Evidence map›Paper›PMID 40956850›Full record

ArticlePloS one2025

Osmolality as a strong predictor of COVID-19 mortality and its possible links to other biomarkers.

Sirin Cetin, Ayse Ulgen, Hakan Sivgin, Meryem Cetin, Wentian Li

Abstract read
In one paragraph

Article in PloS one, 2025. 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
–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

1 citing paper in PubMed.

  1. 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

5 authors.

Sirin CetinDepartment of Biostatistics, Faculty of Medicine, Amasya University, Amasya, Türkiye.
Ayse UlgenDepartment of Mathematics, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.ORCID 0000-0002-0872-667X
Hakan SivginDepartment of Internal Medicine, Faculty of Medicine, Tokat Gaziosmanpaşa University, Tokat, Türkiye.
Meryem CetinDepartment of Medical Microbiology, Faculty of Medicine, Amasya University, Amasya, Türkiye.
Wentian LiDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, United States of America.ORCID 0000-0003-1155-110X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osmolality, concentration of solute particles, was rarely used for prognosis for COVID-19. By analyzing blood samples of more than 1300 COVID-19 patients from Tokat, Turkey (including 100 surviving and 30 deceased inpatients), we found calculated osmolality to be an excellent prognostic biomarker for mortality and significantly associated with hospitalization, independent from gender and age. Although calculated osmolality is defined as a weighted sum of sodium, glucose, and urea, the three are not necessarily independent. Other blood test biomarkers, ferritin, creatine, and chloride are also correlated with osmolality after conditioning on age. By applying a combination of collider analysis and mediation analysis, we design a pipeline to construct a causal model among all these variables in their relationship to osmolality. We confirm that while glucose and sodium are independent contributors of osmolality, glucose and urea, urea and sodium are correlated. We also conclude that ferritin and creatine are associated with osmolality through urea, and chloride's association to osmolality is through sodium.

Indexed as

COVID-19AdultAgedAged, 80 and overBiomarkersChloridesCreatineFemaleFerritinsHumansMaleMiddle AgedOsmolar ConcentrationPrognosisSARS-CoV-2SodiumBiomarkersChloridesCreatineFerritinsSodiumUrea

Identifiers

PMID40956850
PMCPMC12440178

What OpenQuestion holds

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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.