Reduced morbidity for elderly patients with a hip fracture after implementation of a perioperative evidence-based clinical pathway
Bibliographic record
Abstract
BACKGROUND: Hip fractures, common in the elderly population, result in significant morbidity and mortality. A study was undertaken to determine how an evidence based clinical pathway (CP) for treatment of elderly patients with hip fracture affected morbidity, in-hospital mortality, and health service utilization. METHODS: A pre-post study design using two population based inception cohorts of hip fracture patients aged > or =65 years was used. The control group (n = 678) was enrolled between July 1996 and September 1997 before implementation of the pathway and the CP group (n = 663) was enrolled between July 1999 and September 2000 following pathway implementation. Chart reviews were completed during study time frames to determine complications, mortality, and health service utilization. RESULTS: Only nine patients (1%) in the CP group experienced postoperative congestive heart failure compared with 37 (5%) control patients (p<0.001). Postoperative cardiac arrythmias were significantly lower in the CP group than in the control group (8 (1%) v 36 (5%); p<0.001). Postoperative delirium occurred in 22% of the CP group and 51% of the control group (p<0.001). There was no difference in risk adjusted in-hospital mortality between the two groups. Overall length of stay (LOS) and costs were unchanged between the groups; however, hospital LOS increased while rehabilitation LOS decreased in the CP group. CONCLUSION: Implementation of an evidence based clinical pathway reduced postoperative morbidity and did not affect in-hospital mortality or overall costs of inpatient care. The effect of changing trends in medical care cannot be ruled out, but the reduction in complications in several clinical areas lends support to the positive impact of the clinical pathway. Perioperative CP is one successful management approach for this fragile patient population as patient morbidity was reduced without negatively affecting resource utilization.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".