This study aimed to summarize the evidence on sleep alterations in medication-naïve children and adolescents with autism spectrum disorder (ASD).

We systematically searched PubMed/Medline, Embase and Web of Science databases from inception through March 22, 2021. This study was registered with PROSPERO (CRD42021243881). Any observational study was included that enrolled medication-naïve children and adolescents with ASD and compared objective (actigraphy and polysomnography) or subjective sleep parameters with typically developing (TD) counterparts. We extracted relevant data such as the study design and outcome measures. The methodological quality was assessed through the Newcastle-Ottawa Scale (NOS). A meta-analysis was carried out using the random-effects model by pooling effect sizes as Hedges’ g. To assess publication bias, Egger’s test and p-curve analysis were done. A priori planned meta-regression and subgroup analysis were also performed to identify potential moderators.

Out of 4277 retrieved references, 16 studies were eligible with 981 ASD patients and 1220 TD individuals. The analysis of objective measures showed that medication-naïve ASD patients had significantly longer sleep latency (Hedges’ g 0.59; 95% confidence interval [95% CI] 0.26 to 0.92), reduced sleep efficiency (Hedges’ g −0.58; 95% CI −0.87 to −0.28), time in bed (Hedges’ g −0.64; 95% CI −1.02 to −0.26) and total sleep time (Hedges’ g −0.64; 95% CI −1.01 to −0.27). The analysis of subjective measures showed that they had more problems in daytime sleepiness (Hedges’ g 0.48; 95% CI 0.26 to 0.71), sleep latency (Hedges’ g 1.15; 95% CI 0.72 to 1.58), initiating and maintaining sleep (Hedges’ g 0.86; 95% CI 0.39 to 1.33) and sleep hyperhidrosis (Hedges’ g 0.48; 95% CI 0.29 to 0.66). Potential publication bias was detected for sleep latency, sleep period time and total sleep time measured by polysomnography. Some sleep alterations were moderated by age, sex and concurrent intellectual disability. The median NOS score was 8 (interquartile range 7.25–8.75).

We found that medication-naïve children and adolescents with ASD presented significantly more subjective and objective sleep alterations compared to TD and identified possible moderators of these differences. Future research requires an analysis of how these sleep alterations are linked to core symptom severity and comorbid behavioural problems, which would provide an integrated therapeutic intervention for ASD. However, our results should be interpreted in light of the potential publication bias.

During the coronavirus disease 2019 (COVID-19) pandemic, undergraduate students were exposed to symptoms of psychological suffering during remote classes. Therefore, it is important to investigate the factors that may be generated and be related to such outcomes.

To investigate the association between fear of COVID-19, depression, anxiety, and related factors in undergraduate students during remote classes.

This cross-sectional study included 218 undergraduate students (60.6% women and 39.4% men). Students answered a self-administered online questionnaire designed to gather personal information, pandemic exposure, physical activity level, fear of COVID-19 using the ‘Fear of COVID-19 Scale’, symptoms of depression using the Patient Health Questionnaire-9, and anxiety using General Anxiety Disorder-7.

Undergraduate students had a high prevalence of depression and anxiety (83.0% and 76.1%, respectively) but a low prevalence of fear of COVID-19 (28.9%) during remote classes. Multivariate analysis revealed that women who reported health status as neither good nor bad and who had lost a family member from COVID-19 had the highest levels of fear. For depression and anxiety, the main related factors found were female gender, bad health status, insufficiently active, and complete adherence to the restriction measures.

These findings may be used to develop actions to manage symptoms of anxiety and depression among students, with interventions through physical activity programmes to improve mental health.

Despite the multitude of clinical manifestations of post-acute sequelae of SARS-CoV-2 infection (PASC), studies applying statistical methods to directly investigate patterns of symptom co-occurrence and their biological correlates are scarce.

We assessed 30 symptoms pertaining to different organ systems in 749 adults (age = 55 ± 14 years; 47% female) during in-person visits conducted at 6–11 months after hospitalization due to coronavirus disease 2019 (COVID-19), including six psychiatric and cognitive manifestations. Symptom co-occurrence was initially investigated using exploratory factor analysis (EFA), and latent variable modeling was then conducted using Item Response Theory (IRT). We investigated associations of latent variable severity with objective indices of persistent physical disability, pulmonary and kidney dysfunction, and C-reactive protein and D-dimer blood levels, measured at the same follow-up assessment.

The EFA extracted one factor, explaining 64.8% of variance; loadings were positive for all symptoms, and above 0.35 for 16 of them. The latent trait generated using IRT placed fatigue, psychiatric, and cognitive manifestations as the most discriminative symptoms (coefficients > 1.5, p < 0.001). Latent trait severity was associated with decreased body weight and poorer physical performance (coefficients > 0.240; p ⩽ 0.003), and elevated blood levels of C-reactive protein (coefficient = 0.378; 95% CI 0.215–0.541; p < 0.001) and D-dimer (coefficient = 0.412; 95% CI 0.123–0.702; p = 0.005). Results were similar after excluding subjects with pro-inflammatory comorbidities.

Different symptoms that persist for several months after moderate or severe COVID-19 may unite within one latent trait of PASC. This trait is dominated by fatigue and psychiatric symptoms, and is associated with objective signs of physical disability and persistent systemic inflammation.

The clinical outcomes of individuals at clinical high risk of psychosis (CHR-P) who do not transition to psychosis are heterogeneous and inconsistently reported. We aimed to comprehensively evaluate longitudinally a wide range of outcomes in CHR-P individuals not developing psychosis.

“Preferred Reporting Items for Systematic reviews and Meta-Analyses” and “Meta-analysis Of Observational Studies in Epidemiology”-compliant meta-analysis (PROSPERO: CRD42021229212) searching original CHR-P longitudinal studies in PubMed and Web of Science databases up to 01/11/2021. As primary analysis, we evaluated the following outcomes within CHR-P non-transitioning individuals: (a) change in the severity of attenuated psychotic symptoms (Hedge's g); (b) change in the severity of negative psychotic symptoms (Hedge's g); (c) change in the severity of depressive symptoms (Hedge's g); (d) change in the level of functioning (Hedge's g); (e) frequency of remission (at follow-up). As a secondary analysis, we compared these outcomes in those CHR-P individuals who did not transition vs. those who did transition to psychosis at follow-up. We conducted random-effects model meta-analyses, sensitivity analyses, heterogeneity analyses, meta-regressions and publication bias assessment. The risk of bias was assessed using a modified version of the Newcastle-Ottawa Scale (NOS).

Twenty-eight studies were included (2756 CHR-P individuals, mean age = 20.4, 45.5% females). The mean duration of follow-up of the included studies was of 30.7 months. Primary analysis: attenuated psychotic symptoms [Hedges’ g = 1.410, 95% confidence interval (CI) 1.002–1.818]; negative psychotic symptoms (Hedges’ g = 0.683, 95% CI 0.371–0.995); depressive symptoms (Hedges’ g = 0.844, 95% CI 0.371–1.317); and functioning (Hedges’ g = 0.776, 95% CI 0.463–1.089) improved in CHR-P non-transitioning individuals; 48.7% remitted at follow-up (95% CI 39.3–58.2%). Secondary analysis: attenuated psychotic symptoms (Hedges’ g = 0.706, 95% CI 0.091–1.322) and functioning (Hedges’ g = 0.623, 95% CI 0.375–0.871) improved in CHR-P individuals not-transitioning compared to those transitioning to psychosis, but there were no differences in negative or depressive symptoms or frequency of remission (p > 0.05). Older age was associated with higher improvements of attenuated psychotic symptoms (β = 0.225, p = 0.012); publication years were associated with a higher improvement of functioning (β = −0.124, p = 0.0026); a lower proportion of Brief Limited Intermittent Psychotic Symptoms was associated with higher frequencies of remission (β = −0.054, p = 0.0085). There was no metaregression impact for study continent, the psychometric instrument used, the quality of the study or proportion of females. The NOS scores were 4.4 ± 0.9, ranging from 3 to 6, revealing the moderate quality of the included studies.

Clinical outcomes improve in CHR-P individuals not transitioning to psychosis but only less than half remit over time. Sustained clinical attention should be provided in the longer term to monitor these outcomes.

Individuals at clinical high risk of psychosis (CHR-P) recruited in randomized clinical trials (RCTs) and observational cohorts may display a different enrichment and hence risk of transition to psychosis. No meta-analysis has ever addressed this issue.

“Preferred Reporting Items for Systematic reviews and Meta-Analyses” (PRISMA) and “Meta-analysis Of Observational Studies in Epidemiology” (MOOSE)–compliant meta-analysis. PubMed and Web of Science were searched until November 2020 (PROSPERO:CRD42021229223). We included nonoverlapping longitudinal studies (RCTs-control condition and observational cohorts) reporting the transition to psychosis in CHR-P individuals. The primary effect size measure was the cumulative risk of transition at 0.5, 1, and 2 years follow-up in RCTs compared to observational cohorts. Random effects meta-analyses, heterogeneity assessment, quality assessment, and meta-regressions were conducted.

Ninety-four independent studies (24 RCTs, 70 observational cohorts) and 9,243 individuals (mean age = 20.1 ± 3.0 years; 43.7% females) were included. The meta-analytical risk of transitioning to psychosis from a CHR-P stage was 0.091 (95% confidence intervals [CI] = 0.068–0.121) at 0.5 years, 0.140 (95% CI = 0.101–0.191) at 1 year and 0.165 (95% CI = 0.097–0.267) at 2 years follow-up in RCTs, and 0.081 (95% CI = 0.067–0.099) at 0.5 years, 0.138 (95% CI = 0.114–0.167) at 1 year, and 0.174 (95% CI = 0.156–0.193) at 2 years follow-up in observational cohorts. There were no between-group differences in transition risks (p > 0.05). The proportion of CHR-P individuals with substance use disorders (excluding alcohol and cannabis) was higher in observational cohorts (16.8, 95% CI = 13.3–21.0%) than in RCTs (3.4, 95% CI = 0.8–12.7%; p = 0.018).

There is no meta-analytic evidence supporting sampling biases in RCTs of CHR-P individuals. Further RCTs are needed to detect effective interventions to prevent psychosis in this at-risk group.

Birthweight (BW) has been associated with anthropometry, body composition and physical fitness during growth and development of children. However, less is known about the mediation effect of those variables on the relationship between BW and basal metabolic rate (BMR) in children.

To analyse the mediation effect of anthropometry, body composition and physical fitness on the association between BW and BMR in children.

In total, 499 children (254 boys, 245 girls) aged 7–10 years were included. Anthropometry (weight, height, head, waist and hip circumferences), body composition (skinfolds thickness, body fat percentage), physical fitness (handgrip strength, flexibility, muscular endurance, muscular explosive power, agility, running speed) and BMR were evaluated. The analyses were conducted by: single-mediator analysis (SMA) and multi-mediator analysis (MMA).

The SMA indicates height, head, waist and hip circumferences and handgrip strength as significant mediators of BW on BMR for boys and height, hip circumference and handgrip strength as significant mediators of BW on BMR for girls. In MMA for girls, there were significant indirect effects for height, hip circumference and handgrip strength, with 79.08% of percent mediation. For boys, the head and waist circumferences mediation had a significant indirect effect, with 83.37% of percent mediation.

The anthropometric variables associated with BW were body height, head, hip and waist circumferences for boys and body height and hip circumference for girls. The current study provides new evidence that height and handgrip strength during childhood mediated the relationship between BW and BMR.

The elderly population and numbers of nursing homes residents are growing at a rapid pace globally. Uncertainty exists regarding the actual rates of major depressive disorder (MDD), bipolar disorder and schizophrenia as previous evidence documenting high rates relies on suboptimal methodology.

To carry out a systematic review and meta-analysis on the prevalence and correlates of MDD, bipolar disorder and schizophrenia spectrum disorder among nursing homes residents without dementia.

Major electronic databases were systematically searched from 1980 to July 2017 for original studies reporting on the prevalence and correlates of MDD among nursing homes residents without dementia. The prevalence of MDD in this population was meta-analysed through random-effects modelling and potential sources of heterogeneity were examined through subgroup/meta-regression analyses.

Across 32 observational studies encompassing 13 394 nursing homes residents, 2110 people were diagnosed with MDD, resulting in a pooled prevalence rate of 18.9% (95% CI 14.8–23.8). Heterogeneity was high (I2 = 97%, P≤0.001); no evidence of publication bias was observed. Sensitivity analysis indicated the highest rates of MDD among North American residents (25.4%, 95% CI 18–34.5, P≤0.001). Prevalence of either bipolar disorder or schizophrenia spectrum disorder could not be reliably pooled because of the paucity of data.

MDD is highly prevalent among nursing homes residents without dementia. Efforts towards prevention, early recognition and management of MDD in this population are warranted.

Our aim was to summarize the efficacy and safety of atomoxetine, amphetamines, and methylphenidate in schizophrenia.

We undertook a systematic review, searching PubMed/Scopus/Clinicaltrials.gov for double-blind, randomized, placebo-controlled studies of psychostimulants or atomoxetine in schizophrenia published up to 1 January 2017. A meta-analysis of outcomes reported in two or more studies is presented.

We included 22 studies investigating therapeutic effects of stimulants (k=14) or measuring symptomatic worsening/relapse prediction after stimulant challenge (k=6). Six studies of these two groups plus one additional study investigated biological effects of psychostimulants or atomoxetine. No effect resulted from interventional studies on weight loss (k=1), smoking cessation (k=1), and positive symptoms (k=12), and no improvement was reported with atomoxetine (k=3) for negative symptoms, with equivocal findings for negative (k=6) and mood symptoms (k=2) with amphetamines. Attention, processing speed, working memory, problem solving, and executive functions, among others, showed from no to some improvement with atomoxetine (k=3) or amphetamines (k=6). Meta-analysis did not confirm any effect of stimulants in any symptom domain, including negative symptoms, apart from atomoxetine improving problem solving (k=2, standardized mean difference (SMD)=0.73, 95% CI=0.10–1.36, p=0.02, I2=0%), and trending toward significant improvement in executive functions with amphetamines (k=2, SMD=0.80, 95% CI=−1.68 to +0.08, p=0.08, I2=66%). In challenge studies, amphetamines (k=1) did not worsen symptoms, and methylphenidate (k=5) consistently worsened or predicted relapse. Biological effects of atomoxetine (k=1) and amphetamines (k=1) were cortical activation, without change in β-endorphin (k=1), improved response to antipsychotics after amphetamine challenge (k=2), and an increase of growth hormone–mediated psychosis with methylphenidate (k=2). No major side effects were reported (k=6).

No efficacy for stimulants or atomoxetine on negative symptoms is proven. Atomoxetine or amphetamines may improve cognitive symptoms, while methylphenidate should be avoided in patients with schizophrenia. Insufficient evidence is available to draw firm conclusions.