Collecting and evaluating convalescent plasma for COVID-19 treatment: why and how?

Plasma provided by COVID-19 convalescent patients may provide therapeutic relief as the number of COVID-19 cases escalates steeply worldwide. Prior findings in various viral respiratory diseases including SARS-CoV-related pneumonia suggest that convalescent plasma can reduce mortality, although formal proof of efficacy is still lacking. By reducing viral spread early on, such an approach may possibly downplay subsequent immunopathology. Identifying, collecting, qualifying and preparing plasma from convalescent patients with adequate SARS-CoV-2-neutralizing Ab titres in an acute crisis setting may be challenging, although well within the remit of most blood establishments. Careful clinical evaluation should allow to quickly establish whether such passive immunotherapy, administered at early phases of the disease in patients at high risk of deleterious evolution, may reduce the frequency of patient deterioration, and thereby COVID-19 mortality.     

Automated classification of depression from structural brain measures across two independent community‐based cohorts

Major depressive disorder (MDD) has been the subject of many neuroimaging case–control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically‐ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well‐phenotyped community‐based group of current MDD cases with clinical interview‐based diagnoses (from STratifying Resilience and Depression Longitudinally cohort, ‘STRADL’). We performed a set of exploratory predictive classification analyses with measures related to brain morphometry and white matter integrity. We applied three classifier types—SVM, penalised logistic regression or decision tree—either with or without optimisation, and with or without feature selection. We then determined whether similar accuracies could be replicated in a larger independent population‐based sample with self‐reported current depression (UK Biobank cohort). Additional analyses extended to lifetime MDD diagnoses—remitted MDD in STRADL, and lifetime‐experienced MDD in UK Biobank. The highest cross‐validation accuracy (75%) was achieved in the initial current MDD sample with a decision tree classifier and cortical surface area features. The most frequently selected decision tree split variables included surface areas of bilateral caudal anterior cingulate, left lingual gyrus, left superior frontal, right precentral and paracentral regions. High accuracy was not achieved in the larger samples with self‐reported current depression (53.73%), with remitted MDD (57.48%), or with lifetime‐experienced MDD (52.68–60.29%). Our results indicate that high predictive classification accuracies may not immediately translate to larger samples with broader criteria for depression, and may not be robust across different classification approaches.     

Animal Models of Barrett's Esophagus and Esophageal Adenocarcinoma–Past,Present, and Future

Esophageal adenocarcinoma is the fastest rising cancer in the United States. It develops from long‐standing gastroesophageal reflux disease which affects >20% of the general population. It carries a very poor prognosis with 5‐year survival <20%. The disease is known to sequentially progress from reflux esophagitis to a metaplastic precursor, Barrett''s esophagus and then onto dysplasia and esophageal adenocarcinoma. However, only few patients with reflux develop Barrett''s esophagus and only a minority of these turn malignant. The reason for this heterogeneity in clinical progression is unknown. To improve patient management, molecular changes which facilitate disease progression must be identified. Animal models can provide a comprehensive functional and anatomic platform for such a study. Rats and mice have been the most widely studied but disease homology with humans has been questioned. No animal model naturally simulates the inflammation to adenocarcinoma progression as in humans, with all models requiring surgical bypass or destruction of existing antireflux mechanisms. Valuable properties of individual models could be utilized to holistically evaluate disease progression. In this review paper, we critically examined the current animal models of Barrett''s esophagus, their differences and homologies with human disease and how they have shaped our current understanding of Barrett''s carcinogenesis.     

Symptoms During or Shortly After Isolated Carpal Tunnel Release and Problems Within 24?hours After Surgery

This study used the National Survey of Ambulatory Surgery (NSAS) database to measure the incidence of and risk factors for symptoms in the ambulatory surgery center and problems within 24 h after isolated carpal tunnel release (CTR). The NSAS contained records on 400,000 adult patients with carpal tunnel syndrome who were treated with CTR in 2006, based on ICD-9 codes. The type of anesthesia used and factors associated with symptoms and problems were sought in bivariate and multivariable statistical analyses. The mean duration of the procedure was 16 ± 8.8 min. Only 5 % were performed under local anesthesia without sedation, 45 % with IV sedation, 28 % regional anesthesia, and 19 % general anesthesia. Symptoms in the ambulatory surgery center or a problem within 24 h after discharge were recorded in 10 % of patients, all of them minor and transient, including difficulties with pain and its treatment. The strongest risk factors were male sex, age of 45 years and older, and participation of an anesthesiologist. Local anesthesia and regional anesthesia were associated with more perioperative symptoms and postoperative problems. Most CTR are performed with some sedation in the United States. CTR is a safe procedure: one in 10 patients will experience a minor issue in the perioperative or immediate postoperative period.