Molnupiravir Extends COVID-19 Viral Phase, Evidenced by the High Frequency of Rare and Dangerous Mutations in SARS-COV-2

This paper analyzes SARS-COV-2 mutations data from Merck’s Molnupiravir trials, in the larger context. •5-day treatment with Molnupiravir caused the appearance and selection (to a frequency >5%) of two of the most dangerous spike mutations – E484K and P681H – in multiple patients of a very small group (2/202 and 4/202, respectively).•Molnupiravir disproportionately increases the frequency of dangerous and unusual mutations•Molnupiravir worsens COVID-19 in patients, especially those who start treatment within 3 days of symptom onset. Some theoretically possible mechanisms causing this include acute bone marrow disorder and/or the generation of immune-evasive or even immunosuppressive viral genomes. •These mechanisms are likely to extend the virus shedding period in a substantial number of patients. The virus shed by these patients would be highly mutated and likely selected toward virulence.•Molnupiravir allows for virus diversification in the treated minority and purification in the untreated, a luxury rarely experienced by any virus in the nature. •Merck failed to collect enough data about Molnupiravir driven mutations. •For each important safety event, the collected data represents a few realizations of a random variable with unknown heavy tailed statistical distribution. Merck incorrectly treated this data as worst-case scenarios.

ASK ME!—Routine measurement of patient experience with patient safety in ambulatory care: A mixed-mode survey

Objective Routine measurement of patient safety from the patients’ perspective receives increasing attention as an important component of safety measurement systems. The aim of this study was to examine patients’ experience with patient safety in ambulatory care and the results’ implications for routine patient safety measurement in ambulatory care. Design Cross-sectional mixed-mode survey. Setting General practitioner and specialist practices. Participants Patients aged >18 years seeking care in ambulatory care practices between February and June 2020. Methods A 22-item-questionnaire was completed in the practice or at home either on paper or online. Multivariate logistic regression was used to analyse the influence of survey mode and patient characteristics on patient experience with patient safety. Results The overall response rate was 71.1%. Most patients completed the questionnaire on site (76.6%) and on paper (96.1%). Between 30.1% to 68.5% of the respondents report the most positive option for patient experience with the main domains of patient safety. A total of 2.9% of patients reported having experienced a patient-safety event (PSE) during the last 12 months. Patients who filled in the questionnaire off site were more likely to report negative experiences for the scales communication & information (OR 1.2, 95% CI 1.0–1.5), rapport & participation (OR 1.4, 95% CI 1.1–1.7) and access (OR 1.3, 95% CI 0.9–1.4) than those who completed it on site. Those who chose a paper questionnaire were more likely to report negative experiences for all five scales compared to web responders. Conclusion Routine measurement of patient experience with factors contributing to the occurrence of PSEs can achieve high response rates by offering flexible participation options. Results gained from mixed-mode surveys need to take mode-effects into account when interpreting and using the results. Further research is needed in how to adequately assess number and type of experienced events in routine measurements.

Tanezumab for chronic low back pain: a long-term, randomized, celecoxib-controlled Japanese Phase III safety study

Aim & methods: This trial investigated long-term (56-week treatment/24-week follow-up) use of subcutaneous tanezumab (5 or 10 mg every 8 weeks) or oral celecoxib (200 mg/day) in Japanese patients with chronic low back pain. Results & conclusion: Tanezumab safety was consistent with previous studies, except overall adverse events (tanezumab 5 mg = 63.0%, tanezumab 10 mg = 54.8%, celecoxib = 67.4%) and events of abnormal peripheral sensation (tanezumab 5 mg = 9.8%, tanezumab 10 mg = 4.3%, celecoxib = 4.3%) were more frequent with 5 mg than 10 mg tanezumab. Joint safety event rates were 1.1% for tanezumab 5 mg, 2.2% for tanezumab 10 mg and 0% for celecoxib. All treatments improved pain and function throughout the treatment period. Clinical trial registration number: NCT02725411

Myocarditis After mRNA-1273 Vaccination: A Population-Based Analysis of 151 Million Vaccine Recipients Worldwide

Background: Growing evidence indicates a causal relationship between SARS–CoV–2 infection and myocarditis. Post–authorization safety data have also identified myocarditis as a rare safety event following mRNA COVID–19 vaccination, most notably among younger adult males and after dose 2. To further evaluate the potential risk after vaccination, we queried the Moderna global safety database to assess the occurrence of myocarditis/myopericarditis among mRNA–1273 vaccine recipients worldwide since first international Emergency Use Authorization issuance. Methods: Reports of myocarditis/myopericarditis entered into the Moderna global safety database from December 18, 2020 to September 30, 2021 were reviewed and classified based on the Brighton Collaboration case definition. The cumulative observed occurrence of myocarditis/myopericarditis was assessed by calculating the reported rate after any known dose of mRNA–1273 according to age and sex. This reporting rate was compared to a population–based incidence rate (US military) to calculate observed–to–expected rate ratios (RR). Results: Through September 30, 2021, a total of 1,439 cases of myocarditis/myopericarditis among approximately 151.1 million mRNA–1273 vaccine recipients were reported to the Moderna global safety database. The overall reporting rate among all vaccine recipients was 0.95 cases per 100,000 vaccine recipients, which was lower than the expected rate from the reference population (2.12 cases per 100,000 vaccine recipients; RR [95% CI]: 0.45 [0.42–0.48]). When stratified by sex and age, observed rates were highest for males aged ≤39 years, particularly those aged 18–24 years (7.40 cases per 100,000 vaccine recipients), which was higher than expected (RR [95% CI]: 3.49 [2.88–4.22]). For males and females aged <18 years, the rate ratio for myocarditis was 1.05 (95% CI, 0.52–2.13) and 0.21 (95% CI, 0.04–0.94), respectively. When considering only cases occurring within 7 days after vaccination, the observed rate was highest for males aged 18–24 years after dose 2 (4.9 cases per 100,000 doses administered). Conclusion: Myocarditis/myopericarditis accounted for 0.4% of adverse events reported to the Moderna global safety database after mRNA–1273 vaccination; rates were higher than expected in males aged 18–24 years, with most occurring by 7 days after dose 2, but were not higher than expected for the overall population of vaccine recipients and were lower than that observed in individuals infected with SARS–CoV–2.

Developing an Analytical Pipeline to Classify Patient Safety Event Reports Using Optimized Predictive Algorithms

Background Patient safety event reports provide valuable insight into systemic safety issues but deriving insights from these reports requires computational tools to efficiently parse through large volumes of qualitative data. Natural language processing (NLP) combined with predictive learning provides an automated approach to evaluating these data and supporting the work of patient safety analysts. Objectives The objective of this study was to use NLP and machine learning techniques to develop a generalizable, scalable, and reliable approach to classifying event reports for the purpose of driving improvements in the safety and quality of patient care. Methods Datasets for 14 different labels (themes) were vectorized using a bag-of-words, tf-idf, or document embeddings approach and then applied to a series of classification algorithms via a hyperparameter grid search to derive an optimized model. Reports were also analyzed for terms strongly associated with each theme using an adjusted F-score calculation. Results F1 score for each optimized model ranged from 0.951 (“Fall”) to 0.544 (“Environment”). The bag-of-words approach proved optimal for 12 of 14 labels, and the naïve Bayes algorithm performed best for nine labels. Linear support vector machine was demonstrated as optimal for three labels and XGBoost for four of the 14 labels. Labels with more distinctly associated terms performed better than less distinct themes, as shown by a Pearson's correlation coefficient of 0.634. Conclusions We were able to demonstrate an analytical pipeline that broadly applies NLP and predictive modeling to categorize patient safety reports from multiple facilities. This pipeline allows analysts to more rapidly identify and structure information contained in patient safety data, which can enhance the evaluation and the use of this information over time.

Dashboards for visual display of patient safety data: a systematic review

BackgroundMethods to visualise patient safety data can support effective monitoring of safety events and discovery of trends. While quality dashboards are common, use and impact of dashboards to visualise patient safety event data remains poorly understood.ObjectivesTo understand development, use and direct or indirect impacts of patient safety dashboards.MethodsWe conducted a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched PubMed, EMBASE and CINAHL for publications between 1 January 1950 and 30 August 2018 involving use of dashboards to display data related to safety targets defined by the Agency for Healthcare Research and Quality’s Patient Safety Net. Two reviewers independently reviewed search results for inclusion in analysis and resolved disagreements by consensus. We collected data on development, use and impact via standardised data collection forms and analysed data using descriptive statistics.ResultsLiterature search identified 4624 results which were narrowed to 33 publications after applying inclusion and exclusion criteria and consensus across reviewers. Publications included only time series and case study designs and were inpatient focused and emergency department focused. Information on direct impact of dashboards was limited, and only four studies included informatics or human factors principles in development or postimplementation evaluation.DiscussionUse of patient-safety dashboards has grown over the past 15 years, but impact remains poorly understood. Dashboard design processes rarely use informatics or human factors principles to ensure that the available content and navigation assists task completion, communication or decision making.ConclusionDesign and usability evaluation of patient safety dashboards should incorporate informatics and human factors principles. Future assessments should also rigorously explore their potential to support patient safety monitoring including direct or indirect impact on patient safety.