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Predictive value of 5-Factor modified frailty index in Oncologic and benign hysterectomies
Catherine E Hermann1,2, Nathanael C Koelper3, Leslie Andriani3
1Pennsylvania Hospital, University of Pennsylvania Health Systems, Philadelphia, PA, United States.
Background:
The 5-factor modified frailty index (mFI-5) has been validated against the original 11-factor modified frailty index in gynecologic surgery, however its utility has not been evaluated between benign versus gynecologic oncology patient populations.
Objective:
To evaluate the predictive value of the mFI-5 in identifying women at increased risk for major postoperative complications, readmission, or death within 30 days of hysterectomy for benign and oncologic indications.
Methods:
Patients who underwent hysterectomy between 2015 and 2017 were identified from the NSQIP database and stratified into benign or malignant indications. Demographic and mFI-5 variables were extracted. The mFI-5 was calculated by dividing the sum of all affirmative variables by the total number of input variables in the database. Logistic regression modeling was performed adjusting for confounders. C-statistic with 95% CI was obtained post-regression.
Results:
80,293 hysterectomies (59,078 benign and 21,215 oncologic) were identified. The benign group was more likely to have an mFI-5 score of 0 (70 % vs 50 %, p = 0.001) and had shorter operative times (p = 0.001). In the benign group, mFI-5 was a strong predictor of mortality (c = 0.819, CI 0.704-0.933). Within the oncology group, the mFI-5 was a strong predictor of mortality (c = 0.801, CI 0.750-0.851), particularly for uterine and cervical cancers. It was moderately predictive of readmission (c = 0.671, CI 0.656-0.686) and strongly predictive of Clavien-Dindo class III and IV complications (c = 0.732, CI 0.713-0.750).
Conclusion:
The mFI-5 is a strong predictor of 30-day mortality and serious postoperative complications. These findings have the potential to improve identification of high-risk patients in the preoperative setting.
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