Predicting future onset of depression among middle-aged adults with no psychiatric history.

BACKGROUND: Depression is a major cause of disability worldwide. Recent data suggest that, in industrialised countries, the prevalence of depression peaks in middle age. Identifying factors predictive of future depressive episodes is crucial for developing prevention strategies for this age group. AIMS: We aimed to identify future depression in middle-aged adults with no previous psychiatric history. METHOD: To predict a diagnosis of depression 1 year or more following a comprehensive baseline assessment, we used a data-driven, machine-learning methodology. Our data-set was the UK Biobank of middle-aged participants (N = 245 036) with no psychiatric history. RESULTS: Overall, 2.18% of the study population developed a depressive episode at least 1 year following baseline. Basing predictions on a single mental health questionnaire led to an area under the curve of the receiver operating characteristic of 0.66, and a predictive model leveraging the combined results of 100 UK Biobank questionnaires and measurements improved this to 0.79. Our findings were robust to demographic variations (place of birth, gender) and variations in methods of depression assessment. Thus, machine-learning-based models best predict diagnoses of depression when allowing the inclusion of multiple features. CONCLUSIONS: Machine-learning approaches show potential for being beneficial for the identification of clinically relevant predictors of depression. Specifically, we can identify, with moderate success, people with no recorded psychiatric history as at risk for depression by using a relatively small number of features. More work is required to improve these models and evaluate their cost-effectiveness before integrating them into the clinical workflow.

Data-Driven Assessment of Adolescents' Mental Health During the COVID-19 Pandemic.

OBJECTIVE: Adolescents' mental health was severely compromised during the COVID-19 pandemic. Longitudinal real-world studies on changes in the mental health of adolescents during the later phase of the pandemic are limited. We aimed to quantify the effect of COVID-19 pandemic on adolescents' mental health outcomes based on electronic health records. METHOD: This was a retrospective cohort study using the computerized database of a 2.5 million members, state-mandated health organization in Israel. Rates of mental health diagnoses and psychiatric drug dispensations were measured among adolescents 12 to 17 years of age with and without pre-existing mental history, for the years 2017 to 2021. Relative risks were computed between the years, and interrupted time series (ITS) analyses evaluated changes in monthly incidence rates of psychiatric outcomes. RESULTS: The average population size was 218,146 in 2021. During the COVID-19 period, a 36% increase was observed in the incidence of depression (95% CI = 25-47), 31% in anxiety (95% CI = 23-39), 20% in stress (95% CI = 13-27), 50% in eating disorders (95% CI = 35-67), 25% in antidepressant use (95% CI = 25-33), and 28% in antipsychotic use (95% CI = 18-40). A decreased rate of 26% (95% CI = 0.80-0.88) was observed in ADHD diagnoses. The increase of the examined outcomes was most prominent among youth without psychiatric history, female youth, general secular Jewish population, youth with medium-high socioeconomic status, and those 14 to 15 years of age. ITS analysis confirmed a significantly higher growth in the incidence of psychiatric outcomes during the COVID-19 period, compared to those in previous years. CONCLUSION: This real-world study highlights the deterioration of adolescents' mental health during the COVID-19 pandemic and suggests that youth mental health should be considered during health policy decision making. DIVERSITY & INCLUSION STATEMENT: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We actively worked to promote sex and gender balance in our author group. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Long covid outcomes at one year after mild SARS-CoV-2 infection: nationwide cohort study.

OBJECTIVES: To determine the clinical sequelae of long covid for a year after infection in patients with mild disease and to evaluate its association with age, sex, SARS-CoV-2 variants, and vaccination status. DESIGN: Retrospective nationwide cohort study. SETTING: Electronic medical records from an Israeli nationwide healthcare organisation. POPULATION: 1 913 234 Maccabi Healthcare Services members of all ages who did a polymerase chain reaction test for SARS-CoV-2 between 1 March 2020 and 1 October 2021. MAIN OUTCOME MEASURES: Risk of an evidence based list of 70 reported long covid outcomes in unvaccinated patients infected with SARS-CoV-2 matched to uninfected people, adjusted for age and sex and stratified by SARS-CoV-2 variants, and risk in patients with a breakthrough SARS-CoV-2 infection compared with unvaccinated infected controls. Risks were compared using hazard ratios and risk differences per 10 000 patients measured during the early (30-180 days) and late (180-360 days) time periods after infection. RESULTS: Covid-19 infection was significantly associated with increased risks in early and late periods for anosmia and dysgeusia (hazard ratio 4.59 (95% confidence interval 3.63 to 5.80), risk difference 19.6 (95% confidence interval 16.9 to 22.4) in early period; 2.96 (2.29 to 3.82), 11.0 (8.5 to 13.6) in late period), cognitive impairment (1.85 (1.58 to 2.17), 12.8, (9.6 to 16.1); 1.69 (1.45 to 1.96), 13.3 (9.4 to 17.3)), dyspnoea (1.79 (1.68 to 1.90), 85.7 (76.9 to 94.5); 1.30 (1.22 to 1.38), 35.4 (26.3 to 44.6)), weakness (1.78 (1.69 to 1.88), 108.5, 98.4 to 118.6; 1.30 (1.22 to 1.37), 50.2 (39.4 to 61.1)), and palpitations (1.49 (1.35 to 1.64), 22.1 (16.8 to 27.4); 1.16 (1.05 to 1.27), 8.3 (2.4 to 14.1)) and with significant but lower excess risk for streptococcal tonsillitis and dizziness. Hair loss, chest pain, cough, myalgia, and respiratory disorders were significantly increased only during the early phase. Male and female patients showed minor differences, and children had fewer outcomes than adults during the early phase of covid-19, which mostly resolved in the late period. Findings remained consistent across SARS-CoV-2 variants. Vaccinated patients with a breakthrough SARS-CoV-2 infection had a lower risk for dyspnoea and similar risk for other outcomes compared with unvaccinated infected patients. CONCLUSIONS: This nationwide study suggests that patients with mild covid-19 are at risk for a small number of health outcomes, most of which are resolved within a year from diagnosis.

Robust antibody response after a third BNT162b2 vaccine compared to the second among immunocompromised and healthy individuals, a prospective longitudinal cohort study.

PURPOSE: As protection from COVID-19 following two doses of the BNT162b2 vaccine showed a time dependent waning, a third (booster) dose was administrated. This study aims to compare the antibody response following the third dose versus the second and to evaluate post-booster seroconversion. METHODS: A prospective observational study conducted in Maccabi Healthcare Services. Serial SARS-CoV-2 Spike IgG tests, 1,2,3 and 6 months following the second vaccine dose and one month following the third were obtained. Neutralizing antibody levels were measured in a subset of participants. Per individual SARS-CoV-2 Spike IgG titer ratios were calculated one month after the booster administration compared to titers one month following the second dose and prior to booster. RESULTS: Among 110 participants,56 (51%) were women. Mean age was 61.7 ± 1.9 years and 66 (60%) were immunocompromised. One month after third dose, IgG titers were induced 7.83 (95 %CI 5.25-11.67) folds and 2.40 (95 %CI 1.90-3.03) folds compared to one month after the second, in the immunocompromised and immunocompetent groups, respectively. Of the 17 immunocompromised participants who were seronegative after the second dose, 4 (24%) became seropositive following the third. Comparing the titers prior to the third dose, an increase of 50.7 (95 %CI 32.5-79.1) fold in the immunocompromised group and 25.7 (95 %CI 19.1-34.7) fold in and immunocompetent group, was observed. CONCLUSION: A third BNT162b2 vaccine elicited robust humoral response, superior to the response observed following the second, among immunocompetent and immunocompromised individuals.

BNT162b2 mRNA Vaccine Effectiveness Given Confirmed Exposure: Analysis of Household Members of Coronavirus Disease 2019 Patients.

BACKGROUND: Although BNT162b2 vaccine-efficacy analyses have been published, the effectiveness of the vaccine in preventing coronavirus disease 2019 given confirmed exposure has not been previously demonstrated, even though it has policy implications, such as the need for self-quarantine when exposure has occurred. METHODS: In a retrospective cohort study, we used data collected between 20 December 2020 and 17 March 2021 from the second largest healthcare provider in Israel to analyze the probability of an additional household infection occurring within 10 days after an index infection. In model 1, vaccine effectiveness was described for Fully Vaccinated individuals (7 or more days from second dose) vs either Unvaccinated individuals or those Recently Vaccinated Once (0-7 days from the first dose, presumably still unprotected). Secondary analyses included correction for differing testing rates. In model 2, we conducted a separate analysis of households comprised of only adults with the same vaccination status. RESULTS: A total of 173 569 households were included, of which 6351 had an index infection (mean [standard deviation] age, 58.9 [13.5] years); 50% were women. Adjusted vaccine effectiveness of Fully Vaccinated compared with Unvaccinated participants was 80.3% (95% confidence interval [CI], 73.5-85.4) and 82.0% (95% CI, 75.6-86.8) compared with those Recently Vaccinated Once. CONCLUSIONS: The BNT162b2 vaccine is effective in high-risk real-life exposure scenarios, but the protection afforded in these settings is lower than that previously described. Individuals with a confirmed significant exposure to severe acute respiratory syndrome are still at risk of being infected even if fully vaccinated.

Correlation of SARS-CoV-2-breakthrough infections to time-from-vaccine.

The short-term effectiveness of a two-dose regimen of the BioNTech/Pfizer mRNA BNT162b2 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine was widely demonstrated. However, long term effectiveness is still unknown. Leveraging the centralized computerized database of Maccabi Healthcare Services (MHS), we assessed the correlation between time-from-vaccine and incidence of breakthrough infection between June 1 and July 27, the date of analysis. After controlling for potential confounders as age and comorbidities, we found a significant 1.51 fold (95% CI, 1.38-1.66) increased risk for infection for early vaccinees compared to those vaccinated later that was similar across all ages groups. The increased risk reached 2.26- fold (95% CI, 1.80-3.01) when comparing those who were vaccinated in January to those vaccinated in April. This preliminary finding of vaccine waning as a factor of time from vaccince should prompt further investigations into long-term protection against different strains.

Results of an early second PCR test performed on SARS-CoV-2 positive patients may support risk assessment for severe COVID-19.

Identifying patients at increased risk for severe COVID-19 is of high priority during the pandemic as it could affect clinical management and shape public health guidelines. In this study we assessed whether a second PCR test conducted 2-7 days after a SARS-CoV-2 positive test could identify patients at risk for severe illness. Analysis of a nationwide electronic health records data of 1683 SARS-CoV-2 positive individuals indicated that a second negative PCR test result was associated with lower risk for severe illness compared to a positive result. This association was seen across different age groups and clinical settings. More importantly, it was not limited to recovering patients but also observed in patients who still had evidence of COVID-19 as determined by a subsequent positive PCR test. Our study suggests that an early second PCR test may be used as a supportive risk-assessment tool to improve disease management and patient care.

Protection of BNT162b2 Vaccine Booster against Covid-19 in Israel.

BACKGROUND: On July 30, 2021, the administration of a third (booster) dose of the BNT162b2 messenger RNA vaccine (Pfizer-BioNTech) was approved in Israel for persons who were 60 years of age or older and who had received a second dose of vaccine at least 5 months earlier. Data are needed regarding the effect of the booster dose on the rate of confirmed coronavirus 2019 disease (Covid-19) and the rate of severe illness. METHODS: We extracted data for the period from July 30 through August 31, 2021, from the Israeli Ministry of Health database regarding 1,137,804 persons who were 60 years of age or older and had been fully vaccinated (i.e., had received two doses of BNT162b2) at least 5 months earlier. In the primary analysis, we compared the rate of confirmed Covid-19 and the rate of severe illness between those who had received a booster injection at least 12 days earlier (booster group) and those who had not received a booster injection (nonbooster group). In a secondary analysis, we evaluated the rate of infection 4 to 6 days after the booster dose as compared with the rate at least 12 days after the booster. In all the analyses, we used Poisson regression after adjusting for possible confounding factors. RESULTS: At least 12 days after the booster dose, the rate of confirmed infection was lower in the booster group than in the nonbooster group by a factor of 11.3 (95% confidence interval [CI], 10.4 to 12.3); the rate of severe illness was lower by a factor of 19.5 (95% CI, 12.9 to 29.5). In a secondary analysis, the rate of confirmed infection at least 12 days after vaccination was lower than the rate after 4 to 6 days by a factor of 5.4 (95% CI, 4.8 to 6.1). CONCLUSIONS: In this study involving participants who were 60 years of age or older and had received two doses of the BNT162b2 vaccine at least 5 months earlier, we found that the rates of confirmed Covid-19 and severe illness were substantially lower among those who received a booster (third) dose of the BNT162b2 vaccine.

Longitudinal symptom dynamics of COVID-19 infection.

As the COVID-19 pandemic progresses, obtaining information on symptoms dynamics is of essence. Here, we extracted data from primary-care electronic health records and nationwide distributed surveys to assess the longitudinal dynamics of symptoms prior to and throughout SARS-CoV-2 infection. Information was available for 206,377 individuals, including 2471 positive cases. The two datasources were discordant, with survey data capturing most of the symptoms more sensitively. The most prevalent symptoms included fever, cough and fatigue. Loss of taste and smell 3 weeks prior to testing, either self-reported or recorded by physicians, were the most discriminative symptoms for COVID-19. Additional discriminative symptoms included self-reported headache and fatigue and a documentation of syncope, rhinorrhea and fever. Children had a significantly shorter disease duration. Several symptoms were reported weeks after recovery. By a unique integration of two datasources, our study shed light on the longitudinal course of symptoms experienced by cases in primary care.

What Factors Increase the Risk of Complications in SARS-CoV-2-Infected Patients? A Cohort Study in a Nationwide Israeli Health Organization.

BACKGROUND: Reliably identifying patients at increased risk for coronavirus disease (COVID-19) complications could guide clinical decisions, public health policies, and preparedness efforts. Multiple studies have attempted to characterize at-risk patients, using various data sources and methodologies. Most of these studies, however, explored condition-specific patient cohorts (eg, hospitalized patients) or had limited access to patients' medical history, thus, investigating related questions and, potentially, obtaining biased results. OBJECTIVE: This study aimed to identify factors associated with COVID-19 complications from the complete medical records of a nationally representative cohort of patients, with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: We studied a cohort of all SARS-CoV-2-positive individuals, confirmed by polymerase chain reaction testing of either nasopharyngeal or saliva samples, in a nationwide health organization (covering 2.3 million individuals) and identified those who suffered from serious complications (ie, experienced moderate or severe symptoms of COVID-19, admitted to the intensive care unit, or died). We then compared the prevalence of pre-existing conditions, extracted from electronic health records, between complicated and noncomplicated COVID-19 patient cohorts to identify the conditions that significantly increase the risk of disease complications, in various age and sex strata. RESULTS: Of the 4353 SARS-CoV-2-positive individuals, 173 (4%) patients suffered from COVID-19 complications (all age ≥18 years). Our analysis suggests that cardiovascular and kidney diseases, obesity, and hypertension are significant risk factors for COVID-19 complications. It also indicates that depression (eg, males ≥65 years: odds ratio [OR] 2.94, 95% CI 1.55-5.58; P=.01) as well as cognitive and neurological disorders (eg, individuals ≥65 years old: OR 2.65, 95% CI 1.69-4.17; P<.001) are significant risk factors. Smoking and presence of respiratory diseases do not significantly increase the risk of complications. CONCLUSIONS: Our analysis agrees with previous studies on multiple risk factors, including hypertension and obesity. It also finds depression as well as cognitive and neurological disorders, but not smoking and respiratory diseases, to be significantly associated with COVID-19 complications. Adjusting existing risk definitions following these observations may improve their accuracy and impact the global pandemic containment and recovery efforts.

Development and validation of a predictive model for detection of colorectal cancer in primary care by analysis of complete blood counts: a binational retrospective study.

OBJECTIVE: The use of risk prediction models grows as electronic medical records become widely available. Here, we develop and validate a model to identify individuals at increased risk for colorectal cancer (CRC) by analyzing blood counts, age, and sex, then determine the model's value when used to supplement conventional screening. MATERIALS AND METHODS: Primary care data were collected from a cohort of 606 403 Israelis (of whom 3135 were diagnosed with CRC) and a case control UK dataset of 5061 CRC cases and 25 613 controls. The model was developed on 80% of the Israeli dataset and validated using the remaining Israeli and UK datasets. Performance was evaluated according to the area under the curve, specificity, and odds ratio at several working points. RESULTS: Using blood counts obtained 3-6 months before diagnosis, the area under the curve for detecting CRC was 0.82 ± 0.01 for the Israeli validation set. The specificity was 88 ± 2% in the Israeli validation set and 94 ± 1% in the UK dataset. Detecting 50% of CRC cases, the odds ratio was 26 ± 5 and 40 ± 6, respectively, for a false-positive rate of 0.5%. Specificity for 50% detection was 87 ± 2% a year before diagnosis and 85 ± 2% for localized cancers. When used in addition to the fecal occult blood test, our model enabled more than a 2-fold increase in CRC detection. DISCUSSION: Comparable results in 2 unrelated populations suggest that the model should generally apply to the detection of CRC in other groups. The model's performance is superior to current iron deficiency anemia management guidelines, and may help physicians to identify individuals requiring additional clinical evaluation. CONCLUSIONS: Our model may help to detect CRC earlier in clinical practice.