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Background: Disease prevalence and distribution by patient characteristics data are needed to guide "representative" patient enrollment in clinical trials and assess relevance of results to patient populations. Our objective was to describe disease prevalence, and age/sex distribution of patients with common chronic conditions from a large population sample. Methods: A cross-sectional study of all members of Clalit Health Services, alive on January 1, 2020. Included were 26 chronic diseases, and 21 types of malignancies regarded as active by being diagnosed between January 1, 2018- to January 1, 2020, or by prescription of oncologic treatment medications January 1, 2018 and January 1, 2020. Results: Data from 4,627,183 individuals, 2,274,349 males and 2,352,834 females from newborn to 110 years. Obesity (19%), hypertension (13%), diabetes mellitus (9%), esophagitis-gastritis (5.5%), thyroid disease (5.3%), asthma (5.1%), ischemic heart disease (4.5%), depression (4.5%), osteoporosis (3.8%), and atopic dermatitis (3.6%) were the ten most prevalent conditions. Proportions of age groups varied between conditions (67% of hypertensives were ≥65 years old, 24% ≥80 years; 73% with ischemic heart disease were ≥65 years, 29% ≥80 years; 59% of diabetics were ≥65 years, 17% ≥80 years; 42% of atrial fibrillation patients were ≥80 years; 40% of heart failure patients were ≥80 years). Proportions of males and females for most conditions paralleled prevalence except proportions of women increased after age 80 for cardiovascular diseases, and for diabetes after age 75. The five most frequent active cancers were breast, prostate, colon/rectal, lymphoma and melanoma. The prevalence of cancers increased with age beginning in the middle-aged groups and peaking at very old ages. Women had lower prevalence of lung cancers and accounted for lower percentages of patients with lung cancers (45 vs 55%) but similar percentages for women and men were seen in the patients with colon and rectal cancer (50.4 vs. 49.6% in women) and lymphoma (50.7 vs. 49.3% in women). Conclusions: Prevalence of medical conditions and distributions differ by age and sex. This information serves as an example and resource for data needed to describe a "representative" clinical population. [ABSTRACT FROM AUTHOR]

Background Tixagevimab and cilgavimab, a combined monoclonal antibody (Evusheld), was granted emergency use authorization for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) preexposure prophylaxis in individuals with immunocompromising conditions. In this study we used population-based real-world data to evaluate the effectiveness of Evusheld in immunocompromised patients. Methods Using the computerized database of the largest healthcare provider in Israel, we identified all adult immunocompromised patients who were eligible to receive Evusheld (150 mg tixagevimab and 150 mg cilgavimab) on 15 February 2022. Patients with a documentation of a prior SARS-CoV-2 infection were excluded. A total of 703 patients who received Evusheld were propensity score matched, using a ratio of 1:4, with 2812 patients who had not received Evusheld (control group). Patients were followed through 30 June 2022 for up to 90 days for the first documentation of SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19)–related hospitalization. Results Overall, 72 patients in the Evusheld group and 377 patients in the control group had SARS-CoV-2 infection, reflecting an incidence rate of 4.18 and 5.64 per 100 person-months, respectively. The hazard ratios were 0.75 (95% confidence interval [CI]:.58–.96) for SARS-CoV-2 infection and 0.41 (95% CI:.19–.89) for COVID-19–related hospitalization in the Evusheld group compared to the control group. The magnitude of relative risk reduction of each outcome was greater in nonobese patients (P for interaction =.020 and.045, respectively). Conclusions This study suggests that Evusheld is effective in reducing the risk of SARS-CoV-2 infection and COVID-19 hospitalization in immunocompromised patients. The effectiveness of this dose appears to be greater in nonobese patients. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background 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. Methods 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. Results 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. Conclusions 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. [ABSTRACT FROM AUTHOR]

Objective: Clinical models such as the HAS-BLED (standing for Hypertension, Abnormal liver/renal function, Stroke history, Bleeding history or predisposition, Labile INR, Elderly, Drug/alcohol usage) were developed to predict risk of major bleeding on vitamin K antagonists/antiplatelet therapy. We aimed to develop a model that will improve the ability to predict major bleeding events in patients with non-valvular atrial fibrillation (AF) treated with new oral anticoagulants (NOACs).Methods: Clalit Health Services is the largest of four integrated healthcare organisations in Israel, which insures 4.7 million patients (53% of the population). We identified in Clalit Health Services all patients with AF, new users of an NOAC (2013-2017), and followed them until first occurrence of a major bleeding event, death, switch to another oral anticoagulant, 30 days after discontinuation of NOAC or end of follow-up (31 December 2019). Importance of the candidate model variables was estimated by inclusion frequencies across forward selection algorithm applied to 50 bootstrap samples. Then, backward selection algorithm using the modified Bayesian Information Criterion for competing risks was applied to select predictors for the final model.Results: 47 623 patients with AF prescribed NOAC were studied. 28 055 patients with AF, initiators of apixaban (mean age 78.7, SD 9.0), were included in the first phase and had 662 major bleeding events. Nine variables were selected for inclusion in a final points-based risk-scoring system: male sex, anaemia, thrombocytopaenia (<99×103/µL), concurrent antiplatelet therapy, hypertension, prior major bleeding, risk factors for a fall, low cholesterol level and low estimated glomerular filtration rate, with apparent area-under-curve (AUC) of 0.6546. Applicability of the model was then shown for 14 118 and 5450 patients with AF, initiators of dabigatran and rivaroxaban, where the score achieved c indices of 0.62 and 0.61, respectively.Conclusions: We present a novel and simple risk score for prediction of major bleeding in patients with non-valvular AF treated with NOACs. Validation in additional cohorts is warranted. [ABSTRACT FROM AUTHOR]

This document is a response to a letter to the editor regarding a study on the association between COVID-19 vaccination and myasthenia gravis (MG). The authors address concerns raised about limitations and biases in their study, and explain that they selected confounders based on their known association with both COVID-19 vaccine and MG. They conducted another analysis with additional adjustments and obtained similar results. The authors also provide information on the distribution of COVID-19 vaccine types and dosages among study participants. They argue that large multicenter trials are not feasible for investigating the relationship between COVID-19 vaccines and MG due to the rarity of the condition. The authors express interest in future gene sequencing data to further understand this field. [Extracted from the article]