ArticleBritish journal of anaesthesia2024
Development and multicentre validation of the FLEX score: personalised preoperative surgical risk prediction using attention-based ICD-10 and Current Procedural Terminology set embeddings.
Article in British journal of anaesthesia, 2024. 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.
- Decision-centered artificial intelligence for perioperative care outside the operating room: a practical review for surgeons.Journal of minimally invasive surgery · 2026Review
- Rethinking the Integration of Artificial Intelligence Into Surgery: Centralized Risk Assessment for System-Level Impact.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2026Article
- Pre-anesthetic evaluation for gastrointestinal endoscopy in China: a national web-based questionnaire survey.BMC medical education · 2026Article
- Machine-learning prediction of impaired outcome in diabetic patients undergoing non-cardiac surgery.Frontiers in medicine · 2026Article
- Association of peripheral nerve blocks with increased postoperative pain and opioid use in orthopaedic surgery: a single-centre retrospective cohort study.British journal of anaesthesia · 2025Article
- Prediction of Cardiopulmonary Resuscitation Outcomes for Arrest in Surgical Settings.JAMA network open · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
backgroundPreoperative knowledge of surgical risks can improve perioperative care and patient outcomes. However, assessments requiring clinician examination of patients or manual chart review can be too burdensome for routine use.
methodsWe conducted a multicentre retrospective study of 243 479 adult noncardiac surgical patients at four hospitals within the Mass General Brigham (MGB) system in the USA. We developed a machine learning method using routinely collected coding and patient characteristics data from the electronic health record which predicts 30-day mortality, 30-day readmission, discharge to long-term care, and hospital length of stay.
resultsOur method, the Flexible Surgical Set Embedding (FLEX) score, achieved state-of-the-art performance to identify comorbidities that significantly contribute to the risk of each adverse outcome. The contributions of comorbidities are weighted based on patient-specific context, yielding personalised risk predictions. Understanding the significant drivers of risk of adverse outcomes for each patient can inform clinicians of potential targets for intervention.
conclusionsFLEX utilises information from a wider range of medical diagnostic and procedural codes than previously possible and can adapt to different coding practices to accurately predict adverse postoperative outcomes.
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