Impact of frailty on hiatal hernia repair: a nationwide analysis of in-hospital clinical and healthcare utilization outcomes
Bibliographic record
Abstract
Previous studies recommend a watch-and-wait approach to paraesophageal hernia (PEH) repair due to an increased risk for mortality. While contemporary studies suggest that elective surgery is safe and effective, many patients presenting with PEH are elderly. Therefore, we assessed the impact of frailty on in-hospital outcomes and healthcare utilization among patients receiving PEH repair. This retrospective population-based cohort study assessed patients from the National Inpatient Sample database who received PEH repair between October 2015 to December 2019. Demographic and perioperative data were gathered, and frailty was measured using the 11-item modified frailty index. The outcomes measured were in-hospital mortality, complications, discharge disposition, and healthcare utilization. Overall, 10,716 patients receiving PEH repair were identified, including 1442 frail patients. Frail patients were less often female and were more often in the lowest income quartile compared to robust patients. Frail patients were at greater odds for in-hospital mortality [odds ratio (OR) 2.83 (95% CI 1.65-4.83); P < 0.001], postoperative ICU admissions [OR 2.07 (95% CI 1.55-2.78); P < 0.001], any complications [OR 2.18 (95% CI 1.55-2.78); P < 0.001], hospital length of stay [mean difference (MD) 1.75 days (95% CI 1.30-2.210; P < 0.001], and total admission costs [MD $5631.65 (95% CI $3300.06-$7.963.24); P < 0.001] relative to their robust patients. While PEH repair in elderly patients is safe and effective, frail patients have an increased rate of in-hospital mortality, postoperative ICU admissions, complications, and total admission costs. Clinicians should consider patient frailty when identifying the most appropriate surgical candidates for PEH repair.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".