To predict general medical and surgical mortality, the Charlson Comorbidity Index (CCI) and the 11-factor modified frailty index (mFI-11) have been utilised. However, the demand for a high number of data points, some of which overlap or require data that may be unavailable in huge datasets, limits their clinical relevance. To solve these obstacles, the new 5-factor mFI-5 was recently designed. The researchers looked back at a group of adult patients who underwent brain tumour surgery between January 2017 and December 2018 at a single institution. After correcting for patient age, race, ethnicity, sex, marital status, and diagnosis, logistic regression models were used to evaluate the correlations between health measure scores and postoperative mortality. There were 1692 patients in the research group (mean age 55.5 years; mean CCI, mFI-11, andmFI-5 scores 2.49, 1.05, and 0.80, respectively) Each 1-point rise in a patient’s mFI score was associated with a higher risk of 90-day postoperative mortality. The c-statistics of the adjusted CCI and the adjusted mFI -5 models did not differ significantly (p = 0.089).The adjusted mFI-5 model, like adjusted CCI and adjusted mFI-11 models, predicts 90-day postoperative mortality in brain tumour patients. The mFI-5 can be easily integrated into clinical workflows to predict the results of brain tumour surgery in real time.
Reference Link – https://thejns.org/view/journals/j-neurosurg/135/1/article-p78.xml
