Evidence map›Paper›PMID 35591829›Full record

ArticleArchives of medical science : AMS2022

Ethnicity and other COVID-19 death risk factors in Mexico.

Erwin Chiquete, Jesus Alegre-Díaz, Ana Ochoa-Guzmán, Liz Nicole Toapanta-Yanchapaxi, Carlos González-Carballo, Adrián Garcilazo-Ávila, Rogelio Santacruz-Benitez, Raúl Ramírez-Reyes, Rosa María Wong-Chew, Guadalupe Guerrero and 5 more

Open access · goldAbstract read
In one paragraph

Article in Archives of medical science : AMS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.3field-weighted citation impact, top 29% 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

10 citing papers in PubMed, 18 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

15 authors at 3 institutions in 1 country.

Erwin ChiqueteInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Jesus Alegre-DíazUnidad de Investigación en Medicina Experimental, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico.
Ana Ochoa-GuzmánInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Liz Nicole Toapanta-YanchapaxiInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Carlos González-CarballoInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Adrián Garcilazo-ÁvilaInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Rogelio Santacruz-BenitezInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Raúl Ramírez-ReyesInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Rosa María Wong-ChewFacultad de Medicina, Universidad Nacional Autónoma de México, Mexico.
Guadalupe GuerreroHospital General de México "Dr. Eduardo Liceaga", Mexico City, Mexico City, Mexico.
Max SchmulsonUnidad de Investigación en Medicina Experimental, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico.
Jaime BerumenUnidad de Investigación en Medicina Experimental, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico.
Valeria Sandoval-RodríguezInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Eduardo Ruiz-RuizInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Carlos Cantú-BritoInstituto Nacional de Ciencias Médicas y de la Nutrición "Salvador Zubirán", Mexico City, Mexico.
Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán · MXUniversidad Nacional Autónoma de México · MXHospital General de México · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may develop coronavirus disease 2019 (COVID-19). Risk factors associated with death vary among countries with different ethnic backgrounds. We aimed to describe the factors associated with death in Mexicans with confirmed COVID-19. Material and methods: We analysed the Mexican Ministry of Health's official database on people tested for SARS-CoV-2 infection by real-time reverse transcriptase-polymerase chain reaction (rtRT-PCR) of nasopharyngeal fluids. Bivariate analyses were performed to select characteristics potentially associated with death, to integrate a Cox-proportional hazards model. Results: As of May 18, 2020, a total of 177,133 persons (90,586 men and 86,551 women) in Mexico received rtRT-PCR testing for SARS-CoV-2. There were 5332 deaths among the 51,633 rtRT-PCR-confirmed cases (10.33%, 95% CI: 10.07-10.59%). The median time (interquartile range, IQR) from symptoms onset to death was 9 days (5-13 days), and from hospital admission to death 4 days (2-8 days). The analysis by age groups revealed that the significant risk of death started gradually at the age of 40 years. Independent death risk factors were obesity, hypertension, male sex, indigenous ethnicity, diabetes, chronic kidney disease, immunosuppression, chronic obstructive pulmonary disease, age > 40 years, and the need for invasive mechanical ventilation (IMV). Only 1959 (3.8%) cases received IMV, of whom 1893 were admitted to the intensive care unit (96.6% of those who received IMV). Conclusions: In Mexico, highly prevalent chronic diseases are risk factors for death among persons with COVID-19. Indigenous ethnicity is a poorly studied factor that needs more investigation.

Indexed as

atypical pneumoniacoronavirusCOVID-19ethnicityMexicopandemics

Identifiers

PMID35591829
PMCPMC9103400
OpenAlexW3108402206

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.