Variation in Quality of Care after Emergency General Surgery Procedures in the Elderly
Bibliographic record
Abstract
BACKGROUND: The elderly (age ≥65 years) comprise an increasing proportion of patients undergoing emergency general surgery (EGS) procedures and have distinct needs compared with the young. We postulated that the needs of the elderly require different processes of care than those required for the young to assure optimal outcomes. To explore this hypothesis, we evaluated 30-day outcomes following EGS procedures in the young and the elderly and determined whether hospital performance was consistent across these 2 age strata. STUDY DESIGN: With data from the American College of Surgeons National Surgical Quality Improvement Program (2005 to 2008), regression models were constructed for serious morbidity and mortality for all patients undergoing EGS procedures and separately for young and elderly patients. These models allowed for estimation of the risk of adverse outcomes associated with advanced age and the generation of hospital-level observed to expected (O/E) ratios. We evaluated the correlation between hospital O/E ratios for the young and the elderly and the concordance of outlier status (hospitals with CIs of O/E ratios excluding 1) with weighted κ across these 2 age groups. RESULTS: Among 68,003 procedures at 186 hospitals, elderly patients had a higher crude and adjusted risk for serious morbidity (27.9% versus 9.7%, p < 0.0001; odds ratio 1.17, 95% CI 1.10 to 1.24) and mortality (15.2% versus 2.5%, p < 0.0001; odds ratio 2.29, 95% CI 2.09 to 2.51). When outcomes for elderly versus younger patients were compared, there was fair to moderate agreement on hospital performance for serious morbidity (r = 0.43; κ = 0.30) but not for mortality (r = 0.10; κ = 0.17). CONCLUSIONS: Elderly patients are at substantially greater risk for adverse events following EGS procedures. Hospitals had only slight agreement in mortality outcomes in the elderly compared with those in young patients. Processes of care that may account for this disparity should be further investigated.
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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 | 0.004 | 0.014 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".