Prognostic factors of functional outcome after hip fracture surgery: a systematic review
Bibliographic record
Abstract
Objective: this systematic review aimed to identify immutable and modifiable prognostic factors of functional outcomes and their proposed mechanism after hip fracture surgery. Design: systematic search of MEDLINE, Embase, CINAHL, PEDRO, OpenGrey and ClinicalTrials.gov for observational studies of prognostic factors of functional outcome after hip fracture among surgically treated adults with mean age of 65 years and older. Study selection, quality assessment, and data extraction were completed independently by two reviewers. The Quality in Prognosis Studies Tool was used for quality assessment and assigning a level of evidence to factors. Proposed mechanisms for reported associations were extracted from discussion sections. Results: from 33 studies of 9,552 patients, we identified 25 prognostic factors of functional outcome after hip fracture surgery. We organised factors into groups: demographics, injury and comorbidities, body composition, complications, and acute care. We assigned two factors a weak evidence level-anaemia and cognition. We assigned Parkinson's disease an inconclusive evidence level. We could not assign an evidence level to the remaining 22 factors due to the high risk of bias across studies. Frailty was the proposed mechanism for the association between anaemia and functional outcome. Medication management, perceived potential, complications and time to mobility were proposed as mechanisms for the association between cognition and functional outcome. Conclusion: we identified one modifiable and one immutable prognostic factor for functional outcomes after hip fracture surgery. Future research may target patients with anaemia or cognitive impairment by intervening on the prognostic factor or the underlying mechanisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".