Fit-for-Discharge Criteria after Esophagectomy: An International Expert Delphi Consensus
Bibliographic record
Abstract
There are no internationally recognized criteria available to determine preparedness for hospital discharge after esophagectomy. This study aims to achieve international consensus using Delphi methodology. The expert panel consisted of 40 esophageal surgeons spanning 16 countries and 4 continents. During a 3-round, web-based Delphi process, experts voted for discharge criteria using 5-point Likert scales. Data were analyzed using descriptive statistics. Consensus was reached if agreement was ≥75% in round 3. Consensus was achieved for the following basic criteria: nutritional requirements are met by oral intake of at least liquids with optional supplementary nutrition via jejunal feeding tube. The patient should have passed flatus and does not require oxygen during mobilization or at rest. Central venous catheters should be removed. Adequate analgesia at rest and during mobilization is achieved using both oral opioid and non-opioid analgesics. All vital signs should be normal unless abnormal preoperatively. Inflammatory parameters should be trending down and close to normal (leucocyte count ≤12G/l and C-reactive protein ≤80 mg/dl). This multinational Delphi survey represents the first expert-led process for consensus criteria to determine 'fit-for-discharge' status after esophagectomy. Results of this Delphi survey may be applied to clinical outcomes research as an objective measure of short-term recovery. Furthermore, standardized endpoints identified through this process may be used in clinical practice to guide decisions regarding patient discharge and may help to reduce the risk of premature discharge or prolonged admission.
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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 | 0.182 | 0.135 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".