Overall, the recognition of the disease before the development of the full clinical-neuroimaging picture may be challenging. Moreover, as we recently reported, none of the Background and Purpose-Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) phenotype is highly variable, and, although the full clinical-neuroimaging picture may be suggestive of the disease, no characteristic is pathognomonic. Thus, a genetic test remains the diagnostic gold standard, but because it is costly and time-consuming, a pregenetic screening appears desirable. We aimed at developing the CADASIL scale, a screening tool to be applied in the clinical setting. Methods-A preliminary scale was created assigning weighted scores to common disease features based on their frequencies obtained in a pooled analysis of selected international CADASIL series. The accuracy of the scale versus the genetic diagnosis was tested with receiver operating characteristic analysis after the application of this scale to 61 CADASIL and 54 NOTCH3-negative patients (no pathogenic mutation on exons 2-23 of the NOTCH3 gene). To improve the scale accuracy, we then developed an ad hoc optimization algorithm to detect the definitive scale. A third group of 39 patients affected by sporadic small-vessel disease was finally included in the algorithm to evaluate the stability of the scale. Results-The cutoff score of the definitive CADASIL scale had a sensitivity of 96.7% and a specificity of 74.2%. This scale was robust to contamination of patients with sporadic small-vessel disease. Conclusions-The CADASIL scale is a simple and sufficiently accurate screening tool to select patients with a high probability to be affected by the disease and therefore to be subjected to the genetic testing.

Pediatric-onset HCM is rare and associated with adverse outcomes driven mainly by arrhythmic events. Risk extends well beyond adolescence, which calls for unchanged clinical surveillance into adulthood. In this study, predictors of adverse outcomes differ from those of adult populations with HCM. In secondary prevention, the implantable cardioverter defibrillator did not confer absolute protection in the presence of limiting symptoms of heart failure.

Objective Discontinuation of antiepileptic drugs (AEDs) in seizure‐free patients is an important goal because of possible long‐term side effects and the social stigma burden of epilepsy. The purpose of this work was to assess seizure recurrence risk after suspension of AEDs, to evaluate predictors for recurrence, and to investigate the recovery of seizure control after relapse. In addition, the accuracy of a previously published prediction model of seizure recurrence risk was estimated. Methods Seizure‐free patients with epilepsy who had discontinued AEDs were retrospectively enrolled. The frequency of seizure relapses after AED withdrawal as well as prognosis after recurrence were assessed and the predictive role of baseline clinical‐demographic variables was evaluated. The aforementioned prediction model was also validated and its accuracy assessed at different seizure‐relapse probability levels. Results The enrolled patients (n = 133) had been followed for a median of 3 years (range 0.8–33 years) after AED discontinuation; 60 (45%) of them relapsed. Previous febrile seizures in childhood (hazard ratio [HR] 3.927; 95% confidence interval [CI] 1.403–10.988), a seizure‐free period on therapy of less than 2 years (HR 2.313; 95% CI 1.193–4.486), and persistent motor deficits (HR 4.568; 95% CI 1.412–14.772) were the clinical features associated with relapse risk in univariate analysis. Among these variables, only a seizure‐free period on therapy of less than 2 years was associated with seizure recurrence in multivariate analysis (HR 2.365; 95% CI 1.178–4.7444). Pharmacological control of epilepsy was restored in 82.4% of the patients who relapsed. In this population, the aforementioned prediction model showed an unsatisfactory accuracy. Significance A period of freedom from seizure on therapy of less than 2 years was the main predictor of seizure recurrence. The accuracy of the previously described prediction tool was low in this cohort, thus suggesting its cautious use in real‐world clinical practice.

To compare proportions with several independent binomial samples, we recommend a method of constructing simultaneous confidence intervals that uses the studentized range distribution with a score statistic. It applies to a variety of measures, including the difference of proportions, odds ratio, and relative risk. For the odds ratio, a simulation study suggests that the method has coverage probability closer to the nominal value than ad hoc approaches such as the Bonferroni implementation of Wald or "exact" small-sample pairwise intervals. It performs well even for the problematic but practically common case in which the binomial parameters are relatively small. For the difference of proportions, the proposed method has performance comparable to a method proposed by Piegorsch (1991, Biometrics 47, 45-52).