Evidence map›Paper›PMID 36505139›Full record

ArticleCureus2022

Risk Factors Associated With Six-Month Mortality in Hospitalized COVID-19 Patients: A Single-Institution Study.

Navkirat Kahlon, Jasskiran Kaur, Sishir Doddi, Cameron Burmeister, Taha Sheikh, Ziad Abuhelwa, Aya Abugharbyeh, Ragheb Assaly, William Barnett, Danae Hamouda

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 2 institutions in 1 country.

Navkirat KahlonHematology and Medical Oncology, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
Jasskiran KaurInternal Medicine, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
Sishir DoddiInternal Medicine, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
Cameron BurmeisterInternal Medicine, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
Taha SheikhInternal Medicine, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
Ziad AbuhelwaInternal Medicine, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
Aya AbugharbyehRheumatology, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
Ragheb AssalyPulmonary/Critical Care Medicine, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
William BarnettBiostatistics and Epidemiology, The University of Toledo Medical Center, Toledo, USA.
Danae HamoudaHematology and Medical Oncology, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
University of Toledo · USUniversity of Toledo Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Coronavirus disease 2019 (COVID-19) infection can vary from asymptomatic infection to multi-organ dysfunction. The most serious complication of infection with COVID-19 is death. Various comorbid conditions and inflammatory markers have been associated with an increased risk of mortality, specifically within the immediate post-infection period; however, less is known about long-term mortality outcomes. Objectives Our objective is to determine risk factors associated with six-month mortality in hospitalized COVID-19 patients. Methods This is a single-institution, retrospective study. We included patients hospitalized with COVID-19 from the University of Toledo Medical Center in Toledo, Ohio, who were admitted from March 20, 2020, to June 30, 2021. This study was approved by a biomedical institutional review board at the University of Toledo. Patients with available pre-stored blood samples for laboratory testing were included, and hospital charts were assessed up to six months from the date of a positive COVID-19 test result. Two groups were created based on the mortality outcome at six months from COVID-19 positive test results: survivors and non-survivors. The clinical variables or outcomes and laboratory values were compared between the two groups using non-parametric methods due to the small sample size and non-normality of the data. Either the Mann-Whitney U-test for continuous variables or Fisher's exact test for categorical variables was used for statistical analysis. Results Lactate dehydrogenase (LDH) and D-dimer levels on admission were found to be significantly higher in non-survivors than in survivors. The median high D-dimer level in non-survivors was 5.96 micrograms/milliliter (μg/mL) (interquartile range (IQR): 3.95-11.29 μg/mL) vs 1.82 μg/mL (IQR 1.13-5.55 μg/mL) in survivors (p = 0.019). Median LDH levels were also higher in non-survivors vs survivors, i.e., 621.00 international units per liter (IU/L) (IQR 440.00-849.00 IU/L) vs 328.00 IU/L (IQR 274.00-529.00 IU/L), respectively (p = 0.032). The demographic profile, comorbidity profile, and laboratory data (typically associated with short-term mortality, inflammation, and organ dysfunction) were similar between survivors and non-survivors, except for LDH and D-dimer. Conclusion Higher LDH and D-dimer levels on admission were found to be associated with an increased six-month mortality rate in hospitalized COVID-19 patients. These hematologic data can serve as risk stratification tools to prevent long-term mortality outcomes and provide proactive clinical care in hospitalized COVID-19 patients.

Indexed as

6-month mortalitycovid-19 mortalityelevated d-dimerelevated ldhlactate dehydrogenase

Identifiers

PMID36505139
PMCPMC9728985
OpenAlexW4308408708

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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 OpenQuestion graph.