Paxlovid was granted an Emergency Use Authorization for the treatment of mild to moderate coronavirus disease 2019 (COVID-19), based on the interim analysis of the Evaluation of Protease Inhibition for COVID-19 in High-Risk Patients (EPIC-HR) trial. Paxlovid effectiveness needs to be assessed in a noncontrolled setting. In this study we used population-based real-world data to evaluate the effectiveness of Paxlovid. The database of the largest healthcare provider in Israel was used to identify all adults aged 18 years or older with first-ever positive test for severe acute respiratory syndrome coronavirus 2 between January and February 2022, who were at high risk for severe COVID-19 and had no contraindications for Paxlovid use. Patients were included irrespective of their COVID-19 vaccination status. Cox hazard regression was used to estimate the 28-day hazard ratio (HR) for severe COVID-19 or mortality with Paxlovid examined as time-dependent variable. Overall, 180 351 eligible patients were included; of these, only 4737 (2.6%) were treated with Paxlovid, and 135 482 (75.1%) had adequate COVID-19 vaccination status. Both Paxlovid and adequate COVID-19 vaccination status were associated with significant decrease in the rate of severe COVID-19 or mortality with adjusted HRs of 0.54 (95% confidence interval [CI], .39–.75) and 0.20 (95% CI, .17–.22), respectively. Paxlovid appears to be more effective in older patients, immunosuppressed patients, and patients with underlying neurological or cardiovascular disease (interaction P < .05 for all). No significant interaction was detected between Paxlovid treatment and COVID-19 vaccination status. This study suggests that in the era of Omicron and in real-life settings, Paxlovid is highly effective in reducing the risk of severe COVID-19 or mortality.

Background: Privacy restrictions limit access to protected patient-derived health information for research purposes. Consequently, data anonymization is required to allow researchers data access for initial analysis before granting institutional review board approval. A system installed and activated at our institution enables synthetic data generation that mimics data from real electronic medical records, wherein only fictitious patients are listed. Objective: This paper aimed to validate the results obtained when analyzing synthetic structured data for medical research. A comprehensive validation process concerning meaningful clinical questions and various types of data was conducted to assess the accuracy and precision of statistical estimates derived from synthetic patient data. Methods: A cross-hospital project was conducted to validate results obtained from synthetic data produced for five contemporary studies on various topics. For each study, results derived from synthetic data were compared with those based on real data. In addition, repeatedly generated synthetic datasets were used to estimate the bias and stability of results obtained from synthetic data. Results: This study demonstrated that results derived from synthetic data were predictive of results from real data. When the number of patients was large relative to the number of variables used, highly accurate and strongly consistent results were observed between synthetic and real data. For studies based on smaller populations that accounted for confounders and modifiers by multivariate models, predictions were of moderate accuracy, yet clear trends were correctly observed. Conclusions: The use of synthetic structured data provides a close estimate to real data results and is thus a powerful tool in shaping research hypotheses and accessing estimated analyses, without risking patient privacy. Synthetic data enable broad access to data (eg, for out-of-organization researchers), and rapid, safe, and repeatable analysis of data in hospitals or other health organizations where patient privacy is a primary value.

The coronavirus (COVID-19) pandemic is still evolving, causing hundreds of millions of infections around the world. The long-term sequelae of COVID-19 and neurologic syndromes post COVID remain poorly understood. The present study aims to characterize cognitive performance in patients experiencing cognitive symptoms post-COVID infection. Patients evaluated at a post COVID clinic in Northern Israel who endorsed cognitive symptoms were referred for neurologic consultation. The neurologic work-up included detailed medical history, symptom inventory, neurological examination, the Montreal Cognitive Assessment (MoCA), laboratory tests and brain CT or MRI. Between December 2020 and June 2021, 46 patients were referred for neurological consultation (65% female), mean age 49.5 (19–72 years). On the MoCA test, executive functions, particularly phonemic fluency, and attention, were impaired. In contrast, the total MoCA score, and memory and orientation subscores did not differ from expected ranges. Disease severity, premorbid condition, pulmonary function tests and hypoxia did not contribute to cognitive performance. Cognitive decline may affect otherwise healthy patients post-COVID, independent of disease severity. Our examination identified abnormalities in executive function, attention, and phonemic fluency. These findings occurred despite normal laboratory tests and imaging findings.

Background: Molnupiravir was granted emergency use authorization for the treatment of mild to moderate coronavirus disease 2019 (COVID-19). In this study, we used population-based real-world data to evaluate the effectiveness of molnupiravir. Methods: The database of the largest healthcare provider in Israel was used to identify all adults with first-ever positive test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) performed in the community during January–February 2022, who were at high risk for severe COVID-19, and had no contraindications for molnupiravir use. Patients were included regardless of SARS-CoV-2 vaccination status. A total of 2661 patients who received molnupiravir were propensity score matched with 2661 patients who have not received molnupiravir (control group). Patients were followed through 10 March 2022 for up to 28 days for the first occurrence of the composite severe COVID-19 or COVID-19-specific mortality. Results: The composite outcome occurred in 50 patients in the molnupiravir group and 60 patients in the control group. Molnupiravir was associated with a nonsignificant reduced risk of the composite outcome: hazard ratio, 0.83 (95% confidence interval, .57–1.21). However, subgroup analyses showed that molnupiravir was associated with a significant decrease in the risk of the composite outcome in older patients 0.54 (0.34–0.86), in females 0.41 (0.22–0.77), and in patients with inadequate COVID-19 vaccination 0.45 (0.25–0.82). The results were similar when each component of the composite outcome was examined separately. Conclusions: This study suggests that in the era of Omicron and in real-life setting, molnupiravir might be effective in reducing the risk of severe COVID-19 and COVID-19-related mortality, particularly in specific subgroups.