Analysis of postdischarge costs following emergent general surgery in elderly patients
Bibliographic record
Abstract
Background: As populations age, more elderly patients will undergo surgery. Frailty and complications are considered to increase in-hospital cost in older adults, but little is known on costs following discharge, particularly those borne by the patient. We examined risk factors for increased cost and the type of costs accrued following discharge in elderly surgical patients. Methods: Acute abdominal surgery patients aged 65 years and older were prospectively enrolled. We assessed baseline clinical characteristics, including Clinical Frailty Scale (CFS) scores. We calculated 6-month cost (in Canadian dollars) from patient-reported use following discharge according to the validated Health Resource Utilization Inventory. Primary outcomes were 6-month overall cost and cost for health care services, medical products and lost productive hours. Outcomes were log-transformed and assessed in multivariable generalized linear and zero-inflated negative binomial regressions and can be interpreted as adjusted ratios (AR). Complications were assessed according to Clavien–Dindo classification. Results: We included 150 patients (mean age 75.5 ± 7.6 yr; 54.1% men) in our analysis; 10.8% had major and 43.2% had minor complications postoperatively. The median 6-month overall cost was $496 (interquartile range $140–$1948). Disaggregated by cost type, frailty independently predicted increasing costs of health care services (AR 1.76, 95% confidence interval [CI] 1.43–2.18, p < 0.001) and medical products (AR 1.61, 95% CI 1.15–2.25, p = 0.005), but decreasing costs in lost productive hours (AR 0.39, p = 0.002). Complications did not predict increased cost. Conclusion: Frail patients accrued higher health care services and product costs, but lower costs from lost productive hours. Interventions in elderly surgical patients should consider patient-borne cost in older adults and lost productivity in less frail patients. Trial registration NCT02233153 (clinicaltrials.gov).
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".