Head-up tilt test (HUTT) is an important tool in the diagnosis of pediatric vasovagal syncope. This research will explore the relationship between syncopal symptoms and HUTT modes in pediatric vasovagal syncope.

A retrospective analysis was performed on the clinical data of 2513 children aged 3–18 years, who were diagnosed with vasovagal syncope, from Jan. 2001 to Dec. 2021 due to unexplained syncope or pre-syncope. The average age was 11.76 ± 2.83 years, including 1124 males and 1389 females. The patients were divided into the basic head-up tilt test (BHUT) group (596 patients) and the sublingual nitroglycerine head-up tilt test (SNHUT) group (1917 patients) according to the mode of positive HUTT at the time of confirmed pediatric vasovagal syncope.

(1) Baseline characteristics: Age, height, weight, heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and composition ratio of syncope at baseline status were higher in the BHUT group than in the SNHUT group (all P < 0.05). (2) Univariate analysis: Age, height, weight, HR, SBP, DBP, and syncope were potential risk factors for BHUT positive (all P < 0.05). (3) Multivariate analysis: syncope was an independent risk factor for BHUT positive, with a probability increase of 121% compared to pre-syncope (P<0.001).

The probability of BHUT positivity was significantly higher than SNHUT in pediatric vasovagal syncope with previous syncopal episodes.

Catecholaminergic polymorphic ventricular tachycardia is an ion channelopathy, caused by mutations in genes coding for calcium-handling proteins. It can coexist with left ventricular non-compaction. We aim to investigate the clinical and genetic characteristics of this co-phenotype.

Medical records of 24 patients diagnosed with catecholaminergic polymorphic ventricular tachycardia in two Chinese hospitals between September, 2005, and January, 2020, were retrospectively reviewed. We evaluated their clinical and genetic characteristics, including basic demographic data, electrocardiogram parameters, medications and survival during follow-up, and their gene mutations. We did structural analysis for a novel variant ryanodine receptor 2-E4005V.

The patients included 19 with catecholaminergic polymorphic ventricular tachycardia mono-phenotype and 5 catecholaminergic polymorphic ventricular tachycardia-left ventricular non-compaction overlap patients. The median age of onset symptoms was 9.0 (8.0,13.5) years. Most patients (91.7%) had cardiac symptoms, and 50% had a family history of syncope. Overlap patients had lower peak heart rate and threshold heart rate for ventricular tachycardia and ventricular premature beat during the exercise stress test (p < 0.05). Sudden cardiac death risk may be higher in overlap patients during follow-up. Gene sequencing revealed 1 novel ryanodine receptor 2 missense mutation E4005V and 1 mutation previously unreported in catecholaminergic polymorphic ventricular tachycardia, but no left ventricular non-compaction-causing mutations were observed. In-silico analysis showed the novel mutation E4005V broke down the interaction between two charged residues.

Catecholaminergic polymorphic ventricular tachycardia overlapping with left ventricular non-compaction may lead to ventricular premature beat/ventricular tachycardia during exercise stress test at lower threshold heart rate than catecholaminergic polymorphic ventricular tachycardia alone; it may also indicate a worse prognosis and requires strict follow-up. ryanodine receptor 2 mutations disrupted interactions between residues and may interfere the function of ryanodine receptor 2.

There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.

In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.

In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.

These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

Randomized clinical trials (RCT) are the foundation for medical advances, but participant recruitment remains a persistent barrier to their success. This retrospective data analysis aims to (1) identify clinical trial features associated with successful participant recruitment measured by accrual percentage and (2) compare the characteristics of the RCTs by assessing the most and least successful recruitment, which are indicated by varying thresholds of accrual percentage such as ≥ 90% vs ≤ 10%, ≥ 80% vs ≤ 20%, and ≥ 70% vs ≤ 30%.

Data from the internal research registry at Columbia University Irving Medical Center and Aggregated Analysis of ClinicalTrials.gov were collected for 393 randomized interventional treatment studies closed to further enrollment. We compared two regularized linear regression and six tree-based machine learning models for accrual percentage (i.e., reported accrual to date divided by the target accrual) prediction. The outperforming model and Tree SHapley Additive exPlanations were used for feature importance analysis for participant recruitment. The identified features were compared between the two subgroups.

CatBoost regressor outperformed the others. Key features positively associated with recruitment success, as measured by accrual percentage, include government funding and compensation. Meanwhile, cancer research and non-conventional recruitment methods (e.g., websites) are negatively associated with recruitment success. Statistically significant subgroup differences (corrected p-value < .05) were found in 15 of the top 30 most important features.

This multi-source retrospective study highlighted key features influencing RCT participant recruitment, offering actionable steps for improvement, including flexible recruitment infrastructure and appropriate participant compensation.

Dynamic interpersonal therapy (DIT) is a brief, structured psychodynamic psychotherapy with demonstrated efficacy in treating major depressive disorder (MDD). The aim of the study was to determine whether DIT is an acceptable and efficacious treatment for MDD patients in China.

Patients were randomized to 16-week treatments with either DIT plus antidepressant medication (DIT + ADM; n = 66), general supportive therapy plus antidepressant medication (GST + ADM; n = 75) or antidepressant medication alone (ADM; n = 70). The Hamilton Depression Rating Scale (HAMD) administered by blind raters was the primary efficacy measure. Assessments were completed during the acute 16-week treatment and up to 12-month posttreatment.

The group × time interaction was significant for the primary outcome HAMD (F = 2.900, df1 = 10, df2 = 774.72, p = 0.001) in the acute treatment phase. Pairwise comparisons showed a benefit of DIT + ADM over ADM at weeks 12 [least-squares (LS) mean difference = −3.161, p = 0.007] and 16 (LS mean difference = −3.237, p = 0.004). Because of the unexpected high attrition during the posttreatment follow-up phase, analyses of follow-up data were considered exploratory. Differences between DIT + ADM and ADM remained significant at the 1-, 6-, and 12-month follow-up (ps range from 0.001 to 0.027). DIT + ADM had no advantage over GST + ADM during the acute treatment phase. However, at the 12-month follow-up, patients who received DIT remained less depressed.

Acute treatment with DIT or GST in combination with ADM was similarly efficacious in reducing depressive symptoms and yielded a better outcome than ADM alone. DIT may provide MDD patients with long-term benefits in symptom improvement but results must be viewed with caution.

Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders.

Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed.

Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network.

These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.

Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis.

T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges.

As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms.

In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.

Autism spectrum disorder (ASD) is a neurodevelopmental condition, with symptoms appearing in the early developmental period. Little is known about its current burden at the global, regional and national levels. This systematic analysis aims to summarise the latest magnitudes and temporal trends of ASD burden, which is essential to facilitate more detailed development of prevention and intervention strategies.

The data on ASD incidence, prevalence, disability-adjusted life years (DALYs) in 204 countries and territories between 1990 and 2019 came from the Global Burden of Disease Study 2019. The average annual percentage change was calculated to quantify the secular trends in age-standardised rates (ASRs) of ASD burden by region, sex and age.

In 2019, there were an estimated 60.38 × 104 [95% uncertainty interval (UI) 50.17–72.01] incident cases of ASD, 283.25 × 105 (95% UI 235.01–338.11) prevalent cases and 43.07 × 105 (95% UI 28.22–62.32) DALYs globally. The ASR of incidence slightly increased by around 0.06% annually over the past three decades, while the ASRs of prevalence and DALYs both remained stable over the past three decades. In 2019, the highest burden of ASD was observed in high-income regions, especially in high-income North America, high-income Asia Pacific and Western Europe, where a significant growth in ASRs was also observed. The ASR of ASD burden in males was around three times that of females, but the gender difference was shrunk with the pronounced increase among females. Of note, among the population aged over 65 years, the burden of ASD presented increasing trends globally.

The global burden of ASD continues to increase and remains a major mental health concern. These substantial heterogeneities in ASD burden worldwide highlight the need for making suitable mental-related policies and providing special social and health services.

Increasing evidence supports sarcopenia as an important parameter for predicting cardiometabolic risks. The objective of this study was to investigate the relationship between muscle mass, muscle strength, and physical performance, and cardiovascular risk among older community-dwelling adults.

The associations between dynapenia, sarcopenia, and Framingham risk score (FRS) were estimated by multivariate regression models.

Muscle mass is estimated by skeletal muscle mass index using a bioelectrical impedance analysis. Muscle strength is measured by handgrip strength using an analogue isometric dynamometer. Physical performance is measured by gait speed using a 6-m walking distance. Dynapenia was defined as low muscle strength and/or slow gait speed presents with normal muscle mass. The diagnosis of presarcopenia and sarcopenia was based on criteria proposed by the Asian Working Group for Sarcopenia in 2014. The FRS was used for evaluating 10-year coronary heart disease (CHD) risk.

Adults aged 65 years and older who attended health examinations from 2015 to 2017 were recruited.

There were totally 709 subjects enrolled in this study. Dynapenic men (n 47) had 17·70 ± 5·08 % FRS and sarcopenic women (n 74) had 7·74 ± 6·06 % FRS. Participants with presarcopenia had the lowest FRS (men: 15·41 ± 5·35 %; women: 5·25 ± 3·70 %). Men with dynapenia had higher FRS than the presarcopenia group with odds ratio (OR) of 2·52 (95 % confidence interval (CI): 1·03, 6·14). Women with sarcopenia had significantly higher FRS than the presarcopenia group with OR of 2·81 (95 % CI: 1·09, 7·27).

Older dynapenic men and older sarcopenic women had higher risks of 10-year CHD. Presarcopenic older adults had the lowest CHD risk in both genders.