Costs of complications following distal pancreatectomy: a systematic review
Bibliographic record
Abstract
BACKGROUND: Postoperative complications following distal pancreatectomy (DP) are common, especially postoperative pancreatic fistula (POPF). In order to design adequate prophylactic strategies, it is of relevance to determine the costs of these complications. An overview of the literature on the costs of complications following DP is lacking. METHODS: A systematic literature search was performed in PubMed, Embase, and Cochrane Library (inception until 1 August 2022). The primary outcome was the costs (i.e. cost differential) of major morbidity, individual complications and prolonged hospital stay. Quality of non-RCTs were assessed using the Newcastle-Ottawa scale. Costs were compared with the use of Purchasing Power parity. This systematic review was registered with PROSPERO (CRD42021223019). RESULTS: Overall, seven studies were included with 854 patients after DP. The rate POPF grade B/C varied between 13% and 27% (based on five studies) with a corresponding cost differential of EUR 18,389 (based on two studies). The rate of severe morbidity varied between 13% and 38% (based on five studies) with a corresponding cost differential of EUR 19,281 (based on five studies). CONCLUSION: This systematic review reported considerable costs for POPF grade B/C and severe morbidity after DP. Prospective databases and studies should report on all complications in a uniform matter to better display the economic burden of complications of 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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".