Evidence map›Paper›PMID 36084093›Full record

SynthesisPloS one2022

Procalcitonin as a predictive marker in COVID-19: A systematic review and meta-analysis.

Amit Kumar, Era Karn, Kiran Trivedi, Pramod Kumar, Ganesh Chauhan, Aradhana Kumari, Pragya Pant, Murali Munisamy, Jay Prakash, Prattay Guha Sarkar and 2 more

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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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

12 authors.

Amit KumarDepartment of Laboratory Medicine, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Era KarnDepartment of Biotechnology, Patna University, Bihar, India.
Kiran TrivediDepartment of Obstetrics and Gynecology, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Pramod KumarDepartment of Biochemistry, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.ORCID 0000-0002-5449-1816
Ganesh ChauhanDepartment of Genetics and Genomics, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Aradhana KumariDepartment of Biochemistry, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Pragya PantDepartment of Nephrology, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Murali MunisamyDepartment of Translational Medicine, All India Institute of Medical Sciences, Bhopal, India.
Jay PrakashDepartment of Critical Care, Trauma Centre, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Prattay Guha SarkarDepartment of Cardiology, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Kameshwar PrasadDepartment of Neurology, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Anupa PrasadDepartment of Biochemistry, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.ORCID 0000-0002-9087-8364

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 has emerged as a global pandemic causing millions of critical cases and deaths. Early identification of at-risk patients is crucial for planning triage and treatment strategies. METHODS AND

findingsWe performed this systematic review and meta-analysis to determine the pooled prognostic significance of procalcitonin in predicting mortality and severity in patients with COVID-19 using a robust methodology and clear clinical implications.

designWe used Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Cochrane Handbook for Systematic Reviews of Interventions guidelines. We included thirty-two prospective and retrospective cohort studies involving 13,154 patients.

resultsThe diagnostic odds ratio of procalcitonin for predicting mortality were estimated to be 11 (95% CI: 7 to 17) with sensitivity, specificity, and summary area under the curveof 0.83 (95% CI: 0.70 to 0.91), 0.69 (95% CI: 0.58 to 0.79), and 0.83 (95% CI: 0.79 to 0.86) respectively. While for identifying severe cases of COVID-19, the odds ratio was 8.0 (95% CI 5.0 to 12.0) with sensitivity, specificity, and summary area under the curve of 0.73 (95% CI 0.67 to 0.78), 0.74 (0.66 to 0.81), and 0.78 (95% CI 0.74 to 0.82) respectively.

conclusionProcalcitonin has good discriminatory power for predicting mortality and disease severity in COVID-19 patients. Therefore, procalcitonin measurement may help identify potentially severe cases and thus decrease mortality by offering early aggressive treatment.

Indexed as

COVID-19ProcalcitoninBiomarkersHumansPandemicsProspective StudiesRetrospective StudiesBiomarkersProcalcitonin

Identifiers

PMID36084093
PMCPMC9462680

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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.