Acute respiratory distress syndrome (ARDS) in COVID‐19 is associated with high mortality. Mesenchymal stem cells are known to exert immunomodulatory and anti‐inflammatory effects and could yield beneficial effects in COVID‐19 ARDS. The objective of this study was to determine safety and explore efficacy of umbilical cord mesenchymal stem cell (UC‐MSC) infusions in subjects with COVID‐19 ARDS. A double‐blind, phase 1/2a, randomized, controlled trial was performed. Randomization and stratification by ARDS severity was used to foster balance among groups. All subjects were analyzed under intention to treat design. Twenty‐four subjects were randomized 1:1 to either UC‐MSC treatment (n = 12) or the control group (n = 12). Subjects in the UC‐MSC treatment group received two intravenous infusions (at day 0 and 3) of 100 ± 20 × 106 UC‐MSCs; controls received two infusions of vehicle solution. Both groups received best standard of care. Primary endpoint was safety (adverse events [AEs]) within 6 hours; cardiac arrest or death within 24 hours postinfusion). Secondary endpoints included patient survival at 31 days after the first infusion and time to recovery. No difference was observed between groups in infusion‐associated AEs. No serious adverse events (SAEs) were observed related to UC‐MSC infusions. UC‐MSC infusions in COVID‐19 ARDS were found to be safe. Inflammatory cytokines were significantly decreased in UC‐MSC‐treated subjects at day 6. Treatment was associated with significantly improved patient survival (91% vs 42%, P = .015), SAE‐free survival (P = .008), and time to recovery (P = .03). UC‐MSC infusions are safe and could be beneficial in treating subjects with COVID‐19 ARDS.
The objective of this study was to determine whether the combination therapy of intrapancreatic autologous stem cell infusion (ASC) and hyperbaric oxygen treatment (HBO) before and after ASC can improve islet function and metabolic control in patients with type 2 diabetes mellitus (T2DM). This prospective phase 1 study enrolled 25 patients with T2DM who received a combination therapy of intrapancreatic ASC and periinfusion HBO between March 2004 and October 2006 at Stem Cells Argentina Medical Center Buenos Aires, Argentina. Clinical variables (body mass index, oral hypoglycemic drugs, insulin requirement) and metabolic variables (fasting plasma glucose, C-peptide, HbA1c, and calculation of C-peptide/glucose ratio) were assessed over quartile periods starting at baseline and up to 1 year follow-up after intervention. Means were calculated in each quartile period and compared to baseline. Seventeen male and eight female patients were enrolled. Baseline variables expressed as means ± SEs were: age 55 ± 2.14 years, diabetes duration 13.2 ± 1.62 years, insulin dose 34.8 ± 2.96 U/day, and BMI 27.11 ± 0.51. All metabolic variables showed significant improvement when comparing baseline to 12 months follow-up, respectively: fasting glucose 205.6 ± 5.9 versus 105.2 ± 14.2 mg/dl, HbA1c 8.8 ± 0.2 versus 6.0 ± 0.4%, fasting C-peptide 1.5 ± 0.2 versus 3.3 ± 0.3 ng/ml, C-peptide/glucose ratio 0.7 ± 0.2 versus 3.5 ± 0.3, and insulin requirements 34.8 ± 2.9 versus 2.5 ± 6.7 U/day. BMI remained constant over the 1-year follow-up. Combined therapy of intrapancreatic ASC infusion and HBO can improve metabolic control and reduce insulin requirements in patients with T2DM. Further randomized controlled clinical trials will be required to confirm these findings.
Aims/hypothesis MicroRNAs (miRNAs) are key regulators of gene expression and novel biomarkers for many diseases. We investigated the hypothesis that serum levels of some miRNAs would be associated with islet autoimmunity and/or progression to type 1 diabetes. Methods We measured levels of 93 miRNAs most commonly detected in serum. This retrospective cohort study included 150 autoantibody-positive and 150 autoantibody-negative family-matched siblings enrolled in the TrialNet Pathway to Prevention Study. This was a young cohort (mean age = 11 years), and most autoantibody-positive relatives were at high risk because they had multiple autoantibodies, with 39/150 (26%, progressors) developing type 1 diabetes within an average 8.7 months of follow-up. We analysed miRNA levels in relation to autoantibody status, future development of diabetes and OGTT C-peptide and glucose indices of disease progression. Results Fifteen miRNAs were differentially expressed when comparing autoantibody-positive/negative siblings (range −2.5 to 1.3-fold). but receiver operating characteristic (ROC) analysis indicated low specificity and sensitivity. Seven additional miRNAs were differentially expressed among autoantibody-positive relatives according to disease progression; ROC returned significant AUC values and identified miRNA cut-off levels associated with an increased risk of disease in both cross-sectional and survival analyses. Levels of several miRNAs showed significant correlations (r 0.22-0.55) with OGTT outcomes. miR-21-3p, miR-29a-3p and miR-424-5p had the most robust associations. Conclusions/interpretation Serum levels of selected miRNAs are associated with disease progression and confer additional risk of the development of type 1 diabetes in young autoantibody-positive relatives. Further studies, including longitudinal assessments, are warranted to further define miRNA biomarkers for prediction of disease risk and progression.
The emphasis on team science in clinical and translational research increases the importance of collaborative biostatisticians (CBs) in healthcare. Adequate training and development of CBs ensure appropriate conduct of robust and meaningful research and, therefore, should be considered as a high-priority focus for biostatistics groups. Comprehensive training enhances clinical and translational research by facilitating more productive and efficient collaborations. While many graduate programs in Biostatistics and Epidemiology include training in research collaboration, it is often limited in scope and duration. Therefore, additional training is often required once a CB is hired into a full-time position. This article presents a comprehensive CB training strategy that can be adapted to any collaborative biostatistics group. This strategy follows a roadmap of the biostatistics collaboration process, which is also presented. A TIE approach (Teach the necessary skills, monitor the Implementation of these skills, and Evaluate the proficiency of these skills) was developed to support the adoption of key principles. The training strategy also incorporates a “train the trainer” approach to enable CBs who have successfully completed training to train new staff or faculty.
Rigorous scientific review of research protocols is critical to making funding decisions, and to the protection of both human and non-human research participants. Given the increasing complexity of research designs and data analysis methods, quantitative experts, such as biostatisticians, play an essential role in evaluating the rigor and reproducibility of proposed methods. However, there is a common misconception that a statistician's input is relevant only to sample size/power and statistical analysis sections of a protocol. The comprehensive nature of a biostatistical review coupled with limited guidance on key components of protocol review motived this work. Members of the Biostatistics, Epidemiology, and Research Design (BERD) Special Interest Group (SIG) of the Association for Clinical and Translational Science (ACTS) used a consensus approach to identify the elements of research protocols that a biostatistician should consider in a review, and provide specific guidance on how each element should be reviewed. We present the resulting review framework as an educational tool and guideline for biostatisticians navigating review boards and panels. We briefly describe the approach to developing the framework, and we provide a comprehensive checklist and guidance on review of each protocol element. We posit that the biostatistical reviewer, through their breadth of engagement across multiple disciplines and experience with a range of research designs, can and should contribute significantly beyond review of the statistical analysis plan and sample size justification. Through careful scientific review, we hope to prevent excess resource expenditure and risk to humans and animals on poorly planned studies.
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