Evidence map›Paper›PMID 35765874›Full record

ArticleAnnals of laboratory medicine2022

Predictors of Red Blood Cell Transfusion in Elderly COVID-19 Patients in Korea.

Hye Ryun Lee

Open access · diamondAbstract read
In one paragraph

Article in Annals of laboratory medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

1 author at 1 institution in 1 country.

Hye Ryun LeeDepartment of Laboratory Medicine, National Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0001-9175-6441
National Medical Center · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients who experience clinical deterioration from coronavirus disease (COVID-19) require blood transfusion support. We analyzed blood component usage in COVID-19 patients and identified the predictors of red blood cell (RBC) transfusion in elderly (≥65 years) patients. Methods: Blood component usage in 882 COVID-19 patients hospitalized between January 24, 2020 and April 30, 2021 was analyzed. Elderly patients were categorized into transfused and non-transfused groups according to their RBC transfusion history; their demographic and clinical characteristics, disease severity, and outcomes were compared. Associations were determined using multiple logistic regression. Results: The overall transfusion rate was 8.3% (73/882), and the transfusion rate was 2.7% (14/524) in patients aged <65 years and 16.5% (59/358) in those aged ≥65 years. Among the 358 elderly patients, 344 patients, including 50 who received transfusion and 294 who did not, were enrolled for the analysis. The prevalence of diabetes mellitus (DM), white blood cell count, absolute neutrophil count, and neutrophil-to-lymphocyte ratio (NLR) on admission were significantly higher in the transfused group, whereas Hb and platelet counts were significantly lower. Disease severity in the transfused group was relatively high on admission and increased thereafter. DM, intensive care unit entrance on admission, Hb, platelet count, and NLR on admission were independently associated with RBC transfusion. Conclusions: This study presents transfusion rates in COVID-19 patients according to age groups and predictors of RBC transfusion in elderly patients. The results provide a basis for developing a strategy for the medical treatment of infectious diseases emerging during pandemics.

Indexed as

COVID-19Erythrocyte TransfusionAgedHumansLeukocyte CountPandemicsRepublic of KoreaBlood transfusionCOVID-19ElderlyPredictorsRed blood cell

Identifiers

PMID35765874
PMCPMC9277048
OpenAlexW4283704229

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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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.