Should we routinely screen for frailty prior to gynecologic oncology surgery? Frailty as a potential predictor of adverse postoperative outcomes in elderly patients.
Bibliographic record
Abstract
6517 Background: Frailty is increasingly recognized as an adverse prognostic factor of postoperative morbidity and survival in several surgical disciplines. There is no consensus on routine frailty screening in Gynecologic Oncology. Our goal was to evaluate the predictive role of the National Surgical Quality Improvement Program(NSQIP) comorbidity-based modified Frailty Index-5(mFI-5) in Gynecologic Oncology patients over the age of 70. Methods: Elective laparotomies between 01/2016-09/2020 at the Juravinski Hospital in Hamilton, ON were reviewed using prospectively-collected NSQIP data and chart review. Complication severity was assessed by Clavidien-Dindo classification. The primary outcome was rate of 30-day grade III-V complications. Secondary outcomes were: grade II-V complications, myocardial injury, length of stay(LOS), non-home discharge, and non-initiation/non-completion of adjuvant chemotherapy. Logistic regression analysis was performed. Survival analysis and receiver-operator characteristic curves are underway. Results: In this cohort of 259 patients, frail patients(mFI-5≥2) were at significantly greater risk of grade III-V complications (OR23.77, 95%CI 9.69-66.26, p < 0.0001), grade II-V complications (OR3.8, 95%CI 1.96-7.85, p = 0.0002), myocardial injury (OR3.44, 95%CI 1.66-7.05, p = 0.0009), LOS≥5days (OR2.96, 95%CI 1.61-5.52, p = 0.0006), non-home discharge (OR7.37, 95%CI 2.81-20.46, p < 0.0001), and non-initiation/non-completion of chemotherapy (OR7.34, 95%CI 2.43-23.06, p = 0.0006), than non-frail patients on univariate analysis(UVA). On multivariable analysis, frailty remained independently associated with grade II-V complications and grade III-V complications (OR4.64, 95%CI 2.31-9.94, p < 0.0001, controlling for stage, operative duration and intraoperative complication, and OR24.49, 95%CI 9.72-70.67, p < 0.0001, adjusting for BMI, stage and operative duration, respectively). On UVA, age, surgical complexity score, and smoking were not predictive of complications. Frailty also independently predicted non-home discharge (OR7.37, 95%CI 2.81-20.46, p < 0.0001) when adjusting for age. Conclusions: Frailty as assessed with mFI-5, independent of age, strongly predicted morbidity and non-home discharge after Gynecologic Oncology surgery. Strategies for perioperative optimization could help address these disparities. mFI-5 is a concise tool that can be used for routine frailty screening and risk stratification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".