ArticleSurgical endoscopy2017
The use of patient factors to improve the prediction of operative duration using laparoscopic cholecystectomy.
Article in Surgical endoscopy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Machine learning algorithms as early diagnostic tools for prolonged operative time in patients with fluorescent laparoscopic cholecystectomy: a retrospective cohort study.Frontiers in surgery · 2025Article
- Assessing the Precision of Surgery Duration Estimation: A Retrospective Study.Journal of multidisciplinary healthcare · 2023Article
- Artificial intelligence prediction of cholecystectomy operative course from automated identification of gallbladder inflammation.Surgical endoscopy · 2022Article
- Estimation of Surgery Durations Using Machine Learning Methods-A Cross-Country Multi-Site Collaborative Study.Healthcare (Basel, Switzerland) · 2022Article
- DOES MALE GENDER INCREASE THE RISK OF LAPAROSCOPIC CHOLECYSTECTOMY?Arquivos brasileiros de cirurgia digestiva : ABCD = Brazilian archives of digestive surgery · 2019Article
- The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy.Surgical endoscopy · 2018Article
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Authors and funding
7 authors.
Funding
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Abstract
backgroundReliable prediction of operative duration is essential for improving patient and care team satisfaction, optimizing resource utilization and reducing cost. Current operative scheduling systems are unreliable and contribute to costly over- and underestimation of operative time. We hypothesized that the inclusion of patient-specific factors would improve the accuracy in predicting operative duration.
methodsWe reviewed all elective laparoscopic cholecystectomies performed at a single institution between 01/2007 and 06/2013. Concurrent procedures were excluded. Univariate analysis evaluated the effect of age, gender, BMI, ASA, laboratory values, smoking, and comorbidities on operative duration. Multivariable linear regression models were constructed using the significant factors (p < 0.05). The patient factors model was compared to the traditional surgical scheduling system estimates, which uses historical surgeon-specific and procedure-specific operative duration. External validation was done using the ACS-NSQIP database (n = 11,842).
resultsA total of 1801 laparoscopic cholecystectomy patients met inclusion criteria. Female sex was associated with reduced operative duration (-7.5 min, p < 0.001 vs. male sex) while increasing BMI (+5.1 min BMI 25-29.9, +6.9 min BMI 30-34.9, +10.4 min BMI 35-39.9, +17.0 min BMI 40 + , all p < 0.05 vs. normal BMI), increasing ASA (+7.4 min ASA III, +38.3 min ASA IV, all p < 0.01 vs. ASA I), and elevated liver function tests (+7.9 min, p < 0.01 vs. normal) were predictive of increased operative duration on univariate analysis. A model was then constructed using these predictive factors. The traditional surgical scheduling system was poorly predictive of actual operative duration (R
conclusionThe use of routinely available pre-operative patient factors improves the prediction of operative duration during cholecystectomy.
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