Evidence map›Paper›PMID 34955552›Full record

ArticleJournal of evolutionary biochemistry and physiology2021

Analysis of Some Physiological and Biochemical Indices in Patients with Covid-19 Pneumonia Using Mathematical Methods.

M S Gromov, S M Rogacheva, M A Barulina, A A Reshetnikov, D A Prokhozhev, A Yu Fomina

Open access · bronzeAbstract read
In one paragraph

Article in Journal of evolutionary biochemistry and physiology, 2021. 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
0.1field-weighted citation impact, top 49% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

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

6 authors at 3 institutions in 1 country.

M S GromovSaratov Medical University "Reaviz", Saratov, Russia.
S M RogachevaSaratov Medical University "Reaviz", Saratov, Russia.
M A BarulinaSaratov Medical University "Reaviz", Saratov, Russia.
A A ReshetnikovV.I. Razumovsky Saratov City Clinical Hospital No. 2, Saratov, Russia.
D A ProkhozhevSaratov Medical University "Reaviz", Saratov, Russia.
A Yu FominaSaratov Medical University "Reaviz", Saratov, Russia.
Samara Medical Institute Reaviz · RUInstitute of Precision Mechanics and Control · RUSaratov City Clinical Hospital № 2 named. IN AND. Razumovsky · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the work was to conduct a retrospective analysis of the clinical data of patients with pneumonia caused by the SARS-CoV-2 virus, and to determine via mathematical methods the significance of some physiological and biochemical indices as predictive markers of an unfavorable outcome of the disease. A random cohort of patients with COVID-19 pneumonia numbered 209 people. Mathematical analysis addressed the physiological characteristics of patients recorded at the time of hospital admission, as well as blood coagulation parameters and those reflecting the development of an inflammatory reaction. The analyzed parameters were categorized relative to the reference ranges of physiologically normal values. Correlation analysis was carried out using categorical data on the disease outcome. The algorithms for calculating statistical characteristics, as well as results visualization, were programmed in Python. When comparing patient groups, the significance of differences between the determined parameters was assessed using the Pearson's χ

Indexed as

COVID-19mathematical analysisphysiological and biochemical indicespneumoniaretrospective data

Identifiers

PMID34955552
PMCPMC8685818
OpenAlexW4200099373

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.