Maps.

<p>A) Map of the Parana state. Source: Geographic Atlas of the Parana state, 2011 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059363#pone.0059363-EspritoSantoJnior1" target="_blank">[30]</a>. B): Regional Health Units in Parana state. Source: Secretary of Health of Parana state (BR), 2012 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059363#pone.0059363-Brazil2" target="_blank">[34]</a>.</p

Figure 1

<p>Study flow diagram.</p

Spatial analysis of distance of the Reference Interventional Cardiology Centers and the mortality by IHD.

<p>A) Map with the approximate localization of the services of high complexity in cardiovascular and interventional surgery in Parana state, Brazil (arrows: indicate the localization of the Reference Interventional Cardiology Centers where the neighbor cities direct the IHD patient [Adapted from: Regional Master Plan/SESA, 2009]) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059363#pone.0059363-Brazil4" target="_blank">[46]</a>. B) Moran’s diagram of dispersion showing the relationship between the distance of the Reference Interventional Cardiology Centers to the patients residence city (X axis) and the weighted average of the specific mortality rate (SMR) by IHD of the neighbor cities (Y axis). C) LISA bivariate analysis: cluster formation according to the distance of the Reference Interventional Cardiology Center to the patients city of residence and the weighted average specific mortality rate (SMR) by IHD data of the respective neighbor cities (cluster type: high-high; low-low; low-high, high-low).</p

Acute Myocardial Infarction in Sub-Saharan Africa: The Need for Data

<div><p>Background</p><p>Trends in the prevalence of acute myocardial infarction in sub-Saharan Africa have not been well described, despite growing recognition of the increasing burden of cardiovascular disease in low- and middle-income countries. The aim of this systematic review was to describe the prevalence of acute myocardial infarction in sub-Saharan Africa.</p><p>Methods</p><p>We searched PubMed, EMBASE, Global Health Archive, CINAHL, and Web of Science, and conducted reference and citation analyses. Inclusion criteria were: observational studies, studies that reported incidence or prevalence of acute myocardial infarction, studies conducted in sub-Saharan Africa, and studies that defined acute myocardial infarction by EKG changes or elevation of cardiac biomarkers. Studies conducted prior to 1992 were excluded. Two independent reviewers analyzed titles and abstracts, full-texts, and references and citations. These reviewers also performed quality assessment and data extraction. Quality assessment was conducted with a validated scale for observational studies.</p><p>Findings</p><p>Of 2292 records retrieved, seven studies met all inclusion criteria. These studies included a total of 92,378 participants from highly heterogeneous study populations in five different countries. Methodological quality assessment demonstrated scores ranging from 3 to 7 points (on an 8-point scale). Prevalence of acute myocardial infarction ranged from 0.1 to 10.4% among the included studies.</p><p>Interpretation</p><p>There is insufficient population-based data describing the prevalence of acute myocardial infarction in sub-Saharan Africa. Well-designed registries and surveillance studies that capture the broad and diverse population with acute myocardial infarction in sub-Saharan Africa using common diagnostic criteria are critical in order to guide prevention and treatment strategies.</p><p>Registration</p><p>Registered in International Prospective Register of Systematic Reviews (PROSPERO) Database #CRD42012003161.</p></div

Global Moran’s I coefficient of the IHD specific mortality rate and geographic, demographic and socioeconomic indicators of the cities localized within Regional Health Units with or without Reference Interventional Cardiology Center (RICC).

<p>Global Moran’s I coefficient of the IHD specific mortality rate and geographic, demographic and socioeconomic indicators of the cities localized within Regional Health Units with or without Reference Interventional Cardiology Center (RICC).</p

Exploratory spatial analysis of specific mortality rate by IHD in state of Parana, Brazil, 2006–2010.

<p>A) Spatial distribution of cities’ specific mortality rate (SMR) by IHD, with ranges of standard deviation from the average for the delimitation of class intervals; the number of cities is in parenthesis. B) Moran’s diagram of dispersion (univariate analysis) of specific mortality rate (SMR) by IHD (X axis: city’s SMR; Y axis: weighted average SMR of the neighbor cities). C) LISA univariate analysis: cluster formation according to specific mortality rate (SMR) by IHD (Types of cluster: high-high; low-low; low-high, high-low).</p

Boxplot comparing specific mortality rate by IHD among cities with and without Reference Interventional Cardiology Centers (RICC).

<p>* p<0.001.</p

Moran’s diagram of dispersion (bivariate analysis).

<p>Analysis of socioeconomic or demographics variables of the city of residence of the patient (X axis) and the weighted average specific mortality rate by IHD of the neighbor cities (Y axis). A) Population Elderly Index. B) Illiteracy Rate. C) City Development Index (CDI). D) Gross Domestic Product (GDP). E) Adjusted Population Size.</p

Prevalence of MI among study populations of included studies.

<p>Prevalence of MI among study populations of included studies.</p

Figure 3

<p>Locations of studies of AMI in Sub-Populations of Sub-Saharan Africa.</p