190. IMPLEMENTATION OF THE ESOPHAGECTOMY COMPLICATIONS CONSENSUS GROUP DEFINITIONS: THE BENEFITS OF SPEAKING THE SAME LANGUAGE
Bibliographic record
Abstract
Abstract In 2015 the Esophagectomy Complications Consensus Group (ECCG) reported consensus definitions for complications after oesophagectomy. This aimed to reduce variation in complication reporting, attributed to heterogeneous definitions. This systematic review aimed to describe the implementation of this definition-set, including the effect on complication frequency and variation. A systematic literature review was performed, identifying all observational and randomised studies reporting complication frequencies after oesophagectomy since the ECCG publication. Recruitment periods before and subsequent to the index ECCG publication date were included. Coefficients of variance were calculated to assess outcome heterogeneity. Study quality was assessed using the Newcastle-Ottawa score. Of 144 studies which met inclusion criteria, 70 (48.6%) used ECCG definitions. The median number of separately reported complication types was five per study; only one study reported all ECCG complications. The coefficients of variance of the reported frequencies of eight of the ten most common complications was reduced in ECCG adopting studies vs non-adopting studies (p = 0.036) (see Figure 1). Among ECCG studies, the frequencies of post-operative pneumothorax, re-intubation and pulmonary emboli were reduced in 2020–2021, compared to 2015–2019 (p = 0.006, 0.034 and 0.037 respectively). There was no difference in the quality of ECCG adopting studies and non-adopting studies. The ECCG definition-set has reduced variation in oesophagectomy morbidity reporting. This adds greater confidence to the observed gradual improvement in outcomes with time, and its ongoing use and wider dissemination should be encouraged. However, only a handful of outcomes are widely reported, and only rarely is it used in its entirety.
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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 | 0.188 | 0.337 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".