Impact of hematologic inflammatory markers on the prognosis of geriatric hip fracture: a systematic review and meta-analysis
Bibliographic record
Abstract
Geriatric hip fractures pose a significant health burden, and inflammation may play a role in the short- and long-term prognosis. However, the prognostic significance of hematologic inflammatory markers in geriatric patients with fractures is not understood. The aim of this systematic review and meta-analysis was to assess the prognostic implications of systemic inflammatory markers on the long-term mortality of older patients with hip fractures. PubMed, EMBASE, and Cochrane CENTRAL were searched from inception to December 19, 2023. Prospective, retrospective cohort, and case–control studies investigating the prognostic impact of hematologic inflammatory markers on mortality after hip fracture were eligible. Pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were calculated to determine the associations between the markers and mortality risk, with heterogeneity assessed by I 2 statistic. The quality of the studies was appraised using the Newcastle–Ottawa Scale. Ultimately, 7 retrospective studies involving a total of 7212 patients were included. The meta-analysis revealed that the neutrophil-to-lymphocyte ratio (NLR) (HR = 1.04, 95% CI 1.02–1.08), systemic immune–inflammatory index (SII) (HR = 1.03, 95% CI 1.01–1.05), and red cell distribution width (RDW) (HR = 1.07, 95% CI 1.01–1.14) independently correlated with increased long-term mortality. Elevated NLR, SII, and RDW are independently associated with increased long-term mortality in older patients with hip fractures. These findings imply the potential value of incorporating these inflammatory indicators to aid in prognostic stratification of geriatric patients with hip fractures.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".