Calculating individualized glycaemic targets using an algorithm based on expert worldwide diabetologists: Implications in real-life clinical practice

[Cardiovascular preventive recommendations. PAPPS 2022 thematic updates. Working groups of the PAPPS]

The recommendations of the semFYC's Program for Preventive Activities and Health Promotion (PAPPS) for the prevention of cardiovascular diseases (CVD) are presented. The following sections are included: epidemiological review, where the current morbidity and mortality of CVD in Spain and its evolution as well as the main risk factors are described; cardiovascular (CV) risk and recommendations for the calculation of CV risk; main risk factors such as arterial hypertension, dyslipidemia and diabetes mellitus, describing the method for their diagnosis, therapeutic objectives and recommendations for lifestyle measures and pharmacological treatment; indications for antiplatelet therapy, and recommendations for screening of atrial fibrillation, and recommendations for management of chronic conditions. The quality of testing and the strength of the recommendation are included in the main recommendations.

Glycemic variability and all-cause mortality in a large prospective southern European cohort of patients with differences in glycemic status

Background

Few studies have analyzed the relationship between glucose variability (GV) and adverse health outcomes in patients with differences in glycemic status. The present study tests the hypothesis that GV predicts all-cause mortality regardless of glycemic status after simple adjustment (age and sex) and full adjustment (age, sex, cardiovascular disease, hypertension, use of aspirin, statins, GLP-1 receptor agonists, SGLT-2 inhibitors and DPP-4 inhibitors, baseline FPG and average HbA1c).

Methods

Prospective cohort study with 795 normoglycemic patients, 233 patients with prediabetes, and 4,102 patients with type 2 diabetes. GV was measured using the coefficient of variation of fasting plasma glucose (CV-FPG) over 12 years of follow-up. The outcome measure was all-cause mortality.

Results

A total of 1,223 patients (657 men, 566 women) died after a median of 9.8 years of follow-up, with an all-cause mortality rate of 23.35/1,000 person-years. In prediabetes or T2DM patients, the fourth quartile of CV-FPG exerted a significant effect on all-cause mortality after simple and full adjustment. A sensitivity analysis excluding participants who died during the first year of follow-up revealed the following results for the highest quartile in the fully adjusted model: overall, HR (95%CI) = 1.54 (1.26–1.89); dysglycemia (prediabetes and T2DM), HR = 1.41 (1.15–1.73); T2DM, HR = 1.36 (1.10–1.67).

Conclusion

We found CV-FPG to be useful for measurement of GV. It could also be used for the prognostic stratification of patients with dysglycemia.

Cardiovascular risk factors associated with acute myocardial infarction and stroke in the MADIABETES cohort

We aimed to develop two models to estimate first AMI and stroke/TIA, respectively, in type 2 diabetes mellitus patients, by applying backward elimination to the following variables: age, sex, duration of diabetes, smoking, BMI, and use of antihyperglycemic drugs, statins, and aspirin. As time-varying covariates, we analyzed blood pressure, albuminuria, lipid profile, HbA1c, retinopathy, neuropathy, and atrial fibrillation (only in stroke/TIA model). Both models were stratified by antihypertensive drugs. We evaluated 2980 patients (52.8% women; 67.3 ± 11.2 years) with 24,159 person-years of follow-up. We recorded 114 cases of AMI and 185 cases of stroke/TIA. The factors that were independently associated with first AMI were age (≥ 75 years vs. < 75 years) (p = 0.019), higher HbA1c (> 64 mmol/mol vs. < 53 mmol/mol) (p = 0.003), HDL-cholesterol (0.90–1.81 mmol/L vs. < 0.90 mmol/L) (p = 0.002), and diastolic blood pressure (65–85 mmHg vs. < 65 mmHg) (p < 0.001). The factors that were independently associated with first stroke/TIA were age (≥ 75 years vs. < 60 years) (p < 0.001), atrial fibrillation (first year after the diagnosis vs. more than one year) (p = 0.001), glomerular filtration rate (per each 15 mL/min/1.73 m² decrease) (p < 0.001), total cholesterol (3.88–6.46 mmol/L vs. < 3.88 mmol/L) (p < 0.001), triglycerides (per each increment of 1.13 mmol/L) (p = 0.031), albuminuria (p < 0.001), neuropathy (p = 0.01), and retinopathy (p = 0.023).

[Cardiovascular preventive recommendations. PAPPS 2020 update]

The recommendations of the semFYC's Program for Preventive Activities and Health Promotion (PAPPS) for the prevention of cardiovascular diseases (CVD) are presented. The following sections are included: Epidemiological review, where the current morbidity and mortality of CVD in Spain and its evolution as well as the main risk factors are described; Cardiovascular (CV) risk tables and recommendations for the calculation of CV risk; Main risk factors such as arterial hypertension, dyslipidemia and diabetes mellitus, describing the method for their diagnosis, therapeutic objectives and recommendations for lifestyle measures and pharmacological treatment; Indications for antiplatelet therapy, and recommendations for screening of atrial fibrillation. The quality of testing and the strength of the recommendation are included in the main recommendations.

Trends in HbA1c thresholds for initiation of hypoglycemic agents: Impact of changed recommendations for older and frail patients

Aims

Less strict glycated hemoglobin (HbA_1c) thresholds have been recommended in older and/or frail type 2 diabetes (T2D) patients than in younger and less frail patients for initiating hypoglycemic agents since 2011. We aimed to assess trends in HbA_1c thresholds at initiation of a first hypoglycemic agent(s) in T2D patients and the influence of age and frailty on these trends.

Materials and methods

The groningen initiative to analyze type 2 diabetes treatment (GIANTT) database was used, which includes primary care T2D patients from the north of the Netherlands. Patients initiating a first non‐insulin hypoglycemic agent(s) between 2008 and 2014 with an HbA_1c measurement within 120 days before initiation were included. The influence of calendar year, age, or frailty and the interaction between calendar year and age or frailty were assessed using multilevel regression analyses adjusted for confounders.

Results

We included 4588 patients. The mean HbA_1c threshold at treatment initiation was 7.4% up to 2010, decreasing to 7.1% in 2011 and increasing to 7.4% in 2014. This quadratic change over the years was significant (P < 0.001). Patients aged 60 to 79 initiated treatments at lower HbA_1c and patients of different frailty at similar HbA_1c levels. The interaction between year and age or frailty was not significant (P > 0.05).

Conclusions

HbA_1c thresholds at initiation of a first hypoglycemic agent(s) changed significantly over time, showing a decrease after 2010 and an increase after 2012. The HbA_1c threshold at initiation was not influenced by age or frailty, which is in contrast with recommendations for more personalized treatment.

Comparison of HBA1c Goals Proposed by an Algorithm To Those Set By Different Members of Healthcare Teams Within the Dartmouth Hitchcock Health System

OBJECTIVE

An individualized approach is recommended by guidelines when establishing hemoglobin A1c (HbA1c) goals. Setting a goal requires experience and awareness; it is time consuming and not always trivial. A previous study proposed an algorithm for assessing the recommended HbA1c target according to individual patient characteristics. Few investigations have explored the variation of HbA1c goals recommended among different types of providers.

METHODS

We conducted a survey regarding practice settings, practices related to diabetes mellitus type 2, and HbA1c targets recommended to patients. Our objective was to compare HbA1c goals between Dartmouth Hitchcock Healthcare System providers (including endocrinology department, general internal medicine, and family medicine providers) and a previously validated algorithm. The clinical cases presented were those used in the previously published study.

RESULTS

The survey was sent to 228 healthcare providers of whom 81 (35.5%) responded. As recommended by the guidelines, healthcare providers individualize their patients' glycemic goals. The glycemic goals proposed by the providers in our institution were similar to those proposed by the international diabetologists and by the algorithm.

CONCLUSION

Our results further validate the proposed algorithm within a heterogeneous population of healthcare providers. The algorithm could help establish glycemic goals and assist healthcare systems in providing more standardized care.

ABBREVIATIONS

ADA = American Diabetes Association; APRN = advanced practice registered nurse; DH = Dartmouth Hitchcock Healthcare System; FM = family medicine; GIM = general internal medicine; HbA1c = hemoglobin A1c; PA-C = certified physician assistant.