Characterization of drug-related problems identified by clinical pharmacy staff at Danish hospitals

Background In 2010, a database of drug related problems (DRPs) was implemented to assist clinical pharmacy staff in documenting clinical pharmacy activities locally. A study of quality, reliability and generalisability showed that national analyses of the data could be conducted. Analyses at the national level may help identify and prevent DRPs by performing national interventions. Objective The aim of the study was to explore the DRP characteristics as documented by clinical pharmacy staff at hospital pharmacies in the Danish DRP-database during a 3-year period. Setting Danish hospital pharmacies. Method Data documented in the DRP-database during the initial 3 years after implementation were analyzed retrospectively. The DRP-database contains DRPs reported at hospitals by clinical pharmacy staff. The analyses focused on DRP categories, implementation rates and drugs associated with the DRPs. Main outcome measure Characteristics of DRPs. Results In total, 72,044 DRPs were documented in the DRP-database during the first 3 years of implementation, and the number of documented DRPs increased every year. An overall stable implementation rate of approximately 58 % was identified. The DRPs identified were multi-facetted, however evenly distributed for each of the 3 years. The most frequently identified DRP categories were: “Dose”, followed by “Nonadherence to guidelines” and “Supplement to treatment”. The highest implementation rates were found for the following DRP categories: “Non-adherence to guidelines” (79 %) followed by “Therapeutic duplication” (73 %) and “Dosing time and interval” (70 %). Even though the top 25 drugs were involved in 58 % of all DRPs, multiple drugs were associated with DRPs. The drugs most frequently involved in DRPs were paracetamol (4.6 % of all DRPs), simvastatin (3.0 %), lansoprazole (2.7 %), morphine (2.6 %) and alendronic acid (2.4 %). Conclusions The study found that a national database on DRPs contained multi-facetted DRPs, however evenly distributed for each of the 3 years. Even though the top 25 drugs were involved in 58 % of all DRPs, multiple drugs were associated with DRPs. The study emphasizes the importance of detecting and intervening for DRPs.     

Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis

Glaucoma is a progressive and deteriorating optic neuropathy that leads to visual field defects. The damage occurs as glaucoma is irreversible, so early and timely diagnosis is of significant importance. The proposed system employs the convolution neural network (CNN) for automatic segmentation of the retinal layers. The inner limiting membrane (ILM) and retinal pigmented epithelium (RPE) are used to calculate cup-to-disc ratio (CDR) for glaucoma diagnosis. The proposed system uses structure tensors to extract candidate layer pixels, and a patch across each candidate layer pixel is extracted, which is classified using CNN. The proposed framework is based upon VGG-16 architecture for feature extraction and classification of retinal layer pixels. The output feature map is merged into SoftMax layer for classification and produces probability map for central pixel of each patch and decides whether it is ILM, RPE, or background pixels. Graph search theory refines the extracted layers by interpolating the missing points, and these extracted ILM and RPE are finally used to compute CDR value and diagnose glaucoma. The proposed system is validated using a local dataset of optical coherence tomography images from 196 patients, including normal and glaucoma subjects. The dataset contains manually annotated ILM and RPE layers; manually extracted patches for ILM, RPE, and background pixels; CDR values; and eventually final finding related to glaucoma. The proposed system is able to extract ILM and RPE with a small absolute mean error of 6.03 and 5.56, respectively, and it finds CDR value within average range of ± 0.09 as compared with glaucoma expert. The proposed system achieves average sensitivity, specificity, and accuracies of 94.6, 94.07, and 94.68, respectively.     

Emergence of novel coronavirus and progress toward treatment and vaccine

In late December 2019, a group of patients was observed with pneumonia‐like symptoms that were linked with a wet market in Wuhan, China. The patients were found to have a novel coronavirus genetically related to a bat coronavirus that was termed SARS‐CoV‐2. The virus gradually spread worldwide and was declared a pandemic by WHO. Scientists have started trials on potential preventive and treatment options. Currently, there is no specific approved treatment for SARS‐CoV‐2, and various clinical trials are underway to explore better treatments. Some previously approved antiviral and other drugs have shown some in vitro activity. Here we summarize the fight against this novel coronavirus with particular focus on the different treatment options and clinical trials exploring treatment as well as work done toward development of vaccines.     

EFTUD2 missense variants disrupt protein function and splicing in mandibulofacial dysostosis Guion‐Almeida type

Pathogenic variants in the core spliceosome U5 small nuclear ribonucleoprotein gene EFTUD2/SNU114 cause the craniofacial disorder mandibulofacial dysostosis Guion‐Almeida type (MFDGA). MFDGA‐associated variants in EFTUD2 comprise large deletions encompassing EFTUD2, intragenic deletions and single nucleotide truncating or missense variants. These variants are predicted to result in haploinsufficiency by loss‐of‐function of the variant allele. While the contribution of deletions within EFTUD2 to allele loss‐of‐function are self‐evident, the mechanisms by which missense variants are disease‐causing have not been characterized functionally. Combining bioinformatics software prediction, yeast functional growth assays, and a minigene (MG) splicing assay, we have characterized how MFDGA missense variants result in EFTUD2 loss‐of‐function. Only four of 19 assessed missense variants cause EFTUD2 loss‐of‐function through altered protein function when modeled in yeast. Of the remaining 15 missense variants, five altered the normal splicing pattern of EFTUD2 pre‐messenger RNA predominantly through exon skipping or cryptic splice site activation, leading to the introduction of a premature termination codon. Comparison of bioinformatic predictors for each missense variant revealed a disparity amongst different software packages and, in many cases, an inability to correctly predict changes in splicing subsequently determined by MG interrogation. This study highlights the need for laboratory‐based validation of bioinformatic predictions for EFTUD2 missense variants.     

Thymosin alpha 1: A comprehensive review of the literature

Thymosin alpha 1 is a peptide naturally occurring in the thymus that has long been recognized for modifying, enhancing, and restoring immune function. Thymosin alpha 1 has been utilized in the treatment of immunocompromised states and malignancies, as an enhancer of vaccine response, and as a means of curbing morbidity and mortality in sepsis and numerous infections. Studies have postulated that thymosin alpha 1 could help improve the outcome in severely ill corona virus disease 2019 patients by repairing damage caused by overactivation of lymphocytic immunity and how thymosin alpha 1 could prevent the excessive activation of T cells. In this review, we discuss key literature on the background knowledge and current clinical uses of thymosin alpha 1. Considering the known biochemical properties including antibacterial and antiviral properties, time-honored applications, and the new promising findings regarding the use of thymosin, we believe that thymosin alpha 1 deserves further investigation into its antiviral properties and possible repurposing as a treatment against severe acute respiratory syndrome coronavirus-2.     

Transcranial Doppler waveform changes due to increased cerebrovascular resistance and raised intracranial pressure in a patient with cirrhosis: A difference in shapes,not in numbers

We report and discuss a case that illustrate the clinical utility of transcranial Doppler (TCD) ultrasound in a patient with cirrhosis. A 43-year-old female presented with acute decompensation of cirrhosis with hepatic encephalopathy, requiring mechanical ventilation. TCD showed low diastolic flow velocities and high pulsatility index (PI) consistent with increased cerebrovascular resistance (CVR). The flow velocities and PI normalized over a period of few days and correlated well with neurological improvement after treatment. Subsequently, the patient developed a large intracerebral hemorrhage with mass effect. The TCD measurements in intracranial hypertension were similar to those with cirrhosis and hepatic encephalopathy. However, the windkessel notch in the systolic phase of TCD waveform, related to the distensibility of arterial wall, was absent during raised intracranial pressure (ICP). The absence of a windkessel notch may help to differentiate a high downstream resistance due to raised ICP from increased CVR.     

Autophagy modulators for the treatment of oral and esophageal squamous cell carcinomas

Oral squamous cell carcinomas (OSCC) and esophageal squamous cell carcinomas (ESCC) exhibit a survival rate of less than 60% and 40%, respectively. Late-stage diagnosis and lack of effective treatment strategies make both OSCC and ESCC a significant health burden. Autophagy, a lysosome-dependent catabolic process, involves the degradation of intracellular components to maintain cell homeostasis. Targeting autophagy has been highlighted as a feasible therapeutic strategy with clinical utility in cancer treatment, although its associated regulatory mechanisms remain elusive. The detection of relevant biomarkers in biological fluids has been anticipated to facilitate early diagnosis and/or prognosis for these tumors. In this context, recent studies have indicated the presence of specific proteins and small RNAs, detectable in circulating plasma and serum, as biomarkers. Interestingly, the interplay between biomarkers (eg, exosomal microRNAs) and autophagic processes could be exploited in the quest for targeted and more effective therapies for OSCC and ESCC. In this review, we give an overview of the available biomarkers and innovative targeted therapeutic strategies, including the application of autophagy modulators in OSCC and ESCC. Additionally, we provide a viewpoint on the state of the art and on future therapeutic perspectives combining the early detection of relevant biomarkers with drug discovery for the treatment of OSCC and ESCC.