A Population-based Comparative Effectiveness Study of Peripheral Nerve Blocks for Hip Fracture Surgery
Bibliographic record
Abstract
BACKGROUND: Adverse outcomes and resource use rates are high after hip fracture surgery. Peripheral nerve blocks could improve outcomes through enhanced analgesia and decreased opioid related adverse events. We hypothesized that these benefits would translate into decreased resource use (length of stay [primary outcome] and costs), and better clinical outcomes (pneumonia and mortality). METHODS: The authors conducted a retrospective cohort study of hip fracture surgery patients in Ontario, Canada (2011 to 2015) using linked health administrative data. Multilevel regression, instrumental variable, and propensity scores were used to determine the association of nerve blocks with resource use and outcomes. RESULTS: The authors identified 65,271 hip fracture surgery patients; 10,030 (15.4%) received a block. With a block, the median hospital stay was 7 (interquartile range, 4 to 13) days versus 8 (interquartile range, 5 to 14) days without. Following adjustment, nerve blocks were associated with a 0.6-day decrease in length of stay (95% CI, 0.5 to 0.8). This small difference was consistent with instrumental variable (1.1 days; 95% CI, 0.9 to 1.2) and propensity score (0.2 days; 95% CI, 0.2 to 0.3) analyses. Costs were lower with a nerve block (adjusted difference, -$1,421; 95% CI, -$1,579 to -$1,289 [Canadian dollars]), but no difference in mortality (adjusted odds ratio, 0.99; 95% CI, 0.89 to 1.11) or pneumonia (adjusted odds ratio, 1.01; 95% CI, 0.88 to 1.16) was observed. CONCLUSIONS: Receipt of nerve blocks for hip fracture surgery is associated with decreased length of stay and health system costs, although small effect sizes may not reflect clinical significance for length of stay.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".