Benchmarking Complications Associated with Esophagectomy
Bibliographic record
Abstract
OBJECTIVE: Utilizing a standardized dataset with specific definitions to prospectively collect international data to provide a benchmark for complications and outcomes associated with esophagectomy. SUMMARY OF BACKGROUND DATA: Outcome reporting in oncologic surgery has suffered from the lack of a standardized system for reporting operative results particularly complications. This is particularly the case for esophagectomy affecting the accuracy and relevance of international outcome assessments, clinical trial results, and quality improvement projects. METHODS: The Esophageal Complications Consensus Group (ECCG) involving 24 high-volume esophageal surgical centers in 14 countries developed a standardized platform for recording complications and quality measures associated with esophagectomy. Using a secure online database (ESODATA.org), ECCG centers prospectively recorded data on all resections according to the ECCG platform from these centers over a 2-year period. RESULTS: Between January 2015 and December 2016, 2704 resections were entered into the database. All demographic and follow-up data fields were 100% complete. The majority of operations were for cancer (95.6%) and typically located in the distal esophagus (56.2%). Some 1192 patients received neoadjuvant chemoradiation (46.1%) and 763 neoadjuvant chemotherapy (29.5%). Surgical approach involved open procedures in 52.1% and minimally invasive operations in 47.9%. Chest anastomoses were done most commonly (60.7%) and R0 resections were accomplished in 93.4% of patients. The overall incidence of complications was 59% with the most common individual complications being pneumonia (14.6%) and atrial dysrhythmia (14.5%). Anastomotic leak, conduit necrosis, chyle leaks, recurrent nerve injury occurred in 11.4%, 1.3%, 4.7%, and 4.2% of cases, respectively. Clavien-Dindo complications ≥ IIIb occurred in 17.2% of patients. Readmissions occurred in 11.2% of cases and 30- and 90-day mortality was 2.4% and 4.5%, respectively. CONCLUSION: Standardized methods provide contemporary international benchmarks for reporting outcomes after esophagectomy.
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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 | 0.016 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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 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".