Evidence map›Paper›PMID 32934000›Full record

SynthesisBMJ evidence-based medicine2021

Biomarkers and outcomes of COVID-19 hospitalisations: systematic review and meta-analysis.

Preeti Malik, Urvish Patel, Deep Mehta, Nidhi Patel, Raveena Kelkar, Muhammad Akrmah, Janice L Gabrilove, Henry Sacks

Registry-linked trialOpen access · greenAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMJ evidence-based medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06156241 (Long COVID), which is not on this map. Cited by 345 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
345citing papers in PubMed, 4 pooled it
12.1field-weighted citation impact, top 1% 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.

NCT06156241 phase1unknown statusnot on this mapstarted 2024, after this paper: background citation

Long COVID: Cord Tissue-Derived Mesenchymal Stromal Cells for Persistent NeuroInflammatory Symptoms

TypeinterventionalSponsorCharles CoxRan2024 to 2026Enrolled12ConditionsPost-Acute COVID-19 SyndromeArmsStem Cell
3 · Its place in the literature

Who cites it

345 citing papers in PubMed, 4 syntheses or guidelines pooled it, 641 citations in OpenAlex.

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285 more citing papers are in PubMed but not listed here.

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

8 authors at 4 institutions in 1 country.

Preeti MalikPublic Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA pmalik.ma@gmail.com.ORCID 0000-0002-9427-0225
Urvish PatelPublic Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Deep MehtaClinical Research Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Nidhi PatelMS3, Drexel University College of Medicine, Philadelphia, Pennsylvania, USA.
Raveena KelkarClinical Research Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Muhammad AkrmahPathology, Hartford Hospital, Hartford, Connecticut, USA.
Janice L GabriloveMedicine, Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Henry SacksEnvironmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Icahn School of Medicine at Mount Sinai · USDrexel University · USHartford Hospital · USMount Sinai Health System · US

Funding

MSHS Translational Science HubUL1TR001433 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI WRIGHT, ROSALIND J · 2015 to 2019
$26.6M
NCATS NIH HHS UL1 TR001433
6 · The paper itself

Abstract

objectiveTo evaluate association between biomarkers and outcomes in COVID-19 hospitalised patients. COVID-19 pandemic has been a challenge. Biomarkers have always played an important role in clinical decision making in various infectious diseases. It is crucial to assess the role of biomarkers in evaluating severity of disease and appropriate allocation of resources. DESIGN AND

settingSystematic review and meta-analysis. English full text observational studies describing the laboratory findings and outcomes of COVID-19 hospitalised patients were identified searching PubMed, Web of Science, Scopus, medRxiv using Medical Subject Headings (MeSH) terms COVID-19 OR coronavirus OR SARS-CoV-2 OR 2019-nCoV from 1 December 2019 to 15 August 2020 following Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines.

participantsStudies having biomarkers, including lymphocyte, platelets, D-dimer, lactate dehydrogenase (LDH), C reactive protein (CRP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, procalcitonin (PCT) and creatine kinase (CK), and describing outcomes were selected with the consensus of three independent reviewers.

main outcome measuresComposite poor outcomes include intensive care unit admission, oxygen saturation <90%, invasive mechanical ventilation utilisation, severe disease, in-hospital admission and mortality. The OR and 95% CI were obtained and forest plots were created using random-effects models. Publication bias and heterogeneity were assessed by sensitivity analysis.

results32 studies with 10 491 confirmed COVID-19 patients were included. We found that lymphopenia (pooled-OR: 3.33 (95% CI: 2.51-4.41); p<0.00001), thrombocytopenia (2.36 (1.64-3.40); p<0.00001), elevated D-dimer (3.39 (2.66-4.33); p<0.00001), elevated CRP (4.37 (3.37-5.68); p<0.00001), elevated PCT (6.33 (4.24-9.45); p<0.00001), elevated CK (2.42 (1.35-4.32); p=0.003), elevated AST (2.75 (2.30-3.29); p<0.00001), elevated ALT (1.71 (1.32-2.20); p<0.00001), elevated creatinine (2.84 (1.80-4.46); p<0.00001) and LDH (5.48 (3.89-7.71); p<0.00001) were independently associated with higher risk of poor outcomes.

conclusionOur study found a significant association between lymphopenia, thrombocytopenia and elevated levels of CRP, PCT, LDH, D-dimer and COVID-19 severity. The results have the potential to be used as an early biomarker to improve the management of COVID-19 patients, by identification of high-risk patients and appropriate allocation of healthcare resources in the pandemic.

Indexed as

Outcome Assessment, Health CareBiomarkersClinical Decision-MakingCOVID-19Critical CareHospitalizationHospital MortalityHumansPandemicsRespiration, ArtificialRisk AssessmentSARS-CoV-2Severity of Illness IndexBiomarkerscritical careevidence-based practiceglobal healthinfectious disease medicineprognosis

Identifiers

PMID32934000
PMCPMC7493072
OpenAlexW3085420778

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.