ArticleBMC health services research2019
Development and validation of a predictive model for American Society of Anesthesiologists Physical Status.
Article in BMC health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
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- Classifying American Society of Anesthesiologists Physical Status With a Low-Rank-Adapted Large Language Model: Development and Validation Study.Journal of medical Internet research · 2026Article
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- Prediction of postoperative complications following transanal total mesorectal excision in middle and low rectal cancer: development and internal validation of a clinical prediction model.International journal of colorectal disease · 2024Article
- Large Language Model Capabilities in Perioperative Risk Prediction and Prognostication.JAMA surgery · 2024Article
- Comparative study ofScientific reports · 2024Article
- Nomogram for predicting adhesive small bowel obstruction following emergency gastrointestinal surgery.Langenbeck's archives of surgery · 2023Article
- Recurrence After Operated Adhesive Small Bowel Obstruction: Development and Validation of a Predictive Model.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2023Article
- Postoperative Complications and Outcome After Emergency Laparotomy: A Retrospective Study.World journal of surgery · 2023Article
- Effects of Intra-Articular Autologous Adipose Micrograft for the Treatment of Osteoarthritis in Dogs: A Prospective, Randomized, Controlled Study.Animals : an open access journal from MDPI · 2022Article
- Machine Learning Predicts Femoral and Tibial Implant Size Mismatch for Total Knee Arthroplasty.Arthroplasty today · 2021Article
- Acute appendicitis management during the COVID-19 pandemic: A prospective cohort study from a large UK centre.International journal of surgery (London, England) · 2021Observational
- The effect of obesity on revision total knee arthroplasty: a retrospective cohort study.Canadian journal of surgery. Journal canadien de chirurgieArticle
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12 authors.
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Abstract
backgroundThe American Society of Anesthesiologists Physical Status (ASA-PS) classification system was developed to categorize the fitness of patients before surgery. Increasingly, the ASA-PS has been applied to other uses including justification of inpatient admission. Our objectives were to develop and cross-validate a statistical model for predicting ASA-PS; and 2) assess the concurrent and predictive validity of the model by assessing associations between model-derived ASA-PS, observed ASA-PS, and a diverse set of 30-day outcomes.
methodsUsing the 2014 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Participant Use Data File, we developed and internally cross-validated multinomial regression models to predict ASA-PS using preoperative NSQIP data. Accuracy was assessed with C-Statistics and calibration plots. We assessed both concurrent and predictive validity of model-derived ASA-PS relative to observed ASA-PS and 30-day outcomes. To aid further research and use of the ASA-PS model, we implemented it into an online calculator.
resultsOf the 566,797 elective procedures in the final analytic dataset, 8.9% were ASA-PS 1, 48.9% were ASA-PS 2, 39.1% were ASA-PS 3, and 3.2% were ASA-PS 4. The accuracy of the 21-variable model to predict ASA-PS was C = 0.77 +/- 0.0025. The model-derived ASA-PS had stronger association with key indicators of preoperative status including comorbidities and higher BMI (concurrent validity) compared to observed ASA-PS, but less strong associations with postoperative complications (predictive validity). The online ASA-PS calculator may be accessed at https://s-spire-clintools.shinyapps.io/ASA_PS_Estimator/
conclusionsModel-derived ASA-PS better tracked key indicators of preoperative status compared to observed ASA-PS. The ability to have an electronically derived measure of ASA-PS can potentially be useful in research, quality measurement, and clinical applications.
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