ArticlePloS one2016
Factors Predicting Difficulty of Laparoscopic Low Anterior Resection for Rectal Cancer with Total Mesorectal Excision and Double Stapling Technique.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 25 citations in OpenAlex.
- Surgeon workload in supervised robotic colorectal surgery: a surgical task load index study.Surgical endoscopy · 2026Article
- A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.International journal of computer assisted radiology and surgery · 2026Article
- Development of a predictive score for prolonged pelvic operation time in robot-assisted low anterior resection: a single-center, retrospective study in Japan.Surgical endoscopy · 2025Article
- Posterior mesorectal thickness as a predictor of increased operative time in rectal cancer surgery: a retrospective cohort study.Surgical endoscopy · 2022Article
- Subjective Difficulty Scale in Liver Transplantation: A Prospective Observational Study.Transplant international : official journal of the European Society for Organ Transplantation · 2022Observational
- High-pressure COUpdates in surgery · 2021Article
- Pelvimetric and Nutritional Factors Predicting Surgical Difficulty in Laparoscopic Resection for Rectal Cancer Following Preoperative Chemoradiotherapy.World journal of surgery · 2021Article
- MRI pelvimetry-based evaluation of surgical difficulty in laparoscopic total mesorectal excision after neoadjuvant chemoradiation for male rectal cancer.Surgery today · 2021Article
- Can better surgical outcomes be obtained in the learning process of robotic rectal cancer surgery? A propensity score-matched comparison between learning phases.Surgical endoscopy · 2021Article
- Quantitative assessment of mesorectal fat: new prognostic biomarker in patients with mid-to-lower rectal cancer.European radiology · 2019Article
- Mesorectal fat area as a useful predictor of the difficulty of robotic-assisted laparoscopic total mesorectal excision for rectal cancer.Surgical endoscopy · 2019Article
- Economic burden of cancer among patients with surgical resections of the lung, rectum, liver and uterus: results from a US hospital database claims analysis.Health economics review · 2017Article
- Factors Influencing Difficulty of Laparoscopic Abdominoperineal Resection for Ultra-Low Rectal Cancer.Surgical laparoscopy, endoscopy & percutaneous techniques · 2017Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLaparoscopic sphincter-preserving low anterior resection for rectal cancer is a surgery demanding great skill. Immense efforts have been devoted to identifying factors that can predict operative difficulty, but the results are inconsistent.
objectiveOur study was conducted to screen patients' factors to build models for predicting the operative difficulty using well controlled data.
methodWe retrospectively reviewed records of 199 consecutive patients who had rectal cancers 5-8 cm from the anal verge. All underwent laparoscopic sphincter-preserving low anterior resections with total mesorectal excision (TME) and double stapling technique (DST). Data of 155 patients from one surgeon were utilized to build models to predict standardized endpoints (operative time, blood loss) and postoperative morbidity. Data of 44 patients from other surgeons were used to test the predictability of the built models.
resultsOur results showed prior abdominal surgery, preoperative chemoradiotherapy, tumor distance to anal verge, interspinous distance, and BMI were predictors for the standardized operative times. Gender and tumor maximum diameter were related to the standardized blood loss. Temporary diversion and tumor diameter were predictors for postoperative morbidity. The model constructed for the operative time demonstrated excellent predictability for patients from different surgeons.
conclusionsWith a well-controlled patient population, we have built a predictable model to estimate operative difficulty. The standardized operative time will make it possible to significantly increase sample size and build more reliable models to predict operative difficulty for clinical use.
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