Frailty in inflammatory bowel disease: analysis of the National Inpatient Sample 2015–2019
Bibliographic record
Abstract
AIM: Preoperative frailty has been associated with adverse postoperative outcomes in various populations, but of its use in patients with inflammatory bowel disease (IBD) remains sparse. The present study aimed to characterize the impact of frailty, as measured by the modified frailty index (mFI), on postoperative clinical and resource utilization outcomes in patients with IBD. METHODS: This retrospective population-based cohort study assessed patients from the National Inpatient Sample database from 1 September 2015 to 31 December 2019. Corresponding International Classification of Diseases 10th Revision Clinical Modification codes were used to identify adult patients (>18 years of age) with IBD, undergoing either small bowel resection, colectomy or proctectomy. Patient demographics and institutional data were collected for each patient to calculate the 11-point mFI. Patients were categorized as either frail or robust using a cut-off of 0.27. Primary outcomes were postoperative in-hospital morbidity and mortality, whilst secondary outcomes included system-specific morbidity, length of stay, in-hospital healthcare costs and discharge disposition. Logistic and linear regression models were used for primary and secondary outcomes. RESULTS: Overall, 7144 patients with IBD undergoing small bowel resection, colectomy or proctectomy were identified, 337 of whom were classified as frail (i.e., mFI < 0.27). Frail patients were more likely to be women, older, have lower income and a greater number of comorbidities. After adjusting for relevant covariates, frail patients were at greater odds of in-hospital mortality (adjusted odds ratio [aOR] 5.42, 95% CI 2.31-12.77, P < 0.001), overall morbidity (aOR 1.72, 95% CI 1.30-2.28, P < 0.001), increased length of stay (adjusted mean difference 1.3 days, 95% CI 0.09-2.50, P = 0.035) and less likely to be discharged to home (aOR 0.59, 95% CI 0.45-0.77, P < 0.001) compared to their robust counterparts. CONCLUSIONS: Frail IBD patients are at greater risk of postoperative mortality and morbidity, and reduced likelihood of discharge to home, following surgery. This has implications for clinicians designing care pathways for IBD patients following surgery.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".