Improving Stroke Prevention and Quantifying Outcomes Using a United States' City Model: Intervention Measurement through Population Survey and Hospital-Based Study

PROPOSAL: ABSTRACT

Background: Currently stroke represents a serious problem in public health as one of the leading causes of mortality and morbidity worldwide [1-3] with developing countries accounting for 85% of global deaths from stroke [1, 3-5]. A very good example explains how stroke seems to be increasing in Nigeria and the case fatality is unacceptably high [6].

Good perceptions and knowledge of stroke; a population’s knowledge of the stroke risk factor profiles, and good quality of acute stroke care have been shown to be effective strategies in improving stroke prevention and outcomes [7-9]. In the United States of America, perceptions, knowledge of stroke, and risk factors associated with stroke in defined urban and rural populations need more research assessment in order to establish and/or update currently existing data. In as much as stroke units already exist in the country, improving prevention and interventions measures in diverse populations, and augmenting documented proof of practice using set protocols for acute stroke management is essential for boosting outcomes, and enhancing translational research to poor-resource settings.

Objectives: As a feasibility study for adaptation and/or incorporation into a low resource setting by quantifying the clinical, socioeconomic, and humanistic outcomes of health, and improving the effects of interventional protocol in a stroke unit with regards to a low or inadequate resources provision, as well as obtain and/or revamp data and information to develop, predict/project, and promote targeted interventions and government strategies through health policies (concerning relevant stakeholders) in global populations at risk for stroke and associated disorders.

Aim I: Objective 1 will determine the prevalence of known stroke risk factors and associated socio-behavioural characteristics among urban and rural populations in defined locations in Iowa State, United States of America.

Objective 2 will assess the perceptions and knowledge of stroke, and associated factors among defined urban and rural populations in and around Iowa City, Iowa State.

Aim II will determine the 30-day stroke outcomes and the effect(s) of implementing the already established “Stroke care bundle” (used in the acute stroke clinic unit and cerebrovascular center) on the 30-day outcomes among adult stroke patients presenting to the University of Iowa Hospitals and Clinics (or such other designated hospital, at the advisement, directives, and/or discretion of the Supervisor/Principal Investigator, as may be advised).

Methods: Aim I will be a subset of the cardiovascular disease (CVD) survey of a certain number of volunteers, ranging from 500 – 5000 participants, depending on the capacity that the study period can take (due to other factors such as available resources, financial costs, and time, etc.) in defined urban and rural areas in and around Iowa City.

In Aim I Objective 1, a cross sectional study design will be used to determine the prevalence of stroke risk factors and associated socio-behavioural characteristics among adults living in urban Iowa City and the surrounding suburbs, rural settlements, and villages/townships within and around Johnson County and other nearby counties such as Big Grove, Newport, Solon, Bertram, Monroe, Tipton, Wilton, Oxford, Robins, West Branch, Penn, Cosgrove, Lincoln, Williamsburg, Troy, Windham, Tiffin, Farmington, Hills, River Junction, Amish, Frytown, Lone Tree, Mount Vernon, Le Claire, and Fruitland, etc., that are in proximity to Iowa City.

Following household enumeration and mapping, multi-stage sampling technique will be used to select a sample of participants aged 18 years and above. Data will be collected using a pre-tested modified version of the manuals on WHO STEP wise approach to stroke and risk factor surveillance (STEPS Stroke; http://www.who.int/chp/steps/Manual.pdf). The data collected from the population survey will be compiled and analysed according to the WHO manual guidelines. Logistic regression analysis will be used to identify the socio-behavioural characteristics associated with the three most prevalent known risk factors for stroke. Only socio-behavioural factors that are significantly associated with known stroke risk factors at bi-variable analysis (P