Population-based study of the impact of small bowel obstruction due to adhesions on short- and medium-term mortality
Bibliographic record
Abstract
BACKGROUND: Small bowel obstruction due to adhesions (aSBO) is a common indication for admission to a surgical unit. Despite the prevalence of this condition, the short- and medium-term survival of this patient population has not been well described. The purpose of this study was to measure the short- and medium-term survival of patients admitted to hospital with aSBO. METHODS: Linked administrative data were used to identify patients admitted to hospital in Ontario, Canada, for aSBO between 2005 and 2011. Patients were divided into two groups: those aged less than 65 years (younger group) and those aged 65 years and older (older group). Thirty-day, 90-day and 1-year mortality rates were estimated. One-year mortality was compared with that in the general population, adjusting for age and sex. The timing of deaths in relation to admission was assessed, as well as the proportion of patients discharged before experiencing short-term mortality. RESULTS: There were 22 197 patients admitted to hospital for aSBO for the first time in the study interval. Mean age was 64·5 years and 52·2 per cent of the patients were women. Overall, the 30-day, 90-day and 1-year mortality rates for the cohort were 5·7 (95 per cent c.i. 5·4 to 6·0), 8·7 (8·3 to 9·0) and 13·9 (13·4 to 14·3) per cent respectively. For both groups, the 1-year risk of death was significantly greater than that of the age-matched general population. The majority of deaths (62·5 per cent) occurred within 90 days of admission, with 36·4 per cent occurring after discharge from the aSBO admission. CONCLUSION: Patients admitted with aSBO have a high short-term mortality rate. Increased monitoring of patients in the early period after admission is advisable.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".