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Background: Visuospatial dysfunction and cognitive impairment are common in Parkinson's disease (PD), which draw increasing attention in the current literature. But clinicians still lack rapid, effective and unified cognitive battery for visuospatial assessment. Objective: A new approach was studied to explore the feasibility of using mobile application software (APP) to evaluate visuospatial dysfunction in patients with PD and compared with traditional assessment tools. We aimed to verify the threshold score of the APP for early diagnosis. Materials and methods: A total of 41 patients with PD underwent assessments using several test modules including Digit Symbol Test (DST), Visual Organization Test (VOT), Facial Recognition Test (FRT), Vocabulary Memory Test (VMT) of this APP, as well as Clock Drawing Test (CDT), Cube Copying Test (CCT) and the Mini-Mental State Examination (MMSE) for comparison. Among the 41 PD patients, 30 individuals were found to have visuospatial dysfunction based on CDT score < 5 and CCT score of<18 while the remaining 11 patients served as control. Results: There were statistically significant differences in DST, VOT, and FRT scores (all p ≤ 0.001 for group comparisons). DST, VOT, and FRT-1 were significantly correlated with MMSE, CDT and CCT and the correlations were moderate or fairly strong. For visuospatial dysfunction diagnosis, all the areas under curves (AUC) of DST, VOT, and FRT-1 were statistically significant (p < 0.0001, p = 0.0002, and p = 0.0002, respectively). The estimates and 95% confidence intervals of AUC were 0.8303 (0.6868, 0.9739), 0.8045 (0.6423, 0.9668), and 0.7833 (0.6344, 0.9322), respectively. Their cut-off points for visuospatial dysfunction were 26, 17, and 19, respectively. After dichotomization by the cut-off points, DST had high sensitivity of 96.67% while VOT and FRT-1 had high specificity of 81.82 and 90.91%. Conclusion: This study demonstrated that visuospatial disorders was highly prevalent in PD patients, and the APP used in study could be a practical clinical screening tool for visuospatial ability assessment with high sensitivity and specificity.
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BACKGROUND: Prediabetes risk assessment models derived from large sample sizes are scarce. AIM: To establish a robust assessment model for prediabetes and to validate the model in different populations. METHODS: The China National Diabetes and Metabolic Disorders Study (CNDMDS) collected information from 47325 participants aged at least 20 years across China from 2007 to 2008. The Thyroid Disorders, Iodine Status and Diabetes Epidemiological Survey (TIDE) study collected data from 66108 participants aged at least 18 years across China from 2015 to 2017. A logistic model with stepwise selection was performed to identify significant risk factors for prediabetes and was internally validated by bootstrapping in the CNDMDS. External validations were performed in diverse populations, including populations of Hispanic (Mexican American, other Hispanic) and non-Hispanic (White, Black and Asian) participants in the National Health and Nutrition Examination Survey (NHANES) in the United States and 66108 participants in the TIDE study in China. C statistics and calibration plots were adopted to evaluate the model's discrimination and calibration performance. RESULTS: A set of easily measured indicators (age, education, family history of diabetes, waist circumference, body mass index, and systolic blood pressure) were selected as significant risk factors. A risk assessment model was established for prediabetes with a C statistic of 0.6998 (95%CI: 0.6933 to 0.7063) and a calibration slope of 1.0002. When externally validated in the NHANES and TIDE studies, the model showed increased C statistics in Mexican American, other Hispanic, Non-Hispanic Black, Asian and Chinese populations but a slightly decreased C statistic in non-Hispanic White individuals. Applying the risk assessment model to the TIDE population, we obtained a C statistic of 0.7308 (95%CI: 0.7260 to 0.7357) and a calibration slope of 1.1137. A risk score was derived to assess prediabetes. Individuals with scores ≥ 7 points were at high risk of prediabetes, with a sensitivity of 60.19% and specificity of 67.59%. CONCLUSION: An easy-to-use assessment model for prediabetes was established and was internally and externally validated in different populations. The model had a satisfactory performance and could screen individuals with a high risk of prediabetes.
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Background The Caprini Risk Score (CRS) is one of the most widely used risk assessment models for venous thromboembolism (VTE). A well-validated patient-completed CRS form may allow patients to self-report and simplify the evaluation by health care workers. Methods The Chinese version of the CRS was optimized for easy understanding in a pilot study. The amended CRS form was completed by prospectively recruited patients and blinded nurses. The agreement levels of the individual questions and the total scores of patient and nurse-completed forms were compared using the Kappa value. The total scores were used for risk stratification of patients. Correlation and differences between patient and nurse-completed forms were analyzed using the Spearman correlation and Bland-Altman method, respectively. Results We recruited 504 medical patients and 513 surgical patients, aged 52.7 ± 16.3 years, of which 443 (43.6%) were men, and 91.6% of the patients were educated beyond junior high school. The patients spent less time to complete the form compared with trained nurses. There was good question-to-question agreement between patient and nurse-completed CRS ( k >0.6 for most questions, p < 0.0001). The total scores also showed good agreement ( k = 0.6097, p < 0.0001), and enabled the classification of patients into different risk groups. The patient and nurse-derived scores were highly correlated (Spearman's r = 0.84), and without extreme values ( p < 0.0001). Conclusion We have created and verified a Chinese version of the patient-completed CRS, which showed good agreement and correlation with nurse-completed CRS. CRS represents a suitable tool for VTE risk assessment of hospitalized patients in China.
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Background: To explore the feasibility and effectiveness of multifaceted quality improvement intervention based on the clinical decision support system (CDSS) in VTE prophylaxis in hospitalized patients. Methods: A randomized, department-based clinical trial was conducted in the department of respiratory and critical care medicine, orthopedic, and general surgery wards. Patients aged ≥18 years, without VTE in admission, were allocated to the intervention group and received regular care combined with multifaceted quality improvement intervention based on CDSS during hospitalization. VTE prophylaxis rate and the occurrence of hospital-associated VTE events were analyzed as primary and secondary outcomes. Results: A total of 3644 eligible residents were enrolled in this trial. With the implementation of the multifaceted quality improvement intervention based on the CDSS, the VTE prophylaxis rate of the intervention group increased from 22.93% to 34.56% (p < 0.001), and the incidence of HA-VTE events increased from 0.49% to 1.00% (p = 0.366). In the nonintervention group, the VTE prophylaxis rate increased from 24.49% to 27.90% (p = 0.091), and the incidence of HA-VTE events increased from 0.47% to 2.02% (p = 0.001). Conclusions: Multifaceted quality improvement intervention based on the CDSS strategy is feasible and expected to facilitate implementation of the recommended VTE prophylaxis strategies and reduce the incidence of HA-VTE in hospital. However, it is necessary to conduct more multicenter clinical trials in the future to provide more reliable real-world evidence.
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OBJECTIVES: To identify spatial disparities and demographic characteristics of short stature, we analysed the prevalence of short stature collected in a nationwide health survey. SETTINGS: Data were obtained from the 2014 Chinese National Survey on Students Constitution and Health (a cross-sectional study of China). Participants came from 30 provinces, autonomous regions, and municipalities (except Tibet, Hong Kong, Macao, and Taiwan). PARTICIPANTS: There were 213 795 Han school children between 7 and 18 years old enrolled in our study. All participants were sampled by stratified cluster. PRIMARY AND SECONDARY OUTCOME MEASURES: Short stature; Chinese and WHO age-specific and gender-specific height growth references were used for short stature assessment. RESULTS: The age-standardised and age-gender-standardised prevalence of short stature nationwide was 3.70% and 2.69% according to Chinese and WHO growth references, respectively. The short stature prevalence differed significantly among age groups, urban and rural areas, and regions with different socioeconomic development levels (all p<0.0001). The prevalence was 2.23% in urban versus 5.12% in rural areas (p<0.001). The prevalence was 2.60% in developed, 3.72% in intermediately developed, and 4.69% in underdeveloped regions (p<0.0001). These values were all according to China's growth reference, but similar patterns were observed on prevalence based on the WHO reference. The spatial distribution of prevalence of short stature presented a clustered pattern. Moran's I value was 0.474 (p<0.001) and 0.478 (p<0.001) according to the Chinese and WHO growth references, respectively. The southwest part of China showed a higher prevalence of short stature, whereas lower prevalence of short stature was observed mainly in the northeast part of China. CONCLUSIONS: There is an appreciably high prevalence of short stature in rural, underdeveloped areas of China. There are high prevalence spatial clusters of short stature in southwestern China. This provides corroborating evidence for a tailored strategy on short stature prevention and reduction in special areas.