Primary Care Diabetes最新文献

Aim

Metabolic syndrome (MetS) is associated with higher cardiovascular and metabolic risks, as well as with psychosocial disorders. Data regarding quality of life (QoL) in patients with MetS, point towards a significative association between MetS and a worse QoL. It remains unclear whether MetS components and non-alcoholic fatty liver disease (NAFLD) are associated with QoL in these individuals. We aimed to evaluate the association between QoL of patients with MetS and prespecified metabolic parameters (anthropometric, lipidic and glucose profiles), the risk of hepatic steatosis and fibrosis, and hepatic elastography parameters.

Methods

Cross-sectional study including patients from microDHNA cohort. This cohort includes patients diagnosed with MetS, 18 to 75 years old, followed in our tertiary center. The evaluation included anamnesis, physical examination, a QoL questionnaire (Short-Form Health Survey, SF-36), blood sampling and hepatic elastography. We used ordered logistic regression models adjusted to sex, age and body mass index to evaluate the associations between the QoL domains evaluated by SF-36 and the prespecified parameters.

Results

We included a total of 65 participants with MetS, with 54% being female and the mean age 61.9 ± 9.6 years old. A worse metabolic profile, specifically higher waist circumference, lower HDL, higher triglycerides, and more severe hepatic steatosis, were associated with worse QoL scores in several domains. We found no significant association of hepatic fibrosis with QoL.

Conclusion

Our data suggests that there is a link between a worse metabolic profile (specifically poorer lipidic profile and presence of hepatic steatosis) and a worse QoL in patients with MetS.

Background

Glycated hemoglobin A1c (HbA1c) variation or blood pressure (BP) variation was known to be an independent predictor of all-cause mortality in patients with type 2 diabetes mellitus (T2DM). This study aimed to investigate the combined effect of HbA1c and systolic blood pressure (SBP) variation on all-cause mortality and if there was a gender difference in patients with T2DM.

Methods

Patients with T2DM who had at least three HbA1c, SBP measurements within 12–24 months during 2001–2007 were included. Coefficient of variation (CV) was used to evaluate variation. The 75th percentile of HbA1c-CV and SBP-CV were set as a cutoff to define high and low variation. Hazard ratios (HRs) and 95% confidence intervals were estimated using Cox proportional hazard models.

Results

A total of 2744 patients were included, of whom 769 died during the 11.7 observation years. The associated risk of all-cause mortality was 1.22 [1.01- 1.48], P = 0.044, for low HbA1c-CV & high SBP-CV; 1.28 [1.04–1.57], P = 0.020, for high HbA1c-CV & low SBP-CV; and 1.68 [1.31–2.17], P < 0.001, for high HbA1c-CV & high SBP-CV. The associated risk remained unchanged in either males or females older than 50 years old, although there is only numerically higher for high HbA1c-CV & low SBP-CV in females older than 50 years old.

Conclusions

Both HbA1c and SBP variation were significant predictors of all-cause mortality in patients with T2DM. The combined effect was higher than either alone and no gender difference in patients older than 50 years old.

Introduction

The COVID-19 pandemic affected diabetes care among type 2 diabetes (T2D) patients. However, it is not known whether the observed changes in care concern all T2D patients equally. We examined the changes in health service usage and treatment outcomes among T2D patients according to the pre-pandemic follow-up activity.

Methods

We analysed electronic health records of 11 083 T2D patients in North Karelia, Finland (March 2017–March 2021), categorizing them by pre-pandemic T2D-related in-person contact frequency. We focused on HbA1c and LDL measurement activity and treatment targets as care indicators.

Results

Overall, health service usage and recording rates for HbA1c and LDL decreased during the pandemic. They decreased most but stayed at the highest level among patients with the most consistent pre-pandemic face-to-face service use, characterised by the highest proportion of comorbidities and elevated HbA1c. Their treatment outcomes were not negatively affected. In contrast, service usage and measurement activities increased among those with no pre-pandemic contact.

Conclusion

Those with consistent pre-pandemic service use and greater service needs were more likely to seek face-to-face care despite the lockdown, and no negative effect on treatment outcomes was seen.

Aims

Diabetic kidney disease (DKD) is the major complication of diabetes mellitus (DM) and one of the leading causes of end-stage renal disease. Early detection and treatment are contributing to delay the progression of DKD. Dietary management has potential benefits for DKD, especially the intake of polyunsaturated fatty acids (PUFAs). However, there is a lack of sufficient evidence, so we aimed to explore the association between PUFAs intake and DKD progression.

Methods

In the National Heath and Nutrition Examination Survey (NHANES) between 2011–2018, a cross-sectional study was conducted among adults with T2DM. DKD was diagnosed with urine albumin to creatinine ratio (ACR) ≥ 30 mg/g or estimated glomerular filtration rate (eGFR) ＜60 ml/min/1.73 m². Using Survey package of R to arrange the collected PUFAs intake data in order from small to large and divide them into four equal parts, which were expressed as Q1, Q2, Q3 and Q4 respectively. To investigate the association between PUFAs intake and DKD, a weighted univariate logistic regression analysis was performed and the odds ratio (OR) and 95% confidence interval (CI) were calculated for the association with DKD and PUFAs quartiles.

Results

The study involved 3287 participants with T2DM, including 2043 non-DKD and 1244 DKD patients. The results showed that the intake of PUFAs was a protective factor for DKD (p = 0.022), and with the increase of the PUFAs, renal function improved in DKD patients, the adjusted mean of eGFR and Scr changing from 57 (41, 86) in Q1 to 71 (55, 101) ml/min in Q4 (p 0.001), 103 (73, 131) in Q1 to 90 (68, 117) in Q4 (p = 0.031), respectively.

Conclusion

Our study indicated that intake of more PUFAs may contribute to delay DKD progression, while different n-6/n-3 ratios need to be explored to protect the kidney.

Aims

We aimed to compare the effectiveness of Glargine plus Glulisine to premixed insulin analogue, as measured by HbA1c ≤ 7.0% in insulin naive Type 2 Diabetes (T2D) patients with elevated fasting and/or postprandial plasma glucose.

Methods

Insulin-naive T2D patients (116 men, 84 women) on ≥ 2 oral hypoglycemic agents with inadequate glycemic control were randomized either to group 1 (insulin Glargine plus Glulisine, n = 101) or group 2 (Premixed Insulin analogue, n = 99).

Results

In the intention to treat analysis, at week 24, percentage of patients with good glycaemic control (HbA1c ≤ 7.0%) was similar between the two groups (16.8% in Group 1 vs. 13.1% in Group 2, χ2 – 0.535, p = 0.47). Significant reductions in fasting and postprandial levels were observed in groups 1 and 2 at both post-baseline time points (Week 12 and 24). In group 1, reduction in HbA1c from baseline to week 12 was 0.6 ± 0.1 and 0.7 ± 0.2 at week 24, p < 0.0001 for all. In group 2, no significant change in HbA1c was observed. In group 1, 83.2% required an additional dose of glulisine and in group 2, 88.9% required an additional dose of premixed insulin. Hypoglycemic events were similar in both groups (0.12 events per person-year in group 1 and 0.13 events per person-year in group 2). Weight gain was non-significant in both groups.

Conclusions

Glargine plus Glulisine, though in higher dose was effective as premixed insulin in lowering HbA1c. Hypoglycemic events per person-year were similar in both groups.

Aims

We conducted a systematic review and meta-analysis to investigate the effect of exercise training on HbA1c, and on fasting and postprandial plasma glucose concentrations in patients with diabetic peripheral neuropathy (DPN).

Methods

Two independent researchers performed a systematic search in the electronic databases of PubMed, Web of Science and Scopus. Studies investigating the effect of exercise training on patients diagnosed with DPN using a randomized-controlled design were included in the meta-analysis.

Results

Of 1254 retrieved studies, 68 studies were identified to undergo full-text review; out of these a total of 13 randomized trials met the inclusion criteria. Eleven studies assessed HbA1c, 8 fasting plasma-glucose concentration, and 3 postprandial plasma-glucose concentration. Overall, exercise training significantly decreased HbA1c [−0.54% (95% CI −0.78 to −0.31%)], fasting plasma glucose [−32.6 mg/dl [−1.8 mmol/L] (–44.2 to –20.9 mg/dl [−2.4 to −1.1 mmol/L])] and postprandial plasma glucose [−67.5 mg/dl [−3.7 mmol/L] (–129.5 to −5.4 mg/dl [−7.1 to −0.3 mmol/L])]. Studies with aerobic training intervention yielded the largest significant mean reduction in HbA1c (−0.75%) and fasting plasma glucose concertation (34.0 mg/dl).

Conclusions

aerobic training is the most effective modality to reduces HbA1c, fasting and postprandial plasma glucose concentration in patients with DPN. From a metabolic perspective, the magnitude precision range of the reduction in HbA1c is of clinical importance for patients with DPN. This area of research warrants further attention to investigate the impact of various exercise modalities on glycemic control.

Registration number CRD42023413687

Aims

To assess diabetes-related complications, glycemic levels, and healthcare utilization 12 months after exposure to therapeutic inertia among patients with type 2 diabetes mellitus (T2D).

Methods

This retrospective cohort study analyzed data from the OneFlorida Clinical Research Consortium (electronic health records from Florida practices/clinics). The cohort included adult patients (≥18 years old) with T2D who had an HbA1c≥7.0% (53 mmol/mol) recorded from January 1, 2014-September 30, 2019. Therapeutic inertia (exposed vs. not exposed) was evaluated during the six months following HbA1c≥7.0% (53 mmol/mol). The outcomes assessed during the 12-month follow-up period included diabetes-related complications (continuous Diabetes Complications and Severity Index (DCSI)), glycemic levels (continuous follow-up HbA1c lab), and healthcare utilization counts. We analyzed data using multivariable regression models, adjusting for covariates.

Results

The cohort included 26,881 patients with T2D (58.94% White race, 49.72% female, and mean age of 58.82 (SD=13.09)). After adjusting for covariates, therapeutic inertia exposure was associated with lower DCSI (estimate=−0.14 (SE=0.03), p < 0.001), higher follow-up HbA1c (estimate=0.14 (SE=0.04), p < 0.001), and lower rates of ambulatory visits (rate ratio=0.79, 95% CI=0.75–0.82).

Conclusions

Findings communicate the clinical practice implications and public health implications for combating therapeutic inertia in diabetes care.

Aims

Although diabetes management decisions in primary care are typically based largely on HbA1c, mismatches between HbA1c and other measures of glycemia that are increasingly more available present challenges to optimal management. This study aimed to assess a systematic approach to identify the frequency of mismatches of potential clinical significance amongst various measures of glycemia in a primary care setting.

Methods

Following screening to exclude conditions known to affect HbA1c interpretation, HbA1c, and fructosamine were obtained and repeated after ∼90 days on 53 adults with prediabetes or type 2 diabetes. A subset of 13 participants with repeat labs wore continuous glucose monitoring (CGM) for 10 days.

Results

As expected, HbA1c and fructosamine only modestly correlated (initial R² = 0.768/repeat R² = 0.655). The HbA1c/fructosamine mismatch frequency of ± 0.5% (using the following regression HbA1c = 0.015 *fructosamine + 2.994 calculated from the initial sample) was 27.0%. Of the 13 participants with CGM data, HbA1c and CGM-based Glucose Management Indicator correlated at R² = 0.786 with a mismatch frequency of ± 0.5% at 46.2% compared to a HbA1c/fructosamine mismatch frequency of ± 0.5% at 30.8%.

Conclusions

HbA1c is frequently mismatched with fructosamine and CGM data. As each of the measures has strengths and weaknesses, the utilization of multiple different measures of glycemia may be informative for diabetes assessment in the clinical setting.

The COVID-19 pandemic disrupted chronic disease management in the United States and across the world. This study reports minimal effects of the initial COVID-19 surge on body mass index, blood pressure, cholesterol, and blood glucose control in ambulatory general internal medicine patients with Type 2 diabetes at a single academic center.

Objective

To assess risk factors and factors associated with nonachievement of the treatment target levels among 75-year-old Finns with type 2 diabetes (T2D).

Design

Cross-sectional study.

Setting

Outpatient.

Subjects

Seventy-five-year-old participants of the Turku Senior Health Clinic Study (N = 1296) with T2D (n = 247).

Main outcome measures:

Nonachievement of fasting blood glucose (FBG), low-density lipoprotein (LDL-C), and blood pressure (BP) levels set by the national treatment guidelines.

Results

Nonachievement rates of FBG, BP and LDL-C were 47%, 85%, and 47%, respectively. Non-usage of T2D medication was negatively (adjusted OR 0.38, 95% CI 0.16–0.88) and central obesity positively (1.88, 1.09–3.24) related to nonachievement of FBG target level; alcohol use was positively (3.71, 1.04–13.16) and decreased self-rated health negatively (0.34, 0.12–0.97) related to the nonachievement of BP target level. Nonachievement of LDL-C target level was positively related to poor financial status (3.50, 1.19–10.28) and non-use of lipid-lowering medication (7.70, 4.07–14.56).

Conclusions

Nonachievement rates of the national treatment goals were high among older T2D patients, and nonachievement was related to use of medication, obesity, alcohol use, poor health, and poor financial status. We emphasize the importance of customized target setting by risk factor levels and active treatment.