Influencing factors of delay in seeking medical attention of patients with obstructive sleep apnea based on the Model of Pathways to Treatment in China: a qualitative analysis.

BACKGROUND: There is the highest estimated number of patients with obstructive sleep apnea (OSA) in China. Early treatment could lead to fewer complications associated with OSA. This study aimed to analyze the factors influencing help-seeking from the first symptom discovery to treatment in OSA. METHODS: Semi-structured interview outline was designed to conduct face-to-face interview based on the analyses of a great number of related literatures on the delay in seeking medical attention of patients with OSA. 15 patients diagnosed were interviewed between June 2021 to September 2022 in general hospital of Shenyang, Northeastern of China. Qualitative data was analyzed by content analysis using the Model of Pathways to Treatment. RESULTS: Analyses identified factors contributing to elapsed time from first symptom discovery to received treatment that are linked to disease characteristic, patients, health system organization. Appraisal interval is most obvious for patients with OSA, but it is difficult to pinpoint precisely because the patients didn't remember exactly when the first symptom was detected. CONCLUSIONS: Patients diagnosed with OSA didn't initially interpret the snore as a warning sign and even thought it was a blessing. The findings provided guidance or avenues for reducing elapsed time between the first symptom and received treatment.

Development of a Health Behavioral Digital Intervention for Patients With Hypertension Based on an Intelligent Health Promotion System and WeChat: Randomized Controlled Trial.

BACKGROUND: The effectiveness of timely medication, physical activity (PA), a healthy diet, and blood pressure (BP) monitoring for promoting health outcomes and behavioral changes among patients with hypertension is supported by a substantial amount of literature, with "adherence" playing a pivotal role. Nevertheless, there is a lack of consistent evidence regarding whether digital interventions can improve adherence to healthy behaviors among individuals with hypertension. OBJECTIVE: The aim was to develop a health behavioral digital intervention for hypertensive patients (HBDIHP) based on an intelligent health promotion system and WeChat following the behavior change wheel (BCW) theory and digital micro-intervention care (DMIC) model and assess its efficacy in controlling BP and improving healthy behavior adherence. METHODS: A 2-arm, randomized trial design was used. We randomly assigned 68 individuals aged >60 years with hypertension in a 1:1 ratio to either the control or experimental group. The digital intervention was established through the following steps: (1) developing digital health education materials focused on adherence to exercise prescriptions, Dietary Approaches to Stop Hypertension (DASH), prescribed medication, and monitoring of BP; (2) using the BCW theory to select behavior change techniques; (3) constructing the intervention's logic following the guidelines of the DMIC model; (4) creating an intervention manual including the aforementioned elements. Prior to the experiment, participants underwent physical examinations at the community health service center's intelligent health cabin and received intelligent personalized health recommendations. The experimental group underwent a 12-week behavior intervention via WeChat, while the control group received routine health education and a self-management manual. The primary outcomes included BP and adherence indicators. Data analysis was performed using SPSS, with independent sample t tests, chi-square tests, paired t tests, and McNemar tests. A P value <.05 was considered statistically significant. RESULTS: The final analysis included 54 participants with a mean age of 67.24 (SD 4.19) years (n=23 experimental group, n=31 control group). The experimental group had improvements in systolic BP (-7.36 mm Hg, P=.002), exercise time (856.35 metabolic equivalent [MET]-min/week, P<.001), medication adherence (0.56, P=.001), BP monitoring frequency (P=.02), and learning performance (3.23, P<.001). Both groups experienced weight reduction (experimental: 1.2 kg, P=.002; control: 1.11 kg, P=.009) after the intervention. The diet types and quantities for both groups (P<.001) as well as the subendocardial viability ratio (0.16, P=.01) showed significant improvement. However, there were no statistically significant changes in other health outcomes. CONCLUSIONS: The observations suggest our program may have enhanced specific health outcomes and adherence to health behaviors in older adults with hypertension. However, a longer-term, larger-scale trial is necessary to validate the effectiveness. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200062643; https://www.chictr.org.cn/showprojEN.html?proj=172782. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/46883.

Ankle reflex and neurological symptom score: a primary level screening method for diabetic peripheral neuropathy.

Herein, we aimed to develop an easily available and efficient screening method for diabetic peripheral neuropathy (DPN) suitable for primary care settings, emphasizing simplicity, speed, and accuracy. Nerve conduction studies were conducted on 214 patients with diabetes, encompassing the outcomes of five distinct assessments: diabetic neuropathy symptom (DNS), vibration perception threshold (VPT), and nerve screening. The diagnostic accuracy of the VPT and nerve screening was evaluated by comparing them with that of the nerve conduction study. To assess diagnostic efficacy, various combinations were examined, including DNS combined with VPT, pain, temperature, touch, and ankle reflex. The diagnostic performance of DNS was superior to that of the five neurological screening items and VPT, with sensitivity, specificity, and accuracy of 0.68, 0.81, and 0.73, respectively. Among the two combined methods, "DNS + ankle reflex" was identified as having the highest diagnostic value, with an area under the curve, a sensitivity, a specificity, and an accuracy of 0.81, 0.89, 0.70, and 0.80, respectively. Furthermore, a combination of "DNS + ankle reflex + touch + pain + VPT" achieved the best performance among the five combinations, with an area under the curve, sensitivity, specificity, and accuracy of 0.85, 0.93, 0.68, and 0.81, respectively. The combination of DNS, ankle reflex, touch, pain, and VPT methods showed the highest diagnostic value for DPN. However, considering factors including accuracy, time, and economic cost, we recommend using a simpler combination of DNS and ankle reflex for large-scale screening of patients with DPN.

A Service-Learning Project Based on a Community-Oriented Intelligent Health Promotion System for Postgraduate Nursing Students: Mixed Methods Study.

BACKGROUND: Service learning (SL) is a pedagogical approach that combines community service with cognitive learning for professionals. Its efficacy in promoting community health has gained broad recognition in nursing education. The application of postgraduate nursing SL programs in community-based intelligent health remains underexplored. Thus, additional investigation is necessary to assess the influence of the SL project based on a community-oriented intelligent health promotion system (SLP-COIHPS) on postgraduate nursing students and health service recipients. OBJECTIVE: This study aims to assess how SLP-COIHPS influences the scientific awareness and research innovation abilities of postgraduate nursing students. In addition, the study sought to examine the experiences of both participating students and health service recipients. METHODS: We conducted a mixed methods investigation by using web-based surveys and conducting interviews. The web-based surveys aimed to explore the differences in scientific awareness and research innovation capabilities between 2 distinct groups: an experimental group of 23 postgraduate nursing students actively participated in SLP-COIHPS, while 23 postgraduate students (matched one-to-one with the experimental group in terms of grade, sex, and research methods) served as control participants. Semistructured interviews were conducted with 65% (15/23) of postgraduate students and 3% (12/405) of community residents who received health services, aiming to assess the project's impact on them. The community-based intelligent health promotion system installed in intelligent health cabins can be conceptualized as an expert system providing valuable references for student health education. It has the capability to generate comprehensive assessments and personalized health guidance plans. Following training, students were involved in offering health assessments, health education, and related services. Subsequently, after the web-based surveys and semistructured interviews, quantitative data were analyzed using the SPSS (IBM Corp) software package, using 2-tailed t tests and Mann-Whitney U tests; qualitative data underwent analysis using the constructivist grounded theory approach. RESULTS: Postgraduate nursing students participating in this program scored 12.83 (Cohen d>0.8; P<.001) and 10.56 (Cohen d>0.8; P=.004) points higher than postgraduate students in the control group in research awareness and research innovation capability, respectively. On the basis of the qualitative results, postgraduate students reported improvement in this program. Analysis of the interviews revealed a total of 12 subcategories across three primary domains: (1) specialized skills, (2) scientific research ability, and (3) comprehensive qualities. Community residents reported high satisfaction and positive experiences. Analysis of the interviews with community residents identified two primary categories: (1) satisfaction and (2) perceived benefits. CONCLUSIONS: SLP-COIHPS had a positive impact on students' development of scientific awareness and research innovation ability. Qualitative study findings also support the further development of practical programs that integrate intelligent health and SL theories in the field of medical education. This includes exploring the potential factors influencing postgraduate nursing students' research capabilities or investigating the long-term effects of the project.

Evaluating a WeChat-Based Health Behavioral Digital Intervention for Patients With Hypertension: Protocol for a Randomized Controlled Trial.

BACKGROUND: Hypertension is the most prevalent chronic condition and a significant risk factor for cardiovascular and kidney diseases. The efficacy of health behavioral interventions in blood pressure (BP) control has been demonstrated by a large and expanding body of literature, with "adherence" playing a crucial role. WeChat is the most common social communication mobile app in China, and it has been shown to be an acceptable delivery platform for delivering health interventions. The WeChat-based health behavioral digital intervention program (WHBDIP) showed high feasibility and efficacy. However, the results regarding BP improvement between the WHBDIP and control groups were inconsistent. OBJECTIVE: The objective of this study is to develop a WHBDIP and assess its efficacy in controlling BP and improving adherence among patients with hypertension. METHODS: A 2-arm, parallel-group, and randomized trial design was used. Patients older than 60 years and with hypertension were randomly assigned to either the control group or the experimental group, which received a 12-week intervention. The program, primarily developed based on the Behavior Change Wheel (BCW) theory, offers health education on exercise, diet, BP monitoring, and medicine adherence (MA). It also includes other behavior interventions guided by an intervention manual, incorporating behavior change techniques (BCTs). The primary outcomes encompass BP and adherence indicators, while the secondary outcomes encompass cardiovascular function indicators, body composition indicators, learning performance, satisfaction, and acceptability. The exercise and blood pressure monitoring adherence (BPMA) indicators for the WHBDIP group were assessed weekly via WeChat during the initial 3 months, while other outcome data for both groups will be collected at the baseline assessment phase, 3 months after the intervention, and 1 year after the program. RESULTS: The trial will assess the efficacy of WHBDIP for patients with hypertension (N=68). The WHBDIP seeks to enhance participants' knowledge of healthy behaviors and assist patients in developing positive health behaviors to improve their health outcomes. Patient recruitment for individuals with hypertension commenced on September 5, 2022, and concluded on September 19, 2022. The 3-month intervention and phased data collection were finalized in January 2023. Data analysis will commence in August 2023, and the final 1-year health outcome results will be collected in September 2023. CONCLUSIONS: A successful WHBDIP will establish the management mode as a feasible approach for hypertension management in the community. Additionally, it will pave the way for the development of related mobile health programs. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200062643; https://tinyurl.com/mwyv67wk. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/46883.

Machine learning models for diabetic neuropathy diagnosis using microcirculatory parameters in type 2 diabetes patients.

BACKGROUND: Diabetic peripheral neuropathy (DPN) is a primary cause of diabetic foot, early detection of DPN is essential. This study aimed to construct a machine learning model for DPN diagnosis based on microcirculatory parameters, and identify the most predictive parameters for DPN. METHODS: Our study involved 261 subjects, including 102 diabetics with neuropathy (DMN), 73 diabetics without neuropathy (DM), and 86 healthy controls (HC). DPN was confirmed by nerve conduction velocity and clinical sensory tests. Microvascular function was measured by postocclusion reactive hyperemia (PORH), local thermal hyperemia (LTH), and transcutaneous oxygen pressure (TcPO2). Other physiological information was also investigated. Logistic regression (LR) and other machine learning (ML) algorithms were used to develop the model for DPN diagnosis. Kruskal-Wallis Test (non-parametric) were performed for multiple comparisons. Several performance measures, such as accuracy, sensitivity and specificity, were used to access the efficacy of the developed model. All the features were ranked based on the importance score to find features with higher DPN predictions. RESULTS: There was an overall decrease in microcirculatory parameters in response to PORH and LTH, as well as TcPO2, in DMN group compared to DM group and HC group. Random forest (RF) was found to be the best model, and achieved 84.6% accuracy along with 90.2% sensitivity and 76.7% specificity. RF_PF% of PORH was the main predictor of DPN. In addition, diabetic duration was also an important risk factor. CONCLUSIONS: PORH Test is a reliable screening tool for DPN, which can accurately distinguish DPN from diabetics using RF.

Modeling of the Rating of Perceived Exertion Based on Heart Rate Using Machine Learning Methods.

Rating of perceived exertion (RPE) can serve as a more convenient and economical alternative to heart rate (HR) for exercise intensity control. This study aims to explore the influence of factors, such as indicators of demographic, anthropometric, body composition, cardiovascular function and basic exercise ability on the relationship between HR and RPE, and to develop the model predicting RPE from HR. 48 healthy participants were recruited to perform an incrementally 6-stage pedaling test. HR and RPE were collected during each stage. The influencing factors were identified with the forward selection method to train Gaussian Process regression (GPR), support vector machine (SVM) and linear regression models. Metrics of R2, adjusted R2 and RMSE were calculated to evaluate the performance of the models. The GPR model outperformed the SVM and linear regression models, and achieved an R2 of 0.95, adjusted R2 of 0.89 and RMSE of 0.52. Indicators of age, resting heart rate (RHR), Central arterial pressure (CAP), body fat rate (BFR) and body mass index (BMI) were identified as factors that best predicted the relationship between RPE and HR. It is possible to use GPR model to estimate RPE from HR accurately, after adjusting for age, RHR, CAP, BFR and BMI.

Exercise Intervention Based on Behavioral Change Theory: Influence on Body Morphology and Body Composition.

Context: Increased sedentary time and insufficient physical activity have become independent risk factors for chronic diseases. An exercise intervention can focus on increasing an individual's amount of exercise to change his or her body shape and body composition. No studies have occurred to find out if any relationships exist between the amount of exercise and body shape and body composition. Objective: The research team intended to determine an effective way of improving an individual's body shape and composition and to analyze the relationship between moderate-to-vigorous physical activity (MVPA) and body shape and composition. Design: This study used the method of Pre- and post-control experiments. Setting: The study took place at the Science Island Health Promotion Demonstration and Application Center in Hefei, People's Republic of China. Participants: Participants were 62 community residents at the center, aged 20-60 years. Of them, 46 completed the study, and their data were analyzed. Intervention: The exercise prescriptions were based on each participants' stage, as defined by the Transtheoretical Model of Behavior Change (TTM) theory: pre-intention, intention, preparation, action, or maintenance. The exercises were recommended according to each participant's physical condition, with targeted exercise-technique instructions and methods of prevention of exercise injuries being given for each exercise prescription. Outcome Measures: At baseline and post-intervention, the research team measured body weight, waist-to-hip ratio, abdominal-fat weight, body mass index (BMI), body-fat weight, body-fat percentage, muscle weight, and muscle percentage. Results: Significant reductions in participants' body weights and abdominal-fat weights occurred between baseline and postintervention, with P = .00 and P < .01, respectively, and while their waist-to-hip ratios decreased, the difference wasn't significant. Participants' body compositions significantly improved between baseline and postintervention, with P ≤ .01 for all indices. A positive correlation existed between BMI and body weight and between BMI and abdominal-fat weight, both at baseline and post-intervention, with P < .01 for all correlations, but no correlation existed between BMI and the waist-hip ratio at either time. At baseline, a positive correlation existed between body-fat weight and body weight (P < .01), but no correlation existed between body-fat percentage and body weight at that time. At baseline, a significant correlation was found between skeletal-muscle weight and body weight and between skeletal-muscle weight and waist-hip ratio with P < .01 for all correlations. No correlation existed between skeletal-muscle weight and abdominal-fat weight at baseline, but a positive correlation was found between skeletal-muscle weight and abdominal-fat weight post-intervention (P < .05). Both at baseline and postintervention, the muscle percentage was negatively correlated with the waist-to-hip ratio and abdominal-fat weight, with P < .01 for all correlations, and no correlation existed between muscle percentage and body weight at either time. Conclusions: The eight-week intervention significantly improved participants' body morphology and had corresponding effects on their body composition. A positive correlation existed between participants' body fat and body shape, and an opposite relationship was found between skeletal muscle and body shape, which could be increased using the intervention. Body fat was the core factor that affected participants' body morphology.

A Randomized Controlled Trial Evaluating the Effect of Tai Chi on the Drug Craving in Women.

This study was conducted in the purpose of investigating the effect of Tai Chi on drug craving for women with drug disorders. One hundred and twelve women were recruited from a drug rehabilitation center in China, and 47 and 48 were finally analyzed in the control group and exercise group, respectively. The exercise group underwent a 3-month Tai Chi training, whereas the control group experienced no exercise intervention during the same time period. The drug craving was measured by the visual analog scale. In data analysis, repeated-measures were utilized to test the differences between the control and exercise group over the course of the experiment time. The mean of the craving score significantly dropped from pre-test (control: mean = 5.38, SD = 3.04; exercise: mean = 4.68, SD = 2.93) to post-test (control: mean = 4.03, SD = 2.73; exercise: mean = 1.91, SD = 1.90) in both groups (control group: t = 3.84, df = 46, p < 0.001; exercise group: t = 5.941, df = 47, p < 0.001), with more decrease witnessed in the exercise group. Repeated-measures analysis with a Huynh-Feldt correction showed the significant effect of time (F = 27.383, p < 0.001) as well as the study group by time interaction (F = 3.52, p = 0.024). Tai Chi can ameliorate the drug craving in women and it could be a supportive treatment for drug addiction.

An XGBoost-based model for assessment of aortic stiffness from wrist photoplethysmogram.

BACKGROUND AND OBJECTIVE: Carotid-femoral pulse wave velocity (cf-PWV) is the gold standard for non-invasive assessment of aortic stiffness. Photoplethysmography used in wearable devices provides an indirect measurement method for cf-PWV. This study aimed to construct a cf-PWV prediction method based on the XGBoost algorithm and wrist photoplethysmogram (wPPG) for the early screening of arteriosclerosis in primary healthcare. METHODS: Data from 210 subjects were used for modeling, and 100 subjects were used as an external validation set. The wPPG pulse waves were filtered by discrete wavelet transform, and various features were extracted from each waveform, including two original indexes. The extraction rate (ER) and Pearson P were calculated to evaluate the applicability of each feature for model training. The magnitude of cf-PWV was predicted by an XGBoost-based model using the selected features and basic physiological parameters (age, sex, height, weight and BMI). The level of aortic stiffness was classified by a 3-classification strategy according to the standard cf-PWV (measured by the Complior device). Bland-Altman plot, Pearson correlation analysis, and accuracy tested performance from two aspects: predicting the magnitude of cf-PWV and classifying the level of aortic stiffness. RESULTS: In the external validation set (n = 100, age range 22-79), 97 subjects obtained features (ER = 97%). The predicted cf-PWV was significantly correlated with the standard cf-PWV (r = 0.927, P < 0.001). The accuracy (AC) of the 3-classification was 85.6%. The interrater agreement for assessing aortic stiffness was at least substantial (quadratically weighted Kappa = 0.833). CONCLUSIONS: The multi-parameter fusion cf-PWV prediction method based on the XGBoost algorithm and wPPG pulse wave analysis proves the feasibility of atherosclerosis screening in wearable devices.

Design and evaluation of an exergame system to assist knee disorders patients' rehabilitation based on gesture interaction.

We designed a knee rehabilitation exercise game (Exergame) for home-based rehabilitation of patients with knee disorders. The system includes three functional components: knee exercise plan formulation, exergame, and exercise feedback. The 3D Human Pose Estimation based on images is used as the gesture interaction to capture the patient's primary joint motion data. We recruited 20 knee osteoarthritis (KOA) to evaluate the system's feasibility and user experience. The physician's group formulated the patient's exercise plans. The average accuracy of motion recognition is 95.2%, indicating that the system can effectively guide rehabilitation training for KOA patients. The results of the UEQ-S questionnaire, namely the practical quality value (1.63 ± 0.85), hedonic quality value (1.75 ± 0.86), and the total value (1.69 ± 0.86) of 20 patients, indicate that the system provides an excellent user experience, which improves the willingness and compliance of the patients for the active exercise. The above evidence confirms that the proposed approach is suitable for Knee disorders rehabilitation exercise and has promising application prospects. Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-022-00189-5.

[Simulation Study on the Influence of Sampling Delay on the Accuracy of Energy Metabolism Measurement].

Indirect energy metabolism measurement is the gold standard for providing nutritional support for critical illness. The accuracy of the measurement data directly affects the outcome of the disease. In order to study the influence of sampling delay on the accuracy of energy metabolism measurement under mechanical ventilation, the Matlab/Simulink platform and respiratory electrical model were used for simulation and quantitative analysis. The results show that the error of indirect energy metabolism measurement increases with the increase of sampling delay, the error of sampling delay in mechanical ventilation mode is larger than that of spontaneous breathing, and the error of sampling delay in PCV mode of mechanical ventilation is larger than that in VCV mode. Therefore, there should be different sampling delay compensation strategies under severe mechanical ventilation and its different control modes.

[Design and Verification of Lung Diffusion Function Detection System].

A lung diffusion function detection system is designed. Firstly, the controllable collection of air, test gas source and calibration gas source was based on single-breath method measurement principle. Secondly, pulmonary diffusing capacity for carbon monoxide (DlCO) was calculated by gas concentration measured by the non-dispersive infrared sensor to measure, the gas flow measured by the differential pressure sensor, and the temperature, humidity and atmospheric pressure sensors to test and evaluate the quantitative detection and evaluation of lung diffusion function. Moreover, a preliminary verification of the lung diffusion function detection system was implemented, and the results showed that the error of the lung carbon monoxide diffusion and the alveolar volume did not exceed 5%. Therefore, the system has high accuracy and is of great value for early screening and accurate assessment of COPD.

Effect of Eight-Month Exercise Intervention on Bone Outcomes of Young Opioid-Dependent Women.

OBJECTIVE: To evaluate the bone response to an 8 month aerobic gymnastics training program in young opioid-addicted women. DESIGN: Randomized controlled trial (parallel design). SETTING: Women's Specific Drug Rehabilitation Center in China. PATIENTS: One hundred and two young women with low bone quality and previous opioid addiction were divided into two groups: (a) the low bone quality intervention experimental group (n = 55; age: 30.3 ± 6.1) and (b) the low bone quality observed control group (observation group; n = 47; age: 29.0 ± 5.3). INTERVENTIONS: The intervention group took aerobic gymnastics regularly for 80 min/d and 5 d/wk for 8 months and completed follow-up testing. MAIN OUTCOME MEASURES: Substance use history and other life habits affecting bone quality were assessed by questionnaire-based interviews. Bone quality (stiffness-index, T-score, Z-score) was examined with quantitative ultrasound. Anthropometric characteristics (body weight, fat-free mass, fat mass) were obtained by bioelectrical impedance analysis. RESULTS: After the 8 month intervention, the stiffness index of bone quality increased significantly (before: 82 ± 6, after: 108 ± 14, p < 0.05) in the experimental group. However, the bone quality did not change significantly in the controls (before: 79 ± 10, after: 77 ± 13, p > 0.05). The bone change in the difference group was significant (experimental group: 31.7% vs observation group: -0.03%). Fat mass decreased in the experimental group (experimental group: before: 19.6 ± 3.7 kg, after: 18.8 ± 4.0 kg, p < 0.05). Meanwhile, the change in fat-free mass was the determination of the change in bone quality in the experimental group. CONCLUSIONS: Our results suggested that aerobic gymnastics intervention can be an effective strategy for the prevention and treatment of drug-induced osteoporosis in detoxification addicts.

Predicting the Risk of Hypertension Based on Several Easy-to-Collect Risk Factors: A Machine Learning Method.

Hypertension is a widespread chronic disease. Risk prediction of hypertension is an intervention that contributes to the early prevention and management of hypertension. The implementation of such intervention requires an effective and easy-to-implement hypertension risk prediction model. This study evaluated and compared the performance of four machine learning algorithms on predicting the risk of hypertension based on easy-to-collect risk factors. A dataset of 29,700 samples collected through a physical examination was used for model training and testing. Firstly, we identified easy-to-collect risk factors of hypertension, through univariate logistic regression analysis. Then, based on the selected features, 10-fold cross-validation was utilized to optimize four models, random forest (RF), CatBoost, MLP neural network and logistic regression (LR), to find the best hyper-parameters on the training set. Finally, the performance of models was evaluated by AUC, accuracy, sensitivity and specificity on the test set. The experimental results showed that the RF model outperformed the other three models, and achieved an AUC of 0.92, an accuracy of 0.82, a sensitivity of 0.83 and a specificity of 0.81. In addition, Body Mass Index (BMI), age, family history and waist circumference (WC) are the four primary risk factors of hypertension. These findings reveal that it is feasible to use machine learning algorithms, especially RF, to predict hypertension risk without clinical or genetic data. The technique can provide a non-invasive and economical way for the prevention and management of hypertension in a large population.

Metabolic low-frequency oscillation and abbreviated protocol for estimating REE by indirect calorimetry in healthy adults.

The aim of this study is to propose a new wave protocol to identify low-frequency oscillations for evaluating resting energy expenditure (REE) and compare its performance with the 5-min interval abbreviated protocol and standard protocol. Consecutive 20-min indirect calorimetry (IC) was used to collect metabolic data from 23 women and 37 men (between 23 and 43 yr old). Sliding window filter algorithms were used to eliminate noise. Three protocols were used to evaluate REE: averaging the data between two consecutive waves (wave protocol), averaging the second 5-min intervals (interval protocol), and averaging the last 15-min REE (standard protocol). Based on 60 healthy participants' metabolic data, compared with the interval protocol, the wave protocol showed better consistency with the standard protocol. The mean bias (limits of agreement) using the wave protocol was 0.3458% (-7.817% to 8.509%), and that using the interval protocol was -1.720% (-16.06% to 12.62%). The time required to evaluate REE with the wave protocol and interval protocol was measured. The measurement time for the interval protocol was 10 min, while the average measurement time for the wave protocol was 9.75 min. We recommend the wave protocol for estimating REE in healthy people. This abbreviated protocol can identify low-frequency oscillations and consider individual differences to more accurately reflect the baseline REE compared with the interval protocol. When compared with the standard protocol, the measurement time of the wave protocol was reduced by nearly half [from 20 min (standard protocol) to 9.75 min].NEW & NOTEWORTHY For estimating REE by indirect calorimetry, to shorten the measurement time, a consideration of low-frequency oscillations is essential. Based on that we proposed a new abbreviated protocol named wave protocol, which showed accuracy approaching that of the standard protocol with a measurement time close to that of the interval abbreviated protocol.

Intelligent Personalized Exercise Prescription Based on an eHealth Promotion System to Improve Health Outcomes of Middle-Aged and Older Adult Community Dwellers: Pretest-Posttest Study.

BACKGROUND: A scientific, personalized, and quantitative exercise prescription that has the potential to be an important therapeutic agent for all ages in the prevention of chronic disease is highly recommended. However, it is often poorly implemented, as clinicians lack the necessary knowledge and skills while participants have low adherence due to design defects (eg, prescriptions fail to take individual willingness, the appeal of exercise, and complex physical conditions into account). Intelligent personalized prescription is thus worth exploring. OBJECTIVE: The aim of this study was to investigate whether a year-long cloud platform-based and intelligent personalized exercise prescription intervention could improve Chinese middle-aged and older adult community dwellers' health outcomes. METHODS: A total of 177 participants (aged 52-85 years; mean 67.93, SD 7.05) were recruited from 2 Chinese community health service centers in Anhui Province, China. The exercise intervention was delivered over 12 months with a single-group pretest-posttest design. After being assessed in terms of physical activity, health-related lifestyle, history of chronic diseases and drug use, family history of disease and cardiovascular function, body composition, bone mineral density, and physical fitness through an eHealth promotion system, participants with relative contraindications for exercise were personally prescribed the health care exercise mode by an intelligent system, while those without relative contraindication and who had a regular exercise habit were prescribed the scientific fitness mode. Paired t tests were used for the analysis. RESULTS: A total of 97 participants were classified into the health care mode, and the remaining 80 participants were assigned to the scientific fitness mode. Significant changes in heart rate (mean difference [MD] 2.97; 95% CI 1.1-4.84; P=.002), subendocardial viability ratio (MD -0.13; CI: -1.19 to -0.63; P<.001), weight (MD 0.99; CI 0.29-1.69; P=.006), BMI (MD 0.38; CI 0.11-0.64; P=.006), body fat rate (MD 0.88; CI 0.24-1.51; P=.007), fat mass (MD 0.92; CI 0.33-1.53; P=.003), and brachial-ankle pulse wave velocity (MD: -0.72; CI -1.17 to -0.27; P=.002) were observed among participants with the health care mode exercise prescriptions at the 12-month postintervention versus the baseline assessment, while no changes in systolic blood pressure, diastolic blood pressure, muscle mass, bone mineral density, t value, z value, balance, or ability were discerned. The results showed a functional decline in the physical fitness of both groups, including in handgrip strength (healthcare mode: MD 4.41; scientific fitness mode: MD 3.11), vital capacity (healthcare mode: MD 261.99; scientific fitness mode: MD 250.78), and agility (healthcare mode MD=-0.35; scientific fitness mode: MD=-0.39) with all P values <.001, except handgrip strength in the scientific fitness mode (P=.002). There were no significant differences in other parameters among participants with scientific fitness mode exercise prescriptions. CONCLUSIONS: The observations suggest that our exercise prescription intervention program might promote certain health outcomes in Chinese middle-aged and older adult community dwellers, yet we are unable to recommend such a program given the existing limitations. Future randomized controlled trials with diverse samples are warranted to confirm our findings.

Nutritional Status and Body Composition in Wilson Disease: A Cross-Sectional Study From China.

Background: Abnormal nutritional status is frequently seen in patients with chronic diseases. To date, no study has investigated the detailed characteristics of abnormal nutritional status among Wilson's disease (WD) patients in the Chinese cohort. This study aimed to describe the nutritional status of WD patients, with a particular focus on the differences between patients with different phenotypes. Methods: The study subjects comprised 119 healthy controls, 129 inpatients (hepatic subtype, n = 34; neurological subtype, n = 95) who were being treated at the affiliated hospital of the Institute of Neurology, Anhui University of Chinese Medicine. All of the subjects were assessed for body composition by using bioelectrical impedance analysis. All WD patients received anthropometry, nutritional risk screening 2002 (NRS2002), and laboratory test (hemocyte and serum biomarkers) additionally. Results: Compared with healthy controls, the fat mass and rate of total body and trunk were significantly higher in WD patients (P < 0.001), the muscle and skeletal muscle mass of total body and trunk were significantly lower in WD patients (P < 0.001). Compared with hepatic subtype patients, the fat mass and rate of total body, trunk, and limbs were significantly lower in neurological subtype patients (P<0.01); while there were no significant differences in muscle and skeletal muscle between these two subtypes. The overall prevalence of abnormal nutritional status in WD patients was 43.41% (56/129). The prevalence of high-nutritional risk and overweight in WD patients was 17.83% (23 of 129) and 25.58% (33 of 129), respectively. Compare with patients with high nutritional risk, macro platelet ratio, alkaline phosphatase, the basal metabolic rate (p < 0.05), creatinine, trunk fat rate (p < 0.01) and appendicular skeletal muscle mass (p < 0.001) were significantly higher in patients without nutritional risk (p < 0.001). Patients with a high nutritional risk tend to have a lower cholinesterase concentration (x 2 = 4.227, p < 0.05). Conclusion: Both patients with H-subtype and N-subtype are prone to have an abnormal nutritional status. Longitudinal studies are required to investigate if nutritional status and body composition could reflect prognosis in WD patients, and which of these body composition indexes contribute to malnutrition and worse prognosis.

Association of dietary pattern and physical activity with lipid-related indices among Chinese population: a cross-sectional study.

BACKGROUND AND OBJECTIVES: To explore the relationship between dietary patterns, physical activity and lipid-related indices in Chinese Population. METHODS AND STUDY DESIGN: This study included 21,472 (72.3% men) participants aged 16 to 78 years. Data of anthropometric measurements, biochemical tests and questionnaires were collected through a physical examination. Diet patterns were identified through factor analysis and five patterns were retained ("meat," "high-energy," "high-protein," "healthy" and "traditional Chinese"). Physical activity was classified into low, moderate, or high. Abnormalities in lipid indices were assessed using the Adult Treatment Panel III criterion. RESULTS: Higher factor scores of "high-protein" pattern and "healthy" pattern were found to be related to favorable lipid indices. Quartiles 3 and 4 of "meat" pattern showed increased risks of having elevates total cholesterol and low-density lipoprotein cholesterol concentrations. Participants with higher levels of physical activity showed lowest risk of abnormal lipid profiles. All the associations were equally established among men, while most were no longer significant among women. CONCLUSIONS: Higher physical activity level and a dietary pattern consists of high-quality protein foods, vegetables and fruits were associated with favorable lipid profiles, and these lifestyle factors were related to the risk of dyslipidemia in a sex-specific way.

Dietary diversity and physical activity associations with lipid indices among Beijingese: A cross-sectional study.

BACKGROUND AND OBJECTIVES: To examine the association of dietary diversity and physical activity with lipidrelated indices in a Beijing population. METHODS AND STUDY DESIGN: This cross-sectional study included 21,472 participants (72.3% men) aged 16 to 78 years. Data were obtained through a physical examination that included anthropometric measurements, biochemical tests, and questionnaires. The dietary diversity score (0-8) was calculated according to the baseline consumption frequencies of eight food groups (cereals, fruits, vegetables, meat, eggs, fish, dairy, and legumes). Physical activity level was classified as low, moderate, or high according to International Physical Activity Questionnaire scoring protocol. Abnormalities in lipid-related indices were assessed using the criteria of the National Cholesterol Education Program Adult Treatment Panel III guidelines. RESULTS: Compared with individuals with poor dietary diversity (score 0-5), higher dietary diversity was associated with lower risk of abnormal levels of triglycerides and high-density lipoprotein cholesterol. Dairy intake was associated with a lower risk of having a high triglyceride-to-high-density lipoprotein cholesterol ratio after adjusting for potential covariates. Participants with the lowest risk of abnormal lipid profiles were those who had high levels of physical activity. CONCLUSIONS: Dietary diversity and physical activity level were associated with lipid-related indices. Therefore, to maintain healthy lipid profiles in the general population, improving dietary diversity and physical activity is essential.