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Systematic review of multivariable prognostic models for outcomes at least 30 days after hip fracture finds 18 mortality models but no nonmortality models warranting validation.
Walsh, Mary E; Kristensen, Pia Kjær; Hjelholt, Thomas J; Hurson, Conor; Walsh, Cathal; Ferris, Helena; Crozier-Shaw, Geoff; Keohane, David; Geary, Ellen; O'Halloran, Amanda; Merriman, Niamh A; Blake, Catherine.
Affiliation
  • Walsh ME; School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, D04 C7X2, Ireland. Electronic address: m.walsh@ucd.ie.
  • Kristensen PK; The Department of Clinical Medicine, Orthopaedic, Aarhus University, DK-8200, Aarhus, Denmark.
  • Hjelholt TJ; Department of Geriatrics, Aarhus University Hospital, DK-8200, Aarhus, Denmark.
  • Hurson C; Department of Trauma and Orthopaedics, St Vincent's University Hospital, Dublin D04 T6F4, Ireland.
  • Walsh C; School of Medicine, Trinity College Dublin, Dublin, Ireland.
  • Ferris H; Department of Public Health, Health Service Executive - South West, St. Finbarr's Hospital, Cork, T12 XH60, Ireland.
  • Crozier-Shaw G; Department of Trauma and Orthopaedics, Mater Misercordiae University Hospital, Eccles Street, Dublin, Ireland.
  • Keohane D; Department of Orthopaedics, St. James' Hospital, Dublin, Ireland.
  • Geary E; Department of Trauma and Orthopaedics, St Vincent's University Hospital, Dublin D04 T6F4, Ireland.
  • O'Halloran A; Royal College of Surgeons in Ireland, Dublin, Ireland.
  • Merriman NA; School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, D04 C7X2, Ireland.
  • Blake C; School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, D04 C7X2, Ireland.
J Clin Epidemiol ; 173: 111439, 2024 Jun 24.
Article in En | MEDLINE | ID: mdl-38925343
ABSTRACT

OBJECTIVES:

Prognostic models have the potential to aid clinical decision-making after hip fracture. This systematic review aimed to identify, critically appraise, and summarize multivariable prediction models for mortality or other long-term recovery outcomes occurring at least 30 days after hip fracture. STUDY DESIGN AND

SETTING:

MEDLINE, Embase, Scopus, Web of Science, and CINAHL databases were searched up to May 2023. Studies were included that aimed to develop multivariable models to make predictions for individuals at least 30 days after hip fracture. Risk of bias (ROB) was dual-assessed using the Prediction model Risk Of Bias ASsessment Tool. Study and model details were extracted and summarized.

RESULTS:

From 5571 records, 80 eligible studies were identified. They predicted mortality in n = 55 studies/81 models and nonmortality outcomes (mobility, function, residence, medical, and surgical complications) in n = 30 studies/45 models. Most (n = 46; 58%) studies were published since 2020. A quarter of studies (n = 19; 24%) reported using 'machine-learning methods', while the remainder used logistic regression (n = 54; 68%) and other statistical methods (n = 11; 14%) to build models. Overall, 15 studies (19%) presented 18 low ROB models, all predicting mortality. Common concerns were sample size, missing data handling, inadequate internal validation, and calibration assessment. Many studies with nonmortality outcomes (n = 11; 37%) had clear data complexities that were not correctly modeled.

CONCLUSION:

This review has comprehensively summarized and appraised multivariable prediction models for long-term outcomes after hip fracture. Only 15 studies of 55 predicting mortality were rated as low ROB, warranting further development of their models. All studies predicting nonmortality outcomes were high or unclear ROB. Careful consideration is required for both the methods used and justification for developing further nonmortality prediction models for this clinical population.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Clin Epidemiol Journal subject: EPIDEMIOLOGIA Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Clin Epidemiol Journal subject: EPIDEMIOLOGIA Year: 2024 Document type: Article