The DOI matches its Crossref record; 163 of the 163 references it cites were found in a registry or an index.
Convalescent plasma or hyperimmune immunoglobulin for people with COVID-19: a living systematic review
Open accessAbstract
BACKGROUND: Convalescent plasma and hyperimmune immunoglobulin may reduce mortality in patients with viral respiratory diseases, and are being investigated as potential therapies for coronavirus disease 2019 (COVID-19). A thorough understanding of the current body of evidence regarding benefits and risks of these interventions is required. OBJECTIVES: Using a living systematic review approach, to assess whether convalescent plasma or hyperimmune immunoglobulin transfusion is effective and safe in the treatment of people with COVID-19; and to maintain the currency of the evidence. SEARCH METHODS: To identify completed and ongoing studies, we searched the World Health Organization (WHO) COVID-19 Global literature on coronavirus disease Research Database, MEDLINE, Embase, the Cochrane COVID-19 Study Register, the Epistemonikos COVID-19 L*OVE Platform, and trial registries. Searches were done on 17 March 2021. SELECTION CRITERIA: We included randomised controlled trials (RCTs) evaluating convalescent plasma or hyperimmune immunoglobulin for COVID-19, irrespective of disease severity, age, gender or ethnicity. For safety assessments, we also included non-controlled non-randomised studies of interventions (NRSIs) if 500 or more participants were included. We excluded studies that included populations with other coronavirus diseases (severe acute respiratory syndrome (SARS) or Middle East respiratory syndrome (MERS)), as well as studies evaluating standard immunoglobulin. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methodology. To assess bias in included studies, we used the Cochrane 'Risk of Bias 2' tool for RCTs, and for NRSIs, the assessment criteria for observational studies, provided by Cochrane Childhood Cancer. We rated the certainty of evidence, using the GRADE approach, for the following outcomes: all-cause mortality, improvement and worsening of clinical status (for individuals with moderate to severe disease), development of severe clinical COVID-19 symptoms (for individuals with asymptomatic or mild disease), quality of life (including fatigue and functional independence), grade 3 or 4 adverse events, and serious adverse events. MAIN RESULTS: We included 13 studies (12 RCTs, 1 NRSI) with 48,509 participants, of whom 41,880 received convalescent plasma. We did not identify any completed studies evaluating hyperimmune immunoglobulin. We identified a further 100 ongoing studies evaluating convalescent plasma or hyperimmune immunoglobulin, and 33 studies reporting as being completed or terminated. Individuals with a confirmed diagnosis of COVID-19 and moderate to severe disease Eleven RCTs and one NRSI investigated the use of convalescent plasma for 48,349 participants with moderate to severe disease. Nine RCTs compared convalescent plasma to placebo treatment or standard care alone, and two compared convalescent plasma to standard plasma (results not included in abstract). Effectiveness of convalescent plasma We included data on nine RCTs (12,875 participants) to assess the effectiveness of convalescent plasma compared to placebo or standard care alone. Convalescent plasma does not reduce all-cause mortality at up to day 28 (risk ratio (RR) 0.98, 95% confidence interval (CI) 0.92 to 1.05; 7 RCTs, 12,646 participants; high-certainty evidence). It has little to no impact on clinical improvement for all participants when assessed by liberation from respiratory support (RR not estimable; 8 RCTs, 12,682 participants; high-certainty evidence). It has little to no impact on the chance of being weaned or liberated from invasive mechanical ventilation for the subgroup of participants requiring invasive mechanical ventilation at baseline (RR 1.04, 95% CI 0.57 to 1.93; 2 RCTs, 630 participants; low-certainty evidence). It does not reduce the need for invasive mechanical ventilation (RR 0.98, 95% CI 0.89 to 1.08; 4 RCTs, 11,765 participants; high-certainty evidence). We did not identify any subgroup differences. We did not identify any studies reporting quality of life, and therefore, do not know whether convalescent plasma has any impact on quality of life. One RCT assessed resolution of fatigue on day 7, but we are very uncertain about the effect (RR 1.21, 95% CI 1.02 to 1.42; 309 participants; very low-certainty evidence). Safety of convalescent plasma We included results from eight RCTs, and one NRSI, to assess the safety of convalescent plasma. Some of the RCTs reported on safety data only for the convalescent plasma group. We are uncertain whether convalescent plasma increases or reduces the risk of grade 3 and 4 adverse events (RR 0.90, 95% CI 0.58 to 1.41; 4 RCTs, 905 participants; low-certainty evidence), and serious adverse events (RR 1.24, 95% CI 0.81 to 1.90; 2 RCTs, 414 participants; low-certainty evidence). A summary of reported events of the NRSI (reporting safety data for 20,000 of 35,322 transfused participants), and four RCTs reporting safety data only for transfused participants (61
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
RoB 2: a revised tool for assessing risk of bias in randomised trials
Sterne, J. A. C., Savović, J., Page, M. J., Elbers, R. G., Blencowe, N. S., Boutron, I., Cates, C. J., Cheng, H.-Y., Corbett, M. S., Eldridge, S. M., et al. (2019) · BMJ · doi:10.1136/bmj.l4898 · Cited by 34,787
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions
Sterne, J. A., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., Henry, D., Altman, D. G., Ansari, M. T., Boutron, I., et al. (2016) · BMJ · doi:10.1136/bmj.i4919 · Cited by 20,329
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.06.005 · Cited by 19,575
Cochrane Handbook for Systematic Reviews of Interventions
(2019) · doi:10.1002/9781119536604 · Cited by 14,828
Dexamethasone in Hospitalized Patients with Covid-19
The RECOVERY Collaborative Group (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2021436 · Cited by 11,477
Pathological findings of COVID-19 associated with acute respiratory distress syndrome
Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C., Liu, S., Zhao, P., Liu, H., Zhu, L., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30076-x · Cited by 8,545
GRADE guidelines: 3. Rating the quality of evidence
Balshem, H., Helfand, M., Schünemann, H. J., Oxman, A. D., Kunz, R., Brozek, J., Vist, G. E., Falck-Ytter, Y., Meerpohl, J., & Norris, S. (2011) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2010.07.015 · Cited by 8,285
Cited by
COVID-19: breaking down a global health crisis
Mallah, S. I., Ghorab, O. K., Al-Salmi, S., Abdellatif, O. S., Tharmaratnam, T., Iskandar, M. A., Sefen, J. A. N., Sidhu, P., Atallah, B., El-Lababidi, R., et al. (2021) · Annals of Clinical Microbiology and Antimicrobials · doi:10.1186/s12941-021-00438-7 · Cited by 363
Writing Committee for the REMAP-CAP Investigators, Abdelhady, H., Abdelrazik, M., Abdi, Z., Abdo, D., Abdulle, A., Abel, L., Abouzeenni, S., Abrahamson, G., Abusamra, Y., et al. (2021) · JAMA · doi:10.1001/jama.2021.18178 · Cited by 212
Self-citationSiemieniuk, R. A., Bartoszko, J. J., Díaz Martinez, J. P., Kum, E., Qasim, A., Zeraatkar, D., Izcovich, A., Mangala, S., Ge, L., Han, M. A., et al. (2021) · BMJ · doi:10.1136/bmj.n2231 · Cited by 79
Past, present and future of living systematic review: a bibliometrics analysis
Zheng, Q., Xu, J., Gao, Y., Liu, M., Cheng, L., Xiong, L., Cheng, J., Yuan, M., OuYang, G., Huang, H., et al. (2022) · BMJ Global Health · doi:10.1136/bmjgh-2022-009378 · Cited by 51
Iannizzi, C., Dorando, E., Burns, J., Weibel, S., Dooley, C., Wakeford, H., Estcourt, L. J., Skoetz, N., & Piechotta, V. (2022) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2021.09.013 · Cited by 45
Self-citation
Metadata
- Authors
- Piechotta, V., Chai, K. L., Valk, S. J., Doree, C., Monsef, I., Wood, E. M., Lamikanra, A., Kimber, C., McQuilten, Z., So-Osman, C., Estcourt, L. J., & Skoetz, N.
- Venue
- Cochrane Database of Systematic Reviews
- Publisher
- Wiley
- Published
- 2020-07-10
- Volume
- 5
- Pages
- CD013600-CD013600
- ISSN
- 1361-6137 (ISSN-L)
- 1465-1858
- OpenAlex
- W3041639190
- Cited by
- 367
- References
- 163
- FWCI
- 4.96
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Convalescent plasma or hyperimmune immunoglobulin for people with COVID-19: a living systematic review. https://app.cochat.ai/papers/10.1002/14651858.cd013600.pub2
- The paper
- Piechotta, V., Chai, K. L., Valk, S. J., Doree, C., Monsef, I., Wood, E. M., Lamikanra, A., Kimber, C., McQuilten, Z., So-Osman, C., Estcourt, L. J., & Skoetz, N. (2020). Convalescent plasma or hyperimmune immunoglobulin for people with COVID-19: a living systematic review. Cochrane Database of Systematic Reviews. https://doi.org/10.1002/14651858.cd013600.pub2
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.