Literature DB >> 33898477

Mortality Benefit of Convalescent Plasma in COVID-19: A Systematic Review and Meta-Analysis.

Vikas Bansal1, Kiran S Mahapure2, Ishita Mehra3, Abhishek Bhurwal4, Aysun Tekin1, Romil Singh5, Ishita Gupta6, Sawai Singh Rathore7, Hira Khan8, Sohiel Deshpande9, Shivam Gulati10, Paige Armaly11, Mack Sheraton12, Rahul Kashyap1.   

Abstract

Importance/Background: With a scarcity of high-grade evidence for COVID-19 treatment, researchers and health care providers across the world have resorted to classical and historical interventions. Immunotherapy with convalescent plasma (CPT) is one such therapeutic option.
Methods: A systematized search was conducted for articles published between December 2019 and 18th January 2021 focusing on convalescent plasma efficacy and safety in COVID-19. The primary outcomes were defined as mortality benefit in patients treated with convalescent plasma compared to standard therapy/placebo. The secondary outcome was pooled mortality rate and the adverse event rate in convalescent plasma-treated patients.
Results: A total of 27,706 patients were included in the qualitative analysis, and a total of 3,262 (2,127 in convalescent plasma-treated patients and 1,135 in the non-convalescent plasma/control group) patients died. The quantitative synthesis in 23 studies showed that the odds of mortality in patients who received plasma therapy were significantly lower than those in patients who did not receive plasma therapy [odds ratio (OR) 0.65, 95% confidence interval (CI) 0.53-0.80, p < 0.0001, I 2 = 15%). The mortality benefit remains the same even for 14 trials/prospective studies (OR 0.59, 95% CI 0.43-0.81, p = 0.001, I 2 = 22%) as well as for nine case series/retrospective observational studies (OR 0.78, 95% CI 0.65-0.94, p = 0.01, I 2 = 0%). However, in a subgroup analysis for 10 randomized controlled trials (RCTs), there was no statistically significant reduction in mortality between the CPT group compared to the non-CPT group (OR 0.76, 95% CI 0.53-1.08, p = 0.13, I 2 = 7%). Furthermore, the sensitivity analysis of 10 RCTs, excluding the study with the highest statistical weight, displayed a lower mortality rate compared to that of non-CPT COVID-19 patients (OR 0.64, 95% CI 0.42-0.97, p = 0.04, I 2 = 0%). The observed pooled mortality rate was 12.9% (95% CI 9.7-16.9%), and the pooled adverse event rate was 6.1% (95% CI 3.2-11.6), with significant heterogeneity. Conclusions and Relevance: Our systemic review and meta-analysis suggests that CPT could be an effective therapeutic option with promising evidence on the safety and reduced mortality in concomitant treatment for COVID-19 along with antiviral/antimicrobial drugs, steroids, and other supportive care. Future exploratory studies could benefit from more standardized reporting, especially in terms of the timing of interventions and clinically relevant outcomes, like days until discharge from the hospital and improvement of clinical symptoms.
Copyright © 2021 Bansal, Mahapure, Mehra, Bhurwal, Tekin, Singh, Gupta, Rathore, Khan, Deshpande, Gulati, Armaly, Sheraton and Kashyap.

Entities:  

Keywords:  COVID-19; SARS-CoV 2; convalescent plasma; mortality; plasma therapy; systemic review and meta-analysis

Year:  2021        PMID: 33898477      PMCID: PMC8062901          DOI: 10.3389/fmed.2021.624924

Source DB:  PubMed          Journal:  Front Med (Lausanne)        ISSN: 2296-858X


COVID-19 is an ongoing global pandemic, for which convalescent plasma has been recommended as a possible therapeutic drug. Preliminary clinical trial results propose that there may be a satisfactory safety profile and better clinical outcome for patients treated with convalescent plasma compared with those treated with placebo or were under standard of care; however, data are limited at the current time. This systematic review and meta-analysis provides an exhaustive summary of current literature on the efficacy and safety of convalescent plasma use in COVID-19 patients.

Introduction

The first case of coronavirus was identified in Wuhan, China, at the end of 2019 (1). The World Health Organization (WHO) declared a public health emergency of international concern on 30th January 2020 and a global pandemic on 11th March 2020 (2). The WHO estimates that serious illness occurs in 13.8% of cases and that 6.1% cases are critical (3). As of 3rd February 2021, there have been 104,077,986 confirmed cases of COVID-19, including 2,259,391 deaths, reported worldwide (4). Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is an RNA virus that is believed to primarily affect the respiratory tract; however, numerous complications related to systems other than the respiratory system have also been noted (5). Even though certain drugs, such as remdesivir, have been repositioned for emergency use in COVID-19, no particular drugs have yet been identified as an effective treatment of COVID-19. Therefore, various clinical trials are ongoing in search for the best therapy. With a scarcity of high-grade evidence for COVID-19 treatment, researchers and health care providers across the world have resorted to classical and historical interventions. Immunotherapy with convalescent plasma (CPT) is one such therapeutic option. Convalescent plasma uses have been well-described in various diseases such as severe acute respiratory syndrome (6), Middle East respiratory syndrome coronavirus (6), Ebola virus disease (7), pandemic influenza A (6), and avian-origin influenza A (6), and a neutralizing antibody response directed against the viral S protein of the SARS virus has been reported (8). The antibodies primarily target the trimeric spike (S) surface glycoproteins, which are used by the virus to enter the host cells (9). The antibody thus hinders the ability of the SARS-CoV-ACE2 to enter the host cells and can be detected even 24 months after the onset of infection (9). Subsequently, the Food and Drug Administration (FDA) approved the use of convalescent plasmas for patients with serious or immediately life-threatening COVID-19 infections on 24th March 2020 (10). One of the first studies demonstrating the benefit of CPT was reported in April 2020 (11). Since then, there has been increasing interest (12, 13), and three inconclusive Cochrane reviews (14–16) revealed that unmatched cohort studies are still the most frequent reports. As the literature around CPT is evolving and newer studies are being reported across the world, we conducted a systematic review and meta-analysis to appraise the currently available data for the clinical usefulness of convalescent plasma for the treatment of COVID-19. Organizing summaries of the available clinical evidence regarding safety and effectiveness from published literature through a systematic review can provide a synopsis of clinical evidence on the potential benefits and adverse events of CPT therapy in critically ill COVID-19 patients.

Methods

Our study has been performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement (17, 18).

Search Strategy

The search strategy was designed and conducted by the authors (IM, KM, and VB). A systematic search was conducted from COVID-19 inception through 7th August 2020 for full-length articles focusing on the efficacy and safety of convalescent plasma in COVID-19 in three major COVID-19 research article databases, namely, WHO Global Research Database, CDC COVID-19 Research Articles Downloadable Database, and LitCovid database. These databases automatically gathered for articles related to COVID-19. Other literature sources such as the Eurosurveillance, China CDC Weekly, Homeland Security Digital Library, ClinicalTrials.gov, bioRxiv (preprints), medRxiv (preprints), chemRxiv (preprints), and SSRN (preprints) were searched as well. The search strategy consisted of a combination of keywords such as “Convalescent Plasma, Plasma therapy, COVID-19, SARS-CoV 2, Mortality, Systemic, Review, Meta-analysis” across the combined COVID-19 databases. After a thorough search was performed, full-length articles meeting the inclusion criteria were evaluated. All titles and abstracts were identified by the authors and screened to accrue potentially eligible studies. A manual search of the references of the included studies was also performed to supplement the electronic search. Then, the same reviewers (AT, IG, KM, PA, RS, and SG) independently assessed all selected full-text manuscripts for eligibility.

Eligibility Criteria

The specific inclusion criteria for the systematic review and meta-analysis were as follows: (1) all RCTs or prospective studies or retrospective studies in hospitalized patients with COVID-19, (2) the use of plasma as therapy for COVID-19, (3) all studies with information available to evaluate the incidence of mortality in COVID-19 patients with plasma use [number of events, sample size, odds ratio (OR), and confidence interval (CI)], and (4) full-text articles. Thus, reviewed studies included in our analysis were RCTs and prospective and retrospective studies evaluating the outcomes of plasma therapy in COVID-19 patients. Studies focusing on patients <18 years of age, focusing on pregnant females, and limited to particular comorbidities and organ dysfunctions were excluded to avoid selection bias. We also excluded case reports from our systematic review.

Data Extraction

Once the studies met the inclusion criteria, four reviewers (AT, HK, IG, IM, KM, RS, or SD) independently reviewed and abstracted data for mortality rate and adverse event rate for each eligible study (Figure 1). If there were multiple reports stemming from a specific study database, data from the most robust study were extracted, with other studies contributing toward the bibliography. Subsequently, the data were collected and tabulated using Microsoft Excel. The included data were checked for accuracy by AB, KM, IG, and VB. The reviewers sorted the data separately in all stages of study collection, data extraction, and quality assessment. All discrepancies found between two reviewers were resolved with consensus and inputs from other authors.
Figure 1

PRISMA study flow diagram.

PRISMA study flow diagram.

Study Characteristics and Quality Assessment

Randomized trial and prospective studies were evaluated using the Cochrane risk-of-bias tool (19), and the correlation of quality measures with estimates of treatment effects in the meta-analyses of RCTs (20) was used for quality assessment of the same. We used the NIH Quality Assessment Tool for Case Series Studies (21) and the Newcastle–Ottawa Scale (NOS) (22) for case–control or non-randomized retrospective cohort studies. For each non-randomized study, we assessed the study design and content. The studies were then graded using a “star system” on the basis of (1) the selection of the study groups, (2) the comparability of the groups, and (3) the ascertainment of the outcome of interest. Quality assessments were also conducted independently, and discrepancies were resolved by consensus.

Outcome Measures

All the studies describing the outcomes of plasma therapy in patients with COVID-19 were analyzed in detail. Primary outcomes were mortality benefits for patients on CPT in COVID-19. The mortality rate was evaluated in comparison to that of the control group (placebo or non-CPT). The defined secondary outcome was the pooled mortality rate and pooled adverse event rate.

Quantitative Data Synthesis

Primary outcomes were analyzed by the Review Manager (RevMan) computer program, version 5.4 for Windows (23), and the Comprehensive Meta-Analysis software package (BioStat, Englewood, NJ, USA) (24) was used for calculating the mortality and adverse event rates. The final pooled risk estimates were obtained using random effects models (25). Raw data for outcomes and non-events from each study were used to calculate crude OR with respective 95% CI for each study. The Cochrane Q and the I2 statistics were calculated to assess heterogeneity between studies (25, 26). p < 0.10 for chi-square tests and I2 <20% were interpreted as low-level heterogeneity. We planned to perform a subgroup analysis by study design (trial/prospective studies and observational) to decrease burden of selection bias of the observational studies. It is expected that the estimates from observational studies will be more overestimated than those from RCTs (26). Furthermore, we planned to conduct a sensitivity analysis for randomized trials in trial/prospective studies to check for robustness of the results. The probability of publication bias was assessed using funnel plots and Egger's tests.

Results

The initial library search identified potentially relevant citations from the WHO Global Research Database, CDC COVID-19 Research Articles Downloadable Database, and LitCovid PubMed database comprising 174,398 articles. Subsequently, 61,487 duplicates were removed. Out of the remaining 112,911 articles, a total of 2,262 focused on convalescent plasma. A total of 2,014 articles were excluded after title and abstract reviews due to not having patient data. We added 404 articles during literature update on 18th January 2021 in the initial literature search. The remaining 652 manuscripts were scrutinized further, and 615 were further excluded because of unclear evidence and non-relevance to the objective of the manuscript. Thus, 38 studies (11, 12, 27–62) were included in their entirety, as shown in Table 1. The PRISMA flowchart is shown in Figure 1.
Table 1A

Study characteristics.

ReferencesType of studyDose of convalescent plasmaHospital length of stayAntibodies titerViral sheddingConcomitant treatment with CPTAdverse events
Abolgashemi et al. (27)Trial500 ml9.54 daysN/DN/DLopinavir/ritonavir, hydroxychloroquine and an anti-inflammatory agentTransient mild fever and chill in one patient
Agarwal et al. (28)Trial200 ml14 daysN/DN/DMethylprednisolone, prednisone, azithromycin, hydroxychloroquine, lopinavir, and ritonavirPain in the local infusion site, chills, nausea, bradycardia, and dizziness reported in one patient each. Fever and tachycardia reported in three patients each. Dyspnea and intravenous catheter blockage noted in two patients each. Mortality assessed as possibly related to convalescent plasma (CP) transfusion in three patients
Ahn et al. (29)Case series500 ml, into two doses28 daysN/DN/DLopinavir/ritonavir, hydroxychloroquine, and methylprednisoloneNo adverse reactions were observed
Altuntas et al. (54)Case–control200–600 ml17–18 daysN/DN/DAntiviral azithromycinN/A
Avenado-Sola et al. (62)Multicenter randomized clinical trial250–300 mlN/AN/AN/AYesSix in CP, seven in standard of care (SOC)
Bajpai et al. (59)Open-labeled randomized controlled trial (RCT)500 ml14 days>80N/AHydroxychloroquine, azithromycin, and oseltamivirMild urticaria in one patient each of CP and fresh frozen plasma (FFP) arms
Donato et al. (30)Trial with matched cohort study200–500 mlN/D1:1,000–10,000 to >1:10,000 in some patientsN/DHydroxychloroquine, steroids, remdesivir, azithromycin, and tocilizumabMild rash in one patient
Duan et al. (11)Case control200 mlN/D1:640N/DArbidol, remdesivir, and interferon-alphaFacial red spot in one patient
Gharbaran et al. (31)RCT300 mlN/D>1:20N/DChloroquine, azithromycin, lopinavir/ritonavir, tocilizumab, and anakinraNo adverse reactions were observed
Liu et al. (35)Case–control250 mlN/D≥1:320N/DAzithromycin, broad-spectrum antibiotics, hydroxychloroquine, antivirals, corticosteroids, interleukin-6 inhibitors, and therapeutic anticoagulationNo adverse reactions were observed
Hartman et al. (32)Single-arm trialN/D12 daysN/DN/DData unavailableN/D
Hegerova et al. (33)Case–controlN/D15 daysN/DN/DAzithromycin and hydroxychloroquineNo adverse reactions were observed
Joyner et al. (12)Clinical trial200–500 mlN/DN/DN/DN/DTransfusion reactions (n = 78; <1%), thromboembolic or thrombotic events (n = 113; <1%), and cardiac events (n = 677)
Karekadavath et al. (51)Case series200 ml22–43 daysN/D20–42 daysRemdesivir and ribavirinN/D
Li et al. (34)Trial4–13 ml/kg of recipient body weight7–28 daysN/DN/DAntiviral, interferon, Chinese herbal medicine, antibacterial, antifungal, steroids, and human immunoglobulinSeen in two patients
Libster et al. (58)Double-blind placebo RCT250 mlN/A>1:1,000N/AN/AN/A
Maor et al. (36)Prospective cohort200 mlN/D≥1:80N/DTocilizumabRash in one patient
Martinez-Resendez et al. (37)Case series250 ml22.5 days> 1:100N/DChloroquine/hydroxychloroquine, lopinavir/ritonavir, azithromycin, and ceftarolineNo adverse reactions were observed
Erkurt et al. (52)Trial200 cm37 days>1:640N/DN/DNo adverse reactions were observed
Olivares-Gazca et al. (38)Prospective non-randomized pilot trial200 mlN/DN/DN/DSteroids, hydroxychloroquine, azithromycin, tocilizumab, and lopinavir/ritonavirNo adverse reactions were observed
Omrani et al. (53)Retrospective cohort400 mlN/DN/DN/AHydroxychloroquine, azithromycin, lopinavir, ritonavir, and tocilizumab77
Pappa et al. (39)Phase II trial200–233 ml21 daysN/DN/DHydroxychloroquine, remdesivir, lopinavir/ritonavir, methylprednisolone, dexamethasone, hydrocortisone, tocilizumab, heparin (UFH/LMWH), azithromycin, and intravenous immunoglobulinNo adverse reactions were observed
Pei et al. (40)Case seriesData unavailable26–36 daysN/D12–29 daysData unavailableSevere anaphylactic shock
Perotti et al. (41)Trial250–300 mlN/D>1:160N/DLopinavir/ritonavir, darunavir/ritonavir, darunavir/cobicistat, antibiotics, hydroxychloroquine, and anticoagulantChills and fever during transfusion, anaphylaxis/hypersensitivity, transfusion acute lung injury, urticaria
AlQahtani et al. (60)Open-labeled RCT400 mlNAN/AN/AHydroxychloroquine, ribavirin, lopinavir/ritonavir, and tocilizumabOne transient desaturation, one diarrhea, vomiting
Rasheed et al. (42)Randomized trialN/D21 daysN/DN/DN/DMild skin redness and itching in one patient
Ray et al. (61)Open-labeled phase II RCT200 ml23 for SOC vs. 17 for CPTN/AN/AHydroxychloroquine, azithromycin, ivermectin, doxycycline, and corticosteroidsN/A
Rogers et al. (55)Matched cohort studyOne unitN/DN/DN/DCorticosteroid and remdesivirN/D
Salazar et al. (43)Trial with matched cohort studyOne or two units of COVID-19 convalescent plasma≥1:1,350N/DDexamethasone and hydrocortisoneN/D
Shen et al. (44)Case series400 mlAverage 46 days1:1,000N/DLopinavir/ritonavir, methylprednisolone, arbidol, favipiravir, and interferon-alphaNo adverse event mentioned
Simonovich et al. (56)Trial500 ml30 days1:3,200N/DAntiviral agents and glucocorticoidsNo adverse reactions were observed
Tan et al. (45)Case series400 ml17 days for one patientN/D16 and 49 daysAntiviral medicines and Chinese traditional medicinesN/D
Wang et al. (46)Case series200 ml51 daysN/DN/DHydroxychloroquine, methylprednisolone, lopinavir, ritonavir, tocilizumab, low-molecular-weight heparin, azithromycin, and oseltamivirNo adverse reactions were observed
Xia et al. (47)Case–control200–1,200 ml22 daysN/DN/DN/DMinor allergic reactions (pruritus or erythema) in three patients
Ye et al. (48)Case series200 ml15–24 daysN/DN/DArbidol and levofloxacinNo adverse reactions were observed
Yoon et al. (57)Retrospective cohort200 mlN/A>1:1,000N/ACorticosteroidsN/A
Zeng et al. (49)Case–control300 (200–600) mlN/DN/D23.5 daysGlucocorticoid and traditional Chinese medicineNo adverse reactions were observed
Zhang et al. (50)Case series200–2,400 ml21–41 daysN/DN/DLopinavir/ritonavir, methylprednisolone, arbidol, favipiravir, interferon-alpha, and oseltamivirNo adverse reactions were observed

N/A, not available; N/D, not defined/not mentioned.

Study characteristics. N/A, not available; N/D, not defined/not mentioned.

Study Characteristics

A total of 38 studies (11, 12, 27–62) were included in the qualitative analysis (Tables 1A,B). Out of which, 23 studies (11, 27, 28, 30, 31, 33–35, 41–43, 47, 49, 53–62) compared the mortality in convalescent plasma-treated patients vs. that in patients treated by standard therapy/placebo. Out of 14 trials/prospective studies, 10 trials (28, 31, 34, 42, 56, 58–62) conducted proper randomization, and six trials/prospective studies matched with the cohort retrospectively (27, 30, 41, 43). Zhang et al. (50) concluded that seroconversion occurred in 5–24 days, while Zeng et al. (49) mentioned that all six patients tested negative within 3 days of starting convalescent plasma. Tan et al. (45) evaluated the viral shedding period in convalescent plasma-treated patients, which was 16–46 days. Joyner et al. conducted the largest interventional case study with 20,000 convalescent plasma-treated patients and evaluated the safety profile (12).
Table 1B

Study characteristic outcomes.

ReferencesMortality CPT armTotal CPT patientMortality Non-CPT armTotal Non-CPT patientAdverse event CPTICU admissionARDSMechanical ventilationECMO
Abolgashemi et al. (27)1711518741N/AN/A80
Agarwal et al. (28)34235312299N/AN/A180
Ahn et al. (29)0202220
Altuntas et al. (54)219888245888021N/A926N/A
Avenado-Sola et al. (62)0384436N/AN/AN/AN/A
Bajpai et al. (59)3141151N/AN/A40
Donato et al. (30)11475651,3401N/AN/A150
Duan et al. (11)01031012230
Gharbaran et al. (31)643114303131315
Liu et al. (35)5393815604440
Hartman et al. (32)4310615100
Hegerova et al. (33)22062046660
Joyner et al. (12)1,71120,0001,28211,5609,7296,8640
Karekadavath et al. (51)0404410
Li et al. (34)8511250229N/A1414
Libster et al. (58)28048008760
Maor et al. (36)949128280
Martinez-Resendez et al. (37)0808850
Erkurt et al. (52)6260000060
Olivares-Gazca et al. (38)210010550
Omrani et al. (53)140540N/A80N/A690
Pappa et al. (39)0919920
Pei et al. (40)0310000
Perotti et al. (41)3467234164372
AlQahtani et al. (60)1202203N/AN/A100
Rasheed et al. (42)12182822121210
Ray et al. (61)104014400N/AN/AN/AN/A
Rogers et al. (55)86428177850280
Salazar et al. (43)513619251016121211
Shen et al. (44)0505551
Simonovich et al. (56)252281210522080190
Tan et al. (45)0200000
Wang et al. (46)3505550
Xia et al. (47)3138591,4300322282
Ye et al. (48)0601040
Yoon et al. (57)237328730N/AN/A180
Zeng et al. (49)56141506651
Zhang et al. (50)0404422

N/A, not available/not mentioned.

Study characteristic outcomes. N/A, not available/not mentioned.

Primary Outcome

Mortality Comparison Between Plasma Therapy and Placebo

Twenty-three studies reported the mortality rate in COVID-19 patients on plasma and non-CPT therapy (11, 27, 28, 30, 31, 33–35, 41–43, 47, 49, 53–62). This yielded a sample size of 7,542 patients, with 2,392 patients on plasma therapy and 5,150 patients in the control group. In the CPT therapy cohort, 392 patients died, while 1,135 patients died in the placebo/non-CPT cohort. The meta-analysis of these mortality rates showed that the odds of mortality on plasma therapy were significantly lower than those in patients who did not receive plasma therapy (OR 0.65, 95% CI 0.53–0.80, p < 0.0001, I2 = 15%). This is shown in a Forrest plot (Figure 2A). We performed a subgroup analysis by study designs and observed similar mortality benefits in 14 trial/prospective studies (27, 28, 30, 31, 34, 41–43, 56, 58–62) (OR 0.59, 95% CI 0.43–0.81, p = 0.001, I2 = 22%) (Figure 2B) as well as for nine case series/retrospective observational studies (11, 33, 35, 47, 49, 53–55, 57) (OR 0.78, 95% CI 0.65–0.94, p = 0.01, I2 = 0%) (Figure 2C). However, during the sensitivity analysis of 10 randomized trials (28, 31, 34, 42, 56, 58–62), no statistically significant reduction of COVID-19 deaths was shown (OR 0.76, 95% CI 0.53–1.08, p = 0.13, I2 = 7%) (Figure 2D). Agarwal et al. (28) demonstrated a different effect and had a large statistical weight (34.3%). Therefore, a sensitivity analysis was performed by excluding the study by Agarwal et al. (28). This revealed a significant reduction in the odds of mortality with COVID-19 (OR 0.64, 95% CI 0.42–0.97, p = 0.04, I2 = 0%) (Figure 2E).
Figure 2

(A) Overall comparison of mortality rate in patients on CPT vs. non-CPT treatment. (B) Subgroup analysis of mortality rate in patients on CPT vs. non-CPT treatment (trial/prospective studies). (C) Subgroup analysis of mortality rate in patients on CPT vs. non-CPT treatment (observational). (D) Sensitivity analysis for mortality rate in patients on CPT vs. non-CPT treatment (trial/prospective studies) true randomized controlled trial (removed pseudorandomized or trial with matched cohort). (E) Sensitivity analysis for mortality rate in patients on CPT vs. non-CPT treatment (trial/prospective studies) true randomized controlled trial [removed Agarwal et al. (28)].

(A) Overall comparison of mortality rate in patients on CPT vs. non-CPT treatment. (B) Subgroup analysis of mortality rate in patients on CPT vs. non-CPT treatment (trial/prospective studies). (C) Subgroup analysis of mortality rate in patients on CPT vs. non-CPT treatment (observational). (D) Sensitivity analysis for mortality rate in patients on CPT vs. non-CPT treatment (trial/prospective studies) true randomized controlled trial (removed pseudorandomized or trial with matched cohort). (E) Sensitivity analysis for mortality rate in patients on CPT vs. non-CPT treatment (trial/prospective studies) true randomized controlled trial [removed Agarwal et al. (28)].

Secondary Outcome

Pooled Mortality Rate

Thirty-eight studies (11, 12, 27–62) reported the mortality rate in COVID-19 patients on plasma therapy, as shown in Figure 3. A total of 22,556 patients with CPT were included in the analysis, of which a total of 2,127 patients died. This yielded a pooled post CPT mortality rate of 12.9% (95% CI 9.7–16.9) with a substantial amount of heterogeneity (I2 = 89.6) in the analysis (Figure 3).
Figure 3

Pooled mortality rate with use of CPT in COVID-19.

Pooled mortality rate with use of CPT in COVID-19.

Pooled Adverse Event Rate

Similarly, 37 studies (11, 12, 27–53, 55–62) reported the adverse event rate in COVID-19 patients on plasma therapy, as shown in Figure 4. A total of 21,668 patients with CPT were included in the analysis, of which a total of 1,506 patients had adverse events. This yielded a pooled adverse event rate of 6.1% (95% CI 3.2–11.6) with significant heterogeneity in the analysis (I2 = 94.9) (Figure 4).
Figure 4

Pooled adverse event rate with use of CPT in COVID-19.

Pooled adverse event rate with use of CPT in COVID-19.

Risk-of-Bias Assessment

Two authors (KM and AT) independently assessed the risk of bias of each study included. All disagreements were discussed with all the authors, and decisions were made via a consensus. The Cochrane tool for risk of bias (19) was used for RCTs (Table 2A), and the correlation of quality measures with estimates of treatment effects in meta-analyses of RCTs (20) was used for quality assessment of the same (Table 2B). Non-randomized studies were evaluated using the NOS for the case–control/cohort (22) (Tables 2C,D) and the NIH Quality Assessment Tool for Case Series Studies (21) (Table 2E). Quality assessments were conducted independently, and discrepancies were resolved by consensus. Overall, risk-of-bias assessment showed that the included studies had low to medium risk of bias.
Table 2B

Risk-of-bias assessment of the trials included in the study.

ReferencesSequence generation risk of biasAllocation concealment risk of biasSelective reporting risk of biasOther sources of risk of biasBlinding participants and personnel risk of biasBlinding outcome assessors' risk of biasIncomplete outcome data risk of bias
Abolgashemi et al. (27)HighHighLowLowHighHighLow
Agarwal et al. (28)LowHighLowLowHighHighLow
AlQahtani et al. (60)LowHighLowLowHighUnclearLow
Avenado-Sola et al. (62)UnclearHighLowLowHighHighLow
Bajpai et al. (59)LowHighLowLowHighHighLow
Donato et al. (30)HighHighLowLowHighHighLow
Erkurt et al. (52)HighHighLowLowHighHighLow
Hartman et al. (32)HighHighLowLowHighHighLow
Gharbaran et al. (31)LowHighLowLowHighHighLow
Joyner et al. (12)HighHighLowLowHighHighLow
Li et al. (35)LowModerateLowLowLowLowLow
Libster et al. (58)LowLowLowLowLowUnclearLow
Olivares-Gazca et al. (38)HighHighLowLowHighHighLow
Pappa et al. (39)HighHighLowLowHighHighLow
Perotti et al. (41)LowLowLowLowLowLowLow
Rasheed et al. (42)HighHighLowLowHighHighLow
Ray et al. (61)HighHighLowLowHighUnclearLow
Salazar et al. (43)HighHighLowLowHighHighLow
Simonovich et al. (56)LowLowLowLowLowLowLow
Table 2C

Quality assessment for case–control studies included in the study.

ReferencesAltuntas et al. (54)Duan et al. (11)Hegerova et al. (33)Liu et al. (35)Xia et al. (47)Zeng et al. (49)
SelectionCase definition***
Representativeness of cases*-****
Selection of controls******
Definition of controls******
Comparability of cohorts********
ExposureAscertainment of exposures******
Same method for both groups******
Non-response rate*
Total number of stars8/97/98/98/95/95/9

Note: A study can be awarded a maximum of one star for each numbered item within the Selection and Exposure categories. A maximum of two stars can be given for Comparability.

Table 2D

Quality assessment for cohort studies included in the study.

ReferencesMaor et al. (36)Omrani et al. (53)Rogers et al. (55)Yoon et al. (57)
SelectionRepresentativeness of cohort****
Selection of non-exposed cohort***
Ascertainment of exposure****
Outcome not present at the beginning***
Comparability of cohorts******
OutcomeAssessment of outcome****
Follow-up length-*-*
Adequacy of follow-up****
Total number of stars4/99/98/99/9

Note: A study can be awarded a maximum of one star for each numbered item within the Selection and Exposure categories. A maximum of two stars can be given for Comparability.

Table 2E

Quality assessment of the case studies included in the study.

ReferencesAhn et al. (29)Karekadavath et al. (51)Martinez-Resendez et al. (37)Pei et al. (40)Shen et al. (44)Tan et al. (45)Wang et al. (46)Ye et al. (48)Zhang et al. (50)
1. Was the study question or objective clearly stated?YesYesYesYesYesYesYesYesYes
2. Was the study population clearly and fully described, including a case definition?YesNoYesYesYesYesNoYesYes
3. Were the cases consecutive?NoYesN/DN/DNoN/DN/DNoNo
4. Were the subjects comparable?YesYesYesYesYesNoYesNoYes
5. Was the intervention clearly described?YesYesYesNoYesNoYesYesYes
6. Were the outcome measures clearly defined, valid, reliable, and implemented consistently across all study participants?YesYesYesNoYesNoYesYesYes
7. Was the length of follow-up adequate?YesYesNoYesYesNoNoNoYes
8. Were the statistical methods well-described?N/AN/AYesN/AN/AN/AYesN/AN/A
9. Were the results well-described?YesYesYesYesYesYesYesYesYes
Quality ratingGoodGoodGoodFairGoodPoorFairFairGood

N/A, not applicable; N/D, not defined.

Assessment of the trials included in the study. N/A, not available/not applicable; N/D, not defined. Risk-of-bias assessment of the trials included in the study. Quality assessment for case–control studies included in the study. Note: A study can be awarded a maximum of one star for each numbered item within the Selection and Exposure categories. A maximum of two stars can be given for Comparability. Quality assessment for cohort studies included in the study. Note: A study can be awarded a maximum of one star for each numbered item within the Selection and Exposure categories. A maximum of two stars can be given for Comparability. Quality assessment of the case studies included in the study. N/A, not applicable; N/D, not defined.

Discussion

In this systematic review and meta-analysis of CPT in COVID-19 patients, 38 studies (11, 12, 27–62) were included and critically evaluated. All included studies reported excellent outcomes for CPT in COVID-19. Our systemic review and meta-analysis is one of the first ones to summarize all such existing evidence on the efficacy and safety of CPT in humans with COVID-19. According to the results of our systematic review and meta-analysis, CPT is effective in reducing the mortality rate and has low incidence of serious adverse events during and after convalescent plasma infusion, which are mostly controllable. CPT confers immediate immunity via interruption of the viral entry into the cells. Additionally, in the context of COVID-19, neutralizing antibodies are anticipated to be the primary active agent in convalescent plasma and the marker of plasma potency (9). In the past, CPT has been shown to provide benefits in severe acute respiratory syndromes (6). Prior studies have also reported promising outcomes in Spanish influenza A (H1N1) infection (63), avian influenza A (H5N1) (64), viral hemorrhagic fevers such as Ebola (65), influenza A (H1N1) infections in 2009/2010 (66), and SARS-CoV infections in 2003 (67). A systematic review and meta-analysis revealed a consistent reduction in mortality with the use of plasma therapy (6). The results are similar to our findings. One of the possible hypotheses for the observed decreased mortality could be due to antibodies that can hamper virus reproduction in the active phase of infection and help clear the virus, which is advantageous to the rapid recovery of the disease (67). Mechanistic and clinical data also support the observed mortality reduction benefit associated with convalescent plasma administration (68, 69). There was no significant reduction in mortality rate between patients with CPT and controls based on data from RCTs. However, sensitivity analysis [excluding the study by Agarwal et al. (28)] revealed that patients transfused with CPT had a lower mortality rate. The Agarwal et al. (28) trial comprised ~70% of the patients in the CPT cohort who received plasma with low levels of SARS-CoV-2 antibodies. Additionally, the remaining 30% of the patients received plasma with no detectable antibodies. Thus, there were strong methodical and clinical rationales to exclude this study from statistical models during sensitivity analysis. Nevertheless, Agarwal et al. (28) did observe a positive effect of CPT on clinical symptoms and viral clearance. It is worth noting that the doses of CPT vary between the included studies. However, the Chinese study (11) described the use of a single dose of 200 ml of convalescent plasma, whereas Bin Zhang et al. (50) reported a maximum of 2,400 ml of convalescent plasma. The optimal dose of CPT for COVID-19, therefore, could not be estimated. It is also important to note that the included patients were critically ill and received ICU admission (n = 12,095) or underwent mechanical ventilation (n = 8,200) and that all COVID-19 patients described in our meta-analysis received concomitant antiviral drugs and steroids including CPT; also, many patients received antibacterial/antifungal drugs for co-infection. All included studies described little mortality with the use of CPT, and the pooled analysis suggests a mortality rate of 12.9% (95% CI 9.7–16.9). However, the individual impact of CPT could not be determined as patients also received multiple other agents (including antiviral medications). Therefore, further studies evaluating the use of CPT alone are warranted. The safety profile of CPT in COVID-19 has not been described in detail. The observed pooled adverse event rate was 6.1% (95% CI 3.2–11.6). This suggests that CPT was well-tolerated by the participants in the included studies. It is important to note that no fatality was reported as adverse event with the use of CPT. Human plasma transfusion is routinely performed in hospitals. Human anti-SARS-CoV-2 plasma differs from standard plasma as it contains antibodies against SARS-CoV-2. The risks to transfusion recipients are similar to those of standard plasma. The risk of transfusion-transmissible infection is low in developed countries. The incidence rates of infections such as HIV, hepatitis B, and hepatitis C are less than one infection per 2 million donations (70). Other adverse events with plasma therapy include allergic transfusion reactions, transfusion-associated circulatory overload (TACO), and transfusion-related acute lung injury (TRALI) (71). Even though TRALI occurs in <1 for every 5,000 transfused units, it is concerning in COVID-19 patients. Donor screening including HLA antibody screening decreases the risk of TRALI (72). A risk benefit analysis based on age, symptoms, comorbidities, and COVID-19 transmission parameters was published in a recent review by Bloch et al. (73). Five hundred simulations were carried out, assuming varying degrees of effectiveness of convalescent plasma treatment. The model revealed that convalescent plasma was beneficial in COVID-19 infection even at the lowest estimates of 25% effectiveness. In other words, the model suggests that the potential benefit of plasma therapy outweighs the risk of transfusion in COVID-19 infection (73). The important strengths of our study are a comprehensive search of the already published clinical studies and the large number of patients included in the analysis. This is one of the first meta-analyses on CPT use in COVID-19 patients showing an overwhelming positive result. The review of sample of articles by two co-authors is again a testimony of the quality check of data collection in this review. The generalizability of these results is also a strength of this article. Despite the numerous strengths of the meta-analysis, there are certain limitations. One of the limitations of the meta-analysis is integral to the methodology. The summarization of varying pieces of information may ignore important differences between studies. Nonetheless, this is a controversial aspect of the meta-analysis (74). Additionally, a meta-analysis generalizes results despite differences in primary research and does not simply report a summary effect. The heterogeneity is high in our studies, especially regarding the pooled adverse event rate and pooled mortality rate. Further studies may be needed to confirm the findings and explain the mechanisms. A lack of high-quality RCT studies and relevant literature paucity limited our analyses. All the reported studies were predominately case reports or series, had no proper control groups, and had a moderate to high risk of bias. Most studies in our meta-analysis were observational studies with a high risk of bias, which are subject to inherent limitations of the study design with unmeasured differences in the study population and residual confounders despite all adjustments. The currently available evidence on the safety and effectiveness of convalescent plasma for treatment of people with COVID-19 is of very low strength. Our study predominantly describes the clinical data and incidence rates in hospitalized patients. Also, we could not register the review. We tried to prospectively register our systematic review but decided to go against it as it was taking an unreasonably longer time than expected due to the increased pool of COVID-19-related articles. Another limitation of our study is the inclusion of 12 studies (30, 31, 37, 39, 40, 42, 45, 57–59, 61, 62) from the preprint databases which have not been peer reviewed and are necessary for a thorough evaluation of the currently available data on CPT in our meta-analysis. Preprint articles possibly indicate the undetermined quality of available literature and biased articles on CPT; however, we will update the status of these above-mentioned studies in the risk-of-bias table. Lastly, many studies were determined to have a significant risk of bias. This was related to a combination of factors such as non-randomized design, confounding, poor methodological conduct, and limited information on dose and duration of the CPT. Importantly, many of the patients enrolled in the studies included in the present analysis received convalescent plasma transfusions later in their disease course. As a result, our analysis may underestimate the mortality reduction achievable through early administration of high-titer convalescent plasma for COVID-19. Based on low-quality evidence, there is no suggestion that convalescent plasma would cause any serious adverse events in patients with COVID-19 and lower the mortality in COVID-19 patients. Thus, any conclusions that are drawn based on these data are of limited value, and these conclusions are subject to change as more reliable results become available.

Conclusion

Based on the consolidated clinical data derived from the systemic review and meta-analysis, it is suggested that, in addition to antiviral/antimicrobial drugs and steroids, CPT could be an effective concomitant therapeutic option as the use of CPT decreased mortality with a safe clinical profile and promising evidence on the safety and reduced mortality. We recognize that a definitive conclusion cannot be drawn regarding optimal doses and treatment time point for the CPT. Future larger observational studies (75) and clinical trials could benefit from more standardized reporting, especially in terms of the timing of intervention and clinically relevant outcomes, like days until discharge from hospital and improvement of clinical symptoms.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

Data review and collection were done by KM, IG, SG, RS, AT, PA, HK, and SD. Statistical analysis was done by VB, AB, and MS. Study design and distribution of articles for critical review were done by IM and RK. VB and KM are the guarantors of the paper, taking responsibility for the integrity of the work as a whole, and from inception to publication of the article. Final approval was given by all authors. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
ReferencesAbolgashemi et al. (27)Agarwal et al. (28)AlQahtani et al. (60)Avenado-Sola et al. (62)Bajpai et al. (59)Donato et al. (30)Erkurt et al. (52)Hartman et al. (32)Gharbaran et al. (31)Joyner et al. (12)
Study question well-defined in introduction/methodsYesYesYesYesNoYesYesYesYesYes
Study question well-defined anywhere in the articleYesYesYesYesNoYesYesYesYesYes
Placebo controlNoNoNoNoNoNoNoNoNoNo
Appropriate outcome studiedYesYesYesYesYesYesYesYesYesYes
Multicenter studyYesYesYesYesNoNoNoNoYesYes
Study countryIranIndiaBahrainSpainIndiaUSATurkeyUSANetherlandsUSA
Adequate selection criteriaYesYesYesYesYesYesNoYesYesYes
Randomization methods describedN/AYesYesYesYesN/AN/AN/AYesN/A
Central randomization siteN/AYesN/DN/DN/AN/AN/AN/AN/DN/A
Allocation concealmentN/DYesNoYesYesN/DN/AN/DNoN/D
Patients blindedN/DNoNoNoNoN/DN/AN/DNoN/D
Caregivers blindedN/DNoNoNoNoN/DN/AN/DNoN/D
Outcome assessors blindedN/DNoN/DN/DN/DN/DN/AN/DN/DN/D
Data analysts blindedN/DN/DN/DN/DN/DN/DN/AN/DN/DN/D
Double blindedN/DNoNoNoNoN/DN/AN/DN/DN/D
Vital statistical measuresYesYesYesYesYesYesYesYesYesYes
Statistician author or acknowledgedNoYesNoYesN/DYesNoNoNoYes
Intention-to-treat analysisNoYesNoNoNoNoNoNoNoNo
Power calculation reportedNoYesYesYesN/DYesNoNoYesNo
Stopping rules describedNoNoNoYesN/DNoNoNoYesNo
Baseline characteristics reportedYesYesYesYesYesYesYesYesYesYes
Groups similar at baselineNoYesYesN/DYesN/AN/ANoNoN/A
Confounders accounted forYesYesYesNoYesYesNoYesYesNo
Percentage dropoutsN/AYesN/AYesYesN/AN/AN/AN/AN/A
Reasons for dropout givenN/AYesN/AYesYesN/AN/AN/AN/AN/A
Findings support conclusionYesYesYesYesYesYesYesYesYesYes
ReferencesLi et al. (34)Libster et al. (58)Olivares-Gazca et al. (38)Pappa et al. (39)Perotti et al. (41)Rasheed et al. (42)Ray et al. (61)Salazar et al. (43)Simonovich et al. (56)
Study question well-defined in introduction/methodsYesYesYesYesYesYesYesYesYes
Study question well-defined anywhere in the articleYesYesYesYesYesYesYesYesYes
Placebo controlNoYesNoNoNoNoNoNoYes
Appropriate outcome studiedYesYesYesYesYesYesYesYesYes
Multicenter studyYesYesNoYesYesYesNoYesYes
Study countryChinaArgentinaMexicoGreeceItalyIraqIndiaUSAArgentina
Adequate selection criteriaYesYesYesYesYesYesYesYesYes
Randomization methods describedYesYesN/AN/ANoYesNoN/AYes
Central randomization siteYesYesN/AN/ANoNoN/DN/AN/D
Allocation concealmentN/DYesN/DN/DN/DN/DNoN/DYes
Patients blindedN/DYesN/DN/DN/DN/DNoN/DYes
Caregivers blindedN/DYesN/DN/DN/DN/DNoN/DYes
Outcome assessors blindedN/DN/DN/DN/DN/DN/DN/DN/DYes
Data analysts blindedN/DN/DN/DN/DN/DN/DN/DN/DNo
Double blindedN/DYesN/DN/DN/DN/DNoN/DYes
Vital statistical measuresNoYesNoYesNoNoYesYesYes
Statistician author or acknowledgedYesN/DNoNoYesNoNoNoYes
Intention-to-treat analysisYesYesNoNoYesNoNoNoYes
Power calculation reportedNoYesNoNoNoNoNoNoYes
Stopping rules describedNoYesNoNoNoNoNoNoNo
Baseline characteristics reportedYesYesYesYesYesYesYesYesYes
Groups similar at baselineYesNoN/AN/AYesYesN/DYesNo
Confounders accounted forYesYesYesYesYesNoNoYesYes
Percentage dropoutsN/AYesN/AN/AN/AN/AN/AN/AN/A
Reasons for dropout givenN/AYesN/AN/AN/AN/AN/AN/AN/A
Findings support conclusionYesYesYesYesYesYesYesYesYes

N/A, not available/not applicable; N/D, not defined.

  10 in total

1.  Association of Obesity With COVID-19 Severity and Mortality: An Updated Systemic Review, Meta-Analysis, and Meta-Regression.

Authors:  Romil Singh; Sawai Singh Rathore; Hira Khan; Smruti Karale; Yogesh Chawla; Kinza Iqbal; Abhishek Bhurwal; Aysun Tekin; Nirpeksh Jain; Ishita Mehra; Sohini Anand; Sanjana Reddy; Nikhil Sharma; Guneet Singh Sidhu; Anastasios Panagopoulos; Vishwanath Pattan; Rahul Kashyap; Vikas Bansal
Journal:  Front Endocrinol (Lausanne)       Date:  2022-06-03       Impact factor: 6.055

2.  Rate of COVID-19 infection and 30 day mortality between blue and green (dedicated COVID-19 safe) pathways: Results from phase 1 and 2 of the UK foot and ankle COVID-19 national (UK-FAlCoN) audit.

Authors:  Karan Malhotra; Jitendra Mangwani; Linzy Houchen-Wollof; Lyndon W Mason
Journal:  Foot Ankle Surg       Date:  2022-02-25       Impact factor: 2.840

3.  Cross-Neutralizing Breadth and Longevity Against SARS-CoV-2 Variants After Infections.

Authors:  Yukiya Kurahashi; Silvia Sutandhio; Koichi Furukawa; Lidya Handayani Tjan; Sachiyo Iwata; Shigeru Sano; Yoshiki Tohma; Hiroyuki Ohkita; Sachiko Nakamura; Mitsuhiro Nishimura; Jun Arii; Tatsunori Kiriu; Masatsugu Yamamoto; Tatsuya Nagano; Yoshihiro Nishimura; Yasuko Mori
Journal:  Front Immunol       Date:  2022-02-24       Impact factor: 7.561

4.  The Role of Disease Severity and Demographics in the Clinical Course of COVID-19 Patients Treated With Convalescent Plasma.

Authors:  Tengfei Ma; Chad C Wiggins; Breanna M Kornatowski; Ra'ed S Hailat; Andrew J Clayburn; Winston L Guo; Patrick W Johnson; Jonathon W Senefeld; Stephen A Klassen; Sarah E Baker; Katelyn A Bruno; DeLisa Fairweather; R Scott Wright; Rickey E Carter; Chenxi Li; Michael J Joyner; Nigel S Paneth
Journal:  Front Med (Lausanne)       Date:  2022-01-26

5.  Association of latitude and altitude with adverse outcomes in patients with COVID-19: The VIRUS registry.

Authors:  Aysun Tekin; Shahraz Qamar; Romil Singh; Vikas Bansal; Mayank Sharma; Allison M LeMahieu; Andrew C Hanson; Phillip J Schulte; Marija Bogojevic; Neha Deo; Simon Zec; Diana J Valencia Morales; Katherine A Belden; Smith F Heavner; Margit Kaufman; Sreekanth Cheruku; Valerie C Danesh; Valerie M Banner-Goodspeed; Catherine A St Hill; Amy B Christie; Syed A Khan; Lynn Retford; Karen Boman; Vishakha K Kumar; John C O'Horo; Juan Pablo Domecq; Allan J Walkey; Ognjen Gajic; Rahul Kashyap; Salim Surani
Journal:  World J Crit Care Med       Date:  2022-03-09

6.  SARS-CoV-2 antibody changes in patients receiving COVID-19 convalescent plasma from normal and vaccinated donors.

Authors:  Judith Leon; Anna E Merrill; Kai Rogers; Julie Kurt; Spencer Dempewolf; Alexandra Ehlers; J Brooks Jackson; C Michael Knudson
Journal:  Transfus Apher Sci       Date:  2021-11-23       Impact factor: 2.596

7.  Association of hypothyroidism with outcomes in hospitalized adults with COVID-19: Results from the International SCCM Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS): COVID-19 Registry.

Authors:  Marija Bogojevic; Vikas Bansal; Vishwanath Pattan; Romil Singh; Aysun Tekin; Mayank Sharma; Abigail T La Nou; Allison M LeMahieu; Andrew C Hanson; Phillip J Schulte; Neha Deo; Shahraz Qamar; Simon Zec; Diana J Valencia Morales; Nicholas Perkins; Margit Kaufman; Joshua L Denson; Roman Melamed; Valerie M Banner-Goodspeed; Amy B Christie; Yasir Tarabichi; Smith Heavner; Vishakha K Kumar; Allan J Walkey; Ognjen Gajic; Sumit Bhagra; Rahul Kashyap; Amos Lal; Juan Pablo Domecq
Journal:  Clin Endocrinol (Oxf)       Date:  2022-02-18       Impact factor: 3.523

Review 8.  COVID-19-Induced Seizures: A Meta-Analysis of Case Series and Retrospective Cohorts.

Authors:  Helai Hussaini; Sylvette Rogers; Saurabh Kataria; Khalid Uddin; Khalid H Mohamed; Alaa S Mohamed; Farhan Tariq; Sarfaraz Ahmad; Anum Awais; Zahoor Ahmed; Anthony Chukwurah; Aadil Khan
Journal:  Cureus       Date:  2022-08-31

9.  Characterization of pathogen-inactivated COVID-19 convalescent plasma and responses in transfused patients.

Authors:  Maja Weisser; Nina Khanna; Anemone Hedstueck; Sarah Tschudin Sutter; Sandra Roesch; Gregor Stehle; Mihaela Sava; Nikolaus Deigendesch; Manuel Battegay; Laura Infanti; Andreas Holbro; Stefano Bassetti; Hans Pargger; Hans H Hirsch; Karoline Leuzinger; Laurent Kaiser; Diem-Lan Vu; Katharina Baur; Nadine Massaro; Michael Paul Busch; Graham Simmons; Mars Stone; Philip L Felgner; Rafael R de Assis; Saahir Khan; Cheng-Ting Tsai; Peter V Robinson; David Seftel; Johannes Irsch; Anil Bagri; Andreas S Buser; Laurence Corash
Journal:  Transfusion       Date:  2022-09-05       Impact factor: 3.337

Review 10.  Immunological effects of convalescent plasma therapy for coronavirus: a scoping review.

Authors:  Behnaz Esmaeili; Shahnaz Esmaeili; Zahra Pourpak
Journal:  BMC Infect Dis       Date:  2021-12-24       Impact factor: 3.090

  10 in total

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