What most influences severity and death of COVID-19 patients in Brazil? Is it clinical, social, or demographic factors? An observational study
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Objective
This study aimed to assess the space distribution and factors associated with the risk of severe acute respiratory syndrome (SARS) and death in COVID-19 patients, based on routine register data; and to develop and validate a predictive model of the risk of death from COVID-19.
Methods
A cross-sectional, epidemiological study of positive SARS-CoV-2 cases, reported in the south region of the city of São Paulo, SP, Brazil, from March 2020 to February 2021. Data were obtained from the official reporting databases of the Brazilian Ministry of Health for influenza-like illness (ILI) (esus-VE, in Portuguese) and for patients hospitalized for SARS (SIVEP-Gripe). The space distribution of cases is described by 2D kernel density. To assess potential factors associated with the outcomes of interest, generalized linear and additive logistic models were adjusted. To evaluate the discriminatory power of each variable studied as well as the final model, C-statistic was used (area under the receiver operating characteristics curve). Moreover, a predictive model for risk of death was developed and validated with accuracy measurements in the development, internal and temporal (March and April 2021) validation samples.
Results
A total of 16,061 patients with confirmed COVID-19 were enrolled. Morbidities associated with a higher risk of SARS were obesity (OR=25.32) and immunodepression (OR=12.15). Morbidities associated with a higher risk of death were renal disease (OR=11.8) and obesity (OR=8.49), and clinical and demographic data were more important than the territory per se . Based on the data, a calculator was developed to predict the risk of death from COVID-19, with 92.2% accuracy in the development sample, 92.3% in the internal validation sample, and 80.0% in the temporal validation sample.
Conclusions
The risk factors for SARS and death in COVID-19 patients seeking health care, in order of relevance, were age, comorbidities, and socioeconomic factors, considering each discriminatory power.
Article activity feed
-
SciScore for 10.1101/2021.06.03.21258128: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: This study was approved by the Institutional Review Boards of Hospital Israelita Albert Einstein and the São Paulo Health Department, protocol numbers 4.462.994 and 4.648.956, respectively. Sex as a biological variable not detected. Randomization The data was randomly split in two sets with a 2:1 ratio for training and testing, respectively. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Health care facilities were categorized as privet or public according to the National Registry of Health Care Facilities (CNES, in Portuguese), and was considered in the analyses as an indicator of health care access, since public health services … SciScore for 10.1101/2021.06.03.21258128: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: This study was approved by the Institutional Review Boards of Hospital Israelita Albert Einstein and the São Paulo Health Department, protocol numbers 4.462.994 and 4.648.956, respectively. Sex as a biological variable not detected. Randomization The data was randomly split in two sets with a 2:1 ratio for training and testing, respectively. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Health care facilities were categorized as privet or public according to the National Registry of Health Care Facilities (CNES, in Portuguese), and was considered in the analyses as an indicator of health care access, since public health services are universally accessible, while only those with health insurance or high income have access to private services. Portuguesesuggested: NoneAll analyses were performed with the R software, version 3.6.3 [17], with the mgcv [18], ggplot2 [19] and viridis [20] packages. ggplot2suggested: (ggplot2, RRID:SCR_014601)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Booth et al. [39] proposed a different strategy to predict deaths associated with COVID-19 employing molecular biomarkers measured in laboratory samples used for PCR tests; however, this approach presents limitations related to cost and availability of results in a timely manner, in addition a lower performance when compared to the model proposed by this study, with a C-statistic of 93%, sensitivity of 91% and specificity of 91%. Additional studies have focused only on the elderly or hospitalized individuals [40,41]. The model proposed by this study is a powerful response to support managers and other professionals in planning patient care, prioritizing more targeted and assertive strategies and actions, such as monitoring of positive cases with higher prediction of death, stewardship, and distribution of resources at different care levels, regions and cities, including different vulnerability contexts. Added to the risk factors highlighted in this study, many countries in the world are going through an economic, political and ethical crisis, including Brazil, with defective response, policies that go against social distancing, lack of country-level coordination, negationism, and neoliberal policies [42], which may affect the outcomes of this pandemic. Thus, the response to the pandemic in these settings must be challenged, and larger studies including these variables in the analyses are required, such as the need for interdisciplinary analyses [43–45], considering the clinic...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
-
