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We aimed to identify promising novel medications for child and adolescent mental health problems. We systematically searched https://clinicaltrials.gov/ and https://www.clinicaltrialsregister.eu/ (from 01/01/2010-08/23/2022) for phase 2 or 3 randomized controlled trials (RCTs) of medications without regulatory approval in the US, Europe or Asia, including also RCTs of dietary interventions/probiotics. Additionally, we searched phase 4 RCTs of agents targeting unlicensed indications for children/adolescents with mental health disorders. We retrieved 234 ongoing or completed RCTs, including 26 (11%) with positive findings on ≥ 1 primary outcome, 43 (18%) with negative/unavailable results on every primary outcome, and 165 (70%) without publicly available statistical results. The only two compounds with evidence of significant effects that were replicated in ≥ 1 additional RCT without any negative RCTs were dasotraline for attention-deficit/hyperactivity disorder, and carbetocin for hyperphagia in Prader-Willi syndrome. Among other strategies, targeting specific symptom dimensions in samples stratified based on clinical characteristics or established biomarkers may increase chances of success in future development programmes.

A growing body of research suggests an association between attention deficit hyperactivity disorder (ADHD) and allergic disorders, but little work has been done to explore the role of external factors such as parental smoking at home in the development of comorbid ADHD and allergic disorders. This study aimed to examine the association between allergic diseases and ADHD adjusted for exposure to parental smoking at home in early adolescents. We recruited 250 male (41.7%) and 350 female (58.3%) adolescents (mean [SD] age, 13.29 [0.52] years) via chain-referral sampling. Their ADHD symptoms were assessed by the parent proxy-report version of the Chinese Strengths and Weaknesses of Attention-Deficit/Hyperactivity-symptoms and Normal-behaviours (SWAN) rating scale. Data on the participants' history of clinician-diagnosed allergic diseases, family socio-demographics, and parental smoking habit were collected using a parent-completed questionnaire. Regression analyses were performed to examine the associations of interest. The levels of ADHD symptoms were comparable between allergic and non-allergic participants after controlling for child and family demographics and parental smoking at home. Notably, the risk of probable ADHD was particularly high in participants with food allergies (odd ratio = 4.51, p = 0.011) but not in those with allergic rhinitis after adjusting for parental smoking at home. Our findings suggest that second-hand smoke exposure at home is a potential risk factor underlying the link between ADHD and allergic diseases. Current management guidelines should emphasize the importance of early identification and cessation of tobacco smoke exposure for prevention of comorbidity of ADHD and allergic disorders. Clinical Trial Registration (if any): NA.

Additional file 3. Orphan drugs with newly added boxed warning

Additional file 1. Supplementary figures.

Additional file 2. Extracted data list and data source

Additional file 2: Table S1. ICD-9-CM codes applied for covariates. Table S2. Covariates balance for comparison between gestational L-T4 users and euthyroid control. Table S3. Percentage of gestational users who started L-T4 treatment at different trimesters. Table S4. Covariates balance for the comparison between gestational users and pre-pregnancy users. Table S5. Sensitivity analysis by comparing gestational L-T4 users to pre-pregnancy. Table S6. Sensitivity analysis by excluding mothers exposed to psychotropic or antiepileptic medications before or during pregnancy. Table S7. Subgroup analysis by stratifying offspring sex. Table S8. Sensitivity analysis by using different SGA definitions. Table S9. Sensitivity analysis by different cut-offs for preterm birth. Table S10. Sensitivity analysis for the risk of offspring ADHD by restricting to children born before the year 2014. Table S11. Comparison between gestational L-T4 users before and after year 2011. Table S12. Interaction analysis of before and after year 2011 on the estimates in the comparison between gestational L-T4 users and euthyroid control. Table S13. Post-hoc analysis adjusted cumulative dose of L-T4 during pregnancy. Table S14. Post-hoc analysis adjusted length of time the mothers using L-T4 before pregnancy.

Additional file 1: Table S1. Comparison of long-term outcomes between exposed and unexposed individuals (based on original data). Table S2. Comparison of long-term outcomes between exposed and unexposed individuals (based on imputed data) stratified by follow-up time and age of onsetTable S3.Comparison of long-term outcomes between exposed and unexposed individuals (based on original data) stratified by follow-up time and age of onset

Additional file 1: Figure S1. Pregnancy period and comparison groups’ identification. Figure S2. Cumulative incidence of ADHD and ASD by maternal L-T4 exposure. Figure S3. Box plot of the days between last L-T4 prescription and LMP of pre-pregnancy users. Figure S4. Box plot of cumulative dose among the gestational users during pregnancy. Figure S5. Box plot of length of time the mothers use L-T4 before pregnancy.

Funder: Wellcome Trust, ObjectiveTo assess the associations between coronavirus disease 2019 (COVID-19) infection and thromboembolism including myocardial infarction (MI), ischemic stroke, deep vein thrombosis (DVT), and pulmonary embolism (PE).Patients and methodsA self-controlled case-series study was conducted covering the whole of Scotland's general population. The study population comprised individuals with confirmed (positive test) COVID-19 and at least one thromboembolic event between March 2018 and October 2020. Their incidence rates during the risk interval (5 days before to 56 days after the positive test) and the control interval (the remaining periods) were compared intrapersonally.ResultsAcross Scotland, 1449 individuals tested positive for COVID-19 and experienced a thromboembolic event. The risk of thromboembolism was significantly elevated over the whole risk period but highest in the 7 days following the positive test (incidence rate ratio, 12.01; 95% CI, 9.91 to 14.56) in all included individuals. The association was also present in individuals not originally hospitalized for COVID-19 (incidence rate ratio, 4.07; 95% CI, 2.83 to 5.85). Risk of MI, stroke, PE, and DVT were all significantly higher in the week following a positive test. The risk of PE and DVT was particularly high and remained significantly elevated even 56 days following the test.ConclusionConfirmed COVID-19 infection was associated with early elevations in risk with MI, ischemic stroke, and substantially stronger and prolonged elevations with DVT and PE both in hospital and community settings. Clinicians should consider thromboembolism, especially PE, among people with COVID-19 in the community.

Additional file 1: Table S1. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes used in the study. Table S2. Subgroup analysis by age group. Table S3. Sensitivity analysis excluding patients with chronic kidney diseases. Table S4. Sensitivity analysis by excluding patients diagnosed with diabetes during the first 30 days of the follow-up period. Fig. S1. Cumulative incidence of diabetes in patients receiving anticoagulants (warfarin, apixaban, dabigatran, and rivaroxaban) after atrial fibrillation. Fig. S2. Cumulative incidence of diabetes in patients receiving anticoagulants (warfarin, apixaban/rivaroxaban, and dabigatran) after atrial fibrillation.

Additional file 1: Table S1. Results for various numbers of cardiovascular medications in sensitivity analyses. Table S2. Results for various numbers of specific medication classes in sensitivity analyses. Table S3. Summary of characteristics of study subjects with competed data.

Additional file 1. Semi-structured interview guide.

Additional file 2. Interview guide for semi-structured interviews and tables 2–5 themes of variability, causality, decision making and impact.

Additional file 1. Data extraction form for case note review.

The use of primary care databases has been integral in pharmacoepidemiological studies and pharmacovigilance. Primary care databases derive from electronic health records and offer a comprehensive description of aggregate patient data, from demography to medication history, and good sample sizes. Studies using these databases improve our understanding of prescribing characteristics and associated risk factors to facilitate better patient care, but there are limitations. We describe eight key scenarios where study data outcomes can be affected by absent prescriptions in UK primary care databases: (1) out-of-hours, urgent care and acute care prescriptions; (2) specialist-only prescriptions; (3) alternative community prescribing, such as pharmacy, family planning clinic or sexual health clinic medication prescriptions; (4) newly licensed medication prescriptions; (5) medications that do not require prescriptions; (6) hospital inpatient and outpatient prescriptions; (7) handwritten prescriptions; and (8) private pharmacy and private doctor prescriptions. The significance of each scenario is dependent on the type of medication under investigation, nature of the study and expected outcome measures. We recommend that all researchers using primary care databases be aware of the potential for missing prescribing data and be sensitive to how this can vary substantially between items, drug classes, patient groups and over time. Close liaison with practising primary care clinicians in the UK is often essential to ensure awareness of nuances in clinical practice.