Venlafaxine is used to treat depression worldwide. Previous reviews have demonstrated that venlafaxine lowers scores on depression rating scales, producing statistically significant results but the relevance to patients remains uncertain. Knowledge of the incidence of the adverse effects associated with venlafaxine has previously been based on the results of non-randomised studies. Our primary objective was to assess the risks of adverse events with venlafaxine in the treatment of adults with major depressive disorder in randomised trials.

We searched relevant databases and other sources from inception to 7 March 2024 for randomised clinical trials comparing venlafaxine versus placebo or no intervention in adults with major depressive disorder. Data were synthesised using meta-analysis and Trial Sequential Analysis. The primary outcomes were suicides or suicide attempts, serious adverse events and non-serious adverse events.

We included 28 trials randomising 6,253 participants to venlafaxine versus placebo. All results were at high risk of bias, and the certainty of the evidence was very low. All trials assessed outcomes at a maximum of 12 weeks after randomisation. Meta-analysis and Trial Sequential Analysis showed insufficient information to assess the effects of venlafaxine on the risks of suicides or suicide attempts. Meta-analysis showed evidence of harm of venlafaxine versus placebo on serious adverse events (risk ratio: 2.66; 95% confidence interval: 1.67–4.25; p < 0.01; 22 trials), mainly due to a higher risk of sexual dysfunction and anorexia. Meta-analysis showed that venlafaxine also increased the risk of several non-serious adverse events: nausea, dry mouth, dizziness, sweating, somnolence, constipation, nervousness, insomnia, asthenia, tremor and decreased appetite.

Short-term results show that venlafaxine has uncertain effects on the risks of suicides but increases the risks of serious adverse events (especially sexual dysfunction and anorexia) and many non-serious adverse events. The long-term effects of venlafaxine for major depressive disorder are unknown. It is a particular cause for concern that there are no data on the long-term adverse effects of venlafaxine given that so many people use these drugs for several years.

Psychiatric disorders and type 2 diabetes mellitus (T2DM) are heritable, polygenic, and often comorbid conditions, yet knowledge about their potential shared familial risk is lacking. We used family designs and T2DM polygenic risk score (T2DM-PRS) to investigate the genetic associations between psychiatric disorders and T2DM.

We linked 659 906 individuals born in Denmark 1990–2000 to their parents, grandparents, and aunts/uncles using population-based registers. We compared rates of T2DM in relatives of children with and without a diagnosis of any or one of 11 specific psychiatric disorders, including neuropsychiatric and neurodevelopmental disorders, using Cox regression. In a genotyped sample (iPSYCH2015) of individuals born 1981–2008 (n = 134 403), we used logistic regression to estimate associations between a T2DM-PRS and these psychiatric disorders.

Among 5 235 300 relative pairs, relatives of individuals with a psychiatric disorder had an increased risk for T2DM with stronger associations for closer relatives (parents:hazard ratio = 1.38, 95% confidence interval 1.35–1.42; grandparents: 1.14, 1.13–1.15; and aunts/uncles: 1.19, 1.16–1.22). In the genetic sample, one standard deviation increase in T2DM-PRS was associated with an increased risk for any psychiatric disorder (odds ratio = 1.11, 1.08–1.14). Both familial T2DM and T2DM-PRS were significantly associated with seven of 11 psychiatric disorders, most strongly with attention-deficit/hyperactivity disorder and conduct disorder, and inversely with anorexia nervosa.

Our findings of familial co-aggregation and higher T2DM polygenic liability associated with psychiatric disorders point toward shared familial risk. This suggests that part of the comorbidity is explained by shared familial risks. The underlying mechanisms still remain largely unknown and the contributions of genetics and environment need further investigation.

Although several types of risk factors for anorexia nervosa (AN) have been identified, including birth-related factors, somatic, and psychosocial risk factors, their interplay with genetic susceptibility remains unclear. Genetic and epidemiological interplay in AN risk were examined using data from Danish nationwide registers. AN polygenic risk score (PRS) and risk factor associations, confounding from AN PRS and/or parental psychiatric history on the association between the risk factors and AN risk, and interactions between AN PRS and each level of target risk factor on AN risk were estimated.

Participants were individuals born in Denmark between 1981 and 2008 including nationwide-representative data from the iPSYCH2015, and Danish AN cases from the Anorexia Nervosa Genetics Initiative and Eating Disorder Genetics Initiative cohorts. A total of 7003 individuals with AN and 45 229 individuals without a registered AN diagnosis were included. We included 22 AN risk factors from Danish registers.

Risk factors showing association with PRS for AN included urbanicity, parental ages, genitourinary tract infection, and parental socioeconomic factors. Risk factors showed the expected association to AN risk, and this association was only slightly attenuated when adjusted for parental history of psychiatric disorders or/and for the AN PRS. The interaction analyses revealed a differential effect of AN PRS according to the level of the following risk factors: sex, maternal age, genitourinary tract infection, C-section, parental socioeconomic factors and psychiatric history.

Our findings provide evidence for interactions between AN PRS and certain risk-factors, illustrating potential diverse risk pathways to AN diagnosis.

The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.

Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.

Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web-based multi-device (smartphone, tablet, personal computer) platform optimized for remote self-administered cognitive assessment that includes a computer-adaptive word list memory test (Stricker Learning Span; SLS; Stricker et al., 2022; Stricker et al., in press) and a measure of processing speed (Symbols Test: Wilks et al., 2021). Study aims were to determine criterion validity of MTD by comparing the ability of the MTD raw composite and in-person administered cognitive measures to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11, range=37-94; mean education=16, SD=2, range=6-20; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) or with no evidence of AD pathology (A-T-, n=181). Primary outcome variables were MTD raw composite (SLS sum of trials + an accuracy-weighted Symbols response time measure), Global-z (average of 9 in-person neuropsychological measures) and an in-person screening measure (Kokmen Short Test of Mental Status, STMS; which is like the MMSE). Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Remotely administered MTD raw composite showed comparable to slightly larger effect sizes compared to Global-z. Unadjusted effect sizes for MTD raw composite for differentiating A+ vs. A- and A+T+ vs. A-T- groups, respectively, were -0.57 and -0.84 and effect sizes for Global-z were -0.54 and -0.73 (all p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but MTD raw composite remained significant for A+T+ vs A-T- (adjusted effect size -0.35, p=.007); Global-z did not reach significance for A+T+ vs A-T- (adjusted effect size -0.19, p=.08). Neither composite reached significance for adjusted analyses for the A+ vs A- comparison (MTD raw composite adjusted effect size= -.22, p=.06; Global-z adjusted effect size= -.08, p=.47). Results were the same for an alternative MTD composite using traditional z-score averaging methods, but the raw score method is preferred for comparability to other screening measures. The STMS screening measure did not differentiate biomarker groups in any analyses (unadjusted and adjusted p’s>.05; d’s -0.23 to 0.05).

Remotely administered MTD raw composite shows at least similar ability to separate biomarker-defined groups in CU individuals as a Global-z for person-administered measures within a neuropsychological battery, providing evidence of criterion validity. Both the MTD raw composite and Global-z showed greater ability to separate biomarker positive from negative CU groups compared to a typical screening measure (STMS) that was unable to differentiate these groups. MTD may be useful as a screening measure to aid early detection of Alzheimer’s pathological changes.

Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample.

The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo’s Older Americans Normative Studies (MOANS) norms.

Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6–27% variance explained), sex (0–13%), and education (2–10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS.

Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.

Rates of diagnosed attention-deficit hyperactivity disorder (ADHD) may be increasing in the UK.

Estimate incidence and prevalence of ADHD diagnoses and ADHD prescriptions in UK adults and children in primary care.

We conducted a cohort study using IQVIA Medical Research Data, a UK primary care database. Rates of ADHD diagnoses and ADHD prescriptions were calculated between 2000 and 2018 for individuals aged 3–99 years, analysed by age, gender, social deprivation status and calendar year.

Of 7 655 931 individuals, 35 877 (0.5%) had ADHD diagnoses; 18 518 (0.2%) received ADHD medication prescriptions. Diagnoses and prescription rates were greater in men versus women, children versus adults, and deprivation status (nearly double in most deprived versus least deprived quintile). By 2018, the proportion of ADHD diagnoses was 255 per 10 000 (95% CI 247–263) in boys and 67.7 per 10 000 (95% CI 63.5–71.9) in girls; for adults, it was 74.3 per 10 000 (95% CI 72.3–76.2) in men and 20 per 10 000 (95%CI 19.0–21.0) in women. Corresponding figures for prescriptions were 156 per 10 000 (95% CI 150–163) in boys, 36.8 per 10 000 (95% CI 33.8–40.0) in girls, 13.3 per 10 000 (95% CI 12.5–14.1) in men and 4.5 per 10 000 (95% CI 4.1–5.0) in women. Except among 3- to 5-year-olds, the incidence and prevalence of ADHD diagnoses and prescriptions have increased from 2000 to 2018 in all age groups. The absolute increase was highest in children, but the relative increase was largest among adults (e.g. among men aged 18–29 years, approximately 20-fold and nearly 50-fold increases in diagnoses and prescriptions, respectively).

The incidence and prevalence of both ADHD diagnoses and medication are highest among children. Proportionally, rates increased most among adults during 2000–2018. ADHD diagnoses and prescriptions are associated with socioeconomic deprivation.

The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey’s Auditory Verbal Learning Test (AVLT).

Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A−T−, n = 195). Analyses were repeated among CU participants only.

The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p’s > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A− vs A+) to large (A−T− vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups.

Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

The ENhancing Assessment of Common Therapeutic factors (ENACT) tool measures a set of therapeutic competencies required for the effective psychological intervention, including delivery by non-specialists. This paper describes the systematic adaptation of the ENACT for the South African (SA) context and presents the tool's initial psychometric properties.

We employed a four-step process: (1) Item generation: 204 therapeutic factors were generated by SA psychologists and drawn from the original ENACT as potential items; (2) Item relevance: SA therapists identified 96 items that were thematically coded according to their relationship to one another and were assigned to six domains; (3) Item utility: The ENACT-SA scale was piloted by rating recordings of psychological therapy sessions and stakeholder input; and (4) Psychometric properties: Internal consistency and inter-rater reliability of the final 12-item ENACT-SA were explored using Cronbach's alpha and intraclass correlation co-efficient (ICC) for both clinical psychologists and registered counsellors.

Although the original ENACT provided a framework for developing a tool for use in SA, several modifications were made to improve the applicability of the tool for the SA context, and optimise its adaptability other contexts. The adapted 12-item tool's internal consistency was good, while the inter-rater reliability was acceptable for both clinical psychologists and registered counsellors.

The ENACT-SA is a reliable tool to assess common factors in psychological treatments. It is recommended that the tool be used in conjunction with assessment protocols and treatment-specific competency measures to fully assess implementation fidelity and potential mechanisms of therapeutic change.

Comorbidity with general medical conditions is common in individuals with eating disorders. Many previous studies do not evaluate types of eating disorder.

To provide relative and absolute risks of bidirectional associations between (a) anorexia nervosa, bulimia nervosa and eating disorders not otherwise specified and (b) 12 general medical conditions.

We included all people born in Denmark between 1977 and 2010. We collected information on eating disorders and considered the risk of subsequent medical conditions, using Cox proportional hazards regression. Absolute risks were calculated using competing risks survival analyses. We also considered risks for prior medical conditions and subsequent eating disorders.

An increased risk was seen for almost all disorder pairs (69 of 70). Hazard ratios for those with a prior eating disorder receiving a subsequent diagnosis of a medical condition ranged from 0.94 (95% CI 0.57−1.55) to 2.05 (95% CI 1.86−2.27). For those with a prior medical condition, hazard ratios for later eating disorders ranged from 1.35 (95% CI 1.26–1.45) to 1.98 (95% CI 1.71–2.28). Absolute risks for most later disorders were increased for persons with prior disorders, compared with reference groups.

This is the largest and most detailed examination of eating disorder–medical condition comorbidity. The findings indicate that medical condition comorbidity is increased among those with eating disorders and vice versa. Although there was some variation in comorbidity observed across eating disorder types, magnitudes of relative risks did not differ greatly.

Examine pre-existing learning disorders (LD) and attention deficit/hyperactivity disorders (ADHD) as risk factors for prolonged recovery and increased symptomology following pediatric mild traumatic brain injury (mTBI).

We conducted a retrospective cohort study of children/adolescents (5-17 years) with mTBI who presented to a Children’s Minnesota Concussion Clinic between April 2018 and March 2019. Differences across strata of pre-existing conditions (present vs. absent) in time to recovery measures were estimated via Kaplan–Meier and Cox proportional hazards analyses and differences in symptom trajectories were examined via linear mixed-effects regression models. Regression models were adjusted for age, sex and other confounders.

In our cohort of 680 mTBI patients, those with LD (n = 70) or ADHD (n = 107) experienced significantly longer median durations of symptoms (58 and 68 days, respectively) than those without (43 days). Accordingly, LD was significantly associated with delayed symptom recovery (adjusted hazard ratio (aHR) = 1.63, 95% CI: 1.16–2.29), return to school (1.47, 1.08–2.00), and return to physical activity (1.50, 1.10–2.04). Likewise, ADHD was associated with delayed recovery (1.69, 1.28–2.23), return to school (1.52, 1.17–1.97) and physical activity (1.55, 1.19–2.01). Further, patients with LD or ADHD reported, on average, significantly more concussion symptoms and higher vision symptom scores throughout recovery versus those without. There was no evidence that concussion or vision symptom recovery trajectories varied over time between those with/without LD or ADHD (joint P-interactions > 0.05).

Pre-existing LD and ADHD are risk factors for prolonged and more symptomatic mTBI recovery in youth. These results can inform clinical concussion management and recovery expectations.