Evidence map›Paper›PMID 35324951›Full record

ArticlePloS one2022

Analysis of the impact of coronavirus disease 19 on hospitalization rates for chronic non-communicable diseases in Brazil.

Rafael Alves Guimarães, Gabriela Moreira Policena, Hellen da Silva Cintra de Paula, Charlise Fortunato Pedroso, Raquel Silva Pinheiro, Alexander Itria, Olavo de Oliveira Braga Neto, Adriana Melo Teixeira, Irisleia Aires Silva, Geraldo Andrade de Oliveira and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.9field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 28 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

Rafael Alves GuimarãesFaculty of Nursing, Federal University of Goiás, Goiânia, Goiás, Brazil.ORCID 0000-0001-5171-7958
Gabriela Moreira PolicenaInstitute of Tropical Pathology and Public Health, Federal University of Goiás, Goiânia, Goiás, Brazil.
Hellen da Silva Cintra de PaulaFederal Institute of Education, Science and Technology of Goiás, Goiânia Oeste Campus, Goiânia, Goiás, Brazil.ORCID 0000-0003-2083-3651
Charlise Fortunato PedrosoFederal Institute of Education, Science and Technology of Goiás, Goiânia Oeste Campus, Goiânia, Goiás, Brazil.
Raquel Silva PinheiroInstitute of Tropical Pathology and Public Health, Federal University of Goiás, Goiânia, Goiás, Brazil.
Alexander ItriaFederal University of São Carlos, Sorocaba Campus, Sorocaba, São Paulo, Brazil.
Olavo de Oliveira Braga NetoDepartment of Hospital and Emergency Care of the Ministry of Health, Distrito Federal, Brasília, Brazil.
Adriana Melo TeixeiraDepartment of Hospital and Emergency Care of the Ministry of Health, Distrito Federal, Brasília, Brazil.
Irisleia Aires SilvaDepartment of Hospital and Emergency Care of the Ministry of Health, Distrito Federal, Brasília, Brazil.
Geraldo Andrade de OliveiraFederal Institute of Education, Science and Technology of Goiás, Valparaíso Campus, Valparaíso, Goiás, Brazil.
Karla de Aleluia BatistaFederal Institute of Education, Science and Technology of Goiás, Goiânia Oeste Campus, Goiânia, Goiás, Brazil.
Instituto Federal de Goiás · BRMinistério da Saúde · BRUniversidade Federal de Goiás · BRUniversidade Federal de São Carlos · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe coronavirus disease (COVID-19) pandemic has impacted health services and healthcare systems worldwide. Studies have shown that hospital admissions for causes related to chronic non-communicable diseases (NCDs) have decreased significantly during peak pandemic periods. An analysis of the impact of the COVID-19 pandemic on hospital admissions for NCDs is essential to implement disability and mortality mitigation strategies for these groups. Therefore, this study aimed to analyze the impact of the COVID-19 pandemic on hospital admissions for NCDs in Brazil according to the type of NCD, sex, age group, and region of Brazil.

methodsThis is an ecological study conducted in Brazil. Data on hospital admissions from January 1, 2017 to May 31, 2021 were extracted from the Unified Health System's Hospital Admissions Information System. The hospital admission rates per 100,000 thousand inhabitants were calculated monthly according to the type of NCD, sex, age group, and region of Brazil. Poisson regression models were used to analyze the impact of the COVID-19 pandemic on the number of hospital admissions. In this study, the pre-pandemic period was set from January 1, 2017 to February 29, 2020 and the during-pandemic from March 1, 2020 to May 31, 2021.

resultsThere was a 27.0% (95.0%CI: -29.0; -25.0%) decrease in hospital admissions for NCDs after the onset of the pandemic compared to that during the pre-pandemic period. Decreases were found for all types of NCDs-cancer (-23.0%; 95.0%CI: -26.0; -21.0%), diabetes mellitus (-24.0%; 95.0%CI: -25.0%; -22.0%), cardiovascular diseases (-30.0%; 95.0%CI: -31.0%; -28.0%), and chronic respiratory diseases (-29.0%; 95.0%CI: -30.0%; -27.0%). In addition, there was a decrease in the number of admissions, regardless of the age group, sex, and region of Brazil. The Northern and Southern regions demonstrated the largest decrease in the percentage of hospital admissions during the pandemic period.

conclusionsThere was a decrease in the hospitalization rate for NCDs in Brazil during the COVID-19 pandemic in a scenario of social distancing measures and overload of health services.

Indexed as

COVID-19Noncommunicable DiseasesBrazilHospitalizationHumansPandemics

Identifiers

PMID35324951
PMCPMC8947087
OpenAlexW4220847457

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.