Evidence map›Paper›PMID 35722260›Full record

ArticlePeerJ2022

Association between chronic kidney disease and mortality in patients with a confirmed COVID-19 diagnosis.

Jacqueline Betsabe Puicón-Suárez, Sandra Zeña-Ñañez, Virgilio E Failoc-Rojas

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 33% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. COVID-19 and chronic kidney disease: a bibliometric analysis.Annals of medicine and surgery (2012) · 2024
    Review
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

3 authors at 3 institutions in 1 country.

Jacqueline Betsabe Puicón-SuárezSociedad Científica de Estudiantes de Medicina, SOCIEM-UNPRG, Universidad Nacional Pedro Ruiz Gallo, Lambayeque, Perú.
Sandra Zeña-ÑañezUniversidad Continental, Huancayo, Perú.
Virgilio E Failoc-RojasUniversidad San Ignacio de Loyola, Lima, Peru.
EsSALUD · PEUniversidad Continental · PEUniversidad Nacional Pedro Ruíz Gallo · PE

Funding

Training in Parasitic Diseases and Central Nervous System Infections in Peru.D43TW001140 · FIC · UNIVERSIDAD PERUANA CAYETANO HEREDIA · PI GARCIA, HECTOR HUGO, GILMAN, ROBERT H · 1999 to 2025
$5.7M
FIC NIH HHS D43 TW001140
6 · The paper itself

Abstract

Objective: To determine the association between chronic kidney disease (CKD) and mortality in persons with a confirmed coronavirus disease 2019 (COVID-19) diagnosis. Methods: Cross-sectional secondary baseline study. The study population consisted of 243,065 patients confirmed to have COVID-19 during May-December 2020. Stata 16.0 was used for statistical analysis, Chi-square test was used for bivariate analysis, and Poisson regression with robust variances was used for multiple analysis. Results: The prevalence of patients with a confirmed COVID-19 diagnosis who had CKD and died was 1.42 times the prevalence of mortality in those without CKD. The comorbidities combined with CKD that presented the highest probability of mortality were diabetes mellitus and hypertension. Conclusions: CKD is associated with a high mortality rate in patients with a confirmed COVID-19 diagnosis. Patients with CKD, diabetes mellitus, and arterial hypertension have a higher prevalence of mortality than those without comorbidities.

Indexed as

COVID-19Diabetes MellitusHypertensionRenal Insufficiency, ChronicCOVID-19 TestingCross-Sectional StudiesHumansChronic kidney diseaseCOVID-19MexicoMortality

Identifiers

PMID35722260
PMCPMC9205307
OpenAlexW4282843520

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.