Association of frailty with healthcare utilization and days alive at home in patients with gynecologic cancers: a population-based study
Bibliographic record
Abstract
OBJECTIVE: Existing research on frailty in Gynecologic Oncology is largely limited to short-term metrics and lacks comprehensive analysis of long-term patient-important outcomes and healthcare resource use. We sought to evaluate the association of frailty with days alive at home, healthcare costs, and other healthcare utilization indicators within 1 year after gynecologic oncology laparotomy. STUDY DESIGN: Using province-wide administrative data, we identified patients who underwent laparotomy for gynecologic malignancy between 2009 and 2021. Frailty was defined using the preoperative frailty index and the John Hopkins Adjusted Clinical Groups frailty indicator. RESULTS: Among the 21,359 patients, 1405 (6.6%) and 1144 (5.4%) were classified as frail using the preoperative frailty index and Adjusted Clinical Groups, respectively. Frail patients had fewer days alive at home both within the first 30 days postsurgery (preoperative frailty index: mean 16.4 vs 23.0 days, P<.0001; Adjusted Clinical Groups: 17.7 vs 22.8 days, P<.0001) and from 31 to 365 days postsurgery (preoperative frailty index: 234.5 vs 308.2 days, P<.0001; preoperative frailty index: 248.0 vs 306.5 days, P<.0001), than those who were not frail. In multivariate analysis, frailty was significantly associated with days alive at home within 31 to 365 days of surgery (preoperative frailty index: rate ratio, 0.86; 95% confidence interval [CI], 0.85-0.86; P<.0001, Adjusted Clinical Groups: rate ratio,0.87; 95% CI, 0.86-0.87; P<.0001) when adjusting for age, income quintile, primary cancer, cancer stage, neoadjuvant chemotherapy, type of surgery, and comorbidities. Frailty was also associated with increased need for home care, with frail patients more likely to have required any home care in the year prior to surgery (preoperative frailty index: 53.8% vs 9.6%, P<.0001; Adjusted Clinical Groups: 39.9% vs 10.9%, P<.0001) and at any time prior to surgery (preoperative frailty index: 72.3% vs 19.4%, P<.0001; Adjusted Clinical Groups: 58.9% vs 20.8%, P<.0001). Both frailty indexes were associated with an increase in total mean healthcare costs between 31 to 365 days after surgery (preoperative frailty index: $26,351 vs $9,853, P<.0001, Adjusted Clinical Groups: $23,922 vs $10,203, P<.0001). This remained significant on multivariate analysis (preoperative frailty index: cost rate ratio, 1.65; 95% CI, 1.53-1.77; P<.0001, Adjusted Clinical Groups: cost rate ratio, 1.83; 95% CI, 1.7-1.97; P<.0001). CONCLUSION: Frailty was significantly associated with fewer days alive at home, increased need for home care, as well as higher healthcare costs. This highlights the critical need for tailored interventions to address frailty in this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".