Adapting the 5-factor modified frailty index for prediction of postprocedural outcome in patients with unruptured aneurysms

Stroke
DOI: 10.3171/2021.2.jns204420 Publication Date: 2021-08-20T17:54:02Z
ABSTRACT
The 5-factor modified frailty index (mFI-5) is a practical tool that can be used to estimate by measuring five accessible factors: functional status, history of diabetes, chronic obstructive pulmonary disease, congestive heart failure, and hypertension. authors aimed validate the utility mFI-5 for predicting endovascular microsurgical treatment outcomes in patients with unruptured aneurysms.A prospectively maintained database consecutive aneurysm who were treated clip placement or therapy was used. Because patient age an important predictor aneurysm, supplemented create age-supplemented (AmFI-5). Associations scores on these indices major complications (symptomatic ischemic hemorrhagic stroke, embolism, pneumonia, surgical site infection requiring reoperation) evaluated. Validation carried out American College Surgeons National Surgical Quality Improvement Program (NSQIP) (2006-2017).The institutional included 275 (88 underwent placement, 187 treatment). Multivariable analysis cohort showed complication significantly associated (OR 2.0, p = 0.046) AmFI-5 1.9, 0.028) scores. Significant predictive accuracy provided (c-statistic 0.709, 0.011) 0.720, 0.008). Society Anesthesiologists Physical Status Classification System (ASA) poor discrimination (area under curve 0.541, 0.618) less than (p 0.023) 0.014). Optimal relative fit achieved AmFI-5, which had lowest Akaike information criterion value. Similar results obtained after equivalent cohort, additional significant associations between length stay (β 0.6 0.009 mFI-5; β 0.5 0.003 AmFI-5). In 1047 NSQIP database, 0.001) < severe postoperative adverse events greater 0.600 0.001 c-statistic 0.610 AmFI-5) ASA score 0.580 0.003).mFI-5 represent potential predictors procedure-related patients. After further validation, integration tools into clinical workflows may optimize intervention.
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