Outcome 1 year after digestive surgery in malnourished, elderly patients, with an emphasis on quality of life analysis
Bibliographic record
Abstract
BACKGROUND: Quality of life data after digestive surgery in malnourished, elderly patients are rarely reported. What can we expect as 1-year outcomes in these high-risk patients after digestive surgery? METHODS: We conducted a prospective observational study in a digestive surgery department in a tertiary, nonacademic hospital in Mulhouse, France. Malnourished, older patients (according to the Nutritional Risk Index) undergoing digestive surgery between November 2007 and December 2008 were included and followed up for 1 year. Quality of life was measured by the European Organization for Research and Treatment of Cancer QLQ-C30 questionnaire at the end of the study period. RESULTS: We included 37 patients with a median age of 76 (range 66-86) years in our study. The mean global health status and quality of life score in 17 of 24 living patients 1 year after surgery was 68.6 (standard deviation [SD] 12.4), and no difference with the score of a reference population 70.8 (SD 22.1) was observed (p = 0.68). In-hospital mortality was 11% and morbidity was 70%. CONCLUSION: The present study suggests that despite high postoperative mortality and morbidity, an acceptable quality of life can be achieved in malnourished, elderly survivors of digestive surgery.
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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) | 0.001 | 0.001 |
| 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) | 0.001 | 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".