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TRUVACE RECORD VERSION
record: TRV-2026-1934
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-19T22:01:46.762878Z
status: published
lens: g_space
sector: health
headline: Clinical significance of intraoperative dissection time and machine learning-based prediction in laparoscopic distal gastrectomy for gastric cancer
dek: Background Establishing a clinically meaningful cutoff value for intraoperative dissection time and developing predictive models for this metric among patients with distal gastric cancer. Methods This retrospective multicenter study included 849 patients with distal gastric cancer who underwent laparoscopic distal gastrectomy between November 2020 and May 2025 at three tertiary centers. Using postoperative complications as the status variable, determine the optimal cutoff value for intraoperative dissection time…
gain_title: Machine learning models identified patients likely to need long dissection time (over 133 minutes), a threshold linked to more postoperative complications, which may help preoperative risk evaluation.
problem_title: (none)
trace_subject: (none)
gain_reading: Machine learning models identified patients likely to need long dissection time (over 133 minutes), a threshold linked to more postoperative complications, which may help preoperative risk evaluation.
gain_evidence: may offer additional value for the preoperative evaluation of patients at risk of prolonged intraoperative dissection time
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers analyzed 849 patients who had laparoscopic distal gastrectomy for distal gastric cancer at three tertiary centers between November 2020 and May 2025. They found a dissection time of 133 minutes best separated patients by complication risk, then trained six machine learning models to predict who would fall into the long-dissection group.

The work suggests surgical teams could flag patients likely to face prolonged dissection before surgery and plan accordingly. However, the models showed only moderate discrimination, the data were retrospective, and long dissection time was not an independent predictor of survival, so its clinical usefulness remains to be shown.
limitation: The study is retrospective, and although prolonged dissection time was associated with worse survival in unadjusted analysis, it was not an independent prognostic factor after adjustment.
tag: Evidence-backed gain
key_points: The optimal dissection time cutoff was 133 minutes, derived using postoperative complications as the status variable. | Patients in the long dissection group had more complications and worse unadjusted overall and recurrence-free survival. | Long dissection time was not independently associated with prognosis in multivariable analysis. | Logistic regression had the highest test-cohort AUC (0.770), while random forest had the highest validation AUC (0.759).
rundown: The study was retrospective and multicenter, covering patients treated at three tertiary centers from November 2020 to May 2025. Patients were grouped into short and long intraoperative dissection time based on the 133-minute cutoff.

The long dissection group differed in baseline characteristics: higher body mass index, larger tumors, more advanced clinical stage, and a higher share of patients given neoadjuvant chemotherapy. These differences help explain why survival gaps appeared in unadjusted but not adjusted analyses.

Six machine learning models were developed and validated. Logistic regression led in the test cohort and random forest in the validation cohort, and the authors regarded random forest as the most stable.
sources:
- peer_reviewed | Surgical Endoscopy | https://doi.org/10.1007/s00464-026-13369-1 | 2026-10-16
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