Diagnosis of TIA (DOT) score - design and validation of a new clinical diagnostic tool for transient ischaemic attack

Background: The diagnosis of Transient Ischaemic Attack (TIA) can be difficult and 50-60 % of patients seen in TIA clinics turn out to be mimics. Many of these mimics have high ABCD2 scores and fill urgent TIA clinic slots inappropriately. A TIA diagnostic tool may help non-specialists make the diagnosis with greater accuracy and improve TIA clinic triage. The only available diagnostic score (Dawson et al) is limited in scope and not widely used. The Diagnosis of TIA (DOT) Score is a new and internally validated web and mobile app based diagnostic tool which encompasses both brain and retinal TIA. Methods: The score was derived retrospectively from a single centre TIA clinic database using stepwise logistic regression by backwards elimination to find the best model. An optimum cutpoint was obtained for the score. The derivation and validation cohorts were separate samples drawn from the years 2010/12 and 2013 respectively. Receiver Operating Characteristic (ROC) curves and area under the curve (AUC) were calculated and the diagnostic accuracy of DOT was compared to the Dawson score. A web and smartphone calculator were designed subsequently. Results: The derivation cohort had 879 patients and the validation cohort 525. The final model had seventeen predictors and had an AUC of 0.91 (95 % CI: 0.89-0.93). When tested on the validation cohort, the AUC for DOTS was 0.89 (0.86-0.92) while that of the Dawson score was 0.77 (0.73-0.81). The sensitivity and specificity of the DOT score were 89 % (CI: 84 %-93 %) and 76 % (70 %-81 %) respectively while those of the Dawson score were 83 % (78 %-88 %) and 51 % (45 %-57 %). Other diagnostic accuracy measures (DOT vs. Dawson) include positive predictive values (75 % vs. 58 %), negative predictive values (89 % vs. 79 %), positive likelihood ratios (3.67 vs. 1.70) and negative likelihood ratios (0.15 vs. 0.32). Conclusion: The DOT score shows promise as a diagnostic tool for TIA and requires independent external validation before it can be widely used. It could potentially improve the triage of patients assessed for suspected TIA.