 15.8%, 1 year 24.5% and 2 years 34.5%. By conducting a systematic review of the current evidence base, we have identified 12 strong evidence mortality predictors, including advanced age, male gender, nursing home or facility residence, poor preoperative walking capacity, poor activities of daily living, higher ASA grading, poor mental state, multiple comorbidities, dementia or cognitive impairment, diabetes, cancer and cardiac disease. Besides the 12 strong evidence predictors, we identified 7 moderate evidence and 12 limited evidence mortality predictors, only the race was identified as the conflicting evidence predictor. Our review has raised a number of questions. Besides the well interpreted predictors such as advanced age, male gender, higher ASA grading, multiple comorbidities, cancer and cardiac disease, other 6 factors were also identified as strong evidence predictors such as nursing home or facility residence, poor preoperative walking capacity, poor activities of daily living, poor mental state, dementia or cognitive impairment and diabetes. Although maybe not independent risk factors, as poor preoperative walking capacity could be interpreted as poor activities of daily living, dementia could be interpreted as poor mental state, these predictors could resulted in excess mortality. Furthermore, we

269274

57138

identified nursing home or facility residence and diabetes as mortality predictors, a better understanding of these prognostic factors could help to identify patients at different degrees of risk and help to develop intervention strategies. To our knowledge, the results reported here represent the first systematic analysis for predictors of excess mortality associated with hip fracture. We only included observational studies with prospectively collected data, for a retrospective data collection might result in a substantial incomplete detection of the preoperative exposures. We did not exclude the retrospective studies (10 studies) because the outcome of death was less likely to be influenced by the study design if only the preoperative exposures were collected prospectively. In agreement with other systematic reviews, Abrahamsen1 reviewed 63 studies and reported that both excess and unadjusted mortality rates during the index hospitalisation and in the months and years following the index hip fracture, especially for the advanced age and male patients. Haentjens36 found a 5–8 fold increased risk for all-cause mortality during the first 3 months after hip fracture, and at any given age, excess annual mortality after hip fracture was higher in men than women. Another systematic review conducted by Sterling90 found the mortality risk in men was as much as twice that of women, and he also found a conflicting evidence in the race aspects. Spahn89 conducted a systematic review and found perioperative anaemia was associated with increased mortality in senile hip and knee surgery patients. All the above systematic reviews partly met with our results. This systematic review had several limitations. Firstly, systematic reviews of observational studies remain a contentious issue in research.5,22,33,97 Although our study quality assessment criteria and the best-evidence synthesis have already been adopted by several reviews,5,22,33,61,97 the methods are still under intensive controversy. Secondly, as this review was restricted to observational studies, identification of potential forms of bias was important. Observational studies were sensitive to selection, performance, detection, publication bias and confounding. Publication bias was predominant in the research area, not only significant findings were more readily published, but also most of the authors were only to present significant results by the

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multivariate analysis. Also, there was a potential risk of patient selection problems especially the single centre based studies. Thirdly, the review was limited by significant heterogeneity in the study population, preoperative exposure measurements, followup periods and analysis methodology. The measurements of preoperative exposures such as preoperative walking capacity, activities of daily living, mental state and cognitive impairment differed greatly from each other, either by standard grading forms or by patient-reported questionnaires. Follow-up periods ranged from the duration of the inpatient stay to 5 years, and the adjustments for age, gender and comorbid conditions had not been adopted by some studies. Finally, calculation of pooled estimates for prognostic studies is challenging and discouraged by some, primarily due to the heterogeneity and varying methodological quality of included studies. Despite the clear heterogeneity of the studies, we conducted a meta-analysis to combine the effects of strong evidence predictors only with the high quality studies in which significant differences were reported (for most of the negative results were not reported). This must had overestimated the predict effects and should be interpreted with caution. Furthermore, we pooled OR as HR in three studies,24,101,103 and this might have also overestimated the pooled effects. All results of this review should be interpreted within the above limitations. Implications This systematic review and meta-analysis provided an overview of current knowledge concerning preoperative non-interventional predictors for mortality following hip fractures. Of the 75 included studies involving 64,316 patients, the overall inpatient or 1 month mortality was 13.3%, 3–6 months was 15.8%, 1 year 24.5% and 2 years 34.5%. The available observations is a heterogeneous group, whilst there is no conclusive evidence, we have identified 12 strong evidence predictors, including advanced age, male gender, nursing home or facility residence, poor preoperative walking capacity, poor activities of daily living, higher ASA grading, poor mental state, multiple comorbidities, dementia or cognitive impairment, diabetes, cancer and cardiac disease. We also identified 7 moderate evidence and 12 limited evidence mortality predictors, only the race was identified as the conflicting evidence predictor. We believe disclosure of these data will lead to a better understanding of conditions of the patients and help to develop a better intervention strategy. Future researches are still needed to evaluate the effects of these predictors. They should base on a prospective design, with a large sample size, concentrate both on short-term and long-term mortality and multivariate analysis should be conducted to adjust at least age, gender, and comorbidities. The population characteristics should be clearly presented, preoperative exposures such as preoperative walking capacity, activities of daily living, mental state and cognitive impairment should be measured using a standardised method, details of interventions should be carefully specified and randomised, and the multivariate analysis results should be completely presented including the negative factors. Meanwhile, the reasons for the excess mortality should be explored as to whether the mortality was a direct consequence of hip fracture or those resulted from pre-existing/comorbid medical conditions. References 1. Abrahamsen B, van Staa T, Ariely R, et al. Excess mortality following hip fracture: a systematic epidemiological review. Osteoporos Int 2009;20:1633– 50. 2. Aharonoff GB, Koval KJ, Skovron ML, Zuckerman JD. Hip fractures in the elderly: predictors of one year mortality. J Orthop Trauma 1997;11:162–5.

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