Program for the Epidemiological Evaluation of Stroke in Tandil, Argentina (PREVISTA) Study: Rationale and Design. Issue 7 (October 2013) - Sposato, Luciano A.; Coppola, Mariano L.; Altamirano, Juan; Guerrero, Brenda Borrego; Casanova, Jorge; De Martino, Maximiliano; Díaz, Alejandro; Feigin, Valery L.; Funaro, Fernando; Gradillone, María E.; Lewin, María L.; Lopes, Renato D.; et al.
The availability of population-based epidemiological data on the incident risk of stroke is very scarce in Argentina and other Latin American countries. In response to the priorities established by the World Health Organization and the United Nations, PREVISTA was envisaged as a population-based program to determine the risk of first-ever and recurrent stroke and transient ischemic attack incidence and mortality in Tandil, Buenos Aires, Argentina. The study will be conducted according to Standardized Tools for Stroke Surveillance (STEPS Stroke) methodology and will enroll all new (incident) and recurrent consecutive cases of stroke and transient ischemic attack in the City of Tandil between May 1st, 2013 and April 30, 2015. The study will include patients with ischemic stroke, non-traumatic primary intracerebral hemorrhage, subarachnoid hemorrhage, and transient ischemic attack. To ensure the inclusion of every cerebrovascular event during an observation period of two years, we will instrument an 'intensive screening program', consisting of a comprehensive daily tracking of every potential event of stroke or transient ischemic attack using multiple overlapping sources. Mortality would be determined during follow-up for every enrolled patient. Also, fatal community events would be screened daily through revision of death certificates at funeral homes and local offices of vital statistics. All causes of death will be adjudicated by an ad-hoc committee. The close population of Tandil is representative of a large proportion of Latin-American countries with low- and middle-income economies. The findings and conclusions of PREVISTA may provide data that could support future health policy decision-making in the region.