Modified Frailty Index to Assess Risk in Elderly Patients Undergoing Distal Pancreatectomy: A Retrospective Single‐Center Study
Bibliographic record
Abstract
BACKGROUND: To compare the postoperative course of elderly patients (≥70 years) submitted to minimally invasive (MIDP) versus open distal pancreatectomy (ODP) and to evaluate if the modified Frailty Index (mFI) predicts the surgical course of elderly patients submitted to DP. METHODS: Data of patients aged ≥70 who underwent DP at a single institution between March 2011 and December 2019 were retrospectively retrieved. A 2:1 propensity score matching (PSM) was used to correct for differences in baseline characteristics. Then, postoperative complications were compared between the two groups (MIDP vs. ODP). Additionally, the entire cohort of DP elderly patients was stratified according to the mFI into three groups: non-frail (mFI = 0), mildly frail (mFI = 1/2), or severely frail (mFI = 3) and then compared. RESULTS: A total of 204 patients were analyzed. After PSM, 40 MIDP and 80 ODP patients were identified. The complications considered stratified homogenously between the two groups, with no statistically significant differences. The severity of the postoperative course increased as mFI did among the three groups regarding any complication (p = 0.022), abdominal collection (p = 0.014), pulmonary complication (p = 0.001), postoperative confusion (p = 0.047), Clavien-Dindo severity ≥3 events (p = 0.036), and length of stay (p = 0.018). CONCLUSIONS: Elderly patients can be safely submitted to MIDP. The mFI identifies frail elderly patients more prone to develop surgical and non-surgical complications after DP.
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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 | 0.001 | 0.001 |
| 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".