Author’s Reply: Management of Enterocutaneous Fistula: Outcomes in 276 Patients
Bibliographic record
Abstract
We thank Pham and Canada for their interest in our paper [1].We do have more data about the details of the parenteral nutrition (PN) in our patients but had not analysed this since the focus of the paper was not the content of the parenteral nutrition.All patients in our study had parenteral nutrition for gastroduodenal or small bowel fistula, though for variable periods of time.This defined entry to the study group.In patients whose fistulas closed with conservative treatment, PN/nil orally was continued until the fistula closed.If the fistula failed to close by 60 days and sepsis was controlled, oral intake was re-introduced.In patients whose fistula output remained low enough to allow maintenance of fluid and nutritional status without intravenous supplement, PN was discontinued.The results section of the original paper provides details of those who remained on PN either as inpatients or outpatients prior to definitive surgery.Parenteral nutrition was prescribed by the multidisciplinary team.Dietitians estimated the requirements for protein at 0.2-0.3gN (1.25-1.9g protein)/Kg body weight with adjustments for BMI [ 30 and energy using the Henry equation with stress and activity factors added as required (A Pocket Guide to Clinical Nutrition.British
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".