In many resource-poor countries that are scaling up antiretroviral therapy (ART), 5–25% of patients are reported as “lost to follow-up”. This figure is 9% in Malawi. There is no published information about the true outcome status of these patients. In four facilities in northern Malawi, ART registers and master cards were used to identify patients who had not attended the facility for 3 months or more and were thus registered as “lost to follow-up”. Clinic staff attempted to trace these patients and ascertain their true outcome status. Of 253 patients identified as “lost to follow-up”, 127 (50%) were dead, 58% of these having died within 3 months of their last clinic visit. Of the 58 patients (23%) found to be alive, 21 were still receiving ART and 37 had stopped treatment (high transport costs being the main reason for 13 patients). Sixty-eight patients (27%) could not be traced, most commonly because of an incorrect address in the register. Fewer patients were alive and more patients could not be traced from the central hospital compared with the peripheral hospitals. Better documentation of patients’ addresses and prompt follow-up of patients who are late for their appointments are required. ART clinics in resource-poor countries should ensure that patients’ addresses are correct and comprehensive. Clinics should also undertake contact tracing as soon as possible in the event of non-attendance, consider facilitating access to ART clinics and take loss to follow-up into consideration when assessing death rates.

Background and Purpose—: Various risk score models have been developed to predict symptomatic intracerebral hemorrhage (SICH) after intravenous thrombolysis for acute ischemic stroke. In this study, we aimed to determine the prediction performance of these risk scores in a Taiwanese population Methods—: Prospectively collected data from 4 hospitals were used to calculate probability of SICH with the scores developed by Cucchiara et al, the Hemorrhage After Thrombolysis (HAT) score, the Safe Implementation of Thrombolysis in Stroke-SICH risk score, the Glucose Race Age Sex Pressure Stroke Severity score, and the Stroke Prognostication using Age and National Institutes of Health Stroke Scale-100 index. We used logistic regression to evaluate the effectiveness of each risk model in predicting SICH and the c statistic to assess performance. Results—: A total of 548 patients were included. The rates of SICH were 7.3% by the National Institute of Neurological Diseases and Stroke definition, 5.3% by the European-Australasian Cooperative Acute Stroke Study II definition, and 3.5% by the Safe Implementation of Thrombolysis in Stroke-Monitoring Study definition. The Cucchiara score, the HAT score, and the Safe Implementation of Thrombolysis in Stroke-SICH risk score were significant predictors of SICH for all 3 definitions, whereas the Glucose Race Age Sex Pressure Stroke Severity score and the Stroke Prognostication using Age and National Institutes of Health Stroke Scale-100 index predicted well only for 1 or 2 definitions of SICH. The c statistic was highest for the HAT score (range, 0.69–0.73) across the definitions of SICH. Conclusions—: The Cucchiara score, the HAT score, and the Safe Implementation of Thrombolysis in Stroke-SICH risk score predicted SICH reasonably well regardless of which SICH definition was used. However, only the HAT score had an acceptable discriminatory ability.

Status epilepticus (SE) is a serious neurologic emergency associated with a significant mortality. The objective of this study is to investigate its epidemiology in terms of age- and sex-specific incidences and mortality. By using the Taiwan National Health Insurance Research Database during 2000 to 2011, we identified hospitalized patients with a discharged diagnosis of SE and calculated the incidence and in-hospital mortality of SE with respect to age and sex. The overall incidence of SE was 4.61 per 100,000 person-years, which displayed a “J-shaped” distribution by age with a little higher under the age of 5 and highest over 60 years. The male-to-female rate ratio was 1.57 and it demonstrated a “mountain-shape” across ages with the peak at 45 to 49 years old. The in-hospital mortality was significantly lower in males (7.38%) than in females (11.12%) with an odds ratio of 0.64 (95% CI 0.56-0.72). Notably, the in-hospital mortality for females increased rapidly after the age of 40 to 45 years. The multivariate analysis found males had a significantly lower risk of mortality than females after, but not before, 45 years of age with an odds ratio of 0.56 (95% CI 0.49-0.65). Sex and age are crucial factors associated with the incidence and in-hospital mortality of SE. The females over 45 years of age have a higher risk of occurrence and mortality from SE. The underlying mechanism deserves further study.