Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add filters

Database
Language
Document Type
Year range
1.
Medicine (Baltimore) ; 102(12): e33343, 2023 Mar 24.
Article in English | MEDLINE | ID: covidwho-2256823

ABSTRACT

Health information is particularly essential in times of pandemics in which rapid response is crucial for political and stakeholder decision-making processes, and therefore the availability of data as well as its quality analysis are necessary. This study aimed to describe the completeness and quality of the e-Sistema Único de Saúde (SUS) Health Surveillance database (SUS Vigilância em Saúde) of the state of Espírito Santo, Brazil, from the notification of deaths from corana virus disease 2019 (COVID-19) from January 2020 to June 2021. A descriptive population-based register study was conducted from the analysis of the completeness of secondary data from the record of deaths from COVID-19, retrieved from the e-SUS Vigilância em Saúde (Health Surveillance) (VS) database of the state of Espírito Santo, Brazil, from January 2020 to June 2021. A total of 11,359 death records from COVID-19 via e-SUS VS in the state of Espírito Santo, Brazil, were evaluated. The score used to assess incompleteness was the 1 proposed by Romero and Cunha which classifies as excellent (when < 5%), good (between 5% and 10%), regular (between 10% and 20%), poor (between 20% and 50%), and very poor (when > 50%), according to the percentage of the absence of information. Descriptive statistical analyses were conducted in the Stata program, version 15.1. "Case identification" variables, and "condition" variables were classified as excellent completeness. Among the evolution variables, only "hospitalization" was classified as regular. Among the laboratory variables, only the polymerase chain reaction presented excellent completeness, while the "rapid test" and "serologies for immunoglobulin G, and immunoglobulin M" variables were classified as good completeness. It is concluded that most of the variables available in e-SUS VS of the state of Espírito Santo, Brazil, of notification of deaths from COVID-19 in 2020 presented excellent completeness, confirming the excellent quality of the state database.


Subject(s)
COVID-19 , Virus Diseases , Humans , Brazil/epidemiology , Databases, Factual
2.
Int J Environ Res Public Health ; 19(21)2022 Oct 28.
Article in English | MEDLINE | ID: covidwho-2090167

ABSTRACT

OBJECTIVE: To analyze COVID-19 deaths in public hospitals in a Brazilian state, stratified by the three waves of the pandemic, and to test their association with socio-clinical variables. METHODS: Observational analytical study, where 5436 deaths by COVID-19 occurred in hospitals of the public network of Espírito Santo, between 1 April 2020, and 31 August 2021, stratified by the three waves of the pandemic, were analyzed. For the bivariate analyses, the Pearson's chi-square, Fisher's Exact or Friedman's tests were performed depending on the Gaussian or non-Gaussian distribution of the data. For the relationship between time from diagnosis to death in each wave, quantile regression was used, and multinomial regression for multiple analyses. RESULTS: The mean time between diagnosis and death was 18.5 days in the first wave, 20.5 days in the second wave, and 21.4 days in the third wave. In the first wave, deaths in public hospitals were associated with the following variables: immunodeficiency, obesity, neoplasia, and origin. In the second wave, deaths were associated with education, O2 saturation < 95%, chronic neurological disease, and origin. In the third wave, deaths were associated with race/color, education, difficulty breathing, nasal or conjunctival congestion, irritability or confusion, adynamia or weakness, chronic cardiovascular disease, neoplasms, and diabetes mellitus. Origin was associated with the outcome in the three waves of the pandemic, in the same way that education was in the second and third waves (p < 0.05). CONCLUSION: The time interval between diagnosis and death can be impacted by several factors, such as: plasticity of the health system, improved clinical management of patients, and the start of vaccination at the end of January 2021, which covered the age group with the higher incidence of deaths. The deaths occurring in public hospitals were associated with socio-clinical characteristics.


Subject(s)
COVID-19 , Pandemics , Humans , COVID-19/epidemiology , Brazil/epidemiology , Hospitals, Public , Incidence
SELECTION OF CITATIONS
SEARCH DETAIL