METHODS: This is a retrospective cohort study utilizing data from the National Cardiovascular Disease (NCVD)-PCI registry. The data collected (N = 28,007) were split into training set (n = 24,409) and testing set (n = 3598). Four predictive models (logistic regression [LR], random forest method, support vector machine [SVM], and artificial neural network) were developed and validated. The outcome on risk prediction were compared.
RESULTS: The demographic and clinical features of patients in the training and testing cohorts were similar. Patients had mean age ± standard deviation of 58.15 ± 10.13 years at admission with a male majority (82.66%). In over half of the procedures (50.61%), patients had chronic stable angina. Within 1 year of follow up mortality, target vessel revascularization (TVR), and composite event of mortality and TVR were 3.92%, 9.48%, and 12.98% respectively. LR was the best model in predicting mortality event within 1-year post-PCI (AUC: 0.820). SVM had the highest discrimination power for both TVR event (AUC: 0.720) and composite event of mortality and TVR (AUC: 0.720).
CONCLUSIONS: This study successfully identified optimal prediction models with the good discriminatory ability for mortality outcome and good discrimination ability for TVR and composite event of mortality and TVR with a simple machine learning framework.
METHODS: Analyses were conducted post hoc of this 24-month, phase III, double-blind study, in which RRMS patients were randomized (1:1:1) to once daily oral fingolimod 0.5 mg, 1.25 mg or placebo. The key outcomes were the association between baseline RNFLT and baseline clinical characteristics and clinical/imaging outcomes up to 24 months. Change of RNFLT with fingolimod versus placebo within 24 months and time to retinal nerve fiber layer (RNFL) thinning were evaluated.
RESULTS: Altogether 885 patients were included. At baseline, lower RNFLT was correlated with higher Expanded Disability Status Scale score (r = -1.085, p = 0.018), lower brain volume (r = 0.025, p = 0.006) and deep gray matter volume (r = 0.731, p