Reoperation after oesophageal cancer surgery in relation to long-term survival: a population-based cohort study
Bibliographic record
Abstract
OBJECTIVES: The influence of reoperation on long-term prognosis is unknown. In this large population-based cohort study, it was aimed to investigate the influence of a reoperation within 30 days of oesophageal cancer resection on survival even after excluding the initial postoperative period. DESIGN: This was a nationwide population-based retrospective cohort study. SETTING: All hospitals performing oesophageal cancer resections during the study period (1987-2010) in Sweden. PARTICIPANTS: Patients operated for oesophageal cancer with curative intent in 1987-2010. PRIMARY AND SECONDARY OUTCOMES: Adjusted HRs of all cause, early and late mortality up to 5 years after reoperation following oesophageal cancer resection. RESULTS: Among 1822 included patients, the 200 (11%) who were reoperated had a 27% increased HR of all-cause mortality (adjusted HR 1.27, 95% CI 1.05 to 1.53) and 28% increased HR of disease-specific mortality (adjusted HR 1.28, 95% CI 1.04 to 1.59), compared to those not reoperated. Reoperation for anastomotic insufficiency in particular was followed by an increased mortality (adjusted HR 1.82, 95% CI 1.19 to 2.76). CONCLUSIONS: This large and population-based nationwide cohort study shows that reoperation within 30 days after primary oesophageal resection was associated with increased mortality, even after excluding the initial 3 months after surgery. This finding stresses the need to consider any actions that might prevent complications and reoperation after oesophageal cancer resection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".