Confronting mobile phone signal coverage and helicopter emergency medical service travel time: A geospatial analysis in the northwest macro-region of Paraná State, Brazil.

Objective: The aim of this study was to conduct a detailed geospatial analysis of mobile phone signal coverage in the northwest macro-region of Paraná State, Brazil, seeking to identify areas where limitations in coverage may be related to lengthy travel times of the helicopter emergency medical service (HEMS) for the assistance of victims of road traffic injuries (RTIs).

Methods: An observational study was conducted to examine mobile phone signal coverage and HEMS travel times from 2017 to 2021. HEMS travel times were categorized into four groups: T1 (0-15 min), T2 (16-30 min), T3 (31-45 min), and T4 (over 45 min).

Geographical disparities in access to surgical treatment and mortality rates from abdominal aortic aneurysms in Brazil: A retrospective longitudinal study.

Introduction: Abdominal aortic aneurysm (AAA) is a growing public health problem, and not all patients have access to surgery when needed. This study aimed to analyze spatiotemporal variations in AAA mortality and surgical procedures in Brazilian intermediate geographic regions and explore the impact of different surgical techniques on operative mortality.

Methods: A retrospective longitudinal study was conducted to evaluate AAA mortality from 2008 to 2020 using space-time cube (STC) analysis and the emerging hot spot analysis tool through the Getis-Ord Gi* method.

Open or closed abdomen post laparotomy to control severe abdominal sepsis: a survival analysis.

Introduction: severe abdominal sepsis, accompained by diffuse peritonitis, poses a significant challenge for most surgeons. It often requires repetitive surgical interventions, leading to complications and resulting in high morbidity and mortality rates. The open abdomen technique, facilitated by applying a negative-pressure wound therapy (NPWT), reduces the duration of the initial surgical procedure, minimizes the accumulation of secretions and inflammatory mediators in the abdominal cavity and lowers the risk of abdominal compartment syndrome and its associated complications.

Applicability of machine learning algorithm to predict the therapeutic intervention success in Brazilian smokers.

Smoking cessation is an important public health policy worldwide. However, as far as we know, there is a lack of screening of variables related to the success of therapeutic intervention (STI) in Brazilian smokers by machine learning (ML) algorithms. To address this gap in the literature, we evaluated the ability of eight ML algorithms to correctly predict the STI in Brazilian smokers who were treated at a smoking cessation program in Brazil between 2006 and 2017.

Correction: Applicability of machine learning technique in the screening of patients with mild traumatic brain injury.

[This corrects the article DOI: 10.1371/journal.pone.

Applicability of machine learning technique in the screening of patients with mild traumatic brain injury.

Even though the demand of head computed tomography (CT) in patients with mild traumatic brain injury (TBI) has progressively increased worldwide, only a small number of individuals have intracranial lesions that require neurosurgical intervention. As such, this study aims to evaluate the applicability of a machine learning (ML) technique in the screening of patients with mild TBI in the Regional University Hospital of Maringá, Paraná state, Brazil. This is an observational, descriptive, cross-sectional, and retrospective study using ML technique to develop a protocol that predicts which patients with an initial diagnosis of mild TBI should be recommended for a head CT.

Built environment influence on the incidence of elderly pedestrian collisions in a medium-large city in southern Brazil: a spatial analysis.

Trauma disproportionately affects vulnerable road users, especially the elderly. We analyzed the spatial distribution of elderly pedestrians struck by vehicles in the urban area of Maringa city, from 2014 to 2018. Hotspots were obtained by kernel density estimation and wavelet analysis.

Air Medical Transportation Provided by Norte Novo Regional Urgency Mobile Service: What Is the Current Scenario?

Objective: The aim of this study was to investigate, describe, and analyze the Norte Novo regional air medical service provided by the Brazilian Emergency Medical Rescue Service.

Methods: This was a retrospective and descriptive study with a quantitative approach of the incidents registered from November 2016 to December 2019. For general patient classification, descriptive statistics of the following variables were performed: sex, age/age group, type of diagnosis, city where the incident took place, city of destination, length of patient care, ventilatory support, use of sedation, and use of vasoactive drugs.

Emergency Care Gap in Brazil: Geographical Accessibility as a Proxy of Response Capacity to Tackle COVID-19.

The new coronavirus disease (COVID-19) has claimed thousands of lives worldwide and disrupted the health system in many countries. As the national emergency care capacity is a crucial part of the COVID-19 response, we evaluated the Brazilian Health Care System response preparedness against the COVID-19 pandemic. A retrospective and ecological study was performed with data retrieved from the Brazilian Information Technology Department of the Public Health Care System.

Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access.

Background: The benefits of treatment for many conditions are time dependent. The burden of these emergency care sensitive conditions (ECSCs) is especially high in low- and middle-income countries. Our objective was to analyze geospatial trends in ECSCs and characterize regional disparities in access to emergency care in Brazil.

The Impact of Socioeconomic Factors, Coverage and Access to Health on Heart Ischemic Disease Mortality in a Brazilian Southern State: A Geospatial Analysis.

Background: No other disease has killed more than ischemic heart disease (IHD) for the past few years globally. Despite the advances in cardiology, the response time for starting treatment still leads patients to death because of the lack of healthcare coverage and access to referral centers.

Objectives: To analyze the spatial disparities related to IHD mortality in the Parana state, Brazil.

Spatial inequalities of major lower limb amputation rates in Paraná state, Brazil.

Objective: The aim of this observational cross-sectional study was to analyse the spatial distribution of major lower limb amputation (MLLA) rates and associate them to socioeconomic, demographic and public healthcare access-related variables in the State of Paraná, Brazil, from 2012 to 2017.

Method: Data on MLLA, revascularisation surgeries, diagnostic exams and healthcare coverage were obtained from the Brazilian Public Hospital Information System. Socioeconomic data were obtained from the Brazilian Institute of Geography and Statistics.

Mapping risk of ischemic heart disease using machine learning in a Brazilian state.

Cardiovascular diseases are the leading cause of deaths globally. Machine learning studies predicting mortality rates for ischemic heart disease (IHD) at the municipal level are very limited. The goal of this paper was to create and validate a Heart Health Care Index (HHCI) to predict risk of IHD based on location and risk factors.