Evidence map›Paper›PMID 36819312›Full record

ArticleCureus2023

Biomarkers Predicting Poor Prognosis in Covid-19 Patients: A Survival Analysis.

Amjad Idrissi, Asmae Lekfif, Abdessamad Amrani, Abdelkader Yacoubi, Abir Yahyaoui, Sabrina Belmahi, Oumaima Nassiri, Imane Elmezgueldi, El-Houcine Sebbar, Mohammed Choukri

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 54% 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, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
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 1 institution in 2 countries.

Amjad IdrissiLaboratory of Biochemistry, Central Laboratory Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
Asmae LekfifEpidemiology, Clinical Research, and Public Health Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
Abdessamad AmraniLaboratory of Biochemistry, Central Laboratory Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
Abdelkader YacoubiPublic Health Department, Regional Administration of Health and Social Protection - Eastern Region, Moroccan Ministry of Health, Oujda, MAR.
Abir YahyaouiLaboratory of Biochemistry, Central Laboratory Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
Sabrina BelmahiLaboratory of Biochemistry, Central Laboratory Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
Oumaima NassiriLaboratory of Biochemistry, Central Laboratory Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
Imane ElmezgueldiLaboratory of Biochemistry, Central Laboratory Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
El-Houcine SebbarLaboratory of Biochemistry, Central Laboratory Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
Mohammed ChoukriLaboratory of Biochemistry, Central Laboratory Department, Mohammed VI University Hospital, Faculty of Medicine of Oujda, Mohammed First University, Oujda, MAR.
Ministry of Health · UG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction With the spread of the Covid-19 pandemic and its overwhelming impact on health systems in several countries, the importance of identifying predictors of severity is of paramount importance. The objective of this study is to determine the relationship between death and the biological parameters of patients with Covid-19. Materials and methods This is an analytical retrospective cohort study conducted on 326 patients admitted to the Mohammed VI University Hospital in Oujda, Morocco. The statistical analysis concerned the biological parameters carried out on the admission of the patients, in addition to age and sex. The comparison between the two surviving and non-surviving groups was made by a simple analysis than a multivariate analysis by logistic regression. Next, a survival analysis was performed by the Kaplan-Meier method and then by Cox regression. Results A total of 326 patients were included in the study, including 108 fatal cases. The mean age was 64.66 ± 15.51 and the sex ratio was 1.08:1 (M:F). Age, procalcitonin, liver enzymes, and coagulation factors were significantly higher in patients who died of Covid-19 and are therefore considered to be the main prognostic factors identified in this study. Conclusion Knowledge and monitoring of predictive biomarkers of poor prognosis in patients with Covid-19 could be of great help in the identification of patients at risk and in the implementation of an effective diagnostic and therapeutic strategy to predict severe disease forms.

Indexed as

biological parameterscovid-19prognostic factorsretrospective cohort studysurvival

Identifiers

PMID36819312
PMCPMC9937634
OpenAlexW4317215100

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.