Pub Date : 2025-11-21DOI: 10.1016/j.pcd.2025.11.007
Ayokunle Osonuga, Gloria Okoye, Adewoyin Osonuga, Serge Engamba, Nicholas Aderinto
Background: Prediabetes, marked by elevated blood glucose levels below the type 2 diabetes mellitus (T2DM) threshold, is a growing public health concern due to its rising prevalence and risk of progression to diabetes and cardiovascular issues. Structured weight loss programs in primary care show promise for improving glycemic control, yet their impact on HbA1c remains underexplored. This systematic review evaluates their effectiveness in reducing HbA1c in adults with prediabetes.
Methods: Following the 2020 PRISMA and SWiM guidelines, we searched six databases (PubMed, EMBASE, Cochrane CENTRAL, Scopus, CINAHL, Web of Science) up to July 10, 2025, for studies on structured weight loss programs in primary care. Eligible studies involved adults (≥18 years) with prediabetes, using RCTs, cohort studies, or pilot interventions with HbA1c as the primary outcome. Data were extracted, and risk of bias was assessed using Cochrane RoB 2.0 and ROBINS-I tools. A narrative synthesis was performed due to study heterogeneity.
Results: Seven studies (n = 43-2227) showed HbA1c reductions of 0.03 %-0.83 %, with high-intensity (e.g., frequent behavioral sessions) and digital interventions (e.g., low-carbohydrate apps) yielding the largest effects. Weight loss (up to 7.2 kg), BMI, and lipid profiles also improved. Adherence and intervention intensity were key factors, though inconsistent reporting limited comparisons.
Conclusion: Structured weight loss programs in primary care are consistently associated with modest-to-moderate HbA1c reductions, with high-intensity and digital interventions showing the greatest promise. However, study heterogeneity and inconsistent adherence reporting limit definitive conclusions. Future research should prioritize standardized reporting, long-term outcomes, and diverse populations to enhance generalizability.
背景:前驱糖尿病,以血糖水平升高低于2型糖尿病(T2DM)阈值为标志,由于其患病率和进展为糖尿病和心血管问题的风险不断上升,是一个日益严重的公共卫生问题。初级保健中有组织的减肥计划有望改善血糖控制,但其对HbA1c的影响仍未得到充分探讨。本系统综述评估了它们在降低成人糖尿病前期患者HbA1c方面的有效性。方法:根据2020年PRISMA和SWiM指南,我们检索了六个数据库(PubMed, EMBASE, Cochrane CENTRAL, Scopus, CINAHL, Web of Science),截至2025年7月10日,用于初级保健结构化减肥计划的研究。符合条件的研究涉及成人(≥18岁)前驱糖尿病患者,采用随机对照试验、队列研究或以HbA1c为主要结局的试点干预。提取资料,使用Cochrane RoB 2.0和ROBINS-I工具评估偏倚风险。由于研究的异质性,我们进行了叙事综合。结果:七项研究(n = 43-2227)显示,HbA1c降低0.03% %-0.83 %,高强度(如频繁的行为会话)和数字干预(如低碳水化合物应用程序)产生的效果最大。体重减轻(高达7.2 kg)、BMI和脂质谱也有所改善。依从性和干预强度是关键因素,尽管不一致的报告限制了比较。结论:初级保健中有组织的减肥计划始终与中度至中度HbA1c降低相关,高强度和数字化干预显示出最大的希望。然而,研究的异质性和不一致的依从性报告限制了明确的结论。未来的研究应优先考虑标准化报告、长期结果和多样化人群,以提高普遍性。
{"title":"A systematic review of structured weight loss programs and their association with HbA1c reduction in adults with prediabetes managed in primary care.","authors":"Ayokunle Osonuga, Gloria Okoye, Adewoyin Osonuga, Serge Engamba, Nicholas Aderinto","doi":"10.1016/j.pcd.2025.11.007","DOIUrl":"https://doi.org/10.1016/j.pcd.2025.11.007","url":null,"abstract":"<p><strong>Background: </strong>Prediabetes, marked by elevated blood glucose levels below the type 2 diabetes mellitus (T2DM) threshold, is a growing public health concern due to its rising prevalence and risk of progression to diabetes and cardiovascular issues. Structured weight loss programs in primary care show promise for improving glycemic control, yet their impact on HbA1c remains underexplored. This systematic review evaluates their effectiveness in reducing HbA1c in adults with prediabetes.</p><p><strong>Methods: </strong>Following the 2020 PRISMA and SWiM guidelines, we searched six databases (PubMed, EMBASE, Cochrane CENTRAL, Scopus, CINAHL, Web of Science) up to July 10, 2025, for studies on structured weight loss programs in primary care. Eligible studies involved adults (≥18 years) with prediabetes, using RCTs, cohort studies, or pilot interventions with HbA1c as the primary outcome. Data were extracted, and risk of bias was assessed using Cochrane RoB 2.0 and ROBINS-I tools. A narrative synthesis was performed due to study heterogeneity.</p><p><strong>Results: </strong>Seven studies (n = 43-2227) showed HbA1c reductions of 0.03 %-0.83 %, with high-intensity (e.g., frequent behavioral sessions) and digital interventions (e.g., low-carbohydrate apps) yielding the largest effects. Weight loss (up to 7.2 kg), BMI, and lipid profiles also improved. Adherence and intervention intensity were key factors, though inconsistent reporting limited comparisons.</p><p><strong>Conclusion: </strong>Structured weight loss programs in primary care are consistently associated with modest-to-moderate HbA1c reductions, with high-intensity and digital interventions showing the greatest promise. However, study heterogeneity and inconsistent adherence reporting limit definitive conclusions. Future research should prioritize standardized reporting, long-term outcomes, and diverse populations to enhance generalizability.</p>","PeriodicalId":94177,"journal":{"name":"Primary care diabetes","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145582305","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}
Pub Date : 2023-05-24DOI: 10.1093/eurjpc/zwad125.106
Keyuan Liu, P. Marques-Vidal
AIMS We 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. METHODS Prospective 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). RESULTS Data 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. CONCLUSION Being sedentary, but not being a long or a short sleeper, increases the risk of developing diabetes.
{"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}
Pub Date : 2021-01-28DOI: 10.21203/RS.3.RS-154502/V1
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
AIMS To evaluate the effectiveness of the Enhanced Primary Healthcare (EnPHC) interventions on process of care and intermediate clinical outcomes among type 2 diabetes patients. METHODS This 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. RESULTS We 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). CONCLUSIONS EnPHC interventions was successful in enhancing the quality of care, in terms of process of care, by changing healthcare providers behaviour.
{"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}
Pub Date : 2020-11-16DOI: 10.22541/au.160552637.79851951/v1
Yongwen Zhang, Huanhuan Han, Lanfang Lanfang
BACKGROUND In 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. PURPOSE To 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. METHODS The 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. RESULTS Participants 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). CONCLUSIONS The 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.
{"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}
Pub Date : 2020-06-08DOI: 10.21203/rs.3.rs-30572/v1
B. Feleke, Teferi Elfu Feleke, M. Kassahun, Wondemu Gebrekirose Adane, Desalegn Achenefe, Abere Genetu, Azezu Asres Nigussie, Hailemariam Awoke Engedaw
INTRODUCTION Diabetes 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. METHODS A 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. RESULTS A 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]. CONCLUSION The 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.
{"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}