Association of Hospital-level Neuraxial Anesthesia Use for Hip Fracture Surgery with Outcomes
Bibliographic record
Abstract
BACKGROUND: There is consistent and significant variation in neuraxial anesthesia use for hip fracture surgery across jurisdictions. We measured the association of hospital-level utilization of neuraxial anesthesia, independent of patient-level use, with 30-day survival (primary outcome) and length of stay and costs (secondary outcomes). METHODS: We conducted a population-based cohort study using linked administrative data in Ontario, Canada. We identified all hip fracture patients more than 65 yr of age from 2002 to 2014. For each patient, we measured the proportion of hip fracture patients at their hospital who received neuraxial anesthesia in the year before their surgery. Multilevel, multivariable regression was used to measure the association of log-transformed hospital-level neuraxial anesthetic-use proportion with outcomes, controlling for patient-level anesthesia type and confounders. RESULTS: Of 107,317 patients, 57,080 (53.2%) had a neuraxial anesthetic; utilization varied from 0 to 100% between hospitals. In total, 9,122 (8.5%) of patients died within 30 days of surgery. Survival independently improved as hospital-level neuraxial use increased (P = 0.009). Primary and sensitivity analyses demonstrated that most of the survival benefit was realized with increase in hospital-level neuraxial use above 20 to 25%; there did not appear to be a substantial increase in survival above this point. No significant associations between hospital neuraxial anesthesia-use and other outcomes existed. CONCLUSIONS: Hip fracture surgery patients at hospitals that use more than 20 to 25% neuraxial anesthesia have improved survival independent of patient-level anesthesia type and other confounders. The underlying causal mechanism for this association requires a prospective study to guide improvements in perioperative care and outcomes of hip fracture patients. VISUAL ABSTRACT: An online visual overview is available for this article at http://links.lww.com/ALN/B634.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".