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- Axfors, Cathrine, et al.
(författare)
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Association between convalescent plasma treatment and mortality in COVID-19 : a collaborative systematic review and meta-analysis of randomized clinical trials
- 2021
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Ingår i: BMC Infectious Diseases. - : BioMed Central (BMC). - 1471-2334. ; 21:1
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Forskningsöversikt (refereegranskat)abstract
- Background: Convalescent plasma has been widely used to treat COVID-19 and is under investigation in numerous randomized clinical trials, but results are publicly available only for a small number of trials. The objective of this study was to assess the benefits of convalescent plasma treatment compared to placebo or no treatment and all-cause mortality in patients with COVID-19, using data from all available randomized clinical trials, including unpublished and ongoing trials (Open Science Framework, ). Methods: In this collaborative systematic review and meta-analysis, clinical trial registries (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform), the Cochrane COVID-19 register, the LOVE database, and PubMed were searched until April 8, 2021. Investigators of trials registered by March 1, 2021, without published results were contacted via email. Eligible were ongoing, discontinued and completed randomized clinical trials that compared convalescent plasma with placebo or no treatment in COVID-19 patients, regardless of setting or treatment schedule. Aggregated mortality data were extracted from publications or provided by investigators of unpublished trials and combined using the Hartung-Knapp-Sidik-Jonkman random effects model. We investigated the contribution of unpublished trials to the overall evidence. Results: A total of 16,477 patients were included in 33 trials (20 unpublished with 3190 patients, 13 published with 13,287 patients). 32 trials enrolled only hospitalized patients (including 3 with only intensive care unit patients). Risk of bias was low for 29/33 trials. Of 8495 patients who received convalescent plasma, 1997 died (23%), and of 7982 control patients, 1952 died (24%). The combined risk ratio for all-cause mortality was 0.97 (95% confidence interval: 0.92; 1.02) with between-study heterogeneity not beyond chance (I-2 = 0%). The RECOVERY trial had 69.8% and the unpublished evidence 25.3% of the weight in the meta-analysis. Conclusions: Convalescent plasma treatment of patients with COVID-19 did not reduce all-cause mortality. These results provide strong evidence that convalescent plasma treatment for patients with COVID-19 should not be used outside of randomized trials. Evidence synthesis from collaborations among trial investigators can inform both evidence generation and evidence application in patient care.
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| 2. |
- Furukawa, Toshi A., et al.
(författare)
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Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression : a systematic review and component network meta-analysis using individual data
- 2021
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Ingår i: Lancet psychiatry. - London, United Kingdom : Elsevier. - 2215-0374 .- 2215-0366. ; 8:6, s. 500-511
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Forskningsöversikt (refereegranskat)abstract
- Findings We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42.0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1.83 [95% credible interval (CrI) -2.90 to -0.80]) and that relaxation might be harmful (1.20 [95% CrI 0.17 to 2.27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0.32 [95% CrI 0.13 to 0.93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. 511
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| 3. |
- van der Oost, John, et al.
(författare)
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CRISPR-based adaptive and heritable immunity in prokaryotes
- 2009
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Ingår i: TIBS -Trends in Biochemical Sciences. Regular ed.. - : Elsevier BV. - 0968-0004 .- 1362-4326. ; 34:8, s. 401-407
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Forskningsöversikt (refereegranskat)abstract
- The recently discovered CRISPR (clustered regularly interspaced short palindromic repeat) defense system protects bacteria and archaea against mobile genetic elements. This immunity system has the potential to continuously adjust its reach at the genomic level, implying that both gain and loss of information is inheritable. The CRISPR system consists of typical stretches of interspaced repetitive DNA (CRISPRs) and associated cas genes. Three distinct stages are recognized in the CRISPR defense mechanism: (i) adaptation of the CRISPR via the integration of short sequences of the invaders as spacers; (ii) expression of CRISPRs and subsequent processing to small guide RNAs; and (iii) interference of target DNA by the crRNA guides. Recent analyses of key Cas proteins indicate that, despite some functional analogies, this fascinating prokaryotic system shares no phylogenetic relation with the eukaryotic RNA interference system.
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| 5. |
- So, Michelle, et al.
(författare)
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Advances in Type 1 Diabetes Prediction Using Islet Autoantibodies : Beyond a Simple Count
- 2021
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Ingår i: Endocrine Reviews. - : The Endocrine Society. - 0163-769X .- 1945-7189. ; 42:5, s. 584-604
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Forskningsöversikt (refereegranskat)abstract
- Islet autoantibodies are key markers for the diagnosis of type 1 diabetes. Since their discovery, they have also been recognized for their potential to identify at-risk individuals prior to symptoms. To date, risk prediction using autoantibodies has been based on autoantibody number; it has been robustly shown that nearly all multiple-autoantibody-positive individuals will progress to clinical disease. However, longitudinal studies have demonstrated that the rate of progression among multiple-autoantibody-positive individuals is highly heterogenous. Accurate prediction of the most rapidly progressing individuals is crucial for efficient and informative clinical trials and for identification of candidates most likely to benefit from disease modification. This is increasingly relevant with the recent success in delaying clinical disease in presymptomatic subjects using immunotherapy, and as the field moves toward population-based screening. There have been many studies investigating islet autoantibody characteristics for their predictive potential, beyond a simple categorical count. Predictive features that have emerged include molecular specifics, such as epitope targets and affinity; longitudinal patterns, such as changes in titer and autoantibody reversion; and sequence-dependent risk profiles specific to the autoantibody and the subject's age. These insights are the outworking of decades of prospective cohort studies and international assay standardization efforts and will contribute to the granularity needed for more sensitive and specific preclinical staging. The aim of this review is to identify the dynamic and nuanced manifestations of autoantibodies in type 1 diabetes, and to highlight how these autoantibody features have the potential to improve study design of trials aiming to predict and prevent disease.
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