Evidence map›Paper›PMID 36767733›Full record

ArticleInternational journal of environmental research and public health2023

COVID-19 Mortality in the Colorado Center for Personalized Medicine Biobank.

Amanda N Brice, Lauren A Vanderlinden, Katie M Marker, David Mayer, Meng Lin, Nicholas Rafaels, Jonathan A Shortt, Alex Romero, Jan T Lowery, Christopher R Gignoux and 1 more

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Amanda N BriceDepartment of Epidemiology, Colorado School of Public Health, Aurora, CO 80045, USA.
Lauren A VanderlindenDepartment of Epidemiology, Colorado School of Public Health, Aurora, CO 80045, USA.
Katie M MarkerHuman Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.ORCID 0000-0003-3441-401X
David MayerDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.ORCID 0000-0002-6056-9771
Meng LinDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
Nicholas RafaelsColorado Center for Personalized Medicine, Aurora, CO 80045, USA.
Jonathan A ShorttDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.ORCID 0000-0002-7980-5420
Alex RomeroDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
Jan T LoweryDepartment of Epidemiology, Colorado School of Public Health, Aurora, CO 80045, USA.
Christopher R GignouxHuman Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
Randi K JohnsonDepartment of Epidemiology, Colorado School of Public Health, Aurora, CO 80045, USA.ORCID 0000-0001-9345-4439

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over 6.37 million people have died from COVID-19 worldwide, but factors influencing COVID-19-related mortality remain understudied. We aimed to describe and identify risk factors for COVID-19 mortality in the Colorado Center for Personalized Medicine (CCPM) Biobank using integrated data sources, including Electronic Health Records (EHRs). We calculated cause-specific mortality and case-fatality rates for COVID-19 and common pre-existing health conditions defined by diagnostic phecodes and encounters in EHRs. We performed multivariable logistic regression analyses of the association between each pre-existing condition and COVID-19 mortality. Of the 155,859 Biobank participants enrolled as of July 2022, 20,797 had been diagnosed with COVID-19. Of 5334 Biobank participants who had died, 190 were attributed to COVID-19. The case-fatality rate was 0.91% and the COVID-19 mortality rate was 122 per 100,000 persons. The odds of dying from COVID-19 were significantly increased among older men, and those with 14 of the 61 pre-existing conditions tested, including hypertensive chronic kidney disease (OR: 10.14, 95% CI: 5.48, 19.16) and type 2 diabetes with renal manifestations (OR: 5.59, 95% CI: 3.42, 8.97). Male patients who are older and have pre-existing kidney diseases may be at higher risk for death from COVID-19 and may require special care.

Indexed as

COVID-19Diabetes Mellitus, Type 2AgedBiological Specimen BanksColoradoHumansMalePrecision MedicineRisk FactorsSARS-CoV-2cardiovascular diseasecauses of deathCOVID-19COVID-19 related mortalitydiabetesrespiratory disease

Identifiers

PMID36767733
PMCPMC9916246

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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.