The impact of operative approach for obese colorectal cancer patients: analysis of the National Inpatient Sample 2015–2019
Bibliographic record
Abstract
AIM: Obesity is a well-established risk factor for the development of colorectal cancer. As such, patients undergoing surgery for colorectal cancer have increasingly higher body mass indices (BMIs). The advances in minimally invasive surgical techniques in recent years have helped surgeons circumvent some of the challenges associated with operating in the setting of obesity. While previous studies suggest that laparoscopy improves outcomes compared with open surgery in obese patients, this has never been established at the population level. Therefore, we designed a retrospective database study using the National Inpatient Sample (NIS) with the aim of comparing laparoscopic with open approaches for obese patients undergoing surgery for colorectal cancer. METHOD: undergoing surgery for colorectal cancer. The primary outcomes were postoperative in-hospital morbidity and mortality. Secondary outcomes included postoperative system-specific complications, total admission healthcare cost and length of stay (LOS). Multivariable logistic and linear regressions were utilized to compare the two operative approaches. RESULTS: A total of 4742 patients underwent open surgery and 3231 underwent laparoscopic surgery. We observed a significant decrease in overall postoperative morbidity [17.5% vs. 31.4%, adjusted odds ratio (aOR) 0.56, 95% confidence interval (CI) 0.50-0.64; p < 0.001], gastrointestinal morbidity (8.1% vs. 14.5%, aOR 0.59, 95% CI 0.50-0.69; p < 0.001) and genitourinary morbidity (10.1% vs. 18.6%, aOR 0.61, 95% CI 0.52-0.70; p < 0.001) with the use of laparoscopy. Postoperative LOS was 1.7 days shorter (95% CI 1.5-2.0, p < 0.001) and cost of admission was decreased by $9106 (95% CI $4638-$13 573, p < 0.001) with laparoscopy. CONCLUSION: Laparoscopic surgery for obese patients with colorectal cancer is associated with significantly decreased postoperative morbidity and improved healthcare resource utilization compared with open surgery. Laparoscopic approaches should be relied upon whenever feasible for these patients.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".