This study aims to evaluate the changes in clinical profiles, complications, and treatment modalities of people with diabetes after a decade of implementing the multidisciplinary Risk Assessment and Management Program in DM (RAMP-DM).
Methods
A two-phase cross-sectional study was conducted to examine the evolution of care for people with diabetes in 13 public primary care clinics from 1 August 2008 to 31 July 2009 and 1 August 2019 to 31 July 2020.
Results
The average systolic blood pressure (SBP) improved from 131.66±16.89 to 126.88±12.54 mmHg (P<0.001). Hemoglobin A1c (HbA1c) and low-density lipoprotein concentration (LDL-C) improved from 7.47±1.4 to 6.88±1.00% (P<0.001) and 3.09±0.85 to 2.01±0.68 mmol/L (P<0.001), respectively. However, the percentage of patients with ischemic heart disease (IHD) rose from 7.73% to 10.47% (P<0.001), and stroke increased from 8.22% to 12.44% (P<0.001) over the decade.
Conclusions
This is the first study to demonstrate the improvement of clinical parameters and treatment modalities of diabetes care in a public primary care setting over a decade. The increasing prevalence of IHD and stroke may be related to the aging population and the decreasing trend of all-cause mortality among people with diabetes.
{"title":"Evolution of Diabetes Mellitus Care in Hong Kong Public Primary Care Setting: Changes after 10-year Implementation of Risk Assessment and Management Program in Diabetes Mellitus (RAMP-DM)","authors":"Fangfang Jiao, Lapkin Chiang, Yim Chu Li, Catherine Xiaorui Chen","doi":"10.1016/j.pcd.2025.10.002","DOIUrl":"10.1016/j.pcd.2025.10.002","url":null,"abstract":"<div><h3>Aims</h3><div>This study aims to evaluate the changes in clinical profiles, complications, and treatment modalities of people with diabetes after a decade of implementing the multidisciplinary Risk Assessment and Management Program in DM (RAMP-DM).</div></div><div><h3>Methods</h3><div>A two-phase cross-sectional study was conducted to examine the evolution of care for people with diabetes in 13 public primary care clinics from 1 August 2008 to 31 July 2009 and 1 August 2019 to 31 July 2020.</div></div><div><h3>Results</h3><div>The average systolic blood pressure (SBP) improved from 131.66±16.89 to 126.88±12.54 mmHg (P<0.001). Hemoglobin A1c (HbA1c) and low-density lipoprotein concentration (LDL-C) improved from 7.47±1.4 to 6.88±1.00% (P<0.001) and 3.09±0.85 to 2.01±0.68 mmol/L (P<0.001), respectively. However, the percentage of patients with ischemic heart disease (IHD) rose from 7.73% to 10.47% (P<0.001), and stroke increased from 8.22% to 12.44% (P<0.001) over the decade.</div></div><div><h3>Conclusions</h3><div>This is the first study to demonstrate the improvement of clinical parameters and treatment modalities of diabetes care in a public primary care setting over a decade. The increasing prevalence of IHD and stroke may be related to the aging population and the decreasing trend of all-cause mortality among people with diabetes.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 671-677"},"PeriodicalIF":2.3,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145282370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-07DOI: 10.1016/j.pcd.2025.10.001
Jannie Toft Damsgaard Nørlev , Thomas Kronborg , Morten Hasselstrøm Jensen , Peter Vestergaard , Stine Hangaard
Aims
Although telemonitoring has emerged as a strategy to overcome barriers related to poor adherence, insulin dose deviations remain common. Yet, the reason remains unclear. This study investigated the reasons for dose deviations in people with insulin-treated type 2 diabetes (T2D) receiving telemonitoring.
Methods
Data were provided from 331 participants with insulin-treated T2D (DiaMonT, NCT 04981808). Participants were either telemonitored using a continuous glucose monitor (CGM), a connected insulin pen, and an activity watch or treated according to standard of care, using blinded devices. Reasons for dose deviations were categorized, and descriptive statistics were used to summarize the findings.
Results
A total of 24 distinct reasons for insulin dose deviations were reported. These were grouped into: (1) actual deviations (40.1 %; n = 148) (e.g., limited understanding of T2D and access to CGM data), (2) justified deviations (40.7 %; n = 150) (e.g., illness and use of a non-connected pen), and (3) device-related deviations (19.2 %; n = 71) (e.g., technical issues).
Conclusions
This study highlights the need for a nuanced interpretation of adherence data and suggests that telemonitoring should engage patients in treatment discussions and support education in diabetes self-management. These insights are key to maximizing the benefits of telemonitoring while avoiding misinterpretation or over-intervention.
{"title":"Understanding insulin dose deviations in people with type 2 diabetes receiving telemonitoring","authors":"Jannie Toft Damsgaard Nørlev , Thomas Kronborg , Morten Hasselstrøm Jensen , Peter Vestergaard , Stine Hangaard","doi":"10.1016/j.pcd.2025.10.001","DOIUrl":"10.1016/j.pcd.2025.10.001","url":null,"abstract":"<div><h3>Aims</h3><div>Although telemonitoring has emerged as a strategy to overcome barriers related to poor adherence, insulin dose deviations remain common. Yet, the reason remains unclear. This study investigated the reasons for dose deviations in people with insulin-treated type 2 diabetes (T2D) receiving telemonitoring.</div></div><div><h3>Methods</h3><div>Data were provided from 331 participants with insulin-treated T2D (DiaMonT, NCT 04981808). Participants were either telemonitored using a continuous glucose monitor (CGM), a connected insulin pen, and an activity watch or treated according to standard of care, using blinded devices. Reasons for dose deviations were categorized, and descriptive statistics were used to summarize the findings.</div></div><div><h3>Results</h3><div>A total of 24 distinct reasons for insulin dose deviations were reported. These were grouped into: (1) actual deviations (40.1 %; n = 148) (e.g., limited understanding of T2D and access to CGM data), (2) justified deviations (40.7 %; n = 150) (e.g., illness and use of a non-connected pen), and (3) device-related deviations (19.2 %; n = 71) (e.g., technical issues).</div></div><div><h3>Conclusions</h3><div>This study highlights the need for a nuanced interpretation of adherence data and suggests that telemonitoring should engage patients in treatment discussions and support education in diabetes self-management. These insights are key to maximizing the benefits of telemonitoring while avoiding misinterpretation or over-intervention.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 602-607"},"PeriodicalIF":2.3,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145246105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-04DOI: 10.1016/j.pcd.2025.08.010
Yiwei Qiu , Yao Tang , Yixuan Li , Li Cheng , Xu Wang , Baofeng Du , Ruhai Bai
Background
Online health management has been implemented to improve glycemic control in patients with type 2 diabetes mellitus (T2DM). This study aims to evaluate the effectiveness of online health management interventions in managing T2DM through a systematic review and meta-analysis.
Methods
A comprehensive search was conducted in six databases—PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure, and Wanfang Data—from January 1, 2010, to September 1, 2024. Eligible studies included randomized controlled trials (RCTs) involving adults (≥ 18 years) diagnosed with T2DM. Two independent reviewers screened the studies and assessed the risk of bias. Meta-analyses were performed using Review Manager 5.4 (Cochrane Collaboration). The primary outcomes included glycated hemoglobin (HbA1c), fasting blood glucose (FBG), and postprandial blood glucose (PBG).
Results
Out of 6283 records screened, 44 RCTs involving 27,178 T2DM patients were included (16,972 in the intervention group and 10,206 in the control group). Pooled results showed that online health management interventions significantly improved HbA1c, FBG, PBG, systolic blood pressure, diastolic blood pressure, and waist circumference. Improvements were also observed in dietary behavior, physical activity, and self-efficacy. However, no significant effects were found on body weight, body mass index, or lipid metabolism parameters, including total cholesterol, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. Subgroup analyses indicated that interventions delivered by physicians, those targeting individuals aged ≥ 60 years, and those using digital coaching for less than six months were more effective in glycemic control.
Conclusion
Online health management interventions may effectively support glycemic and blood pressure control and self-management in T2DM patients. Nevertheless, additional research with larger sample sizes and more extended follow-up periods is justified due to the substantial heterogeneity and limitations across the included studies.
背景：在线健康管理已被用于改善2型糖尿病（T2DM）患者的血糖控制。本研究旨在通过系统回顾和荟萃分析来评估在线健康管理干预在管理2型糖尿病方面的有效性。方法：从2010年1月1日至2024年9月1日，对pubmed、Web of Science、Cochrane Library、Embase、中国知识基础设施和万方数据6个数据库进行综合检索。符合条件的研究包括诊断为T2DM的成年人（≥18岁）的随机对照试验（RCTs）。两名独立审稿人筛选了这些研究并评估了偏倚风险。meta分析采用Review Manager 5.4 （Cochrane Collaboration）进行。主要结局包括糖化血红蛋白（HbA1c）、空腹血糖（FBG）和餐后血糖（PBG）。结果：在筛选的6283份记录中，纳入44项随机对照试验，涉及27,178例T2DM患者（干预组16,972例，对照组10,206例）。综合结果显示，在线健康管理干预显著改善了HbA1c、FBG、PBG、收缩压、舒张压和腰围。在饮食行为、体育活动和自我效能方面也有改善。然而，没有发现对体重、体重指数或脂质代谢参数（包括总胆固醇、甘油三酯、高密度脂蛋白胆固醇和低密度脂蛋白胆固醇）有显著影响。亚组分析表明，由医生提供的干预措施，针对年龄≥ 60岁的个体，以及使用数字指导少于6个月的干预措施在血糖控制方面更有效。结论：在线健康管理干预可有效支持T2DM患者血糖、血压控制和自我管理。然而，由于纳入研究的异质性和局限性，需要进行更大样本量和更长的随访期的额外研究。
{"title":"The effect of online health management on type 2 diabetes mellitus: A systematic review and meta-analysis","authors":"Yiwei Qiu , Yao Tang , Yixuan Li , Li Cheng , Xu Wang , Baofeng Du , Ruhai Bai","doi":"10.1016/j.pcd.2025.08.010","DOIUrl":"10.1016/j.pcd.2025.08.010","url":null,"abstract":"<div><h3>Background</h3><div>Online health management has been implemented to improve glycemic control in patients with type 2 diabetes mellitus (T2DM). This study aims to evaluate the effectiveness of online health management interventions in managing T2DM through a systematic review and meta-analysis.</div></div><div><h3>Methods</h3><div>A comprehensive search was conducted in six databases—PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure, and Wanfang Data—from January 1, 2010, to September 1, 2024. Eligible studies included randomized controlled trials (RCTs) involving adults (≥ 18 years) diagnosed with T2DM. Two independent reviewers screened the studies and assessed the risk of bias. Meta-analyses were performed using Review Manager 5.4 (Cochrane Collaboration). The primary outcomes included glycated hemoglobin (HbA1c), fasting blood glucose (FBG), and postprandial blood glucose (PBG).</div></div><div><h3>Results</h3><div>Out of 6283 records screened, 44 RCTs involving 27,178 T2DM patients were included (16,972 in the intervention group and 10,206 in the control group). Pooled results showed that online health management interventions significantly improved HbA1c, FBG, PBG, systolic blood pressure, diastolic blood pressure, and waist circumference. Improvements were also observed in dietary behavior, physical activity, and self-efficacy. However, no significant effects were found on body weight, body mass index, or lipid metabolism parameters, including total cholesterol, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. Subgroup analyses indicated that interventions delivered by physicians, those targeting individuals aged ≥ 60 years, and those using digital coaching for less than six months were more effective in glycemic control.</div></div><div><h3>Conclusion</h3><div>Online health management interventions may effectively support glycemic and blood pressure control and self-management in T2DM patients. Nevertheless, additional research with larger sample sizes and more extended follow-up periods is justified due to the substantial heterogeneity and limitations across the included studies.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 561-576"},"PeriodicalIF":2.3,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145234268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01DOI: 10.1016/j.pcd.2025.09.004
Chih-Yuan Wang , Jung-Fu Chen , Shih-Te Tu , Chun-Chuan Lee , Horng-Yih Ou
The growing prevalence of type 2 diabetes mellitus (T2DM) poses a significant challenge to healthcare systems globally. Microvascular diseases, including diabetic kidney disease, retinopathy, and neuropathy, are frequent complications of T2DM and may signal an increased risk of macrovascular diseases, such as stroke and myocardial infarction. This study, based on prior findings from a nationwide cohort in Taiwan demonstrated that individuals with two or more macrovascular complications had elevated risks of cardiovascular events and mortality over a median follow-up of 3.3 years. Building on this, the current study develops a practical risk calculator for predicting 3-year cardiovascular risk. Shared pathogenic mechanisms, such as vascular injury, endothelial dysfunction, and autonomic neuropathy, may suggest these associations. In response, we developed a Risk Engine Calculator that incorporates the number of microvascular diseases, elevated HbA1c, systolic blood pressure, LDL cholesterol, and insulin use to estimate 3-year cardiovascular risk in patients with T2DM without established macrovascular complications. Patients are stratified into low, moderate, or high risk categories to guide clinical decision-making. While the calculator is practical and evidence-based, limitations include its additive design, potential simplification of risk relationships, and relatively short follow-up period. Overall, this study underscores the importance of integrating microvascular diseases burden into cardiovascular risk assessment and provides a user-friendly tool to support precision medicine in diabetes management.
{"title":"Microvascular disease burden and macrovascular outcomes in type 2 diabetes: Risk calculator in Taiwan","authors":"Chih-Yuan Wang , Jung-Fu Chen , Shih-Te Tu , Chun-Chuan Lee , Horng-Yih Ou","doi":"10.1016/j.pcd.2025.09.004","DOIUrl":"10.1016/j.pcd.2025.09.004","url":null,"abstract":"<div><div>The growing prevalence of type 2 diabetes mellitus (T2DM) poses a significant challenge to healthcare systems globally. Microvascular diseases, including diabetic kidney disease, retinopathy, and neuropathy, are frequent complications of T2DM and may signal an increased risk of macrovascular diseases, such as stroke and myocardial infarction. This study, based on prior findings from a nationwide cohort in Taiwan demonstrated that individuals with two or more macrovascular complications had elevated risks of cardiovascular events and mortality over a median follow-up of 3.3 years. Building on this, the current study develops a practical risk calculator for predicting 3-year cardiovascular risk. Shared pathogenic mechanisms, such as vascular injury, endothelial dysfunction, and autonomic neuropathy, may suggest these associations. In response, we developed a Risk Engine Calculator that incorporates the number of microvascular diseases, elevated HbA1c, systolic blood pressure, LDL cholesterol, and insulin use to estimate 3-year cardiovascular risk in patients with T2DM without established macrovascular complications. Patients are stratified into low, moderate, or high risk categories to guide clinical decision-making. While the calculator is practical and evidence-based, limitations include its additive design, potential simplification of risk relationships, and relatively short follow-up period. Overall, this study underscores the importance of integrating microvascular diseases burden into cardiovascular risk assessment and provides a user-friendly tool to support precision medicine in diabetes management.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 678-680"},"PeriodicalIF":2.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01DOI: 10.1016/j.pcd.2025.09.008
Mark P. Ranasinghe , Marly Ranasinghe , Mayurathan Balachandran , Vinay Goel , Sulochi Subasinghe , Shane Nanayakkara
Aims
Structured community-based diabetes education programs may improve cardiometabolic outcomes, yet objective evidence remains limited. We evaluated the efficacy of a multidisciplinary education program in improving glycaemic control and cardiovascular risk factors in adults with type 2 diabetes mellitus (T2DM).
Methods
Adults with T2DM participated in a four-week program comprising weekly two-hour sessions on diabetes and cardiovascular disease, nutrition, exercise, and mental health. HbA1c, body mass index (BMI), weight, blood pressure, and lipid profile were assessed at baseline and at 3, 6, and 12 months. Outcomes were analysed using pooled linear mixed-effects models with multiple imputation, with sensitivity analyses excluding participants requiring pharmacotherapy escalation.
Results
Fifty participants (median age 49 years; 38 % female) completed the program. HbA1c improved significantly and was sustained at 12 months (−1.57 % (95 %CI(-1.96, −1.17), p < 0.001). LDL cholesterol (-0.51 mmol/L (95 %CI(-0.71,-0.30), p < 0.001), triglycerides (-0.86 mmol/L (95 %CI(-1.34,-0.39), p = 0.001), and BMI (−1.45 kg/m², 95 %CI(-1.99,-0.91), p < 0.001) also improved at 12 months. These findings were supported by sensitivity analysis for HbA1c, but attenuated for other cardiometabolic parameters at 12 months.
Conclusions
A structured, multidisciplinary community-based education program was associated with significant improvements in glycaemic control and key parameters of cardiometabolic risk. As a cost-efficient model, it offers a scalable strategy for T2DM management in primary care, warranting further evaluation of interactions with pharmacotherapy.
目的：有组织的社区糖尿病教育项目可能改善心脏代谢结果，但客观证据仍然有限。我们评估了多学科教育项目在改善成人2型糖尿病（T2DM）患者血糖控制和心血管危险因素方面的效果。方法：成年T2DM患者参加了一个为期四周的项目，包括每周两小时的糖尿病和心血管疾病、营养、运动和心理健康会议。在基线、3个月、6个月和12个月时评估HbA1c、体重指数（BMI）、体重、血压和血脂。结果分析使用多重归因的合并线性混合效应模型，并进行敏感性分析，排除需要增加药物治疗的参与者。结果：50名参与者（中位年龄49岁；38% %女性）完成了该计划。HbA1c显著改善并持续12个月(-1.57 %（95 %CI(-1.96, -1.17), p ）结论：一个结构化的、多学科的社区教育项目与血糖控制和心脏代谢风险关键参数的显著改善有关。作为一种具有成本效益的模式，它为初级保健中的T2DM管理提供了一种可扩展的策略，值得进一步评估与药物治疗的相互作用。
{"title":"A structured education program for improving cardiovascular risk and glycaemic control in type 2 diabetes mellitus (the SUGAR study)","authors":"Mark P. Ranasinghe , Marly Ranasinghe , Mayurathan Balachandran , Vinay Goel , Sulochi Subasinghe , Shane Nanayakkara","doi":"10.1016/j.pcd.2025.09.008","DOIUrl":"10.1016/j.pcd.2025.09.008","url":null,"abstract":"<div><h3>Aims</h3><div>Structured community-based diabetes education programs may improve cardiometabolic outcomes, yet objective evidence remains limited. We evaluated the efficacy of a multidisciplinary education program in improving glycaemic control and cardiovascular risk factors in adults with type 2 diabetes mellitus (T2DM).</div></div><div><h3>Methods</h3><div>Adults with T2DM participated in a four-week program comprising weekly two-hour sessions on diabetes and cardiovascular disease, nutrition, exercise, and mental health. HbA1c, body mass index (BMI), weight, blood pressure, and lipid profile were assessed at baseline and at 3, 6, and 12 months. Outcomes were analysed using pooled linear mixed-effects models with multiple imputation, with sensitivity analyses excluding participants requiring pharmacotherapy escalation.</div></div><div><h3>Results</h3><div>Fifty participants (median age 49 years; 38 % female) completed the program. HbA1c improved significantly and was sustained at 12 months (−1.57 % (95 %CI(-1.96, −1.17), p < 0.001). LDL cholesterol (-0.51 mmol/L (95 %CI(-0.71,-0.30), <em>p</em> < 0.001), triglycerides (-0.86 mmol/L (95 %CI(-1.34,-0.39), p = 0.001), and BMI (−1.45 kg/m², 95 %CI(-1.99,-0.91), p < 0.001) also improved at 12 months. These findings were supported by sensitivity analysis for HbA1c, but attenuated for other cardiometabolic parameters at 12 months.</div></div><div><h3>Conclusions</h3><div>A structured, multidisciplinary community-based education program was associated with significant improvements in glycaemic control and key parameters of cardiometabolic risk. As a cost-efficient model, it offers a scalable strategy for T2DM management in primary care, warranting further evaluation of interactions with pharmacotherapy.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 592-601"},"PeriodicalIF":2.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed to investigate healthcare professionals’ practices, attitudes, and challenges in assessing and managing urological complications, including lower urinary tract symptoms (LUTSs) and erectile dysfunction (ED), in male patients with diabetes.
Methods
A 12-question online survey, distributed between April 2023 and January 2024, gathered responses from 370 physicians in Turkey. Participants represented various specialties, including endocrinology, internal medicine, family medicine, and general practice. The survey evaluated how frequently physicians inquired about symptoms, their use of validated assessment tools, and their management strategies for ED and LUTSs in male patients with diabetes.
Results
Of the participants, 40.3 % frequently asked about LUTSs, whereas 42.4 % reported rarely or never addressing these symptoms. More than 20 years of experience was significantly associated with higher inquiry rates (p = 0.001). Only 0.8 % of participants used validated symptom assessment tools. Concerning ED, 89.5 % of physicians noted that male patients with diabetes seldom reported related complaints, and only 20.3 % routinely asked about ED. Endocrinologists were significantly more likely to inquire about ED, with 36.2 % reporting such inquiries compared to 10.5 % among other specialties (p < 0.001). Most participants (53.5 %) preferred referring patients with ED to urology specialists for further management.
Conclusion
Urological complications in male patients with diabetes are under-assessed, with significant gaps in the use of validated tools and structured approaches. The study underscores the importance of raising awareness and implementing multidisciplinary strategies, such as regular symptom screening and timely interventions, to enhance patient outcomes.
{"title":"Assessment of urological complications in male patients with diabetes: Insights from a survey of healthcare providers","authors":"Mesut Altan , Emre Albayrak , Müjdat Ayva , Uğur Ünlütürk , Tomris Erbas","doi":"10.1016/j.pcd.2025.09.007","DOIUrl":"10.1016/j.pcd.2025.09.007","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to investigate healthcare professionals’ practices, attitudes, and challenges in assessing and managing urological complications, including lower urinary tract symptoms (LUTSs) and erectile dysfunction (ED), in male patients with diabetes.</div></div><div><h3>Methods</h3><div>A 12-question online survey, distributed between April 2023 and January 2024, gathered responses from 370 physicians in Turkey. Participants represented various specialties, including endocrinology, internal medicine, family medicine, and general practice. The survey evaluated how frequently physicians inquired about symptoms, their use of validated assessment tools, and their management strategies for ED and LUTSs in male patients with diabetes.</div></div><div><h3>Results</h3><div>Of the participants, 40.3 % frequently asked about LUTSs, whereas 42.4 % reported rarely or never addressing these symptoms. More than 20 years of experience was significantly associated with higher inquiry rates (p = 0.001). Only 0.8 % of participants used validated symptom assessment tools. Concerning ED, 89.5 % of physicians noted that male patients with diabetes seldom reported related complaints, and only 20.3 % routinely asked about ED. Endocrinologists were significantly more likely to inquire about ED, with 36.2 % reporting such inquiries compared to 10.5 % among other specialties (p < 0.001). Most participants (53.5 %) preferred referring patients with ED to urology specialists for further management.</div></div><div><h3>Conclusion</h3><div>Urological complications in male patients with diabetes are under-assessed, with significant gaps in the use of validated tools and structured approaches. The study underscores the importance of raising awareness and implementing multidisciplinary strategies, such as regular symptom screening and timely interventions, to enhance patient outcomes.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 667-670"},"PeriodicalIF":2.3,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145208921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-25DOI: 10.1016/j.pcd.2025.09.006
Jenifar Prashanthan , Amirthanathan Prashanthan
Background and aim
It is essential to identify the risk of developing Type 2 Diabetes Mellitus (T2DM) in women with a history of Gestational Diabetes Mellitus (GDM). This study seeks to create a machine learning (ML) model combined with explainable artificial intelligence (XAI) to predict and explain the risk of Type 2 Diabetes Mellitus (T2DM) in women with a history of Gestational Diabetes Mellitus (GDM).
Methods
A literature review found 28 risk factors, including pregnancy-related clinical risk factors, maternal characteristics, genetic risk factors, and lifestyle and modifiable risk factors. A synthetic dataset was generated utilizing subject expertise and clinical experience through Python programming. Various machine learning classification techniques were employed on the data to identify the optimal model, which integrates interpretability approaches (SHAP) to guarantee the transparency of model predictions.
Results
The developed machine learning model exhibited superior accuracy in predicting the risk of T2DM relative to conventional clinical risk scores, with notable contributions from factors such as insulin treatment during pregnancy, physical inactivity, obesity, breastfeeding, a history of recurrent GDM, an unhealthy diet, and ethnicity. Integrated XAI assists clinicians in comprehending the relevant risk factors and their influence on certain predictive outcomes.
Conclusions
Machine learning and explainable artificial intelligence provide a comprehensive methodology for individualized risk evaluation in women with a history of gestational diabetes mellitus. This methodology, by integrating extensive real-world data, offers healthcare clinicians actionable insights for early intervention.
{"title":"Predicting the future risk of developing type 2 diabetes in women with a history of gestational diabetes mellitus using machine learning and explainable artificial intelligence","authors":"Jenifar Prashanthan , Amirthanathan Prashanthan","doi":"10.1016/j.pcd.2025.09.006","DOIUrl":"10.1016/j.pcd.2025.09.006","url":null,"abstract":"<div><h3>Background and aim</h3><div>It is essential to identify the risk of developing Type 2 Diabetes Mellitus (T2DM) in women with a history of Gestational Diabetes Mellitus (GDM). This study seeks to create a machine learning (ML) model combined with explainable artificial intelligence (XAI) to predict and explain the risk of Type 2 Diabetes Mellitus (T2DM) in women with a history of Gestational Diabetes Mellitus (GDM).</div></div><div><h3>Methods</h3><div>A literature review found 28 risk factors, including pregnancy-related clinical risk factors, maternal characteristics, genetic risk factors, and lifestyle and modifiable risk factors. A synthetic dataset was generated utilizing subject expertise and clinical experience through Python programming. Various machine learning classification techniques were employed on the data to identify the optimal model, which integrates interpretability approaches (SHAP) to guarantee the transparency of model predictions.</div></div><div><h3>Results</h3><div>The developed machine learning model exhibited superior accuracy in predicting the risk of T2DM relative to conventional clinical risk scores, with notable contributions from factors such as insulin treatment during pregnancy, physical inactivity, obesity, breastfeeding, a history of recurrent GDM, an unhealthy diet, and ethnicity. Integrated XAI assists clinicians in comprehending the relevant risk factors and their influence on certain predictive outcomes.</div></div><div><h3>Conclusions</h3><div>Machine learning and explainable artificial intelligence provide a comprehensive methodology for individualized risk evaluation in women with a history of gestational diabetes mellitus. This methodology, by integrating extensive real-world data, offers healthcare clinicians actionable insights for early intervention.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 658-666"},"PeriodicalIF":2.3,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145180734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-23DOI: 10.1016/j.pcd.2025.09.003
Nanna Husted Jensen , Inger Katrine Dahl-Petersen , Karoline Kragelund Nielsen , Dorte Møller Jensen , Peter Damm , Per Ovesen , Elisabeth R. Mathiesen , Ulla Kampmann , Christina Anne Vinter , Sharleen O’Reilly , Helle Terkildsen Maindal , On behalf of the Face-it Study Group
Aims
We evaluated the fidelity of the Face-it intervention and its impact on behaviour change mechanisms among women with recent gestational diabetes mellitus (GDM).
Methods
In this randomised controlled trial, 277 women were allocated to usual care or an intervention comprising three home visits, digital platform health coaching and cross-sectoral communication to support health behaviour change during the first year after delivery. Behaviour change mechanisms included social support, motivation, self-efficacy, risk perception and health literacy. High fidelity was defined as completing three home visits and ≥ 9 coaching contacts.
Results
Within the intervention group, 86.4 % completed ≥ 2 home visits, 88.6 % registered digitally with a median (IQR) of 10.0 (3.0–20.0) contacts. At one-year after delivery, the high-fidelity group (n = 73; 39.7 %) had higher odds of perceiving moderate/high diabetes risk (OR 2.42; 95 % CI 1.06–5.51) and higher health literacy (adjusted difference 0.20; 95 % CI 0.04–0.35), whereas no difference was found for social support, motivation and self-efficacy compared with usual care. No difference was observed between the low fidelity and the usual care group in behaviour change mechanisms.
Conclusions
The Face-it intervention achieved acceptable fidelity. High fidelity appears essential for improving risk perception, health literacy and supporting behaviour change mechanisms among women with recent GDM.
目的：我们评估Face-it干预的保真度及其对近期妊娠期糖尿病（GDM）妇女行为改变机制的影响。方法：在这项随机对照试验中，277名妇女被分配到常规护理或干预措施，包括三次家访、数字平台健康指导和跨部门沟通，以支持分娩后第一年的健康行为改变。行为改变机制包括社会支持、动机、自我效能、风险认知和卫生知识。高保真度定义为完成3次家访和≥ 9次辅导接触。结果：在干预组中，86.4%完成了≥ 2次家访，88.6% %进行了数字登记，中位数（IQR）为10.0（3.0-20.0）个接触者。在分娩后一年，高保真组（n = 73;39.7 %）有更高的察觉中度/高度糖尿病风险的几率（OR 2.42; 95 % CI 1.06-5.51）和更高的健康知识（调整差值0.20;95 % CI 0.04-0.35），而与常规护理相比，社会支持、动机和自我效能感没有差异。低保真度组和常规护理组在行为改变机制上没有差异。结论：Face-it干预达到了可接受的保真度。高保真度对于提高新近患GDM妇女的风险认知、健康知识和支持行为改变机制至关重要。
{"title":"Intervention fidelity and behaviour change mechanisms in a health promotion intervention for women following gestational diabetes mellitus: Secondary analysis of the Face-it RCT","authors":"Nanna Husted Jensen , Inger Katrine Dahl-Petersen , Karoline Kragelund Nielsen , Dorte Møller Jensen , Peter Damm , Per Ovesen , Elisabeth R. Mathiesen , Ulla Kampmann , Christina Anne Vinter , Sharleen O’Reilly , Helle Terkildsen Maindal , On behalf of the Face-it Study Group","doi":"10.1016/j.pcd.2025.09.003","DOIUrl":"10.1016/j.pcd.2025.09.003","url":null,"abstract":"<div><h3>Aims</h3><div>We evaluated the fidelity of the Face-it intervention and its impact on behaviour change mechanisms among women with recent gestational diabetes mellitus (GDM).</div></div><div><h3>Methods</h3><div>In this randomised controlled trial, 277 women were allocated to usual care or an intervention comprising three home visits, digital platform health coaching and cross-sectoral communication to support health behaviour change during the first year after delivery. Behaviour change mechanisms included social support, motivation, self-efficacy, risk perception and health literacy. High fidelity was defined as completing three home visits and ≥ 9 coaching contacts.</div></div><div><h3>Results</h3><div>Within the intervention group, 86.4 % completed ≥ 2 home visits, 88.6 % registered digitally with a median (IQR) of 10.0 (3.0–20.0) contacts. At one-year after delivery, the high-fidelity group (n = 73; 39.7 %) had higher odds of perceiving moderate/high diabetes risk (OR 2.42; 95 % CI 1.06–5.51) and higher health literacy (adjusted difference 0.20; 95 % CI 0.04–0.35), whereas no difference was found for social support, motivation and self-efficacy compared with usual care. No difference was observed between the low fidelity and the usual care group in behaviour change mechanisms.</div></div><div><h3>Conclusions</h3><div>The Face-it intervention achieved acceptable fidelity. High fidelity appears essential for improving risk perception, health literacy and supporting behaviour change mechanisms among women with recent GDM.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 584-591"},"PeriodicalIF":2.3,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145139951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-22DOI: 10.1016/j.pcd.2025.09.002
Nurten Terkes , Hicran Bektas , Mustafa Aydemir
Aim
This study aimed to evaluate the effectiveness of a structured distance education program on metabolic control, self-care activities, and health literacy in patients with newly diagnosed type 2 diabetes mellitus.
Methods
A randomized controlled trial design with block randomization (1:1 allocation) was conducted at a university hospital's endocrine outpatient clinic. A total of 100 patients newly diagnosed with type 2 diabetes were randomly assigned to either an intervention group (n = 50), receiving structured weekly distance education via Zoom sessions (each 40 min) for four weeks, or a control group (n = 50) receiving routine outpatient care. Data were collected using metabolic control parameters (BMI, fasting blood sugar, HbA1c), Diabetes Self-Care Activities Questionnaire, and Health Literacy Scale at baseline and after three months.
Results
Significant improvements were observed in metabolic control parameters, self-care activities, and health literacy in the intervention group compared to the control group (p < 0.01). Positive correlations were identified between health literacy and diabetes self-care behaviors post-intervention.
Conclusion
Structured distance education significantly enhances metabolic control, self-care, and health literacy in newly diagnosed T2DM patients. The study highlights the importance and practicality of integrating telehealth technologies into routine diabetes management and patient education, offering effective strategies to overcome barriers inherent in traditional educational methods.
{"title":"Effectiveness of structured distance education on metabolic control, self-care, and health literacy in newly diagnosed type 2 diabetes: A randomized controlled trial","authors":"Nurten Terkes , Hicran Bektas , Mustafa Aydemir","doi":"10.1016/j.pcd.2025.09.002","DOIUrl":"10.1016/j.pcd.2025.09.002","url":null,"abstract":"<div><h3>Aim</h3><div>This study aimed to evaluate the effectiveness of a structured distance education program on metabolic control, self-care activities, and health literacy in patients with newly diagnosed type 2 diabetes mellitus.</div></div><div><h3>Methods</h3><div>A randomized controlled trial design with block randomization (1:1 allocation) was conducted at a university hospital's endocrine outpatient clinic. A total of 100 patients newly diagnosed with type 2 diabetes were randomly assigned to either an intervention group (n = 50), receiving structured weekly distance education via Zoom sessions (each 40 min) for four weeks, or a control group (n = 50) receiving routine outpatient care. Data were collected using metabolic control parameters (BMI, fasting blood sugar, HbA1c), Diabetes Self-Care Activities Questionnaire, and Health Literacy Scale at baseline and after three months.</div></div><div><h3>Results</h3><div>Significant improvements were observed in metabolic control parameters, self-care activities, and health literacy in the intervention group compared to the control group (p < 0.01). Positive correlations were identified between health literacy and diabetes self-care behaviors post-intervention.</div></div><div><h3>Conclusion</h3><div>Structured distance education significantly enhances metabolic control, self-care, and health literacy in newly diagnosed T2DM patients. The study highlights the importance and practicality of integrating telehealth technologies into routine diabetes management and patient education, offering effective strategies to overcome barriers inherent in traditional educational methods.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"19 6","pages":"Pages 577-583"},"PeriodicalIF":2.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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