[Association Between Medication Compliance and Various Risky Behaviors in Patients With Schizophrenia]. / ç²¾ç¥žåˆ†è£‚ç—‡æ‚£è€ æœè¯ä¾ä»Žæ€§ä¸Žä¸åŒç±»åž‹å±é™©è¡Œä¸ºçš„å ³è”ç ”ç©¶.

Objective: To investigate the status of medication adherence and various types of risky behaviors of schizophrenia patients in a certain area of western China and to explore accordingly the correlation between the two. Methods: A total of 292 667 patients with schizophrenia were enrolled in a follow-up survey between 2006 and 2018. In addition, based on the outcome-wide analysis strategy, a multivariate Cox proportional risk regression model was used to estimate and compare the impact of medication adherence on different types of risky behaviors in schizophrenia patients. Results: In this 13-year prospective cohort, 65 175 patients (31.4%) showed good medication adherence, while 142 394 patients (68.6%) showed poor medication adherence. The incidence rates of various risky behaviors during the follow-up period were as follows, minor nuisances, 12.25%, violation of the Law of the People's Republic of China on Penalties for Administration of Public Security (APS law), 3.82%, violation of criminal law, 0.94%, suicide completed, 0.28%, self-harm, 1.42%, and attempted suicide, 0.82%. Schizophrenia patients who had poor medication adherence had higher risks of committing violence against others and self-inflicted injury compared to patients with good medication adherence did, with the associated effects being minor nuisances (hazard ratio [HR]=1.31, 95% confidence interval [CI]: 1.27-1.35), violation of APS law (HR=1.47, 95% CI: 1.38-1.56), violation of criminal law (HR=1.17, 95% CI: 1.05-1.31), and self-harm (HR=1.43, 95% CI: 1.32-1.56), respectively, while the risk of suicide completed is lower in schizophrenia patients with poor medication adherence than that in patients with good medication adherence (HR=0.56, 95% CI: 0.47-0.66). There was no statistically significant association between attempted suicide and medication adherence. Conclusion: There are variations in the direction and strength of the association between medication adherence and different types of risky behaviors and further research is needed to elucidate the mechanisms of the association.

COVID-19 distributes socially in China: A Bayesian spatial analysis.

PURPOSE: The ongoing coronavirus disease 2019 (COVID-19) epidemic increasingly threatens the public health security worldwide. We aimed to identify high-risk areas of COVID-19 and understand how socioeconomic factors are associated with the spatial distribution of COVID-19 in China, which may help other countries control the epidemic. METHODS: We analyzed the data of COVID-19 cases from 30 provinces in mainland China (outside of Hubei) from 16 January 2020 to 31 March 2020, considering the data of demographic, economic, health, and transportation factors. Global autocorrelation analysis and Bayesian spatial models were used to present the spatial pattern of COVID-19 and explore the relationship between COVID-19 risk and various factors. RESULTS: Global Moran's I statistics of COVID-19 incidences was 0.31 (P<0.05). The areas with a high risk of COVID-19 were mainly located in the provinces around Hubei and the provinces with a high level of economic development. The relative risk of two socioeconomic factors, the per capita consumption expenditure of households and the proportion of the migrating population from Hubei, were 1.887 [95% confidence interval (CI): 1.469~2.399] and 1.099 (95% CI: 1.053~1.148), respectively. The two factors explained up to 78.2% out of 99.7% of structured spatial variations. CONCLUSION: Our results suggested that COVID-19 risk was positively associated with the level of economic development and population movements. Blocking population movement and reducing local exposures are effective in preventing the local transmission of COVID-19.

What are the risk factors of hospital length of stay in the novel coronavirus pneumonia (COVID-19) patients? A survival analysis in southwest China.

BACKGROUND: The global epidemic of novel coronavirus pneumonia (COVID-19) has resulted in substantial healthcare resource consumption. Since patients' hospital length of stay (LoS) is at stake in the process, an investigation of COVID-19 patients' LoS and its risk factors becomes urgent for a better understanding of regional capabilities to cope with COVID-19 outbreaks. METHODS: First, we obtained retrospective data of confirmed COVID-19 patients in Sichuan province via National Notifiable Diseases Reporting System (NNDRS) and field surveys, including their demographic, epidemiological, clinical characteristics and LoS. Then we estimated the relationship between LoS and the possibly determinant factors, including demographic characteristics of confirmed patients, individual treatment behavior, local medical resources and hospital grade. The Kaplan-Meier method and the Cox Proportional Hazards Model were applied for single factor and multi-factor survival analysis. RESULTS: From January 16, 2020 to March 4, 2020, 538 human cases of COVID-19 infection were laboratory-confirmed, and were hospitalized for treatment, including 271 (50%) patients aged ≥ 45, 285 (53%) males, and 450 patients (84%) with mild symptoms. The median LoS was 19 (interquartile range (IQR): 14-23, range: 3-41) days. Univariate analysis showed that age and clinical grade were strongly related to LoS (P<0.01). Adjusted multivariate analysis showed that the longer LoS was associated with those aged ≥ 45 (Hazard ratio (HR): 0.74, 95% confidence interval (CI): 0.60-0.91), admission to provincial hospital (HR: 0.73, 95% CI: 0.54-0.99), and severe illness (HR: 0.66, 95% CI: 0.48-0.90). By contrast, the shorter LoS was linked with residential areas with more than 5.5 healthcare workers per 1,000 population (HR: 1.32, 95% CI: 1.05-1.65). Neither gender factor nor time interval from illness onset to diagnosis showed significant impact on LoS. CONCLUSIONS: Understanding COVID-19 patients' hospital LoS and its risk factors is critical for governments' efficient allocation of resources in respective regions. In areas with older and more vulnerable population and in want of primary medical resources, early reserving and strengthening of the construction of multi-level medical institutions are strongly suggested to cope with COVID-19 outbreaks.