Background Intramuscular AZD7442 (Tixagevimab–Cilgavimab, (Evusheld)) has been found effective among immunocompromised individuals (ICI) in reducing Sars-Cov-2 infection and severe disease in ICIs. We evaluated the association between AZD7442 administration and SARS-CoV-2 infection and severe disease (COVID-19 hospitalization and all-cause mortality) among selected ICIs, during a fifth Omicron-dominated wave of COVID-19 (Dec 2021-April 2022) in Israel. Methods ICIs aged 12 and over identified in the Maccabi HealthCare Services database were invited by SMS/email to receive AZD7442. Demographic information, comorbidities, coronavirus vaccination and prior SARS-CoV-2 infection and COVID-19 outcome data (infection, severe disease), were extracted from the database. Rates of infection and severe disease were compared between those administered AZD7442 and those who did not respond to the invitation, over a three-month period. Results Of all 825 ICIs administered AZD7442, 29 (3.5%) became infected with SARS-CoV-2 compared to 308 (7.2%) of 4299 ICIs not administered AZD7442 (p < 0.001). After adjustment, the AZD7442 group were half as less likely to become infected with Sars-Cov-2 than the non-administered group (OR: 0.51, 95% CI: 0.30-0.84). One person in the AZD7442 group (0.1%) was hospitalized for COVID-19 compared to 27 (0.6%) in the non-administered group (p = 0.07). No mortality was recorded among the AZD7442 group, compared to 40 deaths (0.9%) in the non-administered group (p = 0.005). After adjustment, ICIs administered AZD7442 were 92% less likely to be hospitalized/die than those not administered AZD7442 (OR: 0.08, 95% CI: 0.01-0.54). Conclusions AZD7442 among ICI may protect against Omicron variant infection and severe disease, and should be considered for pre-exposure prophylactic AZD7442.

ObjectivesTo estimate the prevalence of long COVID symptoms in children with and without a history of SARS-CoV-2 infection and to evaluate factors associated with long COVID.DesignA nationwide cross-sectional study.SettingPrimary care.Participants3240 parents of children aged 5–18 with and without SARS-CoV-2 infection completed an online questionnaire (11.9% response rate); 1148 and 2092 with/without a history of infection, respectively.Primary and secondary outcome measuresPrimary outcome was the prevalence of long COVID symptoms in children with/without a history of infection. Secondary outcomes were the factors associated with the presence of long COVID symptoms and with failure to return to baseline health status in children with a history of infection including gender, age, time from illness, symptomatic illness and vaccine status.ResultsMost long COVID symptoms were more prevalent in children with a history of SARS-CoV-2 infection: headaches (211 (18.4%) vs 114 (5.4%), p<0.001), weakness (173 (15.1%) vs 70 (3.3%), p<0.001), fatigue (141 (12.3%) vs 133 (6.4%), p<0.001) and abdominal pain (109 (9.5%) vs 79 (3.8%), p<0.001). Most long COVID symptoms in children with a history of SARS-CoV-2 infection were more prevalent in the older age group (12–18) compared with the younger age group (5–11). Some symptoms were more prevalent in children without a history of SARS-CoV-2 infection, including attention problems with school malfunctioning (225 (10.8%) vs 98 (8.5%), p=0.05), stress (190 (9.1%) vs 65 (5.7%), p<0.001), social problems (164 (7.8%) vs 32 (2.8%)) and weight changes (143 (6.8%) vs 43 (3.7%), p<0.001).ConclusionThis study suggests that the prevalence of long COVID symptoms in children with a history of SARS-CoV-2 infection might be higher and more prevalent in adolescents than in young children. Some of the symptoms, mainly somatic symptoms, were more prevalent in children without a history of SARS-CoV-2 infection, highlighting the impact of the pandemic itself rather than the infection.

Objective Evaluating the prevalence of long-COVID symptoms in patients with a history of mild or asymptomatic infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and the factors associated with developing long-COVID. Design A nationwide cohort study. Using a centralized database, we have identified patients with and without a history of SARS-CoV-2 infection 1–6 months before data collection. Patients were asked to fill out an online questionnaire through text messages. Setting Israeli general practice. Subjects 2755 persons participated in the study in September 2021 (a response rate of 7.5%): 819 with and, 936 without a history of SARS-CoV-2 infection. Main outcome measures We asked patients to provide details about their demographic status, medical history, COVID-related variables and the presence of long-COVID symptoms. Results Most prevalent long-COVID symptoms were decreased smell sensation (35.1% vs. 4.3%, p < 0.001), decreased taste sensation (25.2% vs. 3.2%, p < 0.001), memory disturbances (36.9% vs. 14.4%, p < 0.001), dyspnea (24.2% vs. 10.7%, p < 0.001) and arthralgia (33% vs. 16.3%, p < 0.001). Risk factors associated with long-COVID included female gender, symptomatic COVID-19, overweight or obesity and the presence of dyslipidemia. About 34.6% of participants reported not returning to their baseline health condition after the acute illness. Conclusion Long-COVID is frequently seen following a mild symptomatic COVID-19 infection and, to a lesser extent, following an asymptomatic SARS-CoV-2 infection. Primary care physicians should be aware of these symptoms and consider this option in their differential diagnosis. Health policymakers should expect a significant impact of this syndrome on public health. Key Points Long-COVID has emerged as a significant health problem with a serious impact on normal daily function • Long-COVID symptoms were evident in patients with mild symptomatic disease and in asymptomatic patients to a lesser extent. • Risk factors for having Long-COVID symptoms include female gender, symptomatic disease, increased BMI, and the presence of dyslipidemia. • Fatigue, dyspnea, weakness, decreased libido, weight changes, memory, and sleep disturbances were associated with not returning to the baseline health state.

Background Behavioral treatments can augment the success of pharmacotherapy in smoking cessation. The aim of this study was to compare smoking quit rates between patients receiving individual counseling with their general practitioner during office visits or intensive counselling with behavioral support, both augmented by varenicline. Methods A nationwide retrospective cohort study conducted in a large Healthcare Maintenance Organization in Israel. We selected randomly patients who filled a prescription for varenicline and received either individual consulting by their general practitioner or intensive counselling with behavioural support, and asked them to answer a questionnaire. The outcome variables were smoking cessation 26–52 weeks following the beginning of treatment and satisfaction with the process. Results 870 patients were contacted and 604 agreed to participate (a response rate of 69%); 301 patients in the general practitioner group, 300 in the intensive counselling group and 3 were excluded due to missing date. The quit rate was 36.5% in the general practitioner group and 42.3% in the intensive counselling group (P = 0.147). In a logistic regression analysis, controlling for age, gender, socioeconomic status, ischemic heart disease, chronic obstructive pulmonary disease, pack years and duration of varenicline consumption, the adjusted OR for quitting in the general practitioner group was 0.79 (95% CI 0.56,1.13). The adjusted OR was higher in the group with the highest socioeconomic status at 2.06 (1.39,3.07) and a longer period of varenicline consumption at 1.30 (1.15,1.47). Age, gender and cigarette pack-years were not associated with quit rate. In the general practitioner group 68% were satisfied with the process, while 19% were not. In the intensive counselling group 64% were satisfied and 14% were not (P = 0.007). Conclusion We did not detect a statistically significant difference in smoking quit rates, though there was a trend towards higher quit rates with intensive counselling.

Background: Risk stratification models have been developed to identify patients that are at a higher risk of COVID-19 infection and severe illness. Objectives To develop and implement a scoring tool to identify COVID-19 patients that are at risk for severe illness during the Omicron wave. Methods: This is a retrospective cohort study that was conducted in Israel’s second-largest healthcare maintenance organization. All patients with a new episode of COVID-19 between 26 November 2021 and 18 January 2022 were included. A model was developed to predict severe illness (COVID-19-related hospitalization or death) based on one-third of the study population (the train group). The model was then applied to the remaining two-thirds of the study population (the test group). Risk score sensitivity, specificity, and positive predictive value rates, and receiver operating characteristics (ROC) were calculated to describe the performance of the model. Results: A total of 409,693 patients were diagnosed with COVID-19 over the two-month study period, of which 0.4% had severe illness. Factors that were associated with severe disease were age (age > 75, OR-70.4, 95% confidence interval [CI] 42.8–115.9), immunosuppression (OR-4.8, 95% CI 3.4–6.7), and pregnancy (5 months or more, OR-82.9, 95% CI 53–129.6). Factors that were associated with a reduced risk for severe disease were vaccination status (patients vaccinated in the previous six months OR-0.6, 95% CI 0.4–0.8) and a prior episode of COVID-19 (OR-0.3, 95% CI 0.2–0.5). According to the model, patients who were in the 10th percentile of the risk severity score were considered at an increased risk for severe disease. The model accuracy was 88.7%. Conclusions: This model has allowed us to prioritize patients requiring closer follow-up by their physicians and outreach services, as well as identify those that are most likely to benefit from anti-viral treatment during the fifth wave of infection in Israel, dominated by the Omicron variant.