O-POSSUM and P-POSSUM as predictors of morbidity and mortality in older patients after hip fracture surgery: a meta-analysis

Arch Orthop Trauma Surg. 2023 Nov;143(11):6837-6847. doi: 10.1007/s00402-023-04897-9. Epub 2023 May 10.

Abstract

Background: The POSSUM model has been widely used to predict morbidity and mortality after general surgery. Modified versions known as O-POSSUM and P-POSSUM have been used extensively in orthopedic surgery, but their accuracy is unclear. This systematic review evaluated the predictive value of these models in older patients with hip fractures.

Methods: This study was performed and reported based on the "Preferred reporting items for systematic reviews and meta-analyses" guidelines. PubMed, Cochrane, EMBASE, and Web of Science were comprehensively searched for relevant studies, whose methodological quality was evaluated according to the "Methodological index for non-randomized studies" scale. Revman 5 was used to calculate weighted ratios of observed to expected morbidity or mortality.

Results: The meta-analysis included 10 studies, of which nine (2549 patients) assessed the ability of O-POSSUM to predict postoperative morbidity, nine (3649 patients) assessed the ability of O-POSSUM to predict postoperative mortality, and four (1794 patients) assessed the ability of P-POSSUM to predict postoperative mortality. The corresponding weighted ratios of observed to expected morbidity or mortality were 0.84 (95% CI 0.70-1.00), 0.68 (95% CI 0.49-0.95), and 0.61 (95% CI 0.16-2.38).

Conclusions: While O-POSSUM shows reasonable accuracy in predicting postoperative morbidity in older patients with hip fractures, both P-POSSUM and O-POSSUM substantially overestimate postoperative mortality. The POSSUM model should be optimized further for this patient population.

Keywords: Hip fracture; Morbidity; Mortality; Older patients; POSSUM.

Publication types

  • Systematic Review
  • Meta-Analysis

MeSH terms

  • Aged
  • Hip Fractures* / surgery
  • Humans
  • Morbidity
  • Postoperative Complications / epidemiology
  • Risk Assessment
  • Severity of Illness Index