Emergency Colectomies in the Elderly Population—Perioperative Mortality Risk-Factors and Long-Term Outcomes
Bibliographic record
Abstract
BACKGROUND: As the population ages emergency surgeries among the elderly population, including colonic resections, is also increasing. Data regarding the short- and long-term outcomes in this population is scarce. METHODS: A retrospective study was performed to investigate mortality and mortality risk factors associated with emergent colectomies in older compared to younger patients in a single university affiliated tertiary hospital. Patients with metastatic disease, colectomy due to trauma or index colectomy within 30 days prior to emergent surgery were excluded. RESULTS: Operative outcomes compared among age groups, included 30-day mortality, mortality risk-factors and long-term survival. 613 eligible patients were included in the cohort. Mean age was 69.4 years, 45.1% were female. Patients were divided into four age groups: 18-59, 60-69, 70-79 and ≥80-years. Thirty-day mortality rates were 3.2%, 11%, 29.3% and 37.8%, respectively and 22% for the entire cohort. Risk-factors for perioperative death in the younger group were related to severity of ASA score and WBC count. In groups 60-69, 70-79, main risk-factors were ADL dependency and ASA score. In the ≥80 group, risk-factors affecting perioperative mortality, included ASA score, pre-operative albumin, creatinine, WBC levels, cancer etiology, ADL dependency, and dementia. Long-term survival differed significantly between age groups. CONCLUSION: Perioperative mortality with emergency colectomy increases with patients' age. Patients older than eighty-years undergoing urgent colectomies have extremely high mortality rates, leading to a huge burden on medical services. Evaluating risk-factors for mortality and pre-operative discussion with patients and families is important. Screening the elderly population for colonic pathologies can result in early diagnosis potentially leading to elective surgeries with decreased mortality.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".