Development and multicentre validation of the FLEX score: personalised preoperative surgical risk prediction using attention-based ICD-10 and Current Procedural Terminology set embeddings.
Br J Anaesth
; 132(3): 607-615, 2024 Mar.
Article
en En
| MEDLINE
| ID: mdl-38184474
ABSTRACT
BACKGROUND:
Preoperative 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.METHODS:
We 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.RESULTS:
Our 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.CONCLUSIONS:
FLEX 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.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Clasificación Internacional de Enfermedades
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Current Procedural Terminology
Tipo de estudio:
Etiology_studies
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Guideline
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Adult
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Humans
Idioma:
En
Año:
2024
Tipo del documento:
Article