Medication nonadherence is a public health concern and can impact clinical trial data quality. Traditional compliance collection (pill counts, diaries) can be unreliable in central nervous system trials. As such, strategies such as adherence technologies may play a key role in trial outcomes. AiCure, a computer vision-assisted dosing mobile application (app), collects dosing data and connects patients to sites for dosing support. Phone-based computer vision algorithms confirm dosing and transfer videos for artificial intelligence and human review. Boehringer Ingelheim is partnering with AiCure on pilot trials using AiCure adherence data to improve patient retention and clinical trial data quality. Here we report initial findings.

This pilot used data from two Phase II trials on the efficacy and safety of BI 409306 in people with schizophrenia (NCT03351244) or Attenuated Psychosis Syndrome (NCT03230097). The AiCure mobile app alerted participants to dosing protocols. The dose event was visually confirmed, providing sites a real-time view of adherence and allowing for targeted outreach and intervention. Adherence data from the first 2 weeks generated quantitative, machine-learning models to predict the individual adherence over the trial. Predictive modeling explored different monitoring periods (7-, 10-, and 14-day) and adherence cutoff points (0.8, 0.7, 0.6).

Initial AiCure assessment identified 43% of participants in NCT03351244 as ≤80% compliant (definition of compliance >80% compliant). Variance in adherence rates between electronic case report forms (eCRF; 78%) and AiCure (26%) data was also observed in the highly compliant/adherent group in NCT03230097. Using the first 2 weeks of adherence data (both studies combined), a participant’s adherence predicted their average adherence for the remainder of the trial. Observation of a participant’s adherence for the latest 4 weeks predicted the probability of premature dropout from the trial. There were further correlations of lower predicted adherence with actual disposition-based dropouts.

The early adherence predictive model (0.6 adherence cutoff) identified 22%, 20%, and 19% of patients for trial NCT03351244 (total n=235) as high-risk patients (low-adherence prediction) across 7-, 10-, and 14-day monitoring periods, respectively. Of those high-risk patients, 81%, 90%, and 96%, respectively, were truly nonadherent based on actual adherence data. The 14-day monitoring period model provided the lowest false omission rate, indicative of a better performing model.

AiCure data provided insights into patient behavior and adherence patterns which would not be available via CRF. Predictive models developed with AiCure adherence data can identify and predict future poor adherers. This creates opportunities to plan interventions and mitigation strategies to improve patient adherence during trials, thereby providing test drugs the best opportunity at proving efficacy.

Boehringer Ingelheim International GmbH (NCT03351244/1289-0049 and NCT03230097/1289-0032)

Depressive symptoms, functional impairment, and decreased quality of life (QOL) are three important domains of major depressive disorder (MDD). However, the possible causal relationship between these factors has yet to be elucidated. Moreover, it is not known whether certain symptoms of MDD are more impairing than others. The network approach is a promising solution to these shortfalls.

The baseline data of a multicenter prospective project conducted in 11 governances of China were analyzed. In total, 1385 patients with MDD were included. Depressive symptoms, functioning disability, and QOL were evaluated by the 17-item Hamilton Depression Rating Scale (HAMD-17), the Sheehan Disability Scale (SDS), and the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF). The network was estimated through the graphical Least Absolute Shrinkage and Selection Operator (LASSO) technique in combination with the directed acyclic graph.

Three centrality metrics of the graphical LASSO showed that social life dysfunction, QOL, and late insomnia exhibited the highest strength centrality. The network accuracy and stability were estimated to be robust and stable. The Bayesian network indicated that some depressive symptoms were directly associated with QOL, while other depressive symptoms showed an indirect association with QOL mediated by impaired function. Depressed mood was positioned at the highest level in the model and predicted the activation of functional impairment and anxiety.

Functional disability mediated the relationship between depressive symptoms and QOL. Family functionality and suicidal symptoms were directly related to QOL. Depressed mood played the predominant role in activating both anxiety symptom and functional impairment.

Despite increasing knowledge on the neuroimaging patterns of eating disorder (ED) symptoms in non-clinical populations, studies using whole-brain machine learning to identify connectome-based neuromarkers of ED symptomatology are absent. This study examined the association of connectivity within and between large-scale functional networks with specific symptomatic behaviors and cognitions using connectome-based predictive modeling (CPM).

CPM with ten-fold cross-validation was carried out to probe functional networks that were predictive of ED-associated symptomatology, including body image concerns, binge eating, and compensatory behaviors, within the discovery sample of 660 participants. The predictive ability of the identified networks was validated using an independent sample of 821 participants.

The connectivity predictive of body image concerns was identified within and between networks implicated in cognitive control (frontoparietal and medial frontal), reward sensitivity (subcortical), and visual perception (visual). Crucially, the set of connections in the positive network related to body image concerns identified in one sample was generalized to predict body image concerns in an independent sample, suggesting the replicability of this effect.

These findings point to the feasibility of using the functional connectome to predict ED symptomatology in the general population and provide the first evidence that functional interplay among distributed networks predicts body shape/weight concerns.

The relationship of a diet low in fibre with mortality has not been evaluated. This study aims to assess the burden of non-communicable chronic diseases (NCD) attributable to a diet low in fibre globally from 1990 to 2019.

All data were from the Global Burden of Disease (GBD) Study 2019, in which the mortality, disability-adjusted life-years (DALY) and years lived with disability (YLD) were estimated with Bayesian geospatial regression using data at global, regional and country level acquired from an extensively systematic review.

All data sourced from the GBD Study 2019.

All age groups for both sexes.

The age-standardised mortality rates (ASMR) declined in most GBD regions; however, in Southern sub-Saharan Africa, the ASMR increased from 4·07 (95 % uncertainty interval (UI) (2·08, 6·34)) to 4·60 (95 % UI (2·59, 6·90)), and in Central sub-Saharan Africa, the ASMR increased from 7·46 (95 % UI (3·64, 11·90)) to 9·34 (95 % UI (4·69, 15·25)). Uptrends were observed in the age-standardised YLD rates attributable to a diet low in fibre in a number of GBD regions. The burden caused by diabetes mellitus increased in Central Asia, Southern sub-Saharan Africa and Eastern Europe.

The burdens of disease attributable to a diet low in fibre in Southern sub-Saharan Africa and Central sub-Saharan Africa and the age-standardised YLD rates in a number of GBD regions increased from 1990 to 2019. Therefore, greater efforts are needed to reduce the disease burden caused by a diet low in fibre.

Based on hubs of neural circuits associated with addiction and their degree centrality (DC), this study aimed to construct the addiction-related brain networks for patients diagnosed with heroin dependence undertaking stable methadone maintenance treatment (MMT) and further prospectively identify the ones at high risk for relapse with cluster analysis.

Sixty-two male MMT patients and 30 matched healthy controls (HC) underwent brain resting-state functional MRI data acquisition. The patients received 26-month follow-up for the monthly illegal-drug-use information. Ten addiction-related hubs were chosen to construct a user-defined network for the patients. Then the networks were discriminated with K-means-clustering-algorithm into different groups and followed by comparative analysis to the groups and HC. Regression analysis was used to investigate the brain regions significantly contributed to relapse.

Sixty MMT patients were classified into two groups according to their brain-network patterns calculated by the best clustering-number-K. The two groups had no difference in the demographic, psychological indicators and clinical information except relapse rate and total heroin consumption. The group with high-relapse had a wider range of DC changes in the cortical−striatal−thalamic circuit relative to HC and a reduced DC in the mesocorticolimbic circuit relative to the low-relapse group. DC activity in NAc, vACC, hippocampus and amygdala were closely related with relapse.

MMT patients can be identified and classified into two subgroups with significantly different relapse rates by defining distinct brain-network patterns even if we are blind to their relapse outcomes in advance. This may provide a new strategy to optimize MMT.

To evaluate the relationship between religious beliefs and mental state, care burden, and quality of life in parents of infantile patients with CHD.

A cross-sectional study was conducted at a provincial hospital in Fujian, China. In this study, 114 parents of infant patients with CHD were successfully enrolled. Data were collected using the Duke University Religion Index, Hospital Anxiety and Depression Scale, Zarit Caregiver Burden Interview, and 36-Item Short-Form Health Survey.

The organisational religious activity, non-organisational religious activity, and intrinsic religiosity of parents were significantly related to the care burden and quality of life, and the two dimensions of non-organisational religious activity and intrinsic religiosity of parents were significantly related to their anxiety symptoms. No association was found between parents’ religious beliefs and their depressive symptoms. Among Buddhist parents, non-organisational religious activity and intrinsic religiosity reduced the care burden and improved quality of life. Among Christian parents, organisational religious activity and non-organisational religious activity were found to reduce the care burden, while organisational religious activity and intrinsic religiosity were found to improve quality of life. There was no correlation between the sub-dimensions of religious beliefs and a negative impact on the care process in Muslim parents.

Religious beliefs have a protective effect on the parents of infant patients with CHD. They help relieve parents’ anxiety, reduce their care burden, and improve their quality of life. In addition, different religious beliefs have different dimensions of influence on caregivers.

To explore the feasibility and superiority of applying the WeChat platform in a midterm follow-up of surgical repair for ventricular septal defects in infants.

Eighty-six infants with VSD who underwent surgical repair were divided into an outpatient follow-up group and a WeChat follow-up group. The clinical data, including complications, economic cost, time spent, loss to follow-up rate, and parents’ satisfaction at the 3-month and 1-year follow-ups, were recorded and analysed.

There was no significant difference in the incidence of post-operative complications between the two groups. Although the loss to follow-up rate in the WFU group was lower than that of the OFU group, the difference was not statistically significant. The economic cost and time spent in the 3 months and 1 year after discharge in the WFU group were significantly lower than those in the OFU group. One year after discharge, the PSQ-18 score of the WFU group was significantly higher than that of the OFU group.

Compared with outpatient follow-up, the WeChat platform at the midterm follow-up after surgical repair of VSDs in infants has the advantages of saving time and economic costs and improves parents’ satisfaction.

To investigate the safety and feasibility of midazolam for conscious sedation in transcatheter device closure of atrial septal defects guided solely by transthoracic echocardiography.

A retrospective analysis was performed on 55 patients who underwent transcatheter device closure of atrial septal defects from October, 2019 to May, 2020. All patients received intravenous midazolam and local anesthesia with lidocaine to maintain sedation. A group of previous patients with unpublished data who underwent the same procedure with general anesthesia was set as the control group. The relevant clinical parameters, the Ramsay sedation scores, the numerical rating scale, and the post-operative satisfaction questionnaire were recorded and analyzed.

In the midazolam group, the success rate of atrial septal defect closure was 98.2%. Hemodynamic stability was observed during the procedure. None of the patients needed additional endotracheal intubation for general anesthesia. Compared with the control group, the midazolam group had no statistically significant differences in the Ramsay sedation score and numerical rating scale scores. Patients in the midazolam group experienced more post-operative satisfaction than those in the control group.

Conscious sedation using midazolam is a safe and effective anesthetic technique for transcatheter device closure of atrial septal defects guided solely by transthoracic echocardiography.

This study explored the clinical effect of employing breast milk oral care for infants who underwent surgical correction of ventricular septal defect.

A prospective randomised controlled study was conducted in a provincial hospital between January, 2020 and July, 2020 in China. Patients were randomly divided into an intervention group (breast milk oral care, n = 28) and a control group (physiological saline oral care, n = 28). The intervention group was given oral nursing using breast milk for infants in the early post-operative period, and the control group was given oral nursing using physiological saline. Related clinical data were recorded and analysed.

There were no significant differences in age, gender, weight, operation time, cardiopulmonary bypass time, or aortic cross-clamping time between the two groups. Compared with the physiological saline oral care group, the mechanical ventilation duration, the length of ICU stay in the breast milk oral care group were significantly shorter. The time of start feeding and total enteral nutrition were significantly earlier in the intervention group than those in the control group. The incidence of post-operative pneumonia in the breast milk oral care group was 3.6%, which was significantly lower than that of the physiological saline oral care group.

The use of breast milk for oral care in infants who underwent surgical correction of VSD can reduce the incidence of post-operative pneumonia and promote the recovery of gastrointestinal function.

Pulmonary arterial hypertension symptoms in systemic lupus erythematosus patients are non-specific and early diagnosis and intervention are challenging. It remains essential to explore risk factors for pulmonary arterial hypertension in systemic lupus erythematosus patients to identify high risk patients and allow intensive monitoring.

From January 2010 to December 2018, 84 patients with systemic lupus erythematosus and pulmonary arterial hypertension and 160 patients with systemic lupus erythematosus but without pulmonary arterial hypertension were enrolled. Clinical manifestations and laboratory test results were compared between the two groups to identify predictors of pulmonary arterial hypertension. Candidate pulmonary arterial hypertension risk factors were further compared among systemic lupus erythematosus-pulmonary arterial hypertension patients with different characteristics.

Among collected patient characteristics, Raynaud’s phenomenon (OR 2.32, 95% CI: 1.17–4.61), digital vasculitis (OR 4.12, 95% CI: 1.48–11.49), pericardial effusion, pulmonary interstitial lesions, positive anti-u1 ribonucleoprotein antibodies, and positive anticardiolipin antibodies immunoglobulin G were associated with significantly higher risk of pulmonary arterial hypertension in systemic lupus erythematosus patients. Among these candidate risk factors, positive anti-u1 ribonucleoprotein antibody was independently associated with severe pulmonary arterial hypertension and more active disease. Digital vasculitis was independently associated with systemic lupus erythematosus alleviation, while pericardial effusion was associated with systemic lupus erythematosus deterioration. Pericardial effusion was associated with longer pulmonary arterial hypertension duration.

The significant association between studied clinical and laboratory indicators and risk of pulmonary arterial hypertension, pulmonary arterial hypertension and systemic lupus erythematosus characteristics suggested that these factors can be used to identify patients at higher risk of pulmonary arterial hypertension and adverse outcomes. Close monitoring may be indicated in patients with these risk factors, especially with more than one risk factor.

The current study evaluated the associations between different forms and sources of Fe and breast cancer risk in Southern Chinese women.

Case–control study. We collected data on the consumption of Fe from different forms and food sources by using a validated FFQ. Multivariable logistic regression and restricted cubic spline (RCS) analysis was used to reveal potential associations between Fe intake and breast cancer risk.

A case-control study of women at three major hospitals in Guangzhou, China.

From June 2007 to March 2019, 1591 breast cancer cases and 1622 age-matched controls were recruited.

In quartile analyses, Fe from plants and Fe from white meat intake were inversely associated with breast cancer risk, with OR of 0·65 (95 % CI 0·47, 0·89, Ptrend = 0·006) and 0·76 (95 % CI 0·61, 0·96, Ptrend = 0·014), respectively, comparing the highest with the lowest quartile. No associations were observed between total dietary Fe, heme or non-heme Fe, Fe from meat or red meat and breast cancer risk. RCS analysis demonstrated J-shaped associations between total dietary Fe, non-heme Fe and breast cancer, and reverse L-shaped associations between heme Fe, Fe from meat and Fe from red meat and breast cancer.

Fe from plants and white meat were inversely associated with breast cancer risk. Significant non-linear J-shaped associations were found between total dietary Fe, non-heme Fe and breast cancer risk, and reverse L-shaped associations were found between heme Fe, Fe from meat or red meat and breast cancer risk.