Can the Charlson Comorbidity Index be used to predict the ASA grade in patients undergoing spine surgery?
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ORIGINAL ARTICLE
Can the Charlson Comorbidity Index be used to predict the ASA grade in patients undergoing spine surgery? A. F. Mannion1 · G. Bianchi1 · F. Mariaux1 · T. F. Fekete1 · R. Reitmeir1 · B. Moser2,3 · R. G. Whitmore4 · J. Ratliff5 · D. Haschtmann1 Received: 16 January 2020 / Revised: 17 August 2020 / Accepted: 5 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Background The American Society of Anaesthesiologists’ Physical Status Score (ASA) is a key variable in predictor models of surgical outcome and "appropriate use criteria". However, at the time when such tools are being used in decision-making, the ASA rating is typically unknown. We evaluated whether the ASA class could be predicted statistically from Charlson Comorbidy Index (CCI) scores and simple demographic variables. Methods Using established algorithms, the CCI was calculated from the ICD-10 comorbidity codes of 11′523 spine surgery patients (62.3 ± 14.6y) who also had anaesthetist-assigned ASA scores. These were randomly split into training (N = 8078) and test (N = 3445) samples. A logistic regression model was built based on the training sample and used to predict ASA scores for the test sample and for temporal (N = 341) and external validation (N = 171) samples. Results In a simple model with just CCI predicting ASA, receiver operating characteristics (ROC) analysis revealed a cut-off of CCI ≥ 1 discriminated best between being ASA ≥ 3 versus
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