A comparison of the left thoracoabdominal and Ivor–Lewis esophagectomy
Bibliographic record
Abstract
The purpose of this study was to assess the oncological outcomes of a large multicenter series of left thoracoabdominal esophagectomies, and compare these to the more widely utilized Ivor-Lewis esophagectomy. With ethics approval and an established study protocol, anonymized data from five centers were merged into a structured database. The study exposure was operative approach (ILE or LTE). The primary outcome measure was time to death. Secondary outcome measures included time to tumor recurrence, positive surgical resection margins, lymph node yield, postoperative death, and hospital length of stay. Cox proportional hazards models provided hazard ratios (HR) with 95% confidence intervals (CI) adjusting for age, pathological tumor stage, tumor grade, lymphovascular invasion, and neoadjuvant treatment. Among 1228 patients (598 ILE; 630 LTE), most (86%) had adenocarcinoma (AC) and were male (81%). Comparing ILE and LTE for AC patients, no difference was seen in terms of time to death (HR 0.904 95%CI 0.749-1.1090) or time to recurrence (HR 0.973 95%CI 0.768-1.232). The risk of a positive resection margin was also similar (OR 1.022 95%CI 0.731-1.429). Median lymph node yield did not differ between approaches (LTE 21; ILE 21; P = 0.426). In-hospital mortality was 2.4%, significantly lower in the LTE group (LTE 1.3%; ILE 3.6%; P = 0.004). Median hospital stay was 11 days in the LTE group and 14 days in the ILE group (P < 0.0001). In conclusion, this is the largest series of left thoracoabdominal esophagectomies to be submitted for publication and the only one to compare two different transthoracic esophagectomy strategies. It demonstrates oncological equivalence between operative approaches but possible short- term advantages to the left thoracoabdominal 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".