Evidence map›Paper›PMID 36575597›Full record

ArticleNursing open2023

Predictors of mortality and ICU requirement in hospitalized COVID-19 patients with diabetes: A multicentre study.

Md Asaduzzaman, Mohammad Romel Bhuia, Mohammad Zabed Jillul Bari, Zhm Nazmul Alam, Khalidur Rahman, Enayet Hossain, Munsi Mohammad Jahangir Alam

Abstract readMulticenter Study
In one paragraph

Article in Nursing open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

7 authors.

Md AsaduzzamanDepartment of Medicine, Sylhet MAG Osmani Medical College Hospital, Sylhet, Bangladesh.ORCID 0000-0001-9558-0594
Mohammad Romel BhuiaDepartment of Statistics, Shahjalal University of Science and Technology, Sylhet, Bangladesh.
Mohammad Zabed Jillul BariDepartment of Medicine, Sylhet MAG Osmani Medical College, Sylhet, Bangladesh.
Zhm Nazmul AlamDepartment of Medicine, Sylhet MAG Osmani Medical College Hospital, Sylhet, Bangladesh.
Khalidur RahmanDepartment of Statistics, Shahjalal University of Science and Technology, Sylhet, Bangladesh.ORCID 0000-0002-2899-804X
Enayet HossainDepartment of Medicine, Sylhet MAG Osmani Medical College, Sylhet, Bangladesh.
Munsi Mohammad Jahangir AlamDepartment of Medicine, Sylhet MAG Osmani Medical College, Sylhet, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThis study aimed to identify the predictors of mortality and ICU requirements in hospitalized COVID-19 Patients with Diabetes.

designCross-sectional study.

methodsIt was a retrospective study of patients hospitalized with COVID-19 infection from October 2020-February 2021 in four hospitals in Sylhet, Bangladesh. Logistic regression analysis was applied to explore the predictors of ICU requirement and in-hospital mortality.

resultsIn the whole cohort (n = 500), 11% of patients died and 24% of patients required intensive care unit (ICU) support. Non-survivors had significantly higher prevalence of lymphopenia, thrombocytopenia and leukocytosis. Significant predictors of in-hospital mortality were older age, neutrophil count, platelet count and admission peripheral capillary oxygen saturation (SpO2). Older age, ischemic heart disease, WBC count, D-dimer and admission SpO2 were identified as significant predictors for ICU requirement. PATIENT OR PUBLIC CONTRIBUTION: No.

Indexed as

COVID-19Diabetes MellitusThrombocytopeniaBangladeshCross-Sectional StudiesHumansIntensive Care UnitsRetrospective StudiesSARS-CoV-2COVID-19DMICU requirementMortality

Identifiers

PMID36575597
PMCPMC9880734

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.