TY - JOUR
T1 - Age and BMI equal Modified Frailty Index, Modified Charlson Comorbidity Index and ASA in predicting adverse events in spinal surgery for cervical degenerative diseases
AU - Woldu, Sara
AU - Solumsmoen, Stian
AU - Bech-Azeddine, Rachid
N1 - Copyright © 2023 Elsevier B.V. All rights reserved.
PY - 2023/5
Y1 - 2023/5
N2 - OBJECTIVE: To compare Modified Frailty Index (mFI), Modified Charlson Comorbidity (mCCI) and ASA with demographic data such as age, BMI and gender in the prediction of AEs obtained using a validated systematic reporting system in a prospective cohort undergoing cervical spine surgery.METHODS: All adult patients undergoing spine surgery for cervical degenerative disease at our academic tertiary referral center from February 1, 2016, to January 31, 2017, were included. Morbidity and mortality were determined according to the predefined adverse event (AE) variables using the Spinal Adverse Events Severity (SAVES) System. Area under the curve (AUC) analyses from receiver operating characteristics (ROC) curves were used to assess the discriminative ability in predicting AEs for the comorbidity indices mFI, mCCI, ASA and for BMI, age and gender.RESULTS: A total of 288 consecutive cervical cases were included. BMI was the most predictive demographic factor for an AE (AUC = 0.58), the most predictive comorbidity index was mCCI (AUC = 0.52). No combination of comorbidity indices or demographic factors reached a threshold of AUC ≥ 0.7 for AEs. As predictor of extended length of stay: age (AUC = 0.77), mFI (AUC = 0.70) and ASA (AUC = 0.70) were similar and fair.CONCLUSION: Age and BMI equal mFI, mCCI and ASA in predicting postoperative AEs, amongst patients operated for cervical degenerative disease. No significant difference was found between mFI, mCCI and ASA in the discriminative abilities in predicting morbidity, based on prospectively collected AEs according to the SAVES grading system.
AB - OBJECTIVE: To compare Modified Frailty Index (mFI), Modified Charlson Comorbidity (mCCI) and ASA with demographic data such as age, BMI and gender in the prediction of AEs obtained using a validated systematic reporting system in a prospective cohort undergoing cervical spine surgery.METHODS: All adult patients undergoing spine surgery for cervical degenerative disease at our academic tertiary referral center from February 1, 2016, to January 31, 2017, were included. Morbidity and mortality were determined according to the predefined adverse event (AE) variables using the Spinal Adverse Events Severity (SAVES) System. Area under the curve (AUC) analyses from receiver operating characteristics (ROC) curves were used to assess the discriminative ability in predicting AEs for the comorbidity indices mFI, mCCI, ASA and for BMI, age and gender.RESULTS: A total of 288 consecutive cervical cases were included. BMI was the most predictive demographic factor for an AE (AUC = 0.58), the most predictive comorbidity index was mCCI (AUC = 0.52). No combination of comorbidity indices or demographic factors reached a threshold of AUC ≥ 0.7 for AEs. As predictor of extended length of stay: age (AUC = 0.77), mFI (AUC = 0.70) and ASA (AUC = 0.70) were similar and fair.CONCLUSION: Age and BMI equal mFI, mCCI and ASA in predicting postoperative AEs, amongst patients operated for cervical degenerative disease. No significant difference was found between mFI, mCCI and ASA in the discriminative abilities in predicting morbidity, based on prospectively collected AEs according to the SAVES grading system.
UR - http://www.scopus.com/inward/record.url?scp=85151872162&partnerID=8YFLogxK
U2 - 10.1016/j.clineuro.2023.107698
DO - 10.1016/j.clineuro.2023.107698
M3 - Journal article
C2 - 37028252
SN - 0303-8467
VL - 228
JO - Clinical Neurology and Neurosurgery
JF - Clinical Neurology and Neurosurgery
M1 - 107698
ER -