Morbid obesity is adversely associated with perioperative outcomes in patients undergoing robot-assisted laparoscopic radical prostatectomy
Bibliographic record
Abstract
INTRODUCTION: Robot-assisted laparoscopic radical prostatectomy (RALRP) may be more challenging in obese individuals. This study aimed to evaluate whether obesity had an adverse effect on perioperative outcomes following RALRP. METHODS: Hospitalized patients who underwent RALRP from 2008-2014 were identified using the National Inpatient Sample database. We grouped RALRP patients into non-obese, obesity class I-II, and obesity class III (morbid obesity). Rates of blood transfusion, intraoperative and postoperative complications, in-hospital mortality, prolonged length of stay, and total costs were compared among the three groups by univariate regression, multivariate regression, and propensity score weighting analysis. RESULTS: Of 53 301 patients identified, 48 725 were non-obese, 3572 were diagnosed with obesity class I-II, and 1004 were diagnosed with morbid obesity. Compared to non-obesity (7.62%), overall postoperative complications were commonly observed in obesity class I-II (10.55%) and morbid obesity (17.11%). Multivariable analyses suggested that morbid obesity was associated with increased overall postoperative (odds ratio [OR] 2.00, 95% confidence interval [CI] 1.65-2.42), cardiac (OR 1.63, 95% CI 1.03-2.58), respiratory (OR 4.03, 95% CI 3.04-5.36), genitourinary (OR 1.77, 95% CI 1.08-2.90), miscellaneous medical (OR 1.94, 95% CI 1.58-2.39) complications, prolonged hospitalization (OR 1.86, 95% CI 1.57-2.21), and 12% higher total cost. Propensity score weighting analysis yielded similar results. Adequate covariate balance was achieved for all variables after weighting. CONCLUSIONS: Morbid obesity is adversely associated with perioperative outcomes in RALRP. Close management is required in patients undergoing RALRP with morbid obesity for potential worse prognosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 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 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".