Health Economic Implications of Perioperative Delirium in Older Patients After Surgery for a Fragility Hip Fracture
Bibliographic record
Abstract
BACKGROUND: Patients who experience a fragility hip fracture are at high risk for perioperative delirium. The purpose of the present study was to evaluate the impact, from a hospital perspective, of perioperative delirium on the length of the hospital stay and episode-of-care costs for elderly patients who underwent surgical treatment of a fragility hip fracture. METHODS: A total of 242 patients sixty-five years of age or older (mean age, eighty-two years; range, sixty-five to 103 years) who underwent surgical treatment of a fragility hip fracture at a single center between January 2011 and December 2012 were evaluated. Demographic, clinical, surgical, and adverse-events data were extracted and analyzed. The confusion assessment method (CAM) was used prospectively to detect perioperative delirium. RESULTS: One hundred and sixteen (48%) of the 242 patients developed perioperative delirium during their stay in the hospital. Compared with patients with no delirium, delirium was associated with a mean incremental total length of hospital stay of 7.4 days (95% confidence interval [CI] = 3.7 to 11.2 days; p < 0.001), a mean incremental length of stay following surgery of 7.4 days (95% CI = 3.8 to 11.1 days; p < 0.001), and a mean incremental episode-of-care cost (in 2012 Canadian dollars) of $8286 (95% CI = $3690 to $12,881; p < 0.001). The total incremental episode-of-care cost attributable to delirium over the study period was $961,131 in 2012 Canadian dollars. CONCLUSIONS: Nearly 50% of elderly patients who underwent surgery for a fragility hip fracture developed perioperative delirium, which was associated with a significant incremental in-hospital length of stay and significant incremental episode-of-care costs. These findings highlight the importance of implementing cost-effective interventions to reduce the prevalence of perioperative delirium in elderly patients with a low-energy hip fracture.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".