Value of D-dimer in predicting various clinical outcomes following community-acquired pneumonia: A network meta-analysis.

BACKGROUND: Whether high D-dimer level before treatment has any impact on poor outcomes in patients with community-associated pneumonia (CAP) remains unclear. Therefore, we conducted the first meta-analysis focusing specifically on prognostic value of high D-dimer level before treatment in CAP patients. METHODS: Pubmed, Embase, the Cochrane Central Register of Controlled Trials and World Health Organization clinical trials registry center were searched up to the end of March 2021. Randomized clinical trials (RCT) and observational studies were included to demonstrate the association between the level of D-dimer and clinical outcomes. Data were extracted using an adaptation of the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS-PF). When feasible, meta-analysis using random-effects models was performed. Risk of bias and level of evidence were assessed with the Quality in Prognosis Studies tool and an adaptation of Grading of Recommendations Assessment, Development, and Evaluation. Data were analyzed using STATA 14.0 to complete meta and network analysis. MAIN OUTCOMES AND MEASURES: Besides d-dimer levels in CAP patients with poor outcomes, we also analyzed proportion of patients with or without poor outcomes correctly classified by the d-dimer levels as being at high or low risk. The poor outcome includes severe CAP, death, pulmonary embolism (PE) and invasive mechanical ventilators. RESULTS: 32 studies with a total of 9,593 patients were eventually included. Pooled effect size (ES) suggested that d-dimer level was significantly higher in severe CAP patients than non-severe CAP patients with great heterogeneity (SMD = 1.21 95%CI 0.87-1.56, I2 = 86.8% p = 0.000). D-dimer level was significantly elevated in non-survivors compared to survivors with CAP (SMD = 1.22 95%CI 0.67-1.77, I2 = 85.1% p = 0.000). Prognostic value of d-dimer for pulmonary embolism (PE) was proved by hierarchical summary receiver operating characteristic curve (HSROC) with good summary sensitivity (0.74, 95%CI, 0.50-0.89) and summary specificity (0.82, 95%CI, 0.41-0.97). Network meta-analysis suggested that there was a significant elevation of d-dimer levels in CAP patients with poor outcome than general CAP patients but d-dimer levels weren't significantly different among poor outcomes. CONCLUSION: The prognostic ability of d-dimer among patients with CAP appeared to be good at correctly identifying high-risk populations of poor outcomes, suggesting potential for clinical utility in patients with CAP.

Protective efficient comparisons among all kinds of respirators and masks for health-care workers against respiratory viruses: A PRISMA-compliant network meta-analysis.

BACKGROUND: There is no definite conclusion about comparison of better effectiveness between N95 respirators and medical masks in preventing health-care workers (HCWs) from respiratory infectious diseases, so that conflicting results and recommendations regarding the protective effects may cause difficulties for selection and compliance of respiratory personal protective equipment use for HCWs, especially facing with pandemics of corona virus disease 2019. METHODS: We systematically searched MEDLINE, Embase, PubMed, China National Knowledge Infrastructure, Wanfang, medRxiv, and Google Scholar from initiation to November 10, 2020 for randomized controlled trials, case-control studies, cohort studies, and cross-sectional studies that reported protective effects of masks or respirators for HCWs against respiratory infectious diseases. We gathered data and pooled differences in protective effects according to different types of masks, pathogens, occupations, concurrent measures, and clinical settings. The study protocol is registered with PROSPERO (registration number: 42020173279). RESULTS: We identified 4165 articles, reviewed the full text of 66 articles selected by abstracts. Six randomized clinical trials and 26 observational studies were included finally. By 2 separate conventional meta-analyses of randomized clinical trials of common respiratory viruses and observational studies of pandemic H1N1, pooled effects show no significant difference between N95 respirators and medical masks against common respiratory viruses for laboratory-confirmed respiratory virus infection (risk ratio 0.99, 95% confidence interval [CI] 0.86-1.13, I2 = 0.0%), clinical respiratory illness (risk ratio 0.89, 95% CI 0.45-1.09, I2 = 83.7%, P = .002), influenza-like illness (risk ratio 0.75, 95% CI 0.54-1.05, I2 = 0.0%), and pandemic H1N1 for laboratory-confirmed respiratory virus infection (odds ratio 0.92, 95% CI 0.49-1.70, I2 = 0.0%, P = .967). But by network meta-analysis, N95 respirators has a significantly stronger protection for HCWs from betacoronaviruses of severe acute respiratory syndrome, middle east respiratory syndrome, and corona virus disease 2019 (odds ratio 0.43, 95% CI 0.20-0.94). CONCLUSIONS: Our results provide moderate and very-low quality evidence of no significant difference between N95 respirators and medical masks for common respiratory viruses and pandemic H1N1, respectively. And we found low quality evidence that N95 respirators had a stronger protective effectiveness for HCWs against betacoronaviruses causative diseases compared to medical masks. The evidence of comparison between N95 respirators and medical masks for corona virus disease 2019 is open to question and needs further study.