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2.
Diabetes Metab ; 47(4): 101196, 2021 07.
Article in English | MEDLINE | ID: mdl-33039672

ABSTRACT

AIM: Current guideline recommends insulin as fourth-line glucose-lowering medications. However, treatment effects of sodium glucose co-transporter-2 inhibitors (SGLT2i) on the risk of complications are uncertain. This study examines risks of all-cause mortality, cardiovascular diseases (CVD) and end-stage renal diseases (ESRD) in type 2 diabetes mellitus (T2DM) patients on triple oral glucose-lowering medications initiating SGLT2i, insulin or other oral medications. METHODS: A population-based retrospective cohort of patients with T2DM between 2006-2017 was extracted from Hong Kong Hospital Authority database. Patients who were initiated a fourth-line therapy with SGLT2i, insulin or other oral medications were included. Hazard ratios (HRs) for all-cause mortality, CVD and ESRD were assessed using Cox proportional hazard models. RESULTS: Over a median follow-up period of 18.5 months with 63,122 person-years, SGLT2i and insulin group had the lowest and highest incidence rate of all-cause mortality, CVD and ESRD (1.06, 0.65 and 0.61 vs 4.25, 5.58 and 4.39/100 person-years), respectively. Initiating SGLT2i as fourth-line medication had more benefits on CVD, in particular coronary heart disease and stroke. Insulin users had higher risks of CVD (HR=8.04, 95%CI=3.06-21.12) than SGLT2i users. SGLT2i was associated with insignificant reduction in ESRD (HR=4.62, 95%CI=0.73-29.09) and all-cause mortality (HR=3.06, 95%CI=0.75-12.45), and HF (HR=2.99, 95%CI=0.37-24.42) among patients without established HF. CONCLUSION: Among T2DM patients initiating fourth-line therapy, SGLT2i users had significant benefits in lowering risk of CVD, and potential benefits in lowering risks of ESRD and all-cause mortality. SGLT2i was the preferred fourth-line glucose-lowering medication least likely to be associated with complication risks.


Subject(s)
Diabetes Mellitus, Type 2 , Sodium-Glucose Transporter 2 Inhibitors , Cardiovascular Diseases/epidemiology , Diabetes Mellitus, Type 2/drug therapy , Humans , Kidney Failure, Chronic/epidemiology , Mortality , Risk Assessment , Sodium-Glucose Transporter 2 Inhibitors/adverse effects
3.
Public Health ; 186: 144-156, 2020 Sep.
Article in English | MEDLINE | ID: mdl-32836004

ABSTRACT

OBJECTIVES: Diabetes mellitus (DM) is a serious public health issue worldwide, and DM patients have higher risk of cardiovascular diseases (CVDs), which is the leading cause of DM-related deaths. China has the largest DM population, yet a robust model to predict CVDs in Chinese DM patients is still lacking. This systematic review is carried out to summarize existing models and identify potentially important predictors for CVDs in Chinese DM patients. STUDY DESIGN: Systematic review. METHODS: Medline and Embase were searched for data from April 1st, 2011 to May 31st, 2018. A study was eligible if it developed CVD (defined as total CVD or any major cardiovascular component) risk prediction models or explored potential predictors of CVD specifically for Chinese people with type 2 DM. Standardized forms were utilized to extract information, appraise applicability, risk of bias, and availabilities. RESULTS: Five models and 29 studies focusing on potential predictors were identified. Models for a primary care setting, or to predict total CVD, are rare. A number of common predictors (e.g. age, sex, diabetes duration, smoking status, glycated hemoglobin (HbA1c), blood pressure, lipid profile, and treatment modalities) were observed in existing models, in which urine albumin:creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) are highly recommended for the Chinese population. Variability of blood pressure (BP) and HbA1c should be included in prediction model development as novel factors. Meanwhile, interactions between age, sex, and risk factors should also be considered. CONCLUSIONS: A 10-year prediction model for CVD risk in Chinese type 2 DM patients is lacking and urgently needed. There is insufficient evidence to support the inclusion of other novel predictors in CVDs risk prediction functions for routine clinical use.


Subject(s)
Cardiovascular Diseases/epidemiology , Diabetes Mellitus, Type 2/epidemiology , China/epidemiology , Diabetes Mellitus, Type 2/therapy , Humans , Models, Statistical , Risk
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