Primary Care Diabetes最新文献

Introduction

This study will explore the effectiveness of fish skin grafts (FSG) in ulcer healing in diabetic foot disease compared to standard of care (SOC).

Methods

The systematic review and meta-analysis were performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standard. The electronic databases of PubMed, EMBASE, and Web of Science (WoS) internet were searched for the outcome rate of complete ulcer healing. The risk of bias assessment was conducted using the tool recommended by the Cochrane Collaboration. Statistical analysis included the individual and combined result of the studies, heterogeneity test, the effect size, sensitivity analysis, and publication bias tests.

Results

Five randomised controlled trials (RCTs) with a total of 411 patients were included in this study. This meta-analysis showed a higher rate of complete ulcer healing in groups receiving fish skin grafts (OR = 3.34, 95% CI 2.14–5.20, p < 0.01, I² = 0%) compared to control groups.

Conclusion

Fish skin grafts have been shown to be more effective for achieving complete ulcer healing compared to current conventional treatments in diabetic foot disease.

Studies have shown that fasting during Ramadan has different effects on circulating levels of several biochemical markers. This study aims to conduct a comprehensive evaluation of studies related to the effect of fasting in the holy month of Ramadan on lipid profile, uric acid, and HbA1c in CKD patients. Studies were systematically searched and collected from three databases (PubMed, Scopus, and Web of Science). After screening, the quality and risk of bias assessment of the selected articles were evaluated. Study heterogeneity was assessed using the Cochrane test and I² statistic. In case of any heterogeneity random effects model with the inverse-variance method was applied. All analyses were performed using STATA software version 16. Four observational studies were included in this study. The results of this meta-analysis were that cholesterol (Weighted mean differences (WMD):0.21 with 95% CI:-0.09–0.51 (P-value=:0.18)), LDL (WMD:0.06 with 95% CI −0.24–0.36 (P-value:0.69)), triglyceride (WMD:0.05 with 95% CI:-0.25–0.35 (P-value:0.73)) had not-significant increase. Uric acid (WMD: −0.11 with 95% CI: −0.42–0.21 (P-value:0.51)) and HbA1c (WMD: −0.22 with 95% CI: −0.79–0.36 (P-value: 0.46)) show a non-significant decrease. The results of the analyses did not report significant changes in the lipid profile, uric acid, and HbA1c in CKD patients after Ramadan fasting.

Aims

Machine learning models can use image and text data to predict the number of years since diabetes diagnosis; such model can be applied to new patients to predict, approximately, how long the new patient may have lived with diabetes unknowingly. We aimed to develop a model to predict self-reported diabetes duration.

Methods

We used the Brazilian Multilabel Ophthalmological Dataset. Unit of analysis was the fundus image and its meta-data, regardless of the patient. We included people 40 + years and fundus images without diabetic retinopathy. Fundus images and meta-data (sex, age, comorbidities and taking insulin) were passed to the MedCLIP model to extract the embedding representation. The embedding representation was passed to an Extra Tree Classifier to predict: 0–4, 5–9, 10–14 and 15 + years with self-reported diabetes.

Results

There were 988 images from 563 people (mean age = 67 years; 64 % were women). Overall, the F1 score was 57 %. The group 15 + years of self-reported diabetes had the highest precision (64 %) and F1 score (63 %), while the highest recall (69 %) was observed in the group 0–4 years. The proportion of correctly classified observations was 55 % for the group 0–4 years, 51 % for 5–9 years, 58 % for 10–14 years, and 64 % for 15 + years with self-reported diabetes.

Conclusions

The machine learning model had acceptable accuracy and F1 score, and correctly classified more than half of the patients according to diabetes duration. Using large foundational models to extract image and text embeddings seems a feasible and efficient approach to predict years living with self-reported diabetes.

Aim

To assess the willingness of people with type 2 diabetes (T2D) to engage in healthy eating, physical activity and medication taking, and explore associated patient factors.

Methods

Online survey among recently diagnosed T2D patients recruited in the Netherlands and the United Kingdom (UK). Patient factors included general factors and behaviour-specific beliefs. Logistic regression analyses and explorative comparisons were conducted.

Results

Overall, 48% of 67 patients were willing to engage in all three management options, whereas 6% were not willing to follow any of them. 73% were willing to manage T2D with healthy eating, 73% with physical activity, and 72% with medication. Country of recruitment was significantly associated with willingness for healthy eating, with higher willingness among Dutch participants. Beliefs surrounding capability, opportunity, and motivation were significantly associated with willingness to engage in physical activity and medication taking. Many beliefs were similar regardless of willingness but those willing to engage in physical activity perceived less barriers and those willing to take medication had more positive and less negative outcome beliefs than those not willing.

Conclusions

Willingness to engage in all management options was limited among recently diagnosed patients, and partly associated with behaviour-specific patient beliefs.

Aim

Describe the rationale for and design of Diabetes Remote Intervention to improVe use of Evidence-based medications (DRIVE), a remote medication management program designed to initiate and titrate guideline-directed medical therapy (GDMT) in patients with type 2 diabetes (T2D) at elevated cardiovascular (CV) and/or kidney risk by leveraging non-physician providers.

Methods

An electronic health record based algorithm is used to identify patients with T2D and either established atherosclerotic CV disease (ASCVD), high risk for ASCVD, chronic kidney disease, and/or heart failure within our health system. Patients are invited to participate and randomly assigned to either simultaneous education and medication management, or a period of education prior to medication management. Patient navigators (trained, non-licensed staff) are the primary points of contact while a pharmacist or nurse practitioner reviews and authorizes each medication initiation and titration under an institution-approved collaborative drug therapy management protocol with supervision from a cardiologist and/or endocrinologist. Patient engagement is managed through software to support communication, automation, workflow, and standardization.

Conclusion

We are testing a remote, navigator-driven, pharmacist-led, and physician-overseen management strategy to optimize GDMT for T2D as a population-level strategy to close the gap between guidelines and clinical practice for patients with T2D at elevated CV and/or kidney risk.

Introduction

Structured diabetes care based on evidence-based guidelines is one of the main strategies to improve glycemic control and to reduce long-term complications in diabetes mellitus.

Methods

This study is based on the “Diabetes-Landeck Cohort”, a population-based cohort of patients with diabetes mellitus type 2 (T2DM). We assessed the quality of diabetes care and compared it between three groups of care units, that is, general practitioners (GP), diabetes specialists in private practice (DSPP), and hospitals (HOSP).

Results

The total study population comprised 1616 patients with T2DM, including 378 patients of GP, 281 of DSPP, and 957 from HOSP. We identified statistically significant differences: DSPP showed the highest percentage of structured training, sufficient training, eye examinations and foot examinations. The group HOSP showed the highest proportion for increased HbA1c≥ 7.5 and almost all long-term complications surveyed, that is, nephropathy (23.2%), neuropathy (14.4%), diabetic foot (5.1%), and cerebrovascular diseases (10.9%).

Conclusion

This population-based cohort study on patients with T2DM in Austria showed significant differences in important quality-of-care process and outcome parameters across different groups of care units. Future research should also include prediction modeling for early warning and monitoring systems as well as adjustment for patient characteristics and duration and severity of disease.

Background and Aims

To 1) assess the reliability and validity of the Turkish version of the Problem Areas in Diabetes (PAID), PAID-5 and PAID-1 survey among Turkish adults with type 1 or type 2 diabetes, 2) estimate the level of elevated diabetes-specific distress (DD), and 3) determine the demographic and clinical correlates of DD-symptom severity.

Methods and Results

From 2017–2019, 252 adults with type 1(n = 80) (T1DM) or type 2 diabetes (n = 172) (T2DM) self-reported demographic factors, DD(PAID) and related psychological and clinical questionnaires. We examined PAID internal consistency, structural and convergent validity. Associations of measures with DD were explored with hierarchical linear regression analysis. PCA yielded a 3-factor solution for PAID-20 and a 2-factor solution for PAID-5. Cronbach’s α for PAID/PAID-5 subscales ranged from 0.63–0.90. All PAID versions correlated most strongly to BIPQ and HFS. The prevalence of elevated distress (PAID-20 ≥33) was 40% in T1DM and 15% in T2DM. DD severity was significantly positively associated (p < 0.01) with more negative diabetes perceptions (BIPQ) and type 1 diabetes.

Conclusions

The Turkish translation of the PAID and its short forms appeared to have satisfactory psychometric properties. Elevated diabetes distress was more common in T1DM.

Introduction

Gestational diabetes mellitus (GDM) is globally increasing due to changes in risk factors such as gestational age, obesity, and socioeconomic status (SES). This study examined trends of GDM prevalence over ten years using a real-world Primary Health Care database from Catalonia (Spain). Methods: A retrospective analysis of pregnant women screened for GDM was conducted, using clinical and SES data from the SIDIAP database. Results: Among 221,806 women studied from 2010 to 2019,17,587 had GDM, equating to a 7.9% prevalence (95% CI 7.8–8.04). GDM subjects were older (33.5 ± 5.1 vs. 31.2 ± 5.6 years; p < 0.001) and had higher BMI (29.2 ± 5.1 vs .27.8 ± 4.8 kg/m²; p < 0.001) than non-GDM individuals. Overall GDM prevalence remained unchanged throughout the study, although an increase was observed in younger women (below 20 years: 1.28% [95% CI 0.59–2.42] in 2010 to 2.22% [95% CI 0.96–4.33] in 2019, p = 0.02; ages 20–25.9 years: 3.62% [95% CI 3.12–4.17] in 2010 to 4.63% [95% CI 3.88–5.48)] in 2019, p = 0.02). Age, BMI ≥ 25 kg/m2, deprived SES, and previous hypertension and dyslipidaemia were positively associated with GDM.

Conclusions

This study offers insights into GDM prevalence in Catalonia (Spain),showing overall stability except for a rising trend among younger women.

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.

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.