Patients with prediabetes, type 1 diabetes, type 2 diabetes, gestational diabetes, other special types of diabetes, ICU stress-induced hyperglycemia, critically ill patients with diabetes, childhood and adolescent diabetes, adult latent autoimmune diabetes, secondary diabetes due to endocrine disorders, neonatal diabetes, as well as various complications of diabetes.
Conditions
Interventions
Observation group:None
Sponsors
Beijing Friendship Hospital ,Capital Medical University
Eligibility
Sex/Gender
All
Inclusion criteria
Inclusion criteria: 1.Patients with diabetes or related disorders of glucose metabolism who have undergone examinations, outpatient visits, or inpatient treatments in our hospital; 2.Including but not limited to patients with prediabetes, type 1 diabetes, type 2 diabetes, gestational diabetes, other special types of diabetes, ICU stress-induced hyperglycemia, critically ill patients with diabetes, childhood and adolescent diabetes, adult latent autoimmune diabetes, secondary diabetes due to endocrine disorders, neonatal diabetes, and various types of diabetic complications; 3.Have clinical data available for research analysis, including structured data and/or medical record text data; 4.For the consultation assistance module, it is necessary to have complete consultation application materials and the actual consultation opinions from endocrinology specialists; 5.For the sub-module of gestational diabetes, it is necessary to have pregnancy follow-up records and traceable information on pregnancy and childbirth outcomes; 6.For the sub-analysis related to critical cases or the auxiliary consultation module, when including inpatient critical cases, the following conditions must be met: There should be relatively complete medical records during hospitalization; For ICU patients, there must be traceable critical care records, key test and examination results, main treatment process, and relevant consultation records;
Exclusion criteria
Exclusion criteria: 1.The key core variables are severely lacking, making it impossible to complete the data organization and analysis. 2.The medical record is obviously incomplete and cannot be used for model input or outcome determination. 3.Those whose outcome information is missing or whose authenticity cannot be verified. 4.Laboratory indicators are abnormal: indicators such as blood sugar, blood lipids, liver and kidney functions exceed the physiological limits, and the detected values at the same time point are logically inconsistent. 5.The diagnostic codes simultaneously contain conflicting entries (such as the same record indicating both "Type 2 Diabetes" and "Type 1 Diabetes").
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Health - sub-health - disease state transition event; | — |
Secondary
| Measure | Time frame |
|---|---|
| Main clinical indicators;Biochemical indicators (such as blood pressure, blood glucose, blood lipid, liver and kidney function, etc.);Lifestyle indicators (such as physical activity, dietary structure, psychological stress level, etc., all derived from historical physical examinations, medical visits and hospitalization records, including previous self-assessment questionnaire data);The risk probability value output by the model; | — |
Countries
China
Contacts
Public ContactLv Han
Beijing Friendship Hospital ,Capital Medical University
Outcome results
None listed