Association Between Familiarity of the Surgeon-Anesthesiologist Dyad and Postoperative Patient Outcomes for Complex Gastrointestinal Cancer Surgery
Bibliographic record
Abstract
Importance: The surgeon-anesthesiologist teamwork and relationship is crucial to good patient outcomes. Familiarity among work team members is associated with enhanced success in multiple fields but rarely studied in the operating room. Objective: To examine the association between surgeon-anesthesiologist dyad familiarity-as the number of times working together-with short-term postoperative outcomes for complex gastrointestinal cancer surgery. Design, Setting, and Participants: This population-based retrospective cohort study based in Ontario, Canada, included adults undergoing esophagectomy, pancreatectomy, and hepatectomy for cancer from 2007 through 2018. The data were analyzed January 1, 2007, through December 21, 2018. Exposures: Dyad familiarity captured as the annual volume of procedures of interest done by the surgeon-anesthesiologist dyad in the 4 years before the index surgery. Main Outcomes and Measures: Ninety-day major morbidity (any Clavien-Dindo grade 3 to 5). The association between exposure and outcome was examined using multivariable logistic regression. Results: Seven thousand eight hundred ninety-three patients with a median age of 65 years (66.3% men) were included. They were cared for by 737 anesthesiologists and 163 surgeons who were also included. The median surgeon-anesthesiologist dyad volume was 1 (range, 0-12.2) procedures per year. Ninety-day major morbidity occurred in 43.0% of patients. There was a linear association between dyad volume and 90-day major morbidity. After adjustment, the annual dyad volume was independently associated with lower odds of 90-day major morbidity, with an odds ratio of 0.95 (95% CI, 0.92-0.98; P = .01) for each incremental procedure per year, per dyad. The results did not change when examining 30-day major morbidity. Conclusions and Relevance: Among adults undergoing complex gastrointestinal cancer surgery, increasing familiarity of the surgeon-anesthesiologist dyad was associated with improved short-term patient outcomes. For each additional time that a unique surgeon-anesthesiologist dyad worked together, the odds of 90-day major morbidity decreased by 5%. These findings support organizing perioperative care to increase the familiarity of surgeon-anesthesiologist dyads.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".