Introduction: Factors influencing healthcare utilization in China have been frequently analyzed and discussed from various angles, based upon different objectives. However, few studies have attempted to categorize and summarize key determinants of healthcare utilization in China. Methods: To fill this gap, we reviewed all empirical studies that made use of data from the China Health and Nutrition Survey (CHNS), a longitudinal survey covering nine Chinese provinces for nearly three decades. The review was guided by Andersen’s behavioral model, a conceptual framework widely used to analyze determinants of healthcare utilization. Results: Our review discovered many strong and consistent predictors of healthcare utilization at the individual level, including predisposing factors (e.g., marriage status and education), enabling factors (e.g., income and wealth), and need factors (e.g., illness severity and health status); in contrast, contextual factors (e.g., employment rates and population health indices) have rarely been examined. Our review also revealed a few factors whose impacts differ from expectations in many studies (e.g., employment status and health insurance coverage). While several factors explored in the reviewed studies (e.g., urbanization and industrialization) are not part of Andersen’s model, some factors specified in the model (e.g., values and knowledge about health and health services) remain unexplored in the context of China. Conclusion: Individual-level factors received much more attention than contextual-level factors in the reviewed studies. It leads to an inadequate understanding of the roles played by contextual factors. Among the individual-level factors that have been extensively examined, enabling variables affect healthcare utilization more than predisposing and need factors.

Background: Fecal microbiota transplantation (FMT) may be helpful in the treatment of autism spectrum disorder (ASD) as rebalancing the gut microbiome has been shown to potentially improve behavioral symptoms in children with ASD.Methods: This systematic review was conducted to assess the effect of FMT for children with ASD. The Embase, PubMed, Web of Science, and Cochrane Library databases were searched for articles published from inception to October 6, 2022. Two reviewers independently screened the identified records and undertook data extraction.Results: The search identified a total of five studies: two prospective open-label studies, two retrospective observational studies, and a case report; however, no randomized controlled trial was identified. All five studies reported a significant post-FMT-treatment improvement in neuropsychological assessment of ASD. The two prospective open-label studies suggested that the Autism Behavior Checklist (ABC) score, and the Social Responsiveness Scale (SRS) score at the posttreatment assessment decreased from the baseline (Wilcoxon signed-rank test; all p < 0.01]). The two retrospective observational studies suggested that FMT helped to improve the ASD symptoms. One observational study reported that the Childhood Autism Rating Scale (CARS) score and ABC score of the constipation group decreased from the baseline after the second course assessment (CARS [baseline: mean 35.25 ± standard deviation 4.36, second course: 32.5 ± 3.1, p = 0.015]; ABC [baseline: 56.21 ± 16.08, second course: 46.54 ± 16.54, p = 0.046]). Another observational study found that both ABC and CARS scores decreased as the number of FMT courses increased, and significant differences were found at the end of each course as compared with the baseline.Conclusion: Compared with the baseline, FMT significantly improved symptoms of autism in children with ASD in observational studies. However, rigorously designed randomized controlled clinical trials are needed to establish the safety and efficacy of FMT as a treatment for ASD.

PTEN hamartoma tumor syndrome (PHTS) is a complex neurodevelopmental disorder characterized by mechanistic target of rapamycin (mTOR) overactivity. Limited data suggest that mTOR inhibitors may be therapeutic. No placebo-controlled studies have examined mTOR inhibition on cognition and behavior in humans with PHTS with/without autism. We conducted a 6-month phase II, randomized, double-blinded, placebo-controlled trial to examine the safety profile and efficacy of everolimus (4.5 mg/m²) in individuals (5–45 years) with PHTS. We measured several cognitive and behavioral outcomes, and electroencephalography (EEG) biomarkers. The primary endpoint was a neurocognitive composite derived from Stanford Binet-5 (SB-5) nonverbal working memory score, SB-5 verbal working memory, Conners’ Continuous Performance Test hit reaction time and Purdue Pegboard Test score. Forty-six participants underwent 1:1 randomization: n = 24 (everolimus) and n = 22 (placebo). Gastrointestinal adverse events were more common in the everolimus group (P < 0.001). Changes in the primary endpoint between groups from baseline to Month 6 were not apparent (Cohen’s d = −0.10, P = 0.518). However, several measures were associated with modest effect sizes (≥0.2) in the direction of improvement, including measures of nonverbal IQ, verbal learning, autism symptoms, motor skills, adaptive behavior and global improvement. There was a significant difference in EEG central alpha power (P = 0.049) and central beta power (P = 0.039) 6 months after everolimus treatment. Everolimus is well tolerated in PHTS; adverse events were similar to previous reports. The primary efficacy endpoint did not reveal improvement. Several secondary efficacy endpoints moved in the direction of improvement. EEG measurements indicate target engagement following 6 months of daily oral everolimus. Trial Registration Information: ClinicalTrials.gov NCT02991807 Classification of Evidence: I.

Standard deviation (SD) and standard error of the mean (SEM) have been applied widely as error bars in scientific plots. Unfortunately, there is no universally accepted principle addressing which of these 2 measures should be used. Here we seek to fill this gap by outlining the reasoning for choosing SEM over SD and hope to shed light on this unsettled disagreement among the biomedical community. The utility of SEM and SD as error bars is further discussed by examining the figures and plots published in 2 research articles on pancreatic disease.

The purpose of this study was to present the design, model, and data analysis of an interrupted time series (ITS) model applied to evaluate the impact of health policy, systems, or environmental interventions using count outcomes. Simulation methods were used to conduct power and sample size calculations for these studies. We proposed the models and analyses of ITS designs for count outcomes using the Strengthening Translational Research in Diverse Enrollment (STRIDE) study as an example. The models we used were observation-driven models, which bundle a lagged term on the conditional mean of the outcome for a time series of count outcomes. A simulation-based approach with ready-to-use computer programs was developed to calculate the sample size and power of two types of ITS models, Poisson and negative binomial, for count outcomes. Simulations were conducted to estimate the power of segmented autoregressive (AR) error models when autocorrelation ranged from -0.9 to 0.9, with various effect sizes. The power to detect the same magnitude of parameters varied largely, depending on the testing level change, the trend change, or both. The relationships between power and sample size and the values of the parameters were different between the two models. This article provides a convenient tool to allow investigators to generate sample sizes that will ensure sufficient statistical power when the ITS study design of count outcomes is implemented.