Primary care diabetes最新文献

{"title":"Trends in type 2 diabetes medication use and guideline adherence in Belgian primary care (2019-2023).","authors":"Willem Raat, Pavlos Mamouris, Chantal Mathieu, Geert Goderis, Bert Vaes","doi":"10.1016/j.pcd.2024.10.007","DOIUrl":"https://doi.org/10.1016/j.pcd.2024.10.007","url":null,"abstract":"<p><strong>Aims: </strong>To assess the prevalence of atherosclerotic cardiovascular disease (ASCVD), heart failure (HF), and chronic kidney disease (CKD) among patients with type 2 diabetes (T2D) in Belgium. To analyze trends in medication use and adherence to guidelines from 2019 to 2023.</p><p><strong>Methods: </strong>We conducted a retrospective cross-sectional analysis using data from the Intego primary care database, encompassing records from 431 general practitioners. We identified adults with T2D through diagnostic codes and glycated hemoglobin levels and analyzed subgroups with ASCVD, HF, and CKD for trends in medication use, particularly SGLT2 inhibitors (SGLT2-i) and GLP-1 receptor agonists (GLP-1).</p><p><strong>Results: </strong>The T2D population increased from 20,766 in 2019 to 21,764 in 2023. The prevalence of ASCVD, HF, and CKD among T2D patients slightly increased to 27 %, 6.7 %, and 23.7 % by 2023 (from 25.2 %, 4.9 % and 21.5 % respectively). Medication prescription trends showed a tripling of SGLT2-i and GLP-1 prescribing in the study period to 6.2 % and 11.5 % respectively. Despite these increases, only 7.5 % of eligible patients received these medications as of 2023.</p><p><strong>Conclusion: </strong>The study highlights a growing burden of ASCVD, HF, and CKD among T2D patients in Belgium and an increase in the use of guideline-recommended medications. However, there remains a substantial gap in the optimal use of these therapies, indicating a need for improved implementation of clinical guidelines in primary care.</p>","PeriodicalId":94177,"journal":{"name":"Primary care diabetes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142564783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sleep well, but be active. Effect of sleep and sedentariness on incidence of diabetes.","authors":"Keyuan Liu, P. Marques-Vidal","doi":"10.1093/eurjpc/zwad125.106","DOIUrl":"https://doi.org/10.1093/eurjpc/zwad125.106","url":null,"abstract":"AIMS\u0000We aimed to determine the individual effect of long/short sleep and of inactivity on diabetes risk using data from a population-based prospective study in Switzerland.\u0000\u0000\u0000METHODS\u0000Prospective study with a median (min-max) follow-up of 9 (2.4-11.5) years. Incident diabetes was defined based on 1) fasting plasma glucose (FPG), 2) glycated hemoglobin (HbA1c), or 3) any diagnostic criterion (FPG, HbA1c or medical diagnosis). Sleep and sedentary levels were assessed by questionnaire. Sleep was categorized into short (<7 h/day), adequate (7-9 h/day) and long (>9 h/day).\u0000\u0000\u0000RESULTS\u0000Data from 3355 participants (57.6% women, mean age years 56.6 ± 10.3) was analyzed. There were 136, 110 and 142 incident cases of diabetes defined by FPG, HbA1c or any criterion, respectively. Participants who developed diabetes had a higher sedentariness but no differences were found regarding sleep duration. Similar results were obtained after adjusting for age, gender, education, smoking and body mass index: hazard ratio (95% confidence interval) for sedentariness 1.61 (1.11-2.35), 1.40 (0.93-2.12) and 1.39 (1.04-1.87) for diabetes defined by FPG, HbA1c or any diagnostic criterion, respectively.\u0000\u0000\u0000CONCLUSION\u0000Being sedentary, but not being a long or a short sleeper, increases the risk of developing diabetes.","PeriodicalId":94177,"journal":{"name":"Primary care diabetes","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42061845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effectiveness of Enhanced Primary Healthcare (EnPHC) interventions on Type 2 diabetes management in Malaysia: Difference-in-differences (DID) analysis.","authors":"M. Husin, X. Teh, S. M. Ong, Y. Lim, Swee Hung Ang, C. Chan, M. Lim, S. Shanmugam, Noraziani Khamis, Faeiz Syezri Adzmin Jaafar, Norliza Ibrahim, N. Nasir, D. Kusuma, A. Wagner, D. Ross-Degnan, R. Atun, S. Sivasampu","doi":"10.21203/RS.3.RS-154502/V1","DOIUrl":"https://doi.org/10.21203/RS.3.RS-154502/V1","url":null,"abstract":"AIMS\u0000To evaluate the effectiveness of the Enhanced Primary Healthcare (EnPHC) interventions on process of care and intermediate clinical outcomes among type 2 diabetes patients.\u0000\u0000\u0000METHODS\u0000This was a quasi-experimental controlled study conducted in 20 intervention and 20 control public primary care clinics in Malaysia from November 2016 to June 2019. Type 2 diabetes patients aged 30 years and above were selected via systematic random sampling. Outcomes include process of care and intermediate clinical outcomes. Difference-in-differences analyses was conducted.\u0000\u0000\u0000RESULTS\u0000We reviewed 12,017 medical records of patients with type 2 diabetes. Seven process of care measures improved: HbA1c tests (odds ratio (OR) 3.31, 95% CI 2.13, 5.13); lipid test (OR 4.59, 95% CI 2.64, 7.97), LDL (OR 4.33, 95% CI 2.16, 8.70), and urine albumin (OR 1.99, 95% CI 1.12, 3.55) tests; BMI measured (OR 15.80, 95% CI 4.78, 52.24); cardiovascular risk assessment (OR 174.65, 95% CI 16.84, 1810.80); and exercise counselling (OR 1.18, 95% CI 1.04, 1.33). We found no statistically significant changes in intermediate clinical outcomes (i.e. HbA1c, LDL, HDL and BP control).\u0000\u0000\u0000CONCLUSIONS\u0000EnPHC interventions was successful in enhancing the quality of care, in terms of process of care, by changing healthcare providers behaviour.","PeriodicalId":94177,"journal":{"name":"Primary care diabetes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45092402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of restricted diet with a plate in patients with type 2 diabetes: A randomized controlled trial.","authors":"Yongwen Zhang, Huanhuan Han, Lanfang Lanfang","doi":"10.22541/au.160552637.79851951/v1","DOIUrl":"https://doi.org/10.22541/au.160552637.79851951/v1","url":null,"abstract":"BACKGROUND\u0000In view of the complexity of dietary and nutritional education for most patients with type 2 diabetes mellitus (T2DM), a simplified approach called the \"restricted diet with a plate\" or \"plate model\" is recommended.\u0000\u0000\u0000PURPOSE\u0000To evaluate whether the plate model can effectively improve glycemic control and cardiovascular risk markers in type 2 diabetes mellitus (T2DM), while reducing the time devoted to education and avoiding weight gain.\u0000\u0000\u0000METHODS\u0000The study was a randomized, multicenter, controlled study, conducted between October 2018 and October 2019, among patients with T2DM living in Nanjing. The study included 419 participants who were randomly divided into a plate group and a counting group. The plate model included three components: a low-literacy, color leaflet containing the explanation and composition of the plate model, health education, and medical visits. Patients in the counting group received health education, group medical visits, and a paper booklet containing traditional carbohydrate counting education. Primary outcomes were glycemic control and weight.\u0000\u0000\u0000RESULTS\u0000Participants in the plate model reduced HbA1c by 0.7% in the first three months, and reduced to a greater extent at six months (1.44%), but this was not sustained, and HbA1c increased slightly over the following six months. Fasting plasma glucose (FPG) and 2-h postprandial glucose (2hPG) values were significantly reduced at the endpoint in the plate model (9.25 ± 1.72% vs. 7.44 ± 0.88%, P = 0.008; 12.07 ± 2.94 vs. 8.35 ± 1.99%; P = 0.004); however, the 2hPG values decreased most significantly. Total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels decreased significantly in the plate group, which occurred at six months and lasted for 12 months. In the first three months, the average weight loss in the plate group was 1.2 kg/month (95% CI 0.92-1.48), and in the fourth to twelfth months, the average weight gain was 0.21 kg/month (95% CI 0.08-0.34). There was significant difference in education time between the groups (17.3 ± 4.42 vs. 38.6 ± 12.63; P < 0.001).\u0000\u0000\u0000CONCLUSIONS\u0000The plate model is at least as effective as the counting model over the short term for glycemic control and perhaps even better for weight and lipid control. Plate model has the potential to improve education of those with low health literacy by reducing reading demands.","PeriodicalId":94177,"journal":{"name":"Primary care diabetes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42015834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Progression of pregnancy induced diabetes mellitus to type two diabetes mellitus, an ambidirectional cohort study.","authors":"B. Feleke, Teferi Elfu Feleke, M. Kassahun, Wondemu Gebrekirose Adane, Desalegn Achenefe, Abere Genetu, Azezu Asres Nigussie, Hailemariam Awoke Engedaw","doi":"10.21203/rs.3.rs-30572/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-30572/v1","url":null,"abstract":"INTRODUCTION\u0000Diabetes mellitus (DM) is a metabolic disorder characterized by elevated level of blood glucose. It affects more than 422 million people globally. In resource limited settings, the progression of gestational diabetes (GDM) to DM was not well investigated and this research work was conducted to estimate the incidence of DM after GDM and their predictors in resource limited settings.\u0000\u0000\u0000METHODS\u0000A retrospective and prospective cohort studies were used from January 2010 until December 2019. The data were collected using patients chart review, interview and collecting blood sample. Initially, baseline data were collected from GDM and GDM free women and update data were collected every 3 month. Clinical nurses were used to extract the necessary data from medical charts and to collect the data using patient interview. Laboratory technologists were used to measure the blood glucose level of the study participants. The study was conducted in pregnant women presenting themselves in the referral hospitals of Amhara regional state. The sample size was calculated using Epi-info software. Descriptive statistics were used to describe the profile of study participants. Kaplan Meier survival curve and life-table were used to estimate the survivals of study participants. Incidence density was used to estimate the incidence of DM. Cox regression was used to identify the predictors DM.\u0000\u0000\u0000RESULTS\u0000A total of 4892 women were followed giving for the response rate of 88.62%. The mean age of study participants at the start of the study was 28.34 years with standard deviation [SD] ±7.48 years. DM was associated with gestational diabetes mellitus [AHR (adjusted hazard ratio); 2.53, 95% CI: 2.14-2.99], frequency of breastfeeding [AHR; 0.72, 95% CI: 0.69-0.74], age [AHR; 1.04, 95% CI: 1.03-1.05], parity [AHR; 1.14, 95% CI: 1.07-1.21], regular physical exercise [AHR; 0.45, 95% CI: 0.37-0.55], family history of DM [AHR; 2.04, 95% CI: 1.76-2.37], stillbirth [AHR; 1.67: 95% CI: 1.34-2.07], abortion [AHR; 2.64, 95% CI: 2.25-3.09].\u0000\u0000\u0000CONCLUSION\u0000The progression of GDM to DM was very high and special follow up should be implemented for women with a history of abortion, stillbirth, and family history of DM.","PeriodicalId":94177,"journal":{"name":"Primary care diabetes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42002517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}