Surgery for pancreatic neuroendocrine tumors during the COVID-19 pandemic: a retrospective cohort from a high-volume center
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Bibliographic record
Abstract
During the COVID-19 pandemic, pancreatic surgery for pancreatic neuroendocrine tumors (PNETs) with surgical indications was postponed or canceled. Patients with PNET patients who underwent pancreatic surgery during the COVID-19 restriction period (3 years) were compared with a similar cohort of patients who underwent surgery in the previous 3 years. Data on patients' characteristics, waiting time, and surgical and pathology outcomes were evaluated. During the study period, 370 patients received surgery for PNETs, 205 (55%) during the first period, and 165 (45%) during the pandemic. A lengthening of the waiting list (182 [IQR 100-357] vs. 60 [40-88] days, p < 0.001) and increased use of anti-tumor medical treatments (any therapy, peptide receptor radionuclide therapy, and somatostatin analogs; all p < 0.001) was found. During the pandemic, surgery occurred after a median of 381 days [IQR 200-610] from diagnosis (vs. 103 [IQR 52-192] of the pre-COVID-19 period, p < 0.001). No statistically significant differences in tumor size and grading distribution were found between the two periods (both p > 0.05), yet only a modest increase of the median Ki67 values in cases operated during the pandemic (4% vs. 3%, p = 0.03). Lastly, these latter patients experienced less major postoperative complications (13% vs. 24%, p = 0.007). During COVID-19, the surgical waiting list of PNET patients was drastically extended, and bridge therapies were preferred. This did not result in more advanced cases at final pathology. PRRT and SSA are valid alternative therapies for PNETs when surgery is not feasible.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it