Evidence map›Paper›PMID 34164419›Full record

ReviewFrontiers in medicine2021

Convalescent Plasma Therapy for COVID-19: A Graphical Mosaic of the Worldwide Evidence.

Stephen A Klassen, Jonathon W Senefeld, Katherine A Senese, Patrick W Johnson, Chad C Wiggins, Sarah E Baker, Noud van Helmond, Katelyn A Bruno, Liise-Anne Pirofski, Shmuel Shoham and 8 more

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
–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

45 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  15. Exercise and Experiments of Nature.Comprehensive Physiology · 2023
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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

18 authors.

Stephen A KlassenDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.
Jonathon W SenefeldDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.
Katherine A SeneseDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.
Patrick W JohnsonDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL, United States.
Chad C WigginsDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.
Sarah E BakerDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.
Noud van HelmondDepartment of Anesthesiology, Cooper Medical School of Rowan University, Cooper University Health Care, Camden, NJ, United States.
Katelyn A BrunoDepartment of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL, United States.
Liise-Anne PirofskiDivision of Infectious Diseases, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, New York, NY, United States.
Shmuel ShohamDivision of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Brenda J GrossmanDepartment of Pathology and Immunology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States.
Jeffrey P HendersonDivision of Infectious Diseases, Department of Medicine, Department of Molecular Microbiology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States.
R Scott WrightDepartment of Cardiovascular Medicine, Human Research Protection Program, Mayo Clinic, Rochester, MN, United States.
DeLisa FairweatherDepartment of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL, United States.
Nigel S PanethDepartment of Epidemiology and Biostatistics, Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, East Lansing, MI, United States.
Rickey E CarterDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL, United States.
Arturo CasadevallDivision of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Michael J JoynerDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.

Funding

CTSA Administrative Supplement for Informatics Core: A novel AI/ML system to predict respiratory failure and ARDS in Covid-19 patientsUL1TR002556 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI KELLER, MARLA J, KIM, MIMI Y · 2018 to 2022
$26.7M
DIABETES AND METABOLISMT32DK007352 · NIDDK · MAYO CLINIC ROCHESTER · PI MICHAEL D. JENSEN · 1986 to 2026
$9.4M
Synergy of Host Defense Mechanisms in the LungR01HL059842 · NHLBI · YESHIVA UNIVERSITY · PI CASADEVALL, ARTURO · 1997 to 2023
$7.4M
Variant Hemoglobin and Cardiorespiratory Regulation in HumansR35HL139854 · NHLBI · MAYO CLINIC ROCHESTER · PI JOYNER, MICHAEL J · 2018 to 2024
$5.8M
Conjugate vaccines for prevention and treatment of cryptococcosis - COVID-19 Revision SupplementR01AI152078 · NIAID · JOHNS HOPKINS UNIVERSITY · PI CASADEVALL, ARTURO · 2020 to 2024
$5.1M
Role of viral mitophagosomes in driving sex differences in myocarditisR21AI145356 · NIAID · MAYO CLINIC JACKSONVILLE · PI FAIRWEATHER, DELISA, SIN, JON · 2019 to 2020
$463k
Adipose-derived biogenic nanoparticles for treatment of myocarditis/DCM(MPDPI)R21AI152318 · NIAID · MAYO CLINIC JACKSONVILLE · PI FAIRWEATHER, DELISA, WOLFRAM, JOY · 2020 to 2021
$430k
Sex differences in exercise-induced mitochondrial function during viral myocarditisR21AI154927 · NIAID · MAYO CLINIC JACKSONVILLE · PI FAIRWEATHER, DELISA · 2020 to 2021
$403k
Skeletal muscle performance and cellular adaptations to high hemoglobin-oxygen affinityF32HL154320 · NHLBI · MAYO CLINIC ROCHESTER · PI SENEFELD, JONATHON · 2020 to 2021
$117k
NCATS NIH HHS UL1 TR002556NHLBI NIH HHS F32 HL154320NHLBI NIH HHS R01 HL059842NHLBI NIH HHS R35 HL139854NIAID NIH HHS R01 AI152078NIAID NIH HHS R21 AI145356NIAID NIH HHS R21 AI152318NIAID NIH HHS R21 AI154927NIDDK NIH HHS T32 DK007352
6 · The paper itself

Abstract

Convalescent plasma has been used worldwide to treat patients hospitalized with coronavirus disease 2019 (COVID-19) and prevent disease progression. Despite global usage, uncertainty remains regarding plasma efficacy, as randomized controlled trials (RCTs) have provided divergent evidence regarding the survival benefit of convalescent plasma. Here, we argue that during a global health emergency, the mosaic of evidence originating from multiple levels of the epistemic hierarchy should inform contemporary policy and healthcare decisions. Indeed, worldwide matched-control studies have generally found convalescent plasma to improve COVID-19 patient survival, and RCTs have demonstrated a survival benefit when transfused early in the disease course but limited or no benefit later in the disease course when patients required greater supportive therapies. RCTs have also revealed that convalescent plasma transfusion contributes to improved symptomatology and viral clearance. To further investigate the effect of convalescent plasma on patient mortality, we performed a meta-analytical approach to pool daily survival data from all controlled studies that reported Kaplan-Meier survival plots. Qualitative inspection of all available Kaplan-Meier survival data and an aggregate Kaplan-Meier survival plot revealed a directionally consistent pattern among studies arising from multiple levels of the epistemic hierarchy, whereby convalescent plasma transfusion was generally associated with greater patient survival. Given that convalescent plasma has a similar safety profile as standard plasma, convalescent plasma should be implemented within weeks of the onset of future infectious disease outbreaks.

Indexed as

convalescent plasma therapyCOVID-19Kaplan–Meier analysispassive antibody transferSARS-CoV-2

Identifiers

PMID34164419
PMCPMC8215127

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.