Introduction To investigate the predictors of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients and establish a nomogram model for predicting the risk of DKD. Methods The clinical data of T2DM patients, admitted to the Endocrinology Department of Chengde Central Hospital from October 2019 to September 2020 and divided into a case group or a control group based on whether they had DKD, were collected. The predictive factors of DKD were screened by univariate and multivariate analysis, and a nomogram prediction model was constructed for the risk of DKD in T2DM. Bootstrapping was used for model validation, receiver operating characteristic (ROC) curve and GiViTI calibration curve were used for evaluating the discrimination and calibration of prediction model, and decision analysis curve (DCA) was used for evaluating the practicality of model. Results Predictors for DKD are diabetic retinopathy (DR), hypertension, history of gout, smoking history, using insulin, elevation of body mass index (BMI), triglyceride (TG), cystatin C (Cys-C), and reduction of 25 (OH) D. The nomogram prediction model based on the above nine predictors had good representativeness (Bootstrap method: precision: 0.866, Kappa: 0.334), differentiation [the area under curve (AUC) value: 0.868], and accuracy (GiViTI-corrected curved bands, P = 0.836); the DAC curve analysis showed that the prediction model, whose threshold probability was in the range of 0.10 to 0.70, had clinical practical value. Conclusion The risk of DKD in T2DM could be predicted accurately by DR, hypertension, history of gout, smoking history, using insulin, elevation of BMI, TG, Cys-C, and reduction of 25 (OH) D.

Construction of a Nomogram-Based Prediction Model for the Risk of Diabetic Kidney Disease in T2DM

Little is known about the association between abnormal metabolic obesity states and the outcomes of chronic myeloid leukemia (CML), especially in patients with obesity with different metabolic status. Here, we used the Nationwide Readmissions Database to assess the effects of metabolically defined obesity on adverse outcomes of CML.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1753-0407.13383

Association of obesity under different metabolic status with adverse outcomes in patients with chronic myeloid leukemia: A retrospective cohort study

Untuk mencegah keterlibatan anak dalam sistem kesejahteraan dengan segera melibatkan keluarga ke intervensi preventif, penting untuk mengidentifikasi risiko keterlibatan ini di masyarakat umum sedini mungkin. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor demografi, sosial ekonomi, dan riwayat kriminal yang terkait dengan keterlibatan anak dalam sistem kesejahteraan. Kami mengumpulkan data antropometri dari 120.641 anak berusia di bawah 15 tahun serta data dari orang tua mereka (81.453 ibu dan 68.202 ayah) melalui Badan Pusat Statistik. Keterlibatan anak dalam kesejahteraan mencakup perintah pengawasan, perwalian yang ditetapkan pengadilan, atau penempatan di luar rumah yang dimulai dalam satu tahun setelah penilaian faktor risiko. Validitas prediktif keterlibatan ini dinilai dengan menghitung nilai AUC untuk setiap faktor risiko. Kami mengembangkan algoritma prediktif berbasis pohon keputusan dan melakukan validasi dengan menggunakan sampel terpisah. Hasil penelitian menunjukkan bahwa satu tahun setelah penilaian, keterlibatan anak dalam sistem kesejahteraan dapat diprediksi secara akurat dengan kombinasi faktor-faktor tertentu pada tingkat individu. Risiko ini meningkat secara signifikan dengan bertambahnya jumlah faktor risiko. Anak-anak yang memiliki empat atau lebih faktor risiko memiliki peluang sepuluh kali lipat untuk terlibat dalam sistem kesejahteraan anak, sementara enam atau lebih faktor risiko meningkatkan risiko ini hingga 21 kali lipat dibandingkan dengan anak-anak tanpa faktor risiko. Semakin banyak faktor risiko yang terakumulasi, model prediktif menunjukkan peningkatan kemungkinan keterlibatan dalam sistem kesejahteraan anak. Nilai AUC yang tinggi dalam model prediktif dan akumulasi faktor risiko ini dapat membantu praktisi memperkirakan kebutuhan untuk merujuk keluarga ke intervensi pencegahan secara tepat waktu

Initial evaluation of the risks of child welfare involvement for preventive measures

Background:One impact that can disrupt students' concentration in studying is gadget dependence. This dependency can have an impact on students' academic achievement, such as decreasing test scores and poor learning quality and achievement. Therefore, schools must better monitor students' use of gadgets during lessons at school and notify students' parents or guardians to supervise or limit students' use of gadgets at home. 
Research purposes:This research was conducted with the aim of understanding the relationship between the impact of dependence on gadgets on students' learning concentration and academic performance, as well as the extent of the impact of dependence on gadgets on students. 
Method:The method used in this research is a quantitative method.This method is a way of collecting numerical data that can be tested. Data was collected through distributing questionnaires addressed to students. Furthermore, the data that has been collected from the results of distributing the questionnaire will be accessible in Excel format which can then be processed using SPSS. 
Results:From this research, researchers were able to obtain research results on the impact of dependence on gadgets on students' learning concentration and academic performance, which can indeed have a very big influence on students' focus in learning. However, if the use of gadgets can be utilized properly, the resulting negative impact on students' concentration and academic performance will be less. 
Conclusion:Based on the results of this research, it can be concluded that the impact of dependence on gadgets, if used frequently, will have an impact on students' learning concentration. By decreasing student concentration in learning, it can result in fatalities such as decreasing the level of student achievement itself. Therefore, supervision is needed, especially by parents, so that students at home do not always play or use gadgets all the time.

The Impact of Dependence on Gadgets on Student Concentration and Academic Performance

Longitudinal Cohort Study Highlights Cancer-preventive Benefits of Lipid-lowering Drugs

Obesity Metabolic Phenotypes and Unplanned Readmission Risk in Diabetic Kidney Disease: An Observational Study from the Nationwide Readmission Database.

Air pollution is the primary environmental risk factor contributing to global cardiovascular mortality. In China, a series of air pollution control policies launched in 2013 have led to substantial improvements...

pdf/climate-change-and-population-aging-may-impact-the-benefits-phzzzj6y.pdf

Climate change and population aging may impact the benefits of improved air quality on cardiovascular mortality in Guangzhou: epidemiological evidence and policy implications

Association of Prediabetes with the Risks of Adverse Health Outcomes and Complex Multimorbidity: An Observational Study

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