Long-term survival in high-risk older adults following emergency general surgery admission
Bibliographic record
Abstract
BACKGROUND: Emergency general surgery (EGS) conditions are increasingly common among nursing home residents. While such patients have a high risk of in-hospital mortality, long-term outcomes in this group are not well described, which may have implications for goals of care discussions. In this study, we evaluate long-term survival among nursing home residents admitted for EGS conditions. METHODS: We performed a population-based, retrospective cohort study of nursing home residents (65 years or older) admitted for one of eight EGS diagnoses (appendicitis, cholecystitis, strangulated hernia, bowel obstruction, diverticulitis, peptic ulcer disease, intestinal ischemia, or perforated viscus) from 2006 to 2018 in a large regional health system. The primary outcome was 1-year survival. To ascertain the effect of EGS admission independent of baseline characteristics, patients were matched to nursing home residents without an EGS admission based on demographics and baseline health. Kaplan-Meier analysis was used to evaluate survival across groups. RESULTS: A total of 7,942 nursing home residents (mean age, 85 years) were admitted with an EGS diagnosis and matched to controls. One quarter of patients underwent surgery, and 18% died in hospital. At 1 year, 55% of cases were alive, compared with 72% of controls (p < 0.001). Among those undergoing surgery, 61% were alive at 1 year, compared with 72% of controls (p < 0.001). The 1-year survival probability was 57% in patients who did not require mechanical ventilation, 43% in those who required 1 to 2 days of ventilation, and 30% in those who required ≥3 days of ventilation. CONCLUSION: Although their risk of in-hospital mortality is high, most nursing home residents admitted for an EGS diagnosis survive at least 1 year. While nursing home residents presenting with an EGS diagnosis should be cited realistic odds for the risk of death, long-term survival is achievable in the majority of these patients. LEVEL OF EVIDENCE: Epidemiological, level III.
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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 | 0.003 |
| 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 | 0.001 | 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".