Seasonal variations in pancreatic surgery outcome A retrospective time-trend analysis of 2748 Whipple procedures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Observing cyclic patterns in surgical outcome is a common experience. We aimed to measure this phenomenon and to hypothesize possible causes using the experience of a high-volume pancreatic surgery department. METHODS: Outcomes of 2748 patients who underwent a Whipple procedure at a single high-volume center from January 2000 to December 2018 were retrospectively analyzed. Three different hypotheses were tested: the effect of climate changes, the "July effect" and the effect of vacations. RESULTS: Clavien-Dindo ≥ 3 morbidity was similar during warm vs. cold months (22.5% vs. 19.8%, p = 0.104) and at the beginning of activity of new trainees vs. the rest of the year (23.5 vs. 22.5%, p = 0.757). Patients operated when a high percentage of staff is on vacation showed an increased Clavien-Dindo ≥ 3 morbidity (22.3 vs. 18.5%, p = 0.022), but similar mortality (2.3 vs. 1.8%, p = 0.553). The surgical waiting list was also significantly longer during these periods (37 vs. 27 days, p = 0.037). Being operated in such a period of the year was an independent predictor of severe morbidity (OR 1.271, CI 95% 1.086-1.638, p = 0.031). CONCLUSION: Being operated when more staff is on vacation significantly affects severe morbidity rate. Future healthcare system policies should prevent the relative shortage of resources during these periods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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 it