Hiatal hernia after robotic-assisted coronary artery bypass graft surgery
Bibliographic record
Abstract
BACKGROUND: The aim of the present study is to determine the incidence/progression of hiatal hernia (HH) after robotic-assisted coronary artery bypass grafting (RA-CABG) surgery. METHODS: We reviewed the pre- and post-operative computed tomography (CT) of 491 patients who underwent RA-CABG between 2000 and 2017. Post-operative CT was acquired prospectively in a research protocol. CT was reviewed to assess the presence and the size of HH. RESULTS: We found 444/491 (90.4%) had pre-operative CT, while 201/491 (40.9%) had post-operative CT. In total, 155/491 (31.6%) had both pre- and long-term post-operative CT with a mean follow-up of 6.2 (±3.5) years. HH was more prevalent on post-operative CT, 64/155 (41.3%) compared to pre-operative CT, 44/155 (28.4%), P<0.0001. The diameter of pre-existing HH 2.8 (±1.8) cm was significantly greater after surgery 3.9 (±2.5) cm, P<0.0001. As well the volume of the pre-existing HH 5.8 (4.4-9.2) mL (quartile) was significantly greater after surgery 14.1 (7.2-64.9) mL, P<0.0001. 20/155 (12.9%) had a newly developed HH after RA-CABG. A binary multivariate regression including HH risk factors showed that male gender is a predictor of developing a HH after RA-CABG with Hazard Ratio of 3.038, confidence interval (1.10-8.43), P=0.033. CONCLUSIONS: RA-CABG is associated with an increased risk of developing HH and increases the size of pre-existing HH.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 teacher head, 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".