A predictive analytics model for differentiating between transient ischemic attacks (TIA) and its mimics.

BACKGROUND: Transient ischemic attack (TIA) is a brief episode of neurological dysfunction resulting from cerebral ischemia not associated with permanent cerebral infarction. TIA is associated with high diagnostic errors because of the subjective nature of findings and the lack of clinical and imaging biomarkers. The goal of this study was to design and evaluate a novel multinomial classification model, based on a combination of feature selection mechanisms coupled with logistic regression, to predict the likelihood of TIA, TIA mimics, and minor stroke. METHODS: We conducted our modeling on consecutive patients who were evaluated in our health system with an initial diagnosis of TIA in a 9-month period. We established the final diagnoses after the clinical evaluation by independent verification from two stroke neurologists. We used Recursive Feature Elimination (RFE) and Least Absolute Shrinkage and Selection Operator (LASSO) for prediction modeling. RESULTS: The RFE-based classifier correctly predicts 78% of the overall observations. In particular, the classifier correctly identifies 68% of the cases labeled as "TIA mimic" and 83% of the "TIA" discharge diagnosis. The LASSO classifier had an overall accuracy of 74%. Both the RFE and LASSO-based classifiers tied or outperformed the ABCD2 score and the Diagnosis of TIA (DOT) score. With respect to predicting TIA, the RFE-based classifier has 61.1% accuracy, the LASSO-based classifier has 79.5% accuracy, whereas the DOT score applied to the dataset yields an accuracy of 63.1%. CONCLUSION: The results of this pilot study indicate that a multinomial classification model, based on a combination of feature selection mechanisms coupled with logistic regression, can be used to effectively differentiate between TIA, TIA mimics, and minor stroke.

Rate and associated factors of transient ischemic attack misdiagnosis.

BACKGROUND AND PURPOSE: The goal of this study was to investigate the rate and associated factors of Transient Ischemic Attack (TIA) misdiagnosis. METHODS: We retrospectively analyzed consecutive patients with an initial diagnosis of TIA in the emergency department (ED) in a 9-month period. All hospitalized TIA patients were evaluated by a neurologist within 24 h and had at least one hospital discharge follow-up visit within three months. Patients' clinical data and neuroimaging were reviewed. The final diagnosis was independently verified by two stroke neurologists. RESULTS: Out of 276 patients with the initial diagnosis of TIA, 254 patients (mean age 68.7 ±â€¯15.4 years, 40.9% male, 25.2% final diagnosis of TIA) were included in the analysis. Twenty-four patients (9.4%) were referred to our rapid-access TIA clinic. The rate of TIA misdiagnosis among TIA clinic referred patients was 45.8%. Among the 230 patients in inpatient setting, the rate of TIA misdiagnosis was 60.0%. A hospital discharge diagnosis of TIA was observed in 54.3% of hospitalized patients; however, only 24.8% had the final diagnosis of TIA. Among hospitalized patients, the univariate analysis suggests a significant difference (P < .05) between the two groups (correctly versus misdiagnosed patients) in terms of hospital discharge diagnosis, final diagnosis, history of diabetes mellitus, and coronary artery disease. In regression model hospital discharge diagnosis (P < .001), final diagnosis (P < .001), and diabetes mellitus (P = .018) retained independent association with TIA misdiagnosis. CONCLUSION: Our study indicates a high rate of TIA misdiagnosis in the emergency department, hospital, and outpatient clinics.

Six-Month Outcome of Transient Ischemic Attack and Its Mimics.

Background and Objective: Although the risk of recurrent cerebral ischemia is higher after a transient ischemic attack (TIA), there is limited data on the outcome of TIA mimics. The goal of this study is to compare the 6-month outcome of patients with negative and positive diffusion-weighted imaging (DWI) TIAs (DWI-neg TIA vs. DWI-pos TIA) and also TIA mimics. Methods: We prospectively studied consecutive patients with an initial diagnosis of TIA in our tertiary stroke centers in a 2-year period. Every included patient had an initial magnetic resonance (MR) with DWI and one-, three-, and six-month follow-up visits. The primary outcome was defined as the composition of intracerebral hemorrhage, ischemic stroke, TIA, coronary artery disease, and death. Results: Out of 269 patients with the initial diagnosis of TIA, 259 patients (mean age 70.5 ± 15.0 [30-100] years old, 56.8% men) were included in the final analysis. Twenty-one (8.1%, 95% confidence interval [CI] 5.1-12.1%) patients had a composite outcome event within the six-month follow-up. Five (23.8%) and 13 (61.9%) composite outcome events occurred in the first 30 and 90 days, respectively. Among patients with DWI-neg TIA, the one- and six-month ischemic stroke rate was 1.5 and 4.6%, respectively. The incidence proportion of composite outcome event was significantly higher among patients who had the diagnosis of DWI-neg TIA compared with those who had the diagnosis of TIA mimics (12.2 vs. 2.1%-relative risk 5.9; 95% CI, 1.4-25.2). In our univariable analysis among patients with DWI-neg TIA and DWI-pos TIA, age (P = 0.017) was the only factor that was significantly associated with the occurrence of the composite outcome. Conclusion: Our study indicated that the overall six-month rate of the composite outcome among patients DWI-neg TIA, DWI-pos TIA, and TIA mimics were 12.2, 9.7, and 2.1%, respectively. Age was the only factor that was significantly associated with the occurrence of the composite outcome.