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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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Gestational diabetes mellitus (GDM) is conventionally confirmed with oral glucose tolerance test (OGTT) in 24 to 28 weeks of gestation, but it is still uncertain whether it can be predicted with secondary use of electronic health records (EHRs) in early pregnancy. To this purpose, the cost-sensitive hybrid model (CSHM) and five conventional machine learning methods are used to construct the predictive models, capturing the future risks of GDM in the temporally aggregated EHRs. The experimental data sources from a nested case-control study cohort, containing 33,935 gestational women in West China Second Hospital. After data cleaning, 4,378 cases and 50 attributes are stored and collected for the data set. Through selecting the most feasible method, the cost parameter of CSHM is adapted to deal with imbalance of the dataset. In the experiment, 3940 samples are used for training and the rest 438 samples for testing. Although the accuracy of positive samples is barely acceptable (62.16%), the results suggest that the vast majority (98.4%) of those predicted positive instances are real positives. To our knowledge, this is the first study to apply machine learning models with EHRs to predict GDM, which will facilitate personalized medicine in maternal health management in the future.
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Diabetes Gestacional/epidemiología , Registros Electrónicos de Salud , Adulto , Algoritmos , Análisis Costo-Beneficio , Bases de Datos Factuales , Diabetes Gestacional/diagnóstico , Diabetes Gestacional/etiología , Registros Electrónicos de Salud/estadística & datos numéricos , Femenino , Edad Gestacional , Humanos , Modelos Estadísticos , Embarazo , Pronóstico , Curva ROC , Flujo de TrabajoRESUMEN
Sarcopenia, a newly recognized geriatric syndrome, is characterized by age-related decline of skeletal muscle plus low muscle strength and/or physical performance. Previous studies have confirmed the association of sarcopenia and adverse health outcomes, such as falls, disability, hospital admission, long term care placement, poorer quality of life, and mortality, which denotes the importance of sarcopenia in the health care for older people. Despite the clinical significance of sarcopenia, the operational definition of sarcopenia and standardized intervention programs are still lacking. It is generally agreed by the different working groups for sarcopenia in the world that sarcopenia should be defined through a combined approach of muscle mass and muscle quality, however, selecting appropriate diagnostic cutoff values for all the measurements in Asian populations is challenging. Asia is a rapidly aging region with a huge population, so the impact of sarcopenia to this region is estimated to be huge as well. Asian Working Group for Sarcopenia (AWGS) aimed to promote sarcopenia research in Asia, and we collected the best available evidences of sarcopenia researches from Asian countries to establish the consensus for sarcopenia diagnosis. AWGS has agreed with the previous reports that sarcopenia should be described as low muscle mass plus low muscle strength and/or low physical performance, and we also recommend outcome indicators for further researches, as well as the conditions that sarcopenia should be assessed. In addition to sarcopenia screening for community-dwelling older people, AWGS recommends sarcopenia assessment in certain clinical conditions and healthcare settings to facilitate implementing sarcopenia in clinical practice. Moreover, we also recommend cutoff values for muscle mass measurements (7.0 kg/m(2) for men and 5.4 kg/m(2) for women by using dual X-ray absorptiometry, and 7.0 kg/m(2) for men and 5.7 kg/m(2) for women by using bioimpedance analysis), handgrip strength (<26 kg for men and <18 kg for women), and usual gait speed (<0.8 m/s). However, a number of challenges remained to be solved in the future. Asia is made up of a great number of ethnicities. The majority of currently available studies have been published from eastern Asia, therefore, more studies of sarcopenia in south, southeastern, and western Asia should be promoted. On the other hand, most Asian studies have been conducted in a cross-sectional design and few longitudinal studies have not necessarily collected the commonly used outcome indicators as other reports from Western countries. Nevertheless, the AWGS consensus report is believed to promote more Asian sarcopenia research, and most important of all, to focus on sarcopenia intervention studies and the implementation of sarcopenia in clinical practice to improve health care outcomes of older people in the communities and the healthcare settings in Asia.
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Sarcopenia/diagnóstico , Sarcopenia/fisiopatología , Aminoácidos/administración & dosificación , Asia/epidemiología , Pueblo Asiatico , Composición Corporal/fisiología , Diagnóstico por Imagen , Proteínas en la Dieta/administración & dosificación , Suplementos Dietéticos , Prueba de Esfuerzo , Terapia por Ejercicio , Marcha/fisiología , Humanos , Tamizaje Masivo , Fuerza Muscular/fisiología , Músculo Esquelético/patología , Músculo Esquelético/fisiopatología , Sarcopenia/epidemiología , Sarcopenia/terapiaRESUMEN
OBJECTIVE: To explore the disease course and outcomes of severe or critical pregnant women with 2009 pandemic H1N1 (pH1N1) infection in China. METHODS: A retrospective observational study was conducted for 394 severe or critical pregnant women with pH1N1 influenza admitted into hospital in 27 Chinese provinces from September 1, 2009 to December 31, 2009. Their clinical features in different trimesters were analyzed. The viral infection of pH1N1 was verified by real-time reverse transcription (rRT)-PCR. Severe and critical cases were defined according to the 2009 H1N1 clinical guidelines. RESULTS: Among them, 374 (94.9%) were infected in the second or third trimester. Fever and cough were the most common symptoms in all trimesters. However, hemoptysis, dyspnea and associated pneumonia were likely to occur in the second or third trimester. The ratio of required mechanical ventilation in the second or third trimester (44.7%, 167/374) was significantly higher than that in the first trimester (3/20). Among 77 mortality cases, 72.7% (56/77) died in the third trimester. Pregnancy was terminated after the onset of pH1N1 symptoms in 52.5%(207/394) pregnant women. And 57.0%(118/207) of them had delivery < 37 weeks and 29.0%(60/207) fetuses deceased. CONCLUSION: A clinician should be on a high alert for pH1N1 infection in pregnant women, particularly in the second or third trimester.