Derivation and external validation of risk algorithms for cerebrovascular (re)hospitalisation in patients with type 2 diabetes: Two cohorts study

Cardiovascular risk in patients with type 2 diabetes: A systematic review of prediction models

AIMS

To identify all cardiovascular disease risk prediction models developed in patients with type 2 diabetes or in the general population with diabetes as a covariate updating previous studies, describing model performance and analysing both their risk of bias and their applicability METHODS: A systematic search for predictive models of cardiovascular risk was performed in PubMed. The CHARMS and PROBAST guidelines for data extraction and for the assessment of risk of bias and applicability were followed. Google Scholar citations of the selected articles were reviewed to identify studies that conducted external validations.

RESULTS

The titles of 10,556 references were extracted to ultimately identify 19 studies with models developed in a population with diabetes and 46 studies in the general population. Within models developed in a population with diabetes, only six were classified as having a low risk of bias, 17 had a favourable assessment of applicability, 11 reported complete model information, and also 11 were externally validated.

CONCLUSIONS

There exists an overabundance of cardiovascular risk prediction models applicable to patients with diabetes, but many have a high risk of bias due to methodological shortcomings and independent validations are scarce. We recommend following the existing guidelines to facilitate their applicability.

Remnant Cholesterol and Cardiovascular Mortality in Patients With Type 2 Diabetes and Incident Diabetic Nephropathy

CONTEXT

The association between remnant cholesterol (remnant-C) and cardiovascular mortality in patients with type 2 diabetes (T2D) and incident diabetic nephropathy remains unclear.

OBJECTIVE

To examinie the association between remnant-C and cardiovascular mortality in patients with T2D, chronic kidney disease (CKD) stages 3 to 5, and newly diagnosed DN.

METHODS

This study determined the baseline lipid profile and searched for deaths with cardiovascular disease (CVD) within 2 years of baseline among 2282 adults enrolled between January 1, 2015 and December 31, 2016, who had T2D, CKD stages 3 to 5, and newly diagnosed DN. Adjusted logistic regression models were used to assess the associations between lipid, especially remnant-C concentration (either as continuous or categorical variables), and risk of cardiovascular mortality.

RESULTS

In multivariable-adjusted analyses, low-density lipoprotein cholesterol (LDL-C) (odds ratio [OR], 1.022; 95% CI, 1.017-1.026, per 10 mg/dL), high-density lipoprotein cholesterol (HDL-C) (OR, 0.929; 95% CI, 0.922-0.936, per 5 mg/dL), non-HDL-C (OR, 1.024; 95% CI, 1.021-1.028, per 10 mg/dL), and remnant-C (OR, 1.115; 95% CI, 1.103-1.127, per 10 mg/dL), but not triglycerides were associated with cardiovascular mortality. Atherogenic dyslipidemia (triglycerides > 150 mg/dL [1.69 mmol/L] and HDL-C < 40 mg/dL in men or < 50 mg/dL in women) was also associated with cardiovascular mortality (OR, 1.073; 95% CI, 1.031-1.116). Remnant-C greater than or equal to 30 mg/dL differentiated patients at a higher risk of cardiovascular mortality from those with lower concentrations, especially with interaction with LDL-C level greater than 100 mg/dL: The highest risk was found in patients with higher levels both of remnant-C and LDL-C (OR, 1.696; 95% CI, 1.613-1.783).

CONCLUSION

In patients with T2D, CKD stages 3 to 5, and incident DN, remnant-C was associated with a higher risk of death with CVD. Different from the general population, the interaction of remnant-C and LDL-C was associated with the highest risk of cardiovascular mortality.

Functionality of Djulis (Chenopodium formosanum) By-Products and In Vivo Anti-Diabetes Effect in Type 2 Diabetes Mellitus Patients

Simple Summary

According to a report from International Diabetes Federation, in 2020 approximately 463 million adults (20–79 years) were living with diabetes, the principles of medical nutrition therapy are to decrease the risk of diabetes by encouraging healthy food choices and physical activity. Djulis is a unique traditional pseudo-cereal crop native to Taiwan. The hull of djulis, which is usually considered to be agricultural waste, is disposed of in landfills and causes some environmental problems. In recent years, many studies have investigated the functional properties of djulis hull. The focus has been on the byproducts of djulis, a waste utilization approach, to further develop enriched functional foods. Djulis hull contained dietary fibre 75.21 ± 0.17% dry weight, and insoluble dietary fibre (IDF) reached 71.54 ± 0.27% dry weight. The IDF postponed the adsorption of glucose and reduced the activity of α-amylase. We found that it is a good source of valuable ingredients that contain a high amount of dietary fibre. Furthermore, for patients with T2DM, consuming djulis hull 30 and 60 min before a meal significantly reduced blood glucose content as compared with patients at the same postprandial times who did not consume it.

Abstract

Djulis (Chenopodium formosanum Koidz.) is a species of cereal grain native to Taiwan. It is rich in dietary fibre and antioxidants and therefore reputed to relieve constipation, suppress inflammation, and lower blood glucose. The aim of this study was to investigate the composition and physicochemical properties of dietary fibre from djulis hull. Meanwhile, determination of the in vivo antidiabetic effect on patients with type 2 diabetes mellitus (T2DM) after consuming the djulis hull powder. Djulis hull contained dietary fibre 75.21 ± 0.17% dry weight, and insoluble dietary fibre (IDF) reached 71.54 ± 0.27% dry weight. The IDF postponed the adsorption of glucose and reduced the activity of α-amylase. Postprandial blood glucose levels in patients with T2DM showed three different tendencies. First, the area under the glucose curve was significantly lower after ingesting 10 or 5 g djulis hull powder, which then postponed the adsorption of glucose, but the area under the glucose curve was similar with the two doses. After consuming 10 g djulis hull before 75 g glucose 30 and 60 min after the meal, patients with T2DM had blood glucose values that were significantly lower at the same postprandial times than those of patients who did not consume djulis hull. In short, patients who consumed djulis hull prior to glucose administration had decreased blood glucose level compared with those who did not. Djulis hull may have benefits for patients with T2DM.

A low-cost laboratory-based method for predicting newly diagnosed biopsy-proven diabetic nephropathy in people with type 2 diabetes

AIMS

To identify significant prognostic factors for newly diagnosed biopsy-proven diabetic nephropathy using routine laboratory measures, from which to derive a low-cost explanatory model, and to use this model to examine associations between the potential low-cost test panels and the risk of diabetic nephropathy in people with type 2 diabetes with normal kidney function.

METHOD

A population-based case-control study was undertaken to test the association between diabetic nephropathy and 47 laboratory variables using a 'hypothesis-free' strategy and five routinely recorded factors in diabetes care (BMI, systolic and diastolic blood pressure, HbA_1c , fasting glucose). Factors that were significant after Bonferroni correction were included in different test panels and used to develop diabetic nephropathy (outcome) explanatory models. Models were derived using risk-set sampling among 950 biopsy-proven diabetic nephropathy cases newly diagnosed in the period between 2012 and 2018 and among 4750 age- and gender-matched controls.

RESULTS

A total of 15 Bonferroni-corrected significant laboratory predictors in the three test panels (blood cell, serum electrolytes and blood coagulation) were identified through multivariable analysis and used to develop the three explanatory models. The optimism-adjusted C-statistics and calibration slope were 0.725 (95% CI 0.723-0.728) and 0.978 (95% CI 0.912-0.999) for the blood cell model, 0.688 (95% CI 0.686-0.690) and 0.923 (95% CI 0.706-0.977) for the serum electrolytes model, 0.648 (95% CI 0.639-0.658) and 0.914 (95% CI 0.641-1.115) for the blood coagulation model, respectively.

CONCLUSIONS

A total of 15 predictors were significantly associated with newly diagnosed biopsy-proven diabetic nephropathy in type 2 diabetes. The blood cell model appeared to be the low-cost model with the best predictive ability.

The triglyceride glucose index can predict newly diagnosed biopsy-proven diabetic nephropathy in type 2 diabetes: A nested case control study

Insulin resistance is usually a key factor in the development of type 2 diabetes. The triglyceride glucose (TyG) index is a marker of insulin resistance which is also implicated in the risk of nephropathy among people with type 2 diabetes. This study aimed to examine associations and potential thresholds between TyG index and the risk of newly diagnosed biopsy-proven diabetic nephropathy in people with type 2 diabetes. A nested case-control study incorporating 950 incident biopsy-proven diabetic nephropathy cases and age, gender matched 4750 patients with treated type 2 diabetes as controls selected by risk-set sampling method was implemented. The dose-response association between TyG index with subsequent risk of newly diagnosed biopsy-proven diabetic nephropathy after adjustment for age, gender, blood pressure, and other major cardiovascular risk factors were examined by conditional logistic regression model. A non-linear relationship was identified between TyG index and the risk of newly diagnosed biopsy-proven diabetic nephropathy with a potential threshold of TyG at 9.05-9.09. Similar relationships with the same threshold were also found in the analyses by fasting glucose and triglyceride levels. TyG index might be a prognostic factor in predicting newly development of biopsy-proven diabetic nephropathy among patients with treated type 2 diabetes. In people with type 2 diabetes, TyG index above 9.05-9.09 could be a prognostic threshold to identify individuals at high risk of diabetic nephropathy. Further replication studies are warranted.

Derivation and external validation of a risk prediction algorithm to estimate future risk of cardiovascular death among patients with type 2 diabetes and incident diabetic nephropathy: prospective cohort study

OBJECTIVE

To derive, and externally validate, a risk score for cardiovascular death among patients with type 2 diabetes and newly diagnosed diabetic nephropathy (DN).

RESEARCH DESIGN AND METHODS

Two independent prospective cohorts with type 2 diabetes were used to develop and externally validate the risk score. The derivation cohort comprised 2282 patients with an incident, clinical diagnosis of DN. The validation cohort includes 950 patients with incident, biopsy-proven diagnosis of DN. The outcome was cardiovascular death within 2 years of the diagnosis of DN. Logistic regression was applied to derive the risk score for cardiovascular death from the derivation cohort, which was externally validated in the validation cohort. The score was also estimated by applying the United Kingdom Prospective Diabetes Study (UKPDS) risk score in the external validation cohort.

RESULTS

The 2-year cardiovascular mortality was 12.05% and 11.79% in the derivation cohort and validation cohort, respectively. Traditional predictors including age, gender, body mass index, blood pressures, glucose, lipid profiles alongside novel laboratory test items covering five test panels (liver function, serum electrolytes, thyroid function, blood coagulation and blood count) were included in the final model.C-statistics was 0.736 (95% CI 0.731 to 0.740) and 0.747 (95% CI 0.737 to 0.756) in the derivation cohort and validation cohort, respectively. The calibration slope was 0.993 (95% CI 0.974 to 1.013) and 1.000 (95% CI 0.981 to 1.020) in the derivation cohort and validation cohort, respectively.The UKPDS risk score substantially underestimated cardiovascular mortality.

CONCLUSIONS

A new risk score based on routine clinical measurements that quantified individual risk of cardiovascular death was developed and externally validated. Compared with the UKPDS risk score, which underestimated the cardiovascular disease risk, the new score is a more specific tool for patients with type 2 diabetes and DN. The score could work as a tool to identify individuals at the highest risk of cardiovascular death among those with DN.