The efficiency of convalescent plasma in COVID-19 patients: A systematic review and meta-analysis of randomized controlled clinical trials

The objective of this study was to assess whether convalescent plasma therapy could offer survival advantages for patients with novel coronavirus disease 2019 (COVID-19). An electronic search of Pubmed, Web of Science, Embase, Cochrane library and MedRxiv was performed from January 1st, 2020 to April 1st, 2022. We included studies containing patients with COVID-19 and treated with CCP. Data were independently extracted by two reviewers and synthesized with a random-effect analysis model. The primary outcome was 28-d mortality. Secondary outcomes included length of hospital stay, ventilation-free days, 14-d mortality, improvements of symptoms, progression of diseases and requirements of mechanical ventilation. Safety outcomes included the incidence of all adverse events (AEs) and serious adverse events (SAEs). The Cochrane risk-of-bias assessment tool 2.0 was used to assess the potential risk of bias in eligible studies. The heterogeneity of results was assessed by I^2 test and Q statistic test. The possibility of publication bias was assessed by conducting Begg and Egger test. GRADE (Grading of Recommendations Assessment, Development and Evaluation) method were used for quality of evidence. This study had been registered on PROSPERO, CRD42021273608. 32 RCTs comprising 21478 patients with Covid-19 were included. Compared to the control group, COVID-19 patients receiving CCP were not associated with significantly reduced 28-d mortality (CCP 20.0% vs control 20.8%; risk ratio 0.94; 95% CI 0.87-1.02; p = 0.16; I² = 8%). For all secondary outcomes, there were no significant differences between CCP group and control group. The incidence of AEs (26.9% vs 19.4%,; risk ratio 1.14; 95% CI 0.99-01.31; p = 0.06; I² = 38%) and SAEs (16.3% vs 13.5%; risk ratio 1.03; 95% CI 0.87-1.20; p = 0.76; I² = 42%) tended to be higher in the CCP group compared to the control group, while the differences did not reach statistical significance. In all, CCP therapy was not related to significantly improved 28-d mortality or symptoms recovery, and should not be viewed as a routine treatment for COVID-19 patients.Trial registration numberCRD42021273608. Registration on February 28, 2022Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, Identifier CRD42022313265

Development and external validation of a prognostic multivariable model on admission for hospitalized patients with COVID-19

Summary Background COVID-19 pandemic has developed rapidly and the ability to stratify the most vulnerable patients is vital. However, routinely used severity scoring systems are often low on diagnosis, even in non-survivors. Therefore, clinical prediction models for mortality are urgently required. Methods We developed and internally validated a multivariable logistic regression model to predict inpatient mortality in COVID-19 positive patients using data collected retrospectively from Tongji Hospital, Wuhan (299 patients). External validation was conducted using a retrospective cohort from Jinyintan Hospital, Wuhan (145 patients). Nine variables commonly measured in these acute settings were considered for model development, including age, biomarkers and comorbidities. Backwards stepwise selection and bootstrap resampling were used for model development and internal validation. We assessed discrimination via the C statistic, and calibration using calibration-in-the-large, calibration slopes and plots. Findings The final model included age, lymphocyte count, lactate dehydrogenase and SpO 2 as independent predictors of mortality. Discrimination of the model was excellent in both internal (c=0·89) and external (c=0·98) validation. Internal calibration was excellent (calibration slope=1). External validation showed some over-prediction of risk in low-risk individuals and under-prediction of risk in high-risk individuals prior to recalibration. Recalibration of the intercept and slope led to excellent performance of the model in independent data. Interpretation COVID-19 is a new disease and behaves differently from common critical illnesses. This study provides a new prediction model to identify patients with lethal COVID-19. Its practical reliance on commonly available parameters should improve usage of limited healthcare resources and patient survival rate. Funding This study was supported by following funding: Key Research and Development Plan of Jiangsu Province (BE2018743 and BE2019749), National Institute for Health Research (NIHR) (PDF-2018-11-ST2-006), British Heart Foundation (BHF) (PG/16/65/32313) and Liverpool University Hospitals NHS Foundation Trust in UK. Research in context Evidence before this study Since the outbreak of COVID-19, there has been a pressing need for development of a prognostic tool that is easy for clinicians to use. Recently, a Lancet publication showed that in a cohort of 191 patients with COVID-19, age, SOFA score and D-dimer measurements were associated with mortality. No other publication involving prognostic factors or models has been identified to date. Added value of this study In our cohorts of 444 patients from two hospitals, SOFA scores were low in the majority of patients on admission. The relevance of D-dimer could not be verified, as it is not included in routine laboratory tests. In this study, we have established a multivariable clinical prediction model using a development cohort of 299 patients from one hospital. After backwards selection, four variables, including age, lymphocyte count, lactate dehydrogenase and SpO 2 remained in the model to predict mortality. This has been validated internally and externally with a cohort of 145 patients from a different hospital. Discrimination of the model was excellent in both internal (c=0·89) and external (c=0·98) validation. Calibration plots showed excellent agreement between predicted and observed probabilities of mortality after recalibration of the model to account for underlying differences in the risk profile of the datasets. This demonstrated that the model is able to make reliable predictions in patients from different hospitals. In addition, these variables agree with pathological mechanisms and the model is easy to use in all types of clinical settings. Implication of all the available evidence After further external validation in different countries the model will enable better risk stratification and more targeted management of patients with COVID-19. With the nomogram, this model that is based on readily available parameters can help clinicians to stratify COVID-19 patients on diagnosis to use limited healthcare resources effectively and improve patient outcome

Early neuromuscular blocking agents for adults with acute respiratory distress syndrome: a systematic review, meta-analysis and meta-regression

Objective To determine whether neuromuscular blocking agents (NMBAs) can decrease the mortality of patients with acute respiratory distress syndrome (ARDS) and improve their clinical outcomes.Design Systematic review, meta-analysis and meta-regression.Data sources PubMed, Embase, Cochrane Library, Web of Science and ClinicalTrials.gov.Methods Randomised controlled trials (RCTs) comparing the treatment effect of NMBAs with that of placebo (or traditional treatment) in patients with ARDS were carefully selected. The primary outcome was 90-day mortality. The secondary outcomes were 21–28 days mortality, NMBA-related complications (barotrauma, pneumothorax and intensive care unit (ICU)-acquired muscle weakness), days free of ventilation and days not in the ICU by day 28, Medical Research Council score, Acute Physiology and Chronic Health Evaluation II score and arterial oxygen tension (PaO2)/fractional inspired oxygen (FiO2) (at 48 hours and 72 hours). Random-effects meta-regression was used to explore models involving potential moderators. Trial sequential analysis was performed to estimate the cumulative effect on mortality across RCTs.Results NMBAs were not associated with reduced 90-day mortality (risk ratio (RR) 0.85; 95% CI 0.66 to 1.09; p=0.20). However, they decreased the 21–28 days mortality (RR 0.71; 95% CI 0.53 to 0.96; p=0.02) and the rates of pneumothorax (RR 0.46; 95% CI 0.28 to 0.77; p=0.003) and barotrauma (RR 0.56; 95% CI 0.37 to 0.86; p=0.008). In addition, NMBAs increased PaO2/FiO2 at 48 hours (mean difference (MD) 18.91; 95% CI 4.29 to 33.53; p=0.01) and 72 hours (MD 12.27; 95% CI 4.65 to 19.89; p=0.002). Meta-regression revealed an association between sample size (p=0.042) and short-term mortality. Publication year (p=0.050), sedation strategy (p=0.047) and sample size (p=0.046) were independently associated with PaO2/FiO2 at 48 hours.Conclusions In summary, the results suggested that use of NMBAs might reduce 21–28 days mortality, NMBA-related complications and oxygenation. However, NMBAs did not reduce the 90-day mortality of patients with ARDS, which contradicts a previous meta-analysis.PROSPERO registration number CRD42019139440