Systematic review and meta-analysis of preoperative predictors for early mortality following hip fracture surgery

Abstract

Hip fractures are a global health problem with a high postoperative mortality rate. Preoperative predictors for early mortality could be used to optimise and personalise healthcare strategies. This study aimed to identify predictors for early mortality following hip fracture surgery. Cohort studies examining independent preoperative predictors for mortality following hip fracture surgery were identified through a systematic search on Scopus and PubMed. Predictors for 30-day mortality were the primary outcome, and predictors for mortality within 1 year were secondary outcomes. Primary outcomes were analysed with random-effects meta-analyses. Confidence in the cumulative evidence was assessed using the GRADE criteria. Secondary outcomes were synthesised narratively. Thirty-three cohort studies involving 462,699 patients were meta-analysed. Five high-quality evidence predictors for 30-day mortality were identified: age per year (OR: 1.06, 95% CI: 1.04-1.07), ASA score ≥ 3 (OR: 2.69, 95% CI: 2.12-3.42), male gender (OR: 2.00, 95% CI: 1.85-2.18), institutional residence (OR: 1.81, 95% CI: 1.31-2.49), and metastatic cancer (OR: 2.83, 95% CI: 2.58-3.10). Additionally, six moderate-quality evidence predictors were identified: chronic renal failure, dementia, diabetes, low haemoglobin, heart failures, and a history of any malignancy. Weak evidence was found for non-metastatic cancer. This review found relevant preoperative predictors which could be used to identify patients who are at high risk of 30-day mortality following hip fracture surgery. For some predictors, the prognostic value could be increased by further subcategorising the conditions by severity.

Keywords: Hip fracture; Meta-analysis; Mortality; Older adults; Risk factors; Systematic review.

Fig. 1

PRISMA flow diagram describing the identification, screening, and selection of articles

Fig. 2

Unweighted risk of bias summary of the studies included in the meta-analysis of predictors for 30-day mortality

Fig. 3

Forest plots of high-quality evidence predictors for 30-day mortality following hip fracture surgery. The right panel depicts the risk of bias assessments according to the bias domains of the Quality in Prognosis Studies tool, i.e. study participation (D1), study attrition (D2), prognostic factor measurement (D3), outcome measurement (D4), study confounding (D5), and statistical analysis and reporting (D6). The risk of bias levels of low, moderate, and high were colour-coded in green, yellow, and red, respectively