Effects of Continuous Care on Gestational Diabetes Mellitus Patients: A Systematic Review and Meta-analysis of 22 RCTs

Effects of Continuous Care on Gestational Diabetes Mellitus Patients: A Systematic Review and Meta-analysis of 22 RCTs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Effects of Continuous Care on Gestational Diabetes Mellitus Patients: A Systematic Review and Meta-analysis of 22 RCTs Feifei Chen, Chengwen Song, Yuanci Lyu, Ting Zhou, Yanyan Zhao, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7893643/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This study aimed to investigate the effects of continuous care on blood glucose and pregnancy outcomes in patients with gestational diabetes mellitus (GDM) through meta-analysis. Method Searches were conducted in PubMed, Web of Science, OVID-Embase, The Cochrane Library, Sinomed, ScienceDirect, IEEE, ProQuest, SpringerLink, EBSCO, JSTOR, BMJ, Taylor, UpToDate, JAMA (Journal of the American Medical Association), CNKI (China National Knowledge Infrastructure), WanFang Data, VIP Database for Chinese Technical Periodicals, China Biology Medicine disc (CBMdisc), Chinese Medical Association Journal Database were systematically searched for randomized controlled trials on the effects of continuous care on blood glucose and pregnancy outcomes in GDM patients from inception to June 2023. Data were then pooled and analyzed using Stata 18.0 software. Results The meta-analysis included 22 randomized controlled trials, comprising 12 English and 10 Chinese publications, involving 2808 patients, with 1410 in the continuous care group and 1398 in the dietary intervention group. Meta-analysis results showed that compared with routine care, continuous care had statistically significant differences in fasting blood glucose [WMD=-0.37, 95%CI (-0.63,-0.11), P < 0.0001], average blood glucose at 2 hours after meals [WMD=-1.34, 95%CI=(-1.93,-0.76), P = 0.0000], HbA1c levels [WMD=-0.78, 95%CI=(-0.89, -0.67), P = 0.353], preterm birth rate [RR = 0.39, 95%CI=(0.26, 0.59), P = 0.085], cesarean section rate [RR = 0.60, 95%CI=(0.52,0.68), P < 0.01], macrosomia rate [RR = 0.42, 95%CI=(0.30,0.59), P = 0.040], postpartum hemorrhage rate [RR = 0.20, 95%CI=(0.10,0.41), P = 0.910], neonatal hypoglycemia rate [RR = 0.17, 95%CI(0.08,0.34), P = 0.291], neonatal asphyxia rate [RR = 0.29, 95%CI=(0.10,0.85), P = 0.996], and low birth weight rate [RR = 0.53, 95%CI=(0.24, 1.20), P = 0.400]. Conclusions Our study systematically evaluates the effects of continuous care on GDM outcomes, affirming its positive impact on blood glucose levels and some adverse pregnancy outcomes in patients with GDM. Continuous Care Pregnancy Gestational Diabetes Mellitus Meta-analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Introduction Gestational diabetes mellitus (GDM) is a form of diabetes characterized by high blood glucose levels that develop during pregnancy without prior abnormal glucose tolerance. 1 Its prevalence has been steadily rising, posing significant risks to both mothers and fetuses worldwide. 2 , 13 , 31 Globally, the International Diabetes Federation reported a prevalence of around 16.7% in 2021, with higher rates observed in developing and low-income countries, particularly in regions like the Middle East, North Africa, Southeast Asia, and the Western Pacific. 2 , 3 , 14 The impact of GDM on maternal and neonatal health is profound, with complications including gestational hypertension, premature birth, and fetal deformities. Moreover, women with GDM face an increased risk of developing type 2 diabetes later in life, while their offspring are more susceptible to obesity and diabetes. 16 , 17 Economic burdens associated with diagnosis, treatment, and hospitalization further compound the challenges posed by GDM. 4 , 5 Given its detrimental effects, addressing the adverse outcomes of GDM is imperative. Efforts to manage GDM have seen advancements in developed countries, with guidelines emphasizing lifestyle modifications as first-line treatment. 19 , 20 These interventions include dietary adjustments, physical activity, self-monitoring of blood glucose, and medical nutrition therapy, all of which have shown efficacy in controlling blood glucose levels and reducing postpartum complications. 6 , 21 , 30 Continuity of nursing, defined as a comprehensive approach to healthcare delivery aimed at improving treatment effectiveness and patient quality of life through personalized management, has gained traction in managing various conditions, including GDM. 23 , 25 , 26 In the context of GDM management, the continuity of care model emphasizes continuous monitoring and intervention throughout pregnancy, encompassing blood glucose monitoring, dietary control, exercise regimens, medication, and prenatal guidance. 7 , 27 , 28 While its benefits are acknowledged, there remains a dearth of systematic research evaluating its effectiveness comprehensively. Thus, conducting meta-analyses and applied research to assess the intervention's impact on various outcomes in GDM patients holds significant clinical relevance. 8 , 9 , 29 Such studies can inform clinical decision-making, improve patient management, and guide future research and practice aimed at preventing and managing GDM effectively. The research objectives include evaluating the impact of continuity of care on blood glucose control, self-management abilities, and delivery outcomes in GDM patients through meta-analysis. Additionally, the study aims to explore differences in psychological and pregnancy outcomes among GDM patients receiving continuity of care interventions, providing insights into its suitability and compliance in this population. The research hypotheses posit that continuous nursing can improve blood glucose levels and adverse pregnancy outcomes in GDM patients, potentially surpassing conventional nursing modes in efficacy. By maximizing patient satisfaction, enhancing pregnancy outcomes, and reducing complications, continuity of care emerges as a pivotal strategy in addressing the challenges posed by GDM. Methods Search Strategy and Study Eligibility The meta-analysis was reported following the Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) statement. Our study protocol was registered with PROSPERO (registration number CRD42023443724) before implementation. To ensure comprehensive coverage, we conducted systematic searches across multiple databases from their inception up to April 2023. These databases included PubMed, Web of Science, OVID-Embase, The Cochrane Library, Sinomed, ScienceDirect, IEEE, ProQuest, SpringerLink, EBSCO, JSTOR, BMJ, Taylor & Francis, UpToDate, JAMA (Journal of the American Medical Association), CNKI, Wanfang Database, VIP Database, and China National Knowledge Infrastructure (CNKI). We utilized a combination of subject terms and free terms tailored to each database's specifications. Additionally, we manually searched relevant meta-analyses, reviews, and reference lists of included studies.Two reviewers (F.C and H.Y) obtained the following information from each of the included studies: the first author, year date of publication, study center, study design, enrollment period, sample size, interventions and so on. English databases were searched using keywords such as "gestational diabetes/GDM/pregnancy-induced diabetes/diabetes" and "continuity of care/continual care/continuous care/follow-up/extended care." Chinese databases were searched using equivalent terms in Chinese characters, with adjustments made according to the corresponding subject terms in each database. The inclusion of related literature from manual searches was supplemented to ensure comprehensive retrieval. A fixed effects model was used when there was significant heterogeneity (I² < 50%). otherwise, a random effects model was employed. Funnel plots and Egger’s tests were used to identify possible publication bias in the results. RevMan 5.4 software was used to prepare and analyze reviews from the Cochrane database. Statistical significance was defined as p < 0.05. In terms of study design, only randomized controlled trials were included. Inclusion criteria: (1) Randomized controlled trials (RCTs) investigating the effect of continuity of care in GDM patients. (2) Patients diagnosed with GDM through OGTT. aged > 18 years. (3) The control group received routine care, while the intervention group received additional continuity of care, including health education through platforms such as QQ, WeChat, outpatient visits, home visits, and maternity lectures. (4) Studies including one or more of the following outcome measures were included: Blood glucose levels, including fasting blood glucose and average blood glucose levels 2 hours after meals. Pregnancy outcomes, such as preterm birth, jaundice, macrosomia, and neonatal asphyxia. Fasting blood glucose and average blood glucose levels 2 hours after meals were considered primary outcome measures, while others were secondary. Exclusion criteria: (1) Duplicate publications. (2) Studies with incomplete data that could not be obtained even after contacting the authors. (3) Inaccessible full-text articles. Data Extraction and Quality Assessment Two reviewers independently extracted data using a predefined form, cross-validating results. Discrepancies were resolved through consultation with a third researcher. Extracted data included author names, publication years, study designs, sample sizes, interventions, and outcome measures. Missing data were requested from the original authors.If there are any disagreement, the third reviewer (S.P) would make the final decision or try to contact the author for supplement data. The reviewers used Cochrane bias risk assessment tool to evaluate the quality of the included randomized controlled trials studies. The quality assessment and data extraction were undertaken using a standardized form. The quality of the studies was divided into three grades (ABC) according to the degree of eccentricity of the studies. The quality of the literature was evaluated by two researchers independently, and the third researcher negotiated and decided in case of disagreement. There were five factors that could reduce the quality of evidence: the limitations of the study, the inconsistency of the study results, the indirectness of the study results, the imprecision of the results, and publication bias. Statistical Analysis We conducted meta-analyses using Stata 18.0 software. For continuous variables, we calculated weighted mean differences or standardized mean differences as appropriate. For binary variables, we computed relative risks (RRs) with 95% confidence intervals (CIs). Heterogeneity among studies was assessed using the Q test and I² statistic. We employed fixed-effects or random-effects models based on the level of heterogeneity observed. Sensitivity analyses and subgroup analyses were conducted to explore sources of heterogeneity and intervention characteristics, respectively. Descriptive analyses were performed when substantial heterogeneity precluded meta-analysis. Results Study characteristics A preliminary search was conducted based on the databases listed in the table, along with other sources, resulting in a total of 2160 grey literature articles, comprising 1324 in Chinese and 836 in English. After removing 683 duplicate articles, a total of 1477 articles were obtained. After reviewing titles and abstracts, 1364 articles were excluded, leaving 123 articles. Upon reading the full texts, 12 articles published before 2018 were excluded, along with 12 reviews and 18 non-RCT articles, resulting in 81 articles. Among these, 15 articles had no usable outcome indicators, and attempts to contact the authors were unsuccessful. Fourteen articles exhibited methodological heterogeneity, ten had poor quality assessments, and twenty were not solely focused on continuous care. Consequently, 22 articles were included in the meta-analysis. The literature search and screening process are illustrated in Fig. 1 . The total sample size of the 22 studies was 2808 cases, with 1410 cases in the intervention group and 1398 cases in the control group. 10–31 The control measures in the control group were conventional care models, while the intervention group received additional continuous care based on the control group. The general characteristics of the included literature are presented in Table 1 . The evaluation of quality of studies were presented in Fig. 2 according to the Cochrane Handbook (5.1.0). 32 Table 1 Basic characteristics of the included literature Author Year Sample Size Country Intervention Group Control Group Outcome Indicators Hu Yating et al. 2019 20 China ① Personalized continuous care plan Routine care ①②③④⑤⑦⑩ Chen Suhua et al. 2019 57 China Network interactive continuous care intervention Routine care ①②③④⑤⑦⑨⑩ Gao Zhenzhen et al. 2021 51 China ① Psychological care, ② Continuous care plan, ③ Lectures, ④ Dietary management, ⑤ Follow-up Routine care ⑤⑦⑨⑰ Duan Lina et al. 2021 201 China ① Departmental intervention team, ② Staged continuous management, ③ Follow-up and comprehensive guidance Routine care ④⑦⑤⑦⑧⑨ Zhao Linli et al. 2019 74 China ① Formation of a nursing team, ② Targeted guidance, ③ Follow-up and comprehensive care Routine care ④⑤⑥⑦⑧⑩ Xiao Xiaoli et al. 2019 60 China ① Establishment of a continuous care team, ② Group lectures for pregnant women, ③ Guidance on self-management, blood glucose monitoring, insulin use, etc. Routine care ④⑤⑥⑧⑩ Yang Xiaoli et al. 2021 49 China ① Establishment of an integrated medical-nursing continuous care team, ② Remote reminder for glucose monitoring, ③ WeChat interactive plan Routine care ①②③⑦ Lei Jun et al. 2021 30 China ① Establishment of a continuous care team, ② Online information platform, ③ Health education, ④ Nutritional support, ⑤ Medication intervention Routine care ①②③⑥ Chen Weifeng et al. 2020 50 China ① Establishment of a continuous care team, ② Psychological care, ③ Dietary intervention, ④ Health education, ⑤ Discharge guidance Routine care ①②③④⑤⑦⑨⑩ Zhou Lingli et al. 2019 50 China ① Multidisciplinary nursing expert team, standardized nursing plan including weight control, health education, psychological counseling, and dietary therapy, ② Regular team training and nursing quality control and assessment, investigation of patient satisfaction with community nursing work Routine care ①④ Sung JH et al. 2019 11 South Korea ① Mobile app for personalized mobile healthcare services, ② MDT team for nursing, ③ Participants carry monitoring system devices, ④ Dedicated app for collecting clinical data and information, ⑤ Automatic transmission of experimental group data to the server via wireless network Routine care ④⑩ Tong Wei Yew et al. 2021 170 Singapore ① Habits-GDM app and healthcare professional information platform, ② Development of 12 interactive courses by endocrinologists, obstetricians, diabetes educators, and nutritionists, ③ Tools for diet, SMBG, physical activity, and weight tracking Routine care ①②⑤⑧⑨ Carolan-Olah M et al. 2018 52 Australia ① Healthy food choices, ② Healthy habits or lifestyle, ③ Emotional, family, and food, ④ Blood glucose level testing Standard clinical education course ⑤⑥ Bingjie Ding et al. 2021 25 Beijing, China ① WeChat intervention, ② Learning dietary guidelines, ③ Dietary nursing, ④ Exercise nursing Routine care ①②③⑤⑥⑩ Chahed S et al. 2022 61 Tunisia ① Continuous care education, ② Dietary care, ③ Exercise education, ④ Self-blood glucose monitoring, ⑤ Follow-up Routine care ⑤⑨⑩ Rasekaba TM et al. 2018 61 Melbourne, Australia ① Remote medical assistance, inputting patient information to medical staff via personal data for personalized GDM care feedback, ③ Reviewing diaries at appointments, informing subsequent management decisions Routine care ⑤ Tian Y et al. 2021 32 China ① WeChat group management: researchers release a bulletin and a task card, ② To determine basic requirements including dietary advice, dietary examples from other group members, and exercise rules, ③ Patients provide self-management based on the basic standards provided, ④ Researchers provide personalized guidance for self-management Routine care ④⑤⑥⑦⑩ Borgen I et al. 2019 112 Norway ① Pregnant + app, ② Support for GDM management by adjusting healthy eating, exercising, and receiving feedback on blood glucose levels, ③ It includes four main icons: "Blood sugar", "Physical activity", "Food and drink", and "Diabetes information" Routine care ④⑤ Chan RS et al. 2018 118 Hong Kong, China ① Participants receive face-to-face or telephone consultations with continuous provision of programs, ② Nutritionists discuss specific diets and ③ exercise coaches assess participants' physical fitness levels and musculoskeletal problems, ④ Design appropriate exercise plans for participants based on international guidelines Routine care ④⑤⑩ Sadiya A et al. 2022 30 United Arab Emirates ① Weight management, dietary, and exercise interventions, ② Motivational interviews, SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) goal setting, self-monitoring (pedometer, food records), and problem-solving skills Routine care ①②④ Munda A et al. 2023 53 Northern California, USA ① Monthly video conferences conducted online, ② On-site visits (assessment of SMBG, ketone presence, weight, and gynecologist examination data), ③ Utilization of remote medical services from the University Medical Center Ljubljana remote medical center, where subjects install designated applications, ④ Nurses at the medical center review the data uploaded by patients weekly Routine care ①②④⑩ Qi S et al. 2022 43 China ① MDT members discuss the continuous care model, ② Self-management education to improve patient self-care awareness, ③ Psychological counseling to improve treatment compliance, ④ Close monitoring of patients, dietary guidance Routine care ④⑤⑨⑬⑩ Outcomes: ① Fasting Plasma Glucose (FPG) ② 2-hour Plasma Glucose (2hPG) ③ HbA1c ④ Cesarean Section (C-section) Rate ⑤ Macrosomia Rate ⑥ Low Birth Weight Rate ⑦ Postpartum Hemorrhage Rate ⑧ Neonatal Asphyxia Rate ⑨ Neonatal Hypoglycemia Rate ⑩ Premature Birth Rate Effect of Continuity Nursing on Fasting Blood Glucose in GDM Patients There were 11 articles with FPG as the outcome indicator, involving a total of 1324 patients, including 666 in the continuity nursing group and 658 in the routine care group. All articles reported fasting blood glucose levels in the intervention and control groups. After combining the data from the 11 studies for meta-analysis, the results are shown in Fig. 3 A (P = 0.0001, I²=94.8%). Egger's test did not indicate publication bias (P = 0.546 > 0.05). Sensitivity analysis revealed a decrease in heterogeneity after excluding three articles. The combined effect size Fig. 3 B (WMD) was − 0.37, 95% CI (-0.63, -0.11), P < 0.0001, indicating a significant difference between the intervention and control groups, with the intervention group showing better control of fasting blood glucose values in GDM patients. Random-effects models were used for subgroup analysis to investigate the effects of online and face to face continuity nursing on fasting blood glucose in GDM patients. As shown in Fig. 4 , face to face continuity nursing had a significant effect on fasting blood glucose (WMD= -0.55, 95% CI [-1.12, 0.01], P < 0.01), with significant heterogeneity among studies (I²=80.8%, Q test P < 0.01). Online continuity nursing did not show a significant effect on fasting blood glucose (WMD=-0.32, 95% CI [-0.76, 0.12], P < 0.01), with significant heterogeneity among studies (I²=98.1%, Q test P < 0.01). The combined effect size of the face to face and online combined mode was not significant (WMD=-0.36, 95% CI [-0.62, 0.10], P < 0.01), with nonsignificant heterogeneity among studies (I²=52.8%, Q test P < 0.01), indicating reasonable grouping. The forest plot in the subgroup analysis showed that the combined effect size of face to face continuity nursing was on the left side of the vertical axis, indicating an improvement in fasting blood glucose in GDM patients. Effect of Continuity Nursing on Postprandial 2-hour Blood Glucose in GDM Patients This included 10 articles with a total of 1224 patients, including 616 in the continuity nursing group and 608 in the dietary nursing group. All 10 articles reported the mean postprandial 2-hour blood glucose values, with significant heterogeneity among studies (P < 0.01, I²=96.3%). Random-effects models were used for meta-analysis, revealing a statistically significant difference between the intervention and control groups (WMD=-1.34, 95% CI (-1.93, -0.76), P = 0.0000), as shown in Fig. 5 A. Egger's test did not indicate publication bias (P = 0.562 > 0.05). Sensitivity analysis did not identify the source of heterogeneity. Although significant heterogeneity still existed among the included studies (P < 0.0001, I²=96.3%), the intervention group showed significantly better control of postprandial 2-hour blood glucose values in GDM patients compared to the control group. Random-effects models were used for subgroup analysis to explore the effects of online and face to face continuity nursing on postprandial 2-hour blood glucose in GDM patients. As shown in Fig. 5 B, face to face continuity nursing had a significant effect (WMD= -1.90, 95% CI [-4.08, 0.28], P < 0.01), with significant heterogeneity among studies (I²=96.4%, Q test P < 0.01). Online continuity nursing also had a significant effect (WMD=-0.99, 95% CI [-1.91, -0.07], P < 0.01), with significant heterogeneity among studies (I²=96.8%, Q test P < 0.01). The combined effect size of the face to face and online combined mode was significant (WMD=-1.06, 95% CI [-1.22, -0.90], P 0.05), indicating reasonable grouping. The forest plot in the subgroup analysis showed that the combined effect size of online continuity nursing and the combined mode was on the left side of the vertical axis, indicating an improvement in postprandial 2-hour blood glucose in GDM patients. Effect of Continuity Nursing on HbA1 in GDM Patients This included 5 articles with a total of 426 patients, including 219 in the continuity nursing group and 207 in the dietary nursing group. All 5 articles reported the HbA1 values of GDM patients, with low heterogeneity among studies (P = 0.353, I²=9.3%). Fixed-effects models were used for meta-analysis, showing a significant difference between the intervention and control groups (WMD=-0.78, 95% CI (-0.89, -0.67), P = 0.353), with a significant effect size, as shown in Fig. 6 . This indicates that continuity nursing has a significant improvement effect on HbA1 in GDM patients compared to routine care and is worthy of clinical promotion. Effect of Continuous Care on Preterm Birth Rate in Pregnant Women with GDM This included a total of 11 articles, with a total of 1770 patients, including 894 cases in the continuity of care group and 876 cases in the dietary care group. All 11 articles reported the number of preterm births in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P = 0.085, I²=39.6%). A fixed-effects model was used for meta-analysis. The preterm birth rate in the intervention group was statistically significant compared to the control group [RR = 0.39, 95% CI= (0.26,0.59), P = 0.085], and the effect size was significant, as shown in Fig. 7 . This indicates that continuity of care, compared to routine care, can effectively reduce the preterm birth rate in pregnant women with GDM. Effect of Continuity of Care on Cesarean Section Rate in Pregnant Women with GDM This included a total of 15 articles, with a total of 2045 patients, including 1025 cases in the continuity of care group and 1020 cases in the dietary care group. All 15 articles reported the number of cesarean sections in two groups of pregnant women with gestational diabetes mellitus. The heterogeneity test results between studies were (P 50%). A random-effects model was used for meta-analysis. Egger's test did not suggest publication bias (P = 0.50 > 0.05). Sensitivity analysis of the literature did not reveal significantly heterogeneous articles. The cesarean section rate in the intervention group was statistically significant compared to the control group [RR = 0.60, 95% CI=(0.52,0.68), P < 0.01], and the effect size was significant, as shown in Fig. 8 . This indicates that continuity of care, compared to routine care, can effectively reduce the cesarean section rate in pregnant women with GDM. Exploring the significant heterogeneity in this study, it may be due to differences in the continuity of care models included in the study, or the I² and Q tests themselves are greatly influenced by sample size. We conducted subgroup analysis using a random-effects model to explore the effects of online and face to face continuity of care states on the impact of continuity of care on cesarean section rate in pregnant women with GDM. As shown in Fig. 8 -B, face to face continuity of care had a significant effect on fasting blood glucose in pregnant women with GDM [RR = 0.50 (95% CI[0.42,0.6], P < 0.01)], with significant heterogeneity between studies (I²=76.8%, Q test P < 0.01). online continuity of care had a significant effect on fasting blood glucose in pregnant women with GDM [RR = 0.78 (95% CI[0.63,0.96], P = 0.118)], with no significant heterogeneity between studies (I²=45.7%, Q test P = 0.118), indicating that the grouping was reasonable. In the forest plot of subgroup analysis, the combined effect size of online and face to face continuity of care models was on the left side of the vertical axis and did not intersect with the null line, indicating that the continuity of care model has an improving effect on cesarean section rate in pregnant women with GDM. Effect of Continuity of Care on Macrosomia Rate in Pregnant Women with GDM This included a total of 15 articles, with a total of 2422 patients, including 1225 cases in the continuity of care group and 1197 cases in the dietary care group. All 15 articles reported the number of macrosomia cases in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P = 0.04, I²=42.9% 0.05). Sensitivity analysis of the literature did not reveal significantly heterogeneous articles. The macrosomia rate in the intervention group was statistically significant compared to the control group [RR = 0.42, 95% CI=(0.30,0.59), P = 0.040], and the effect size was significant, as shown in Fig. 9 . This indicates that continuity of care, compared to routine care, can effectively reduce the probability of macrosomia in pregnant women with GDM. Effect of Continuity of Care on Postpartum Hemorrhage in Pregnant Women with GDM This included a total of 7 articles, with a total of 972 patients, including 485 cases in the continuity of care group and 487 cases in the dietary care group. All 7 articles reported the number of postpartum hemorrhage cases in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P = 0.91, I²=0.0% <50%). There was no heterogeneity, and a fixed-effects model was used for meta-analysis. The postpartum hemorrhage rate in the intervention group was statistically significant compared to the control group [RR = 0.20, 95% CI=(0.10,0.41), P = 0.910], and the effect size was significant, as shown in Fig. 10 . The data in this study demonstrate that continuity of care, compared to routine care, can effectively reduce the likelihood of postpartum hemorrhage in pregnant women with GDM. Effect of Continuity of Care on Neonatal Hypoglycemia in Pregnant Women with GDM This included a total of 6 articles, with a total of 1139 patients, including 576 cases in the continuity of care group and 563 cases in the dietary care group. All 6 articles reported the number of neonatal hypoglycemia cases in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P = 0.039, I²=57.3% >50%) as shown in Fig. 11 A. Moderate heterogeneity was observed, and a random-effects model was used for meta-analysis. Egger's test suggested publication bias (P = 0.002 < 0.05). Sensitivity analysis revealed that Tong Wei Yew et al. may have influenced heterogeneity. 18 After excluding this study, heterogeneity decreased significantly (P = 0.291, I²=19.5%), indicating that Tong Wei Yew et al. may be a possible source of heterogeneity in this analysis. A fixed-effects model was used for combined effect size analysis. The results showed that the rate of neonatal hypoglycemia in the intervention group was significantly lower than that in the control group, with statistical significance [RR = 0.17, 95% CI (0.08,0.34), P = 0.291]. Continuity of care can significantly reduce the rate of neonatal hypoglycemia in pregnant women with GDM, as shown in Fig. 11 B. Effect of Continuity of Care on Neonatal Asphyxia in Pregnant Women with GDM This study included a total of 4 articles, with a total of 1010 patients, including 505 cases in the continuity of care group and 505 cases in the dietary care group. All 4 articles reported the number of cases of neonatal asphyxia in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P = 0.996, I²=0.0% <50%). There was no heterogeneity, and a fixed-effects model was used for meta-analysis. The rate of neonatal asphyxia in the intervention group was statistically significant compared to the control group [RR = 0.29, 95% CI=(0.10,0.85), P = 0.996], and the effect size was significant, as shown in Fig. 12 . In this study, the data demonstrate that continuity of care, compared to routine care, can effectively reduce the probability of neonatal asphyxia in pregnant women with GDM. Effect of Continuity of Care on Low Birth Weight in Newborns of Pregnant Women with GDM This study included a total of 4 articles, with a total of 526 patients, including 258 cases in the continuity of care group and 268 cases in the dietary care group. All 4 articles reported the number of cases of low birth weight in newborns of pregnant women with GDM. The heterogeneity test results between studies were (P = 0.40, I²=0.0% <50%). There was no heterogeneity, and a fixed-effects model was used for meta-analysis. The rate of low birth weight in newborns in the intervention group was not statistically significant compared to the control group [RR = 0.53, 95% CI=(0.24,1.20), P = 0.400], as shown in Fig. 13 . The data in this study indicate that continuity of care, compared to routine care, cannot conclusively demonstrate a reduction in the probability of low birth weight in newborns of pregnant women with GDM. Discussion GDM has emerged as a prevalent condition, imposing significant health and economic burdens. The prevalence of GDM has been steadily increasing over the past few decades, posing a growing impact on public health and potentially leading to chronic non-communicable diseases for both mothers and their offspring. 33 Early identification of high-risk individuals is crucial for implementing preventive and intervention measures to mitigate the risks associated with GDM and adverse pregnancy outcomes. Effective nursing interventions have been shown to be essential frontline strategies for GDM prevention and intervention. Various patterns of continuous care have been established to manage GDM, such as the one-day nursing clinic initiated in 2011, which provides comprehensive education on GDM basics, dietary interventions, physical activity, weight management, and blood glucose self-monitoring methods. 34 , 35 These patterns serve as exemplary approaches for group management of GDM and have been implemented nationwide. 36 However, there remains a lack of understanding among many GDM patients regarding maintaining a balanced diet and healthy lifestyle during pregnancy, highlighting the urgent need for effective nursing interventions and educational guidance on a national scale. Our study have shown that continuous care intervention can improve fasting blood glucose, postprandial 2-hour blood glucose, and glycated hemoglobin in GDM patients. Subgroup analysis of fasting blood glucose showed that the effect size of the online continuous care model and the combined online and face to face continuous care model crossed the null line in the forest plot, indicating that the effect size between the study experimental group and the control group was not significant. the effect size of the face to face continuous care model was to the left of the null line, and the effect size was significant. Subgroup analysis of postprandial 2-hour blood glucose showed that the effect sizes of the combined online and face to face continuous care and the online continuous care models were to the left of the null line, and the effect sizes were significant. Meta-analyses of the two groups of studies both indicated that there was a significant statistical difference between continuous care models and conventional care models, and continuous care could improve the blood glucose status of GDM. Multiple studies have shown that the results of continuous care application in type 2 diabetes mellitus (T2DM) are similar. 37 Continuous care can effectively control blood glucose and improve adverse pregnancy outcomes, which may be related to the comprehensive nursing model of continuous care. Zeng X et al. confirmed that continuous care has clinical value in predicting maternal blood glucose control level during pregnancy and has a positive impact on blood glucose control in gestational diabetes patients. 38 In this study, continuous care can improve the cesarean section rate, macrosomia rate, low birth weight rate, postpartum hemorrhage rate, neonatal asphyxia rate, neonatal hypoglycemia rate, and premature birth rate in GDM. Analysis of postpartum hemorrhage in 7 articles showed homogeneity, among which the 95% CI of Tian Y 2021's study crossed the null line, indicating that the effect size between the study experimental group and the control group was equal, and the experimental factor was invalid, but the effect sizes of the other six studies were to the left of the null line, which did not have a significant impact on the overall study's total effect size, proving that continuous care can alleviate postpartum hemorrhage in GDM. Ugwudike B have proposed early effective nursing interventions to reduce the incidence of postpartum hemorrhage. 39 Analysis of neonatal asphyxia in 5 articles showed homogeneity, although 4 articles intersected with the vertical line, their effect sizes were all to the left of the vertical line, indicating that continuous care can effectively reduce the risk of neonatal asphyxia. Analysis of cesarean section rates in 15 articles showed significant heterogeneity, but the overall effect size was to the left of the vertical line. Subgroup analysis of the face to face continuous care showed significant heterogeneity in the study, among which the effect size of Chan RS 2018's study was to the right of the vertical line, which had a certain impact on the heterogeneity of the article, but the overall subgroup effect size was to the left of the vertical line. Subgroup analysis of the online continuous care showed less heterogeneity, among which the effect sizes of Sung JH 2019 and Tian Y 2021 were to the right of the vertical line, and the rest of the articles were to the left, which had a certain impact on the total effect size of this subgroup, indicating significant statistical differences between the two subgroups of continuous care and routine care, and continuous care can reduce the cesarean section rate in GDM to a certain extent. Analysis of macrosomia rates in 15 articles showed minor heterogeneity, with Carolan-Olah M 2018 and Tian Y 2021 studies' effect sizes to the right of the vertical line, and the overall effect value to the left. Studies have emphasized the significant benefits of continuous care for GDM, yet its widespread implementation remains limited. Many pregnant women do not receive adequate interpregnancy care in medical institutions, leading to deficiencies in optimizing pre-pregnancy chronic disease management, post-pregnancy risk stratification, and pregnancy management. 35 Factors such as BMI and dietary control have been identified as independent risk factors affecting blood glucose control levels in pregnant women with GDM, highlighting the importance of tailored interventions to effectively manage blood glucose levels and improve maternal and neonatal outcomes. 40 In the era of information technology, some hospitals have developed GDM-related apps, which have shown significant advantages in GDM health management, particularly in enhancing patient self-management capabilities and promoting healthy behaviors. 24 , 41 Remote medical interventions, such as sensor trials for blood glucose monitoring without invasive measurements, have demonstrated high acceptability among participants. Harnessing these technological advancements in continuous care could further enhance its effectiveness. There were limitation needed to be issued in this article. The quality of the 22 included studies was generally moderate, primarily due to the lack of strict random design schemes in the included studies. The main problems identified were: (1) Randomization: Many articles only mentioned randomization in the text without providing detailed descriptions of the specific implementation methods and processes, leading to the risk of bias and methodological heterogeneity in the included literature. (2) Blinding: Due to the presence of many complex and uncontrollable factors during the study process, it was difficult to implement blinding for the subjects, intervention implementers, and evaluators in the included literature, i.e., achieving triple blinding. Only 4 articles in this study mentioned blinding, with only 1 of them being double-blinded, leading to methodological heterogeneity in the literature. (3) The continuous care included in the studies belongs to a diversified nursing model, with some differences in continuous care measures in the nursing model. The overall classification was only online, face to face, and combined online and face to face continuous care models, which had a certain impact on the intervention effect of outcome indicators. (4) The intervention content, time, and follow-up situation varied among the studies. Some studies set and guided self-management, while others did not involve self-management. Due to the diversity of continuous care plans collected, there was significant clinical heterogeneity among the literature and limited number of studies on continuous care outcomes for GDM and the rigor of randomized controlled trials, there were relatively few high-quality literature with consistent outcome evaluation indicators. Therefore, when the inclusion criteria were loosed, the clinical heterogeneity among the literature in the meta-analysis results was significant. And under the premise that there may be clinical and methodological heterogeneity in the included literature, there may be statistical heterogeneity among the studies. Conclusion Our study systematically evaluates the effects of continuous care on GDM outcomes, affirming its positive impact. Continuous care offers numerous benefits throughout pregnancy, including fasting blood glucose, average blood glucose at 2 hours after, HbA1c levels, preterm birth rate, cesarean section rate, macrosomia rate, postpartum hemorrhage rate, neonatal hypoglycemia rate, neonatal asphyxia rate and low birth weight rate. Declarations Acknowledgement Not applicable. Authors’ contributions FC designed the study, conducted literature retrieval and data extraction, and wrote the manuscript. CS contributed to the design of the meta-analysis methodology and reviewed the manuscript. YL, TZ, YZ, ZL, and LYparticipated in data verification and result discussion, and reviewed the manuscript. All authors approved the final version of the manuscript. Funding Not applicable. Clinical trial number Not applicable. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials All data generated or analyzed during this study are included in the published article. Competing of interests The authors declare no competing interests. Author details Feifei Chen 1 *, MSc,Chengwen Song 2 ,MPa,Yuanci Lyu,MSc 1 ,Ting Zhou,MSC 1 ,Yanyan Zhao,MSc 1 ,Zhihan Li,MSc 1 ,Lu Yin,MSc 1 * 1. School of Nursing and Health Management, Wuhan Donghu College, Wuhan, Hubei, China, 435400 2. Department of Public Administration, General Graduate School, Kookmin University, Seoul, Republic of Korea,02707 References Sert UY, Ozgu-Erdinc AS. Gestational Diabetes Mellitus Screening and Diagnosis. Adv Exp Med Biol. 2021;1307:231–55. 10.1007/5584_2020_512 . Mistry SK, et al. Gestational diabetes mellitus (GDM) and adverse pregnancy outcome in South Asia: A systematic review. Endocrinol Diabetes Metab. 2021;4:e00285. 10.1002/edm2.285 . Zhu Y, Zhang C. Prevalence of Gestational Diabetes and Risk of Progression to Type 2 Diabetes: a Global Perspective. Curr Diab Rep. 2016;16. 10.1007/s11892-015-0699-x . Meek CL, et al. Seasonal variations in incidence and maternal-fetal outcomes of gestational diabetes. Diabet Med. 2020;37:674–80. 10.1111/dme.14236 . Modzelewski R, Stefanowicz-Rutkowska MM, Matuszewski W, Bandurska-Stankiewicz EM. Gestational Diabetes Mellitus-Recent Literature Review. J Clin Med. 2022;11. 10.3390/jcm11195736 . Choudhury AA. Devi Rajeswari, V. Gestational diabetes mellitus - A metabolic and reproductive disorder. Biomed Pharmacother. 2021;143:112183. 10.1016/j.biopha.2021.112183 . Syed H, Slayman T, DuChene Thoma K. ACOG Committee Opinion 804: Physical Activity and Exercise During Pregnancy and the Postpartum Period. Obstet Gynecol. 2021;137:375–6. 10.1097/aog.0000000000004266 . Tsakiridis I, et al. Diagnosis and Management of Gestational Diabetes Mellitus: An Overview of National and International Guidelines. Obstet Gynecol Surv. 2021;76:367–81. 10.1097/ogx.0000000000000899 . Depla AL, et al. Effect of maternal diabetes on fetal heart function on echocardiography: systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2021;57:539–50. 10.1002/uog.22163 . Ya-ting HU, LI. H.-j. Effect of continuous nursing intervention in nursing care of gestational diabetes mellitus patients. CHINA Mod Med. 2019;26:231–3. Su C. Network interactive continuous nursing intervention for pregnant women with diabetes The impact of treatment compliance and pregnancy outcomes. Med J Chin People's Health. 2019;31:156–8. Yaqin DLYZCCMHL. Effects of three-stage comprehensive continuous management on delivery outcomes in the patients with gestational diabetes. J Navy Med. 2021;42:751–5. LINLI Z. The impact of body quality management combined with continuity of care on the control of body quality and delivery methods of primiparous women. CHINA’S NATUROPATHY. 2019;27:76–8. 10.19621/j.cnki.11-3555/r.2019.1638 . Xiao-li XIAO. -l. Application of Continuation Nursing in Specialist Outpatients in Clinical Nursing of Pregnant Women with Gestational Diabetes. China &Foreign Med Treat. 2019;38:166–8. 10.16662/j.cnki.1674-0742.2019.20.166 . Wei LJYYC. H.-x. S. X.-h. Z. Y. S. Application study of online and face to face mode in continuing nursing care of gestational diabetes. CHINA Mod Med. 2021;28:237–9. Zhouhui ZLZHJFZRG. R. H. B. L. Application of continuous nursing under the mode of hospital nursing team guiding community nursing staff in gestational diabetes. CHINA Mod DOCTOR. 2019;57:152–5. Sung JH, Lee DY, Min KP, Park CY. Peripartum Management of Gestational Diabetes Using a Digital Health Care Service: A Pilot, Randomized Controlled Study. Clin Ther. 2019;41:2426–34. 10.1016/j.clinthera.2019.09.005 . Yew TW, et al. A Randomized Controlled Trial to Evaluate the Effects of a Smartphone Application-Based Lifestyle Coaching Program on Gestational Weight Gain, Glycemic Control, and Maternal and Neonatal Outcomes in Women With Gestational Diabetes Mellitus: The SMART-GDM Study. Diabetes Care. 2021;44:456–63. 10.2337/dc20-1216 . Carolan-Olah M, Sayakhot P. A randomized controlled trial of a web-based education intervention for women with gestational diabetes mellitus. Midwifery. 2019;68:39–47. 10.1016/j.midw.2018.08.019 . Chan RS, et al. Randomized trial examining effectiveness of lifestyle intervention in reducing gestational diabetes in high risk Chinese pregnant women in Hong Kong. Sci Rep. 2018;8:13849. 10.1038/s41598-018-32285-6 . Zhenzhen G. Analysis of the Influence of Continuous Nursing on the Treatment Compliance and Pregnancy Outcome of Gestational Diabetes Patients. DIABETES NEW WORLD. 2021;24:155–7. 10.16658/j.cnki.1672-4062.2021.09.155 . Xiao-li Y, & LR. -b. The Effect of Medical and Nursing Integration + WeChat Interactive Continuous Nursing Intervention on the Self-management Level and Nursing Service Satisfaction of Patients with Gestational Diabetes. DIABETES NEW WORLD. 2021;24:1–3. 10.16658/j.cnki.1672-4062.2021.04.001 . Wei-feng C. -n. The Value of Continuous Nursing in Patients with Gestational Diabetes and the Observation of Nursing Measures and Satisfaction. DIABETES NEW WORLD. 2020;23:128–30. 10.16658/j.cnki.1672-4062.2020.20.128 . Ding B, et al. WeChat-assisted dietary and exercise intervention for prevention of gestational diabetes mellitus in overweight/obese pregnant women: a two-arm randomized clinical trial. Arch Gynecol Obstet. 2021;304:609–18. 10.1007/s00404-021-05984-1 . Chahed S, et al. Impact of a tailored-care education programme on maternal and neonatal outcomes in pregnant women with gestational diabetes: a randomized controlled trial. Pan Afr Med J. 2022;43:128. 10.11604/pamj.2022.43.128.34084 . Rasekaba TM, et al. Using technology to support care in gestational diabetes mellitus: Quantitative outcomes of an exploratory randomised control trial of adjunct telemedicine for gestational diabetes mellitus (TeleGDM). Diabetes Res Clin Pract. 2018;142:276–85. 10.1016/j.diabres.2018.05.049 . Tian Y, Zhang S, Huang F, Ma L. Comparing the Efficacies of Telemedicine and Standard Prenatal Care on Blood Glucose Control in Women With Gestational Diabetes Mellitus: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2021;9:e22881. 10.2196/22881 . Borgen I, et al. Effect of the Pregnant + smartphone application in women with gestational diabetes mellitus: a randomised controlled trial in Norway. BMJ Open. 2019;9:e030884. 10.1136/bmjopen-2019-030884 . Sadiya A, Jakapure V, Shaar G, Adnan R, Tesfa Y. Lifestyle intervention in early pregnancy can prevent gestational diabetes in high-risk pregnant women in the UAE: a randomized controlled trial. BMC Pregnancy Childbirth. 2022;22:668. 10.1186/s12884-022-04972-w . Munda A, Mlinaric Z, Jakin PA, Lunder M. Pongrac Barlovic, D. Effectiveness of a comprehensive telemedicine intervention replacing standard care in gestational diabetes: a randomized controlled trial. Acta Diabetol. 2023;60:1037–44. 10.1007/s00592-023-02099-8 . Qi S, Dong Y. Effect of Multidisciplinary Team Continuous Nursing on Glucose and Lipid Metabolism, Pregnancy Outcome, and Neonatal Immune Function in Gestational Diabetes Mellitus. Dis Markers 2022, 7285639. 10.1155/2022/7285639 (2022). Cumpston M, et al. Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions. Cochrane Database Syst Rev. 2019;10(Ed000142). 10.1002/14651858.Ed000142 . Caissutti C, Berghella V. Scientific Evidence for Different Options for GDM Screening and Management: Controversies and Review of the Literature. Biomed Res Int 2017, 2746471. 10.1155/2017/2746471 (2017). Juan J, Yang H, Prevalence. Prevention, and Lifestyle Intervention of Gestational Diabetes Mellitus in China. Int J Environ Res Public Health. 2020;17. 10.3390/ijerph17249517 . Ogunwole SM, et al. Interconception Care for Primary Care Providers: Consensus Recommendations on Preconception and Postpartum Management of Reproductive-Age Patients With Medical Comorbidities. Mayo Clin Proc Innov Qual Outcomes. 2021;5:872–90. 10.1016/j.mayocpiqo.2021.08.004 . Yeh T, Yeung M, Mendelsohn Curanaj FA. Inpatient Glycemic Management of the Pregnant Patient. Curr Diab Rep. 2018;18:73. 10.1007/s11892-018-1045-x . Ortiz FM, Jimenez EY, Boursaw B, Huttlinger K. Postpartum Care for Women with Gestational Diabetes. MCN Am J Matern Child Nurs. 2016;41:116–22. 10.1097/nmc.0000000000000215 . Zeng X, et al. Information-based continuous nursing on pregnant women with gestational diabetes mellitus. Eur Rev Med Pharmacol Sci. 2023;27:8762–72. 10.26355/eurrev_202309_33798 . Ugwudike B, Kwok M. Update on gestational diabetes and adverse pregnancy outcomes. Curr Opin Obstet Gynecol. 2023;35:453–9. 10.1097/gco.0000000000000901 . Rudner N. Nursing is a health equity and social justice movement. Public Health Nurs. 2021;38:687–91. 10.1111/phn.12905 . Kytö M, et al. Supporting the Management of Gestational Diabetes Mellitus With Comprehensive Self-Tracking: Mixed Methods Study of Wearable Sensors. JMIR Diabetes. 2023;8:e43979. 10.2196/43979 . Additional Declarations No competing interests reported. Supplementary Files searchstrategy20231226.docx Table S1. Major search Strategy details Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7893643","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":535681914,"identity":"508af61e-4ca2-408b-ae3c-8815d21bc058","order_by":0,"name":"Feifei Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIie3RMYvCMBTA8SdCXYJZE5D6FSKu/TDvIWTqieDSwaGHch2ud/dVHG8sFDLF3TEiePMt0kmss2J62w35zfnz8hKAIPiHosHXT4MsifkgJ4fZyp8MmQXhRnoqy+qonDX+JBYpSJfUpPZ0kodNv8PF2K5SmGqU+UxnlEfAi3f07PKJiDaZczB6T98jEHa39UypVEWlXsrXsk1sBEq8eBKBk5wuNW1rfl7QW79Lkk4BWZsY0NAtYUa3ye2RYSbQGubdZVysTa+5feXY0W+TrWJefDxP7rC/HQ+CIAgeugLer05w6KTVVgAAAABJRU5ErkJggg==","orcid":"","institution":"Wuhan Donghu College","correspondingAuthor":true,"prefix":"","firstName":"Feifei","middleName":"","lastName":"Chen","suffix":""},{"id":535681915,"identity":"2ae2fa2e-3a4e-43ce-a3c1-7e6276e398bc","order_by":1,"name":"Chengwen Song","email":"","orcid":"","institution":"Kookmin University","correspondingAuthor":false,"prefix":"","firstName":"Chengwen","middleName":"","lastName":"Song","suffix":""},{"id":535681916,"identity":"53a83c67-54c2-4545-bf3d-2169671d5639","order_by":2,"name":"Yuanci Lyu","email":"","orcid":"","institution":"Wuhan Donghu College","correspondingAuthor":false,"prefix":"","firstName":"Yuanci","middleName":"","lastName":"Lyu","suffix":""},{"id":535681917,"identity":"47ad9417-9075-40d0-9edf-bc1a9ad0f46e","order_by":3,"name":"Ting Zhou","email":"","orcid":"","institution":"Wuhan Donghu College","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Zhou","suffix":""},{"id":535681918,"identity":"b5bbe869-13ba-47fa-8ce7-4db2487125b9","order_by":4,"name":"Yanyan Zhao","email":"","orcid":"","institution":"Wuhan Donghu College","correspondingAuthor":false,"prefix":"","firstName":"Yanyan","middleName":"","lastName":"Zhao","suffix":""},{"id":535681919,"identity":"96c5b766-5d29-4ed6-bba1-27c0fdc867a4","order_by":5,"name":"Zhihan Li","email":"","orcid":"","institution":"Wuhan Donghu College","correspondingAuthor":false,"prefix":"","firstName":"Zhihan","middleName":"","lastName":"Li","suffix":""},{"id":535681920,"identity":"7415eef9-187a-4cbc-b5f2-e528e683a2f1","order_by":6,"name":"Lu Yin","email":"","orcid":"","institution":"Wuhan Donghu College","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Yin","suffix":""}],"badges":[],"createdAt":"2025-10-18 13:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7893643/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7893643/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94633680,"identity":"8381d8ee-4af8-4f5f-8e03-61fb1bafa39e","added_by":"auto","created_at":"2025-10-29 06:39:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94891,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowgram of inclusion of studies.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/0a049202589f07b6154f2377.png"},{"id":94633758,"identity":"5d3ac784-c427-4c96-8262-2f9a4ae74a49","added_by":"auto","created_at":"2025-10-29 06:39:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":669323,"visible":true,"origin":"","legend":"\u003cp\u003eA) Risk analysis of bias in clinical studies on the impact of continuous care on GDM outcomes. 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B) The forest map for comparing the rates of fasting blood glucose in GDM patients after excluding three articles.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/e230ddfe1578992f53aee32a.png"},{"id":94633675,"identity":"b1ad9505-3bfc-4540-8be8-d0e9a179cf14","added_by":"auto","created_at":"2025-10-29 06:39:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":136069,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest map for comparing the rates of fasting blood glucose in GDM patients in three subgroups analysis.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/6bcca8620c10ad280519e87b.png"},{"id":94633747,"identity":"76c7bb32-1305-4a57-aa25-6c7c2710a70b","added_by":"auto","created_at":"2025-10-29 06:39:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":218822,"visible":true,"origin":"","legend":"\u003cp\u003eA) The forest map for comparing the rates of postprandial 2-hour blood glucose in GDM patients. B) The forest map for comparing the rates of postprandial 2-hour blood glucose in GDM patients in three subgroups analysis.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/391a949e3d286d05a47ea086.png"},{"id":94633766,"identity":"33cf20ee-4cb8-42bf-87fe-45221991bf42","added_by":"auto","created_at":"2025-10-29 06:39:12","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":64325,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest map for comparing HbA1 values in GDM patients.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/e23c932fdd16c782381f5f9a.png"},{"id":94633723,"identity":"48fe6d45-7903-49b6-a012-e7277b7014d5","added_by":"auto","created_at":"2025-10-29 06:39:07","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":104768,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest map for comparing the rates of preterm births in GDM patients.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/391e6b51fa6b023184014495.png"},{"id":94633722,"identity":"29c30022-c0d7-483c-95f7-afd6d96dae1e","added_by":"auto","created_at":"2025-10-29 06:39:07","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":259259,"visible":true,"origin":"","legend":"\u003cp\u003eA) The forest map for comparing the rates of cesarean sections in GDM patients. B) The forest map for comparing the rates of cesarean sections in GDM patients in three subgroups analysis.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/e5377982d41d54b5609e82ee.png"},{"id":94633771,"identity":"ab1c518b-e8ed-4a8f-a23d-62de2413fbb4","added_by":"auto","created_at":"2025-10-29 06:39:12","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":125188,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest map for comparing rates of macrosomia in GDM patients.\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/e297f0fde7de109b86d16a04.png"},{"id":94633767,"identity":"3ebe5aca-9899-4865-8830-88e34e6336bf","added_by":"auto","created_at":"2025-10-29 06:39:12","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":78547,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest map for comparing rates of postpartum hemorrhage in GDM patients.\u003c/p\u003e","description":"","filename":"Figure10.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/4e1c8a5ba4742011c0e3713c.png"},{"id":94633762,"identity":"fbf0878c-8f02-462a-8744-d4653db3296b","added_by":"auto","created_at":"2025-10-29 06:39:11","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":138783,"visible":true,"origin":"","legend":"\u003cp\u003eA) The forest map for comparing rates of neonatal hypoglycemia in GDM patients. B) The forest map for comparing the rates of neonatal hypoglycemia in GDM patients after excluding one article.\u003c/p\u003e","description":"","filename":"Figure11.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/bf1b355e1df42dcfaacc63d6.png"},{"id":94633682,"identity":"8140fb08-d71b-49db-a893-a292d1ce2b22","added_by":"auto","created_at":"2025-10-29 06:39:06","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":64510,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest map for comparing rates of neonatal asphyxia in GDM patients.\u003c/p\u003e","description":"","filename":"Figure12.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/9d915b8d9c94ed45c926bbae.png"},{"id":94633742,"identity":"d86bae22-635d-41fb-8aa3-f0fa48edcaa5","added_by":"auto","created_at":"2025-10-29 06:39:09","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":60417,"visible":true,"origin":"","legend":"\u003cp\u003eThe forest map for comparing rates of low birth weight in GDM patients.\u003c/p\u003e","description":"","filename":"Figure13.png","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/2fec1029c4851c5014488e32.png"},{"id":94633828,"identity":"2cca3178-5dd7-4fd0-bf6d-093591abd4d9","added_by":"auto","created_at":"2025-10-29 06:39:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3219442,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/54c35c58-8bbf-4db9-ae55-abae3f4ca5f2.pdf"},{"id":94633751,"identity":"6822f5f8-c00c-4828-9a82-e85fe1d22c4a","added_by":"auto","created_at":"2025-10-29 06:39:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33185,"visible":true,"origin":"","legend":"\u003cp\u003eTable S1. Major search Strategy details\u003c/p\u003e","description":"","filename":"searchstrategy20231226.docx","url":"https://assets-eu.researchsquare.com/files/rs-7893643/v1/208b706b79f6e93bac8c764b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of Continuous Care on Gestational Diabetes Mellitus Patients: A Systematic Review and Meta-analysis of 22 RCTs","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGestational diabetes mellitus (GDM) is a form of diabetes characterized by high blood glucose levels that develop during pregnancy without prior abnormal glucose tolerance.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Its prevalence has been steadily rising, posing significant risks to both mothers and fetuses worldwide.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Globally, the International Diabetes Federation reported a prevalence of around 16.7% in 2021, with higher rates observed in developing and low-income countries, particularly in regions like the Middle East, North Africa, Southeast Asia, and the Western Pacific.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The impact of GDM on maternal and neonatal health is profound, with complications including gestational hypertension, premature birth, and fetal deformities. Moreover, women with GDM face an increased risk of developing type 2 diabetes later in life, while their offspring are more susceptible to obesity and diabetes.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Economic burdens associated with diagnosis, treatment, and hospitalization further compound the challenges posed by GDM.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Given its detrimental effects, addressing the adverse outcomes of GDM is imperative.\u003c/p\u003e\u003cp\u003eEfforts to manage GDM have seen advancements in developed countries, with guidelines emphasizing lifestyle modifications as first-line treatment.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e These interventions include dietary adjustments, physical activity, self-monitoring of blood glucose, and medical nutrition therapy, all of which have shown efficacy in controlling blood glucose levels and reducing postpartum complications.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Continuity of nursing, defined as a comprehensive approach to healthcare delivery aimed at improving treatment effectiveness and patient quality of life through personalized management, has gained traction in managing various conditions, including GDM.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn the context of GDM management, the continuity of care model emphasizes continuous monitoring and intervention throughout pregnancy, encompassing blood glucose monitoring, dietary control, exercise regimens, medication, and prenatal guidance.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e While its benefits are acknowledged, there remains a dearth of systematic research evaluating its effectiveness comprehensively. Thus, conducting meta-analyses and applied research to assess the intervention's impact on various outcomes in GDM patients holds significant clinical relevance.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Such studies can inform clinical decision-making, improve patient management, and guide future research and practice aimed at preventing and managing GDM effectively.\u003c/p\u003e\u003cp\u003eThe research objectives include evaluating the impact of continuity of care on blood glucose control, self-management abilities, and delivery outcomes in GDM patients through meta-analysis. Additionally, the study aims to explore differences in psychological and pregnancy outcomes among GDM patients receiving continuity of care interventions, providing insights into its suitability and compliance in this population. The research hypotheses posit that continuous nursing can improve blood glucose levels and adverse pregnancy outcomes in GDM patients, potentially surpassing conventional nursing modes in efficacy. By maximizing patient satisfaction, enhancing pregnancy outcomes, and reducing complications, continuity of care emerges as a pivotal strategy in addressing the challenges posed by GDM.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSearch Strategy and Study Eligibility\u003c/h2\u003e\u003cp\u003e The meta-analysis was reported following the Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) statement. Our study protocol was registered with PROSPERO (registration number CRD42023443724) before implementation. To ensure comprehensive coverage, we conducted systematic searches across multiple databases from their inception up to April 2023. These databases included PubMed, Web of Science, OVID-Embase, The Cochrane Library, Sinomed, ScienceDirect, IEEE, ProQuest, SpringerLink, EBSCO, JSTOR, BMJ, Taylor \u0026amp; Francis, UpToDate, JAMA (Journal of the American Medical Association), CNKI, Wanfang Database, VIP Database, and China National Knowledge Infrastructure (CNKI). We utilized a combination of subject terms and free terms tailored to each database's specifications. Additionally, we manually searched relevant meta-analyses, reviews, and reference lists of included studies.Two reviewers (F.C and H.Y) obtained the following information from each of the included studies: the first author, year date of publication, study center, study design, enrollment period, sample size, interventions and so on. English databases were searched using keywords such as \"gestational diabetes/GDM/pregnancy-induced diabetes/diabetes\" and \"continuity of care/continual care/continuous care/follow-up/extended care.\" Chinese databases were searched using equivalent terms in Chinese characters, with adjustments made according to the corresponding subject terms in each database. The inclusion of related literature from manual searches was supplemented to ensure comprehensive retrieval. A fixed effects model was used when there was significant heterogeneity (I\u0026sup2; \u0026lt; 50%). otherwise, a random effects model was employed. Funnel plots and Egger\u0026rsquo;s tests were used to identify possible publication bias in the results. RevMan 5.4 software was used to prepare and analyze reviews from the Cochrane database. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eIn terms of study design, only randomized controlled trials were included. Inclusion criteria: (1) Randomized controlled trials (RCTs) investigating the effect of continuity of care in GDM patients. (2) Patients diagnosed with GDM through OGTT. aged\u0026thinsp;\u0026gt;\u0026thinsp;18 years. (3) The control group received routine care, while the intervention group received additional continuity of care, including health education through platforms such as QQ, WeChat, outpatient visits, home visits, and maternity lectures. (4) Studies including one or more of the following outcome measures were included: Blood glucose levels, including fasting blood glucose and average blood glucose levels 2 hours after meals. Pregnancy outcomes, such as preterm birth, jaundice, macrosomia, and neonatal asphyxia. Fasting blood glucose and average blood glucose levels 2 hours after meals were considered primary outcome measures, while others were secondary. Exclusion criteria: (1) Duplicate publications. (2) Studies with incomplete data that could not be obtained even after contacting the authors. (3) Inaccessible full-text articles.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Extraction and Quality Assessment\u003c/h3\u003e\n\u003cp\u003eTwo reviewers independently extracted data using a predefined form, cross-validating results. Discrepancies were resolved through consultation with a third researcher. Extracted data included author names, publication years, study designs, sample sizes, interventions, and outcome measures. Missing data were requested from the original authors.If there are any disagreement, the third reviewer (S.P) would make the final decision or try to contact the author for supplement data. The reviewers used Cochrane bias risk assessment tool to evaluate the quality of the included randomized controlled trials studies. The quality assessment and data extraction were undertaken using a standardized form. The quality of the studies was divided into three grades (ABC) according to the degree of eccentricity of the studies. The quality of the literature was evaluated by two researchers independently, and the third researcher negotiated and decided in case of disagreement. There were five factors that could reduce the quality of evidence: the limitations of the study, the inconsistency of the study results, the indirectness of the study results, the imprecision of the results, and publication bias.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eWe conducted meta-analyses using Stata 18.0 software. For continuous variables, we calculated weighted mean differences or standardized mean differences as appropriate. For binary variables, we computed relative risks (RRs) with 95% confidence intervals (CIs). Heterogeneity among studies was assessed using the Q test and I\u0026sup2; statistic. We employed fixed-effects or random-effects models based on the level of heterogeneity observed. Sensitivity analyses and subgroup analyses were conducted to explore sources of heterogeneity and intervention characteristics, respectively. Descriptive analyses were performed when substantial heterogeneity precluded meta-analysis.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStudy characteristics\u003c/h2\u003e\u003cp\u003eA preliminary search was conducted based on the databases listed in the table, along with other sources, resulting in a total of 2160 grey literature articles, comprising 1324 in Chinese and 836 in English. After removing 683 duplicate articles, a total of 1477 articles were obtained. After reviewing titles and abstracts, 1364 articles were excluded, leaving 123 articles. Upon reading the full texts, 12 articles published before 2018 were excluded, along with 12 reviews and 18 non-RCT articles, resulting in 81 articles. Among these, 15 articles had no usable outcome indicators, and attempts to contact the authors were unsuccessful. Fourteen articles exhibited methodological heterogeneity, ten had poor quality assessments, and twenty were not solely focused on continuous care. Consequently, 22 articles were included in the meta-analysis. The literature search and screening process are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The total sample size of the 22 studies was 2808 cases, with 1410 cases in the intervention group and 1398 cases in the control group. \u003csup\u003e10\u0026ndash;31\u003c/sup\u003e The control measures in the control group were conventional care models, while the intervention group received additional continuous care based on the control group. The general characteristics of the included literature are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The evaluation of quality of studies were presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e according to the Cochrane Handbook (5.1.0).\u003csup\u003e32\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBasic characteristics of the included literature\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAuthor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSample Size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIntervention Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eControl Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eOutcome Indicators\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHu Yating et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Personalized continuous care plan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②③④⑤⑦⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChen Suhua et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNetwork interactive continuous care intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②③④⑤⑦⑨⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGao Zhenzhen et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Psychological care, ② Continuous care plan, ③ Lectures, ④ Dietary management, ⑤ Follow-up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e⑤⑦⑨⑰\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuan Lina et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Departmental intervention team, ② Staged continuous management, ③ Follow-up and comprehensive guidance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e④⑦⑤⑦⑧⑨\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZhao Linli et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Formation of a nursing team, ② Targeted guidance, ③ Follow-up and comprehensive care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e④⑤⑥⑦⑧⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eXiao Xiaoli et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Establishment of a continuous care team, ② Group lectures for pregnant women, ③ Guidance on self-management, blood glucose monitoring, insulin use, etc.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e④⑤⑥⑧⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYang Xiaoli et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Establishment of an integrated medical-nursing continuous care team, ② Remote reminder for glucose monitoring, ③ WeChat interactive plan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②③⑦\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLei Jun et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Establishment of a continuous care team, ② Online information platform, ③ Health education, ④ Nutritional support, ⑤ Medication intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②③⑥\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChen Weifeng et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Establishment of a continuous care team, ② Psychological care, ③ Dietary intervention, ④ Health education, ⑤ Discharge guidance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②③④⑤⑦⑨⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZhou Lingli et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Multidisciplinary nursing expert team, standardized nursing plan including weight control, health education, psychological counseling, and dietary therapy, ② Regular team training and nursing quality control and assessment, investigation of patient satisfaction with community nursing work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①④\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSung JH et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSouth Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Mobile app for personalized mobile healthcare services, ② MDT team for nursing, ③ Participants carry monitoring system devices, ④ Dedicated app for collecting clinical data and information, ⑤ Automatic transmission of experimental group data to the server via wireless network\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e④⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTong Wei Yew et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSingapore\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Habits-GDM app and healthcare professional information platform, ② Development of 12 interactive courses by endocrinologists, obstetricians, diabetes educators, and nutritionists, ③ Tools for diet, SMBG, physical activity, and weight tracking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②⑤⑧⑨\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarolan-Olah M et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Healthy food choices, ② Healthy habits or lifestyle, ③ Emotional, family, and food, ④ Blood glucose level testing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStandard clinical education course\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e⑤⑥\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBingjie Ding et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBeijing, China\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① WeChat intervention, ② Learning dietary guidelines, ③ Dietary nursing, ④ Exercise nursing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②③⑤⑥⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChahed S et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTunisia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Continuous care education, ② Dietary care, ③ Exercise education, ④ Self-blood glucose monitoring, ⑤ Follow-up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e⑤⑨⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRasekaba TM et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMelbourne, Australia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Remote medical assistance, inputting patient information to medical staff via personal data for personalized GDM care feedback, ③ Reviewing diaries at appointments, informing subsequent management decisions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e⑤\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTian Y et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① WeChat group management: researchers release a bulletin and a task card, ② To determine basic requirements including dietary advice, dietary examples from other group members, and exercise rules, ③ Patients provide self-management based on the basic standards provided, ④ Researchers provide personalized guidance for self-management\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e④⑤⑥⑦⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBorgen I et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNorway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Pregnant\u0026thinsp;+\u0026thinsp;app, ② Support for GDM management by adjusting healthy eating, exercising, and receiving feedback on blood glucose levels, ③ It includes four main icons: \"Blood sugar\", \"Physical activity\", \"Food and drink\", and \"Diabetes information\"\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e④⑤\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChan RS et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHong Kong, China\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Participants receive face-to-face or telephone consultations with continuous provision of programs, ② Nutritionists discuss specific diets and ③ exercise coaches assess participants' physical fitness levels and musculoskeletal problems, ④ Design appropriate exercise plans for participants based on international guidelines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e④⑤⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSadiya A et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnited Arab Emirates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Weight management, dietary, and exercise interventions, ② Motivational interviews, SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) goal setting, self-monitoring (pedometer, food records), and problem-solving skills\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②④\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMunda A et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNorthern California, USA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① Monthly video conferences conducted online, ② On-site visits (assessment of SMBG, ketone presence, weight, and gynecologist examination data), ③ Utilization of remote medical services from the University Medical Center Ljubljana remote medical center, where subjects install designated applications, ④ Nurses at the medical center review the data uploaded by patients weekly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e①②④⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQi S et al.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e① MDT members discuss the continuous care model, ② Self-management education to improve patient self-care awareness, ③ Psychological counseling to improve treatment compliance, ④ Close monitoring of patients, dietary guidance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRoutine care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e④⑤⑨⑬⑩\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eOutcomes: ① Fasting Plasma Glucose (FPG) ② 2-hour Plasma Glucose (2hPG) ③ HbA1c ④ Cesarean Section (C-section) Rate ⑤ Macrosomia Rate ⑥ Low Birth Weight Rate ⑦ Postpartum Hemorrhage Rate ⑧ Neonatal Asphyxia Rate ⑨ Neonatal Hypoglycemia Rate ⑩ Premature Birth Rate\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Continuity Nursing on Fasting Blood Glucose in GDM Patients\u003c/h2\u003e\u003cp\u003eThere were 11 articles with FPG as the outcome indicator, involving a total of 1324 patients, including 666 in the continuity nursing group and 658 in the routine care group. All articles reported fasting blood glucose levels in the intervention and control groups. After combining the data from the 11 studies for meta-analysis, the results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA (P\u0026thinsp;=\u0026thinsp;0.0001, I\u0026sup2;=94.8%). Egger's test did not indicate publication bias (P\u0026thinsp;=\u0026thinsp;0.546\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Sensitivity analysis revealed a decrease in heterogeneity after excluding three articles. The combined effect size Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB (WMD) was \u0026minus;\u0026thinsp;0.37, 95% CI (-0.63, -0.11), P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, indicating a significant difference between the intervention and control groups, with the intervention group showing better control of fasting blood glucose values in GDM patients. Random-effects models were used for subgroup analysis to investigate the effects of online and face to face continuity nursing on fasting blood glucose in GDM patients. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, face to face continuity nursing had a significant effect on fasting blood glucose (WMD= -0.55, 95% CI [-1.12, 0.01], P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with significant heterogeneity among studies (I\u0026sup2;=80.8%, Q test P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Online continuity nursing did not show a significant effect on fasting blood glucose (WMD=-0.32, 95% CI [-0.76, 0.12], P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with significant heterogeneity among studies (I\u0026sup2;=98.1%, Q test P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The combined effect size of the face to face and online combined mode was not significant (WMD=-0.36, 95% CI [-0.62, 0.10], P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with nonsignificant heterogeneity among studies (I\u0026sup2;=52.8%, Q test P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating reasonable grouping. The forest plot in the subgroup analysis showed that the combined effect size of face to face continuity nursing was on the left side of the vertical axis, indicating an improvement in fasting blood glucose in GDM patients.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEffect of Continuity Nursing on Postprandial 2-hour Blood Glucose in GDM Patients\u003c/h3\u003e\n\u003cp\u003eThis included 10 articles with a total of 1224 patients, including 616 in the continuity nursing group and 608 in the dietary nursing group. All 10 articles reported the mean postprandial 2-hour blood glucose values, with significant heterogeneity among studies (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, I\u0026sup2;=96.3%). Random-effects models were used for meta-analysis, revealing a statistically significant difference between the intervention and control groups (WMD=-1.34, 95% CI (-1.93, -0.76), P\u0026thinsp;=\u0026thinsp;0.0000), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA. Egger's test did not indicate publication bias (P\u0026thinsp;=\u0026thinsp;0.562\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Sensitivity analysis did not identify the source of heterogeneity. Although significant heterogeneity still existed among the included studies (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, I\u0026sup2;=96.3%), the intervention group showed significantly better control of postprandial 2-hour blood glucose values in GDM patients compared to the control group. Random-effects models were used for subgroup analysis to explore the effects of online and face to face continuity nursing on postprandial 2-hour blood glucose in GDM patients. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, face to face continuity nursing had a significant effect (WMD= -1.90, 95% CI [-4.08, 0.28], P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with significant heterogeneity among studies (I\u0026sup2;=96.4%, Q test P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Online continuity nursing also had a significant effect (WMD=-0.99, 95% CI [-1.91, -0.07], P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with significant heterogeneity among studies (I\u0026sup2;=96.8%, Q test P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The combined effect size of the face to face and online combined mode was significant (WMD=-1.06, 95% CI [-1.22, -0.90], P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with nonsignificant heterogeneity among studies (I\u0026sup2;=15.5%, Q test P\u0026thinsp;=\u0026thinsp;0.277\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating reasonable grouping. The forest plot in the subgroup analysis showed that the combined effect size of online continuity nursing and the combined mode was on the left side of the vertical axis, indicating an improvement in postprandial 2-hour blood glucose in GDM patients.\u003c/p\u003e\n\u003ch3\u003eEffect of Continuity Nursing on HbA1 in GDM Patients\u003c/h3\u003e\n\u003cp\u003eThis included 5 articles with a total of 426 patients, including 219 in the continuity nursing group and 207 in the dietary nursing group. All 5 articles reported the HbA1 values of GDM patients, with low heterogeneity among studies (P\u0026thinsp;=\u0026thinsp;0.353, I\u0026sup2;=9.3%). Fixed-effects models were used for meta-analysis, showing a significant difference between the intervention and control groups (WMD=-0.78, 95% CI (-0.89, -0.67), P\u0026thinsp;=\u0026thinsp;0.353), with a significant effect size, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. This indicates that continuity nursing has a significant improvement effect on HbA1 in GDM patients compared to routine care and is worthy of clinical promotion.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Continuous Care on Preterm Birth Rate in Pregnant Women with GDM\u003c/h2\u003e\u003cp\u003eThis included a total of 11 articles, with a total of 1770 patients, including 894 cases in the continuity of care group and 876 cases in the dietary care group. All 11 articles reported the number of preterm births in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P\u0026thinsp;=\u0026thinsp;0.085, I\u0026sup2;=39.6%). A fixed-effects model was used for meta-analysis. The preterm birth rate in the intervention group was statistically significant compared to the control group [RR\u0026thinsp;=\u0026thinsp;0.39, 95% CI= (0.26,0.59), P\u0026thinsp;=\u0026thinsp;0.085], and the effect size was significant, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. This indicates that continuity of care, compared to routine care, can effectively reduce the preterm birth rate in pregnant women with GDM.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Continuity of Care on Cesarean Section Rate in Pregnant Women with GDM\u003c/h2\u003e\u003cp\u003eThis included a total of 15 articles, with a total of 2045 patients, including 1025 cases in the continuity of care group and 1020 cases in the dietary care group. All 15 articles reported the number of cesarean sections in two groups of pregnant women with gestational diabetes mellitus. The heterogeneity test results between studies were (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, I\u0026sup2;=72.9% \u0026gt;50%). A random-effects model was used for meta-analysis. Egger's test did not suggest publication bias (P\u0026thinsp;=\u0026thinsp;0.50\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Sensitivity analysis of the literature did not reveal significantly heterogeneous articles. The cesarean section rate in the intervention group was statistically significant compared to the control group [RR\u0026thinsp;=\u0026thinsp;0.60, 95% CI=(0.52,0.68), P\u0026thinsp;\u0026lt;\u0026thinsp;0.01], and the effect size was significant, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. This indicates that continuity of care, compared to routine care, can effectively reduce the cesarean section rate in pregnant women with GDM. Exploring the significant heterogeneity in this study, it may be due to differences in the continuity of care models included in the study, or the I\u0026sup2; and Q tests themselves are greatly influenced by sample size. We conducted subgroup analysis using a random-effects model to explore the effects of online and face to face continuity of care states on the impact of continuity of care on cesarean section rate in pregnant women with GDM. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-B, face to face continuity of care had a significant effect on fasting blood glucose in pregnant women with GDM [RR\u0026thinsp;=\u0026thinsp;0.50 (95% CI[0.42,0.6], P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)], with significant heterogeneity between studies (I\u0026sup2;=76.8%, Q test P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). online continuity of care had a significant effect on fasting blood glucose in pregnant women with GDM [RR\u0026thinsp;=\u0026thinsp;0.78 (95% CI[0.63,0.96], P\u0026thinsp;=\u0026thinsp;0.118)], with no significant heterogeneity between studies (I\u0026sup2;=45.7%, Q test P\u0026thinsp;=\u0026thinsp;0.118), indicating that the grouping was reasonable. In the forest plot of subgroup analysis, the combined effect size of online and face to face continuity of care models was on the left side of the vertical axis and did not intersect with the null line, indicating that the continuity of care model has an improving effect on cesarean section rate in pregnant women with GDM.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Continuity of Care on Macrosomia Rate in Pregnant Women with GDM\u003c/h2\u003e\u003cp\u003eThis included a total of 15 articles, with a total of 2422 patients, including 1225 cases in the continuity of care group and 1197 cases in the dietary care group. All 15 articles reported the number of macrosomia cases in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P\u0026thinsp;=\u0026thinsp;0.04, I\u0026sup2;=42.9% \u0026lt;50%). The heterogeneity was moderate, and a fixed-effects model was used for meta-analysis. Egger's test did not suggest publication bias (P\u0026thinsp;=\u0026thinsp;0.369\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Sensitivity analysis of the literature did not reveal significantly heterogeneous articles. The macrosomia rate in the intervention group was statistically significant compared to the control group [RR\u0026thinsp;=\u0026thinsp;0.42, 95% CI=(0.30,0.59), P\u0026thinsp;=\u0026thinsp;0.040], and the effect size was significant, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. This indicates that continuity of care, compared to routine care, can effectively reduce the probability of macrosomia in pregnant women with GDM.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Continuity of Care on Postpartum Hemorrhage in Pregnant Women with GDM\u003c/h2\u003e\u003cp\u003eThis included a total of 7 articles, with a total of 972 patients, including 485 cases in the continuity of care group and 487 cases in the dietary care group. All 7 articles reported the number of postpartum hemorrhage cases in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P\u0026thinsp;=\u0026thinsp;0.91, I\u0026sup2;=0.0% \u0026lt;50%). There was no heterogeneity, and a fixed-effects model was used for meta-analysis. The postpartum hemorrhage rate in the intervention group was statistically significant compared to the control group [RR\u0026thinsp;=\u0026thinsp;0.20, 95% CI=(0.10,0.41), P\u0026thinsp;=\u0026thinsp;0.910], and the effect size was significant, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. The data in this study demonstrate that continuity of care, compared to routine care, can effectively reduce the likelihood of postpartum hemorrhage in pregnant women with GDM.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Continuity of Care on Neonatal Hypoglycemia in Pregnant Women with GDM\u003c/h2\u003e\u003cp\u003eThis included a total of 6 articles, with a total of 1139 patients, including 576 cases in the continuity of care group and 563 cases in the dietary care group. All 6 articles reported the number of neonatal hypoglycemia cases in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P\u0026thinsp;=\u0026thinsp;0.039, I\u0026sup2;=57.3% \u0026gt;50%) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eA. Moderate heterogeneity was observed, and a random-effects model was used for meta-analysis. Egger's test suggested publication bias (P\u0026thinsp;=\u0026thinsp;0.002\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Sensitivity analysis revealed that Tong Wei Yew et al. may have influenced heterogeneity.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e After excluding this study, heterogeneity decreased significantly (P\u0026thinsp;=\u0026thinsp;0.291, I\u0026sup2;=19.5%), indicating that Tong Wei Yew et al. may be a possible source of heterogeneity in this analysis. A fixed-effects model was used for combined effect size analysis. The results showed that the rate of neonatal hypoglycemia in the intervention group was significantly lower than that in the control group, with statistical significance [RR\u0026thinsp;=\u0026thinsp;0.17, 95% CI (0.08,0.34), P\u0026thinsp;=\u0026thinsp;0.291]. Continuity of care can significantly reduce the rate of neonatal hypoglycemia in pregnant women with GDM, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eB.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Continuity of Care on Neonatal Asphyxia in Pregnant Women with GDM\u003c/h2\u003e\u003cp\u003eThis study included a total of 4 articles, with a total of 1010 patients, including 505 cases in the continuity of care group and 505 cases in the dietary care group. All 4 articles reported the number of cases of neonatal asphyxia in two groups of pregnant women with GDM. The heterogeneity test results between studies were (P\u0026thinsp;=\u0026thinsp;0.996, I\u0026sup2;=0.0% \u0026lt;50%). There was no heterogeneity, and a fixed-effects model was used for meta-analysis. The rate of neonatal asphyxia in the intervention group was statistically significant compared to the control group [RR\u0026thinsp;=\u0026thinsp;0.29, 95% CI=(0.10,0.85), P\u0026thinsp;=\u0026thinsp;0.996], and the effect size was significant, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e. In this study, the data demonstrate that continuity of care, compared to routine care, can effectively reduce the probability of neonatal asphyxia in pregnant women with GDM.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEffect of Continuity of Care on Low Birth Weight in Newborns of Pregnant Women with GDM\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study included a total of 4 articles, with a total of 526 patients, including 258 cases in the continuity of care group and 268 cases in the dietary care group. All 4 articles reported the number of cases of low birth weight in newborns of pregnant women with GDM. The heterogeneity test results between studies were (P\u0026thinsp;=\u0026thinsp;0.40, I\u0026sup2;=0.0% \u0026lt;50%). There was no heterogeneity, and a fixed-effects model was used for meta-analysis. The rate of low birth weight in newborns in the intervention group was not statistically significant compared to the control group [RR\u0026thinsp;=\u0026thinsp;0.53, 95% CI=(0.24,1.20), P\u0026thinsp;=\u0026thinsp;0.400], as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e. The data in this study indicate that continuity of care, compared to routine care, cannot conclusively demonstrate a reduction in the probability of low birth weight in newborns of pregnant women with GDM.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGDM has emerged as a prevalent condition, imposing significant health and economic burdens. The prevalence of GDM has been steadily increasing over the past few decades, posing a growing impact on public health and potentially leading to chronic non-communicable diseases for both mothers and their offspring.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Early identification of high-risk individuals is crucial for implementing preventive and intervention measures to mitigate the risks associated with GDM and adverse pregnancy outcomes. Effective nursing interventions have been shown to be essential frontline strategies for GDM prevention and intervention. Various patterns of continuous care have been established to manage GDM, such as the one-day nursing clinic initiated in 2011, which provides comprehensive education on GDM basics, dietary interventions, physical activity, weight management, and blood glucose self-monitoring methods.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e These patterns serve as exemplary approaches for group management of GDM and have been implemented nationwide.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e However, there remains a lack of understanding among many GDM patients regarding maintaining a balanced diet and healthy lifestyle during pregnancy, highlighting the urgent need for effective nursing interventions and educational guidance on a national scale.\u003c/p\u003e\u003cp\u003eOur study have shown that continuous care intervention can improve fasting blood glucose, postprandial 2-hour blood glucose, and glycated hemoglobin in GDM patients. Subgroup analysis of fasting blood glucose showed that the effect size of the online continuous care model and the combined online and face to face continuous care model crossed the null line in the forest plot, indicating that the effect size between the study experimental group and the control group was not significant. the effect size of the face to face continuous care model was to the left of the null line, and the effect size was significant. Subgroup analysis of postprandial 2-hour blood glucose showed that the effect sizes of the combined online and face to face continuous care and the online continuous care models were to the left of the null line, and the effect sizes were significant. Meta-analyses of the two groups of studies both indicated that there was a significant statistical difference between continuous care models and conventional care models, and continuous care could improve the blood glucose status of GDM. Multiple studies have shown that the results of continuous care application in type 2 diabetes mellitus (T2DM) are similar.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Continuous care can effectively control blood glucose and improve adverse pregnancy outcomes, which may be related to the comprehensive nursing model of continuous care. Zeng X et al. confirmed that continuous care has clinical value in predicting maternal blood glucose control level during pregnancy and has a positive impact on blood glucose control in gestational diabetes patients.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn this study, continuous care can improve the cesarean section rate, macrosomia rate, low birth weight rate, postpartum hemorrhage rate, neonatal asphyxia rate, neonatal hypoglycemia rate, and premature birth rate in GDM. Analysis of postpartum hemorrhage in 7 articles showed homogeneity, among which the 95% CI of Tian Y 2021's study crossed the null line, indicating that the effect size between the study experimental group and the control group was equal, and the experimental factor was invalid, but the effect sizes of the other six studies were to the left of the null line, which did not have a significant impact on the overall study's total effect size, proving that continuous care can alleviate postpartum hemorrhage in GDM. Ugwudike B have proposed early effective nursing interventions to reduce the incidence of postpartum hemorrhage.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Analysis of neonatal asphyxia in 5 articles showed homogeneity, although 4 articles intersected with the vertical line, their effect sizes were all to the left of the vertical line, indicating that continuous care can effectively reduce the risk of neonatal asphyxia.\u003c/p\u003e\u003cp\u003eAnalysis of cesarean section rates in 15 articles showed significant heterogeneity, but the overall effect size was to the left of the vertical line. Subgroup analysis of the face to face continuous care showed significant heterogeneity in the study, among which the effect size of Chan RS 2018's study was to the right of the vertical line, which had a certain impact on the heterogeneity of the article, but the overall subgroup effect size was to the left of the vertical line. Subgroup analysis of the online continuous care showed less heterogeneity, among which the effect sizes of Sung JH 2019 and Tian Y 2021 were to the right of the vertical line, and the rest of the articles were to the left, which had a certain impact on the total effect size of this subgroup, indicating significant statistical differences between the two subgroups of continuous care and routine care, and continuous care can reduce the cesarean section rate in GDM to a certain extent. Analysis of macrosomia rates in 15 articles showed minor heterogeneity, with Carolan-Olah M 2018 and Tian Y 2021 studies' effect sizes to the right of the vertical line, and the overall effect value to the left.\u003c/p\u003e\u003cp\u003eStudies have emphasized the significant benefits of continuous care for GDM, yet its widespread implementation remains limited. Many pregnant women do not receive adequate interpregnancy care in medical institutions, leading to deficiencies in optimizing pre-pregnancy chronic disease management, post-pregnancy risk stratification, and pregnancy management.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Factors such as BMI and dietary control have been identified as independent risk factors affecting blood glucose control levels in pregnant women with GDM, highlighting the importance of tailored interventions to effectively manage blood glucose levels and improve maternal and neonatal outcomes.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e In the era of information technology, some hospitals have developed GDM-related apps, which have shown significant advantages in GDM health management, particularly in enhancing patient self-management capabilities and promoting healthy behaviors.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Remote medical interventions, such as sensor trials for blood glucose monitoring without invasive measurements, have demonstrated high acceptability among participants. Harnessing these technological advancements in continuous care could further enhance its effectiveness.\u003c/p\u003e\u003cp\u003eThere were limitation needed to be issued in this article. The quality of the 22 included studies was generally moderate, primarily due to the lack of strict random design schemes in the included studies. The main problems identified were: (1) Randomization: Many articles only mentioned randomization in the text without providing detailed descriptions of the specific implementation methods and processes, leading to the risk of bias and methodological heterogeneity in the included literature. (2) Blinding: Due to the presence of many complex and uncontrollable factors during the study process, it was difficult to implement blinding for the subjects, intervention implementers, and evaluators in the included literature, i.e., achieving triple blinding. Only 4 articles in this study mentioned blinding, with only 1 of them being double-blinded, leading to methodological heterogeneity in the literature. (3) The continuous care included in the studies belongs to a diversified nursing model, with some differences in continuous care measures in the nursing model. The overall classification was only online, face to face, and combined online and face to face continuous care models, which had a certain impact on the intervention effect of outcome indicators. (4) The intervention content, time, and follow-up situation varied among the studies. Some studies set and guided self-management, while others did not involve self-management. Due to the diversity of continuous care plans collected, there was significant clinical heterogeneity among the literature and limited number of studies on continuous care outcomes for GDM and the rigor of randomized controlled trials, there were relatively few high-quality literature with consistent outcome evaluation indicators. Therefore, when the inclusion criteria were loosed, the clinical heterogeneity among the literature in the meta-analysis results was significant. And under the premise that there may be clinical and methodological heterogeneity in the included literature, there may be statistical heterogeneity among the studies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study systematically evaluates the effects of continuous care on GDM outcomes, affirming its positive impact. Continuous care offers numerous benefits throughout pregnancy, including fasting blood glucose, average blood glucose at 2 hours after, HbA1c levels, preterm birth rate, cesarean section rate, macrosomia rate, postpartum hemorrhage rate, neonatal hypoglycemia rate, neonatal asphyxia rate and low birth weight rate.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFC designed the study, conducted literature retrieval and data extraction, and wrote the manuscript. CS contributed to the design of the meta-analysis methodology and reviewed the manuscript. YL, TZ, YZ, ZL, and LYparticipated in data verification and result discussion, and reviewed the manuscript. All authors approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in the published article. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting of interests\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFeifei Chen\u003csup\u003e1\u003c/sup\u003e*, MSc,Chengwen Song\u003csup\u003e2\u003c/sup\u003e,MPa,Yuanci Lyu,MSc\u003csup\u003e1\u003c/sup\u003e,Ting Zhou,MSC\u003csup\u003e1\u003c/sup\u003e,Yanyan Zhao,MSc\u003csup\u003e1\u003c/sup\u003e,Zhihan Li,MSc\u003csup\u003e1\u003c/sup\u003e,Lu Yin,MSc\u003csup\u003e1\u003c/sup\u003e*\u003c/p\u003e\n\u003cp\u003e1. School of Nursing and Health Management, Wuhan Donghu College, Wuhan, Hubei, China, 435400\u003c/p\u003e\n\u003cp\u003e2. Department of Public Administration, General Graduate School, Kookmin University, Seoul, Republic of Korea,02707\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSert UY, Ozgu-Erdinc AS. Gestational Diabetes Mellitus Screening and Diagnosis. Adv Exp Med Biol. 2021;1307:231\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/5584_2020_512\u003c/span\u003e\u003cspan address=\"10.1007/5584_2020_512\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMistry SK, et al. Gestational diabetes mellitus (GDM) and adverse pregnancy outcome in South Asia: A systematic review. Endocrinol Diabetes Metab. 2021;4:e00285. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/edm2.285\u003c/span\u003e\u003cspan address=\"10.1002/edm2.285\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu Y, Zhang C. Prevalence of Gestational Diabetes and Risk of Progression to Type 2 Diabetes: a Global Perspective. Curr Diab Rep. 2016;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11892-015-0699-x\u003c/span\u003e\u003cspan address=\"10.1007/s11892-015-0699-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeek CL, et al. Seasonal variations in incidence and maternal-fetal outcomes of gestational diabetes. Diabet Med. 2020;37:674\u0026ndash;80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/dme.14236\u003c/span\u003e\u003cspan address=\"10.1111/dme.14236\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eModzelewski R, Stefanowicz-Rutkowska MM, Matuszewski W, Bandurska-Stankiewicz EM. Gestational Diabetes Mellitus-Recent Literature Review. J Clin Med. 2022;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm11195736\u003c/span\u003e\u003cspan address=\"10.3390/jcm11195736\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoudhury AA. Devi Rajeswari, V. Gestational diabetes mellitus - A metabolic and reproductive disorder. Biomed Pharmacother. 2021;143:112183. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.biopha.2021.112183\u003c/span\u003e\u003cspan address=\"10.1016/j.biopha.2021.112183\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSyed H, Slayman T, DuChene Thoma K. ACOG Committee Opinion 804: Physical Activity and Exercise During Pregnancy and the Postpartum Period. Obstet Gynecol. 2021;137:375\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/aog.0000000000004266\u003c/span\u003e\u003cspan address=\"10.1097/aog.0000000000004266\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsakiridis I, et al. Diagnosis and Management of Gestational Diabetes Mellitus: An Overview of National and International Guidelines. Obstet Gynecol Surv. 2021;76:367\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/ogx.0000000000000899\u003c/span\u003e\u003cspan address=\"10.1097/ogx.0000000000000899\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDepla AL, et al. Effect of maternal diabetes on fetal heart function on echocardiography: systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2021;57:539\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/uog.22163\u003c/span\u003e\u003cspan address=\"10.1002/uog.22163\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYa-ting HU, LI. H.-j. Effect of continuous nursing intervention in nursing care of gestational diabetes mellitus patients. CHINA Mod Med. 2019;26:231\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSu C. Network interactive continuous nursing intervention for pregnant women with diabetes The impact of treatment compliance and pregnancy outcomes. Med J Chin People's Health. 2019;31:156\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYaqin DLYZCCMHL. Effects of three-stage comprehensive continuous management on delivery outcomes in the patients with gestational diabetes. J Navy Med. 2021;42:751\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLINLI Z. The impact of body quality management combined with continuity of care on the control of body quality and delivery methods of primiparous women. CHINA\u0026rsquo;S NATUROPATHY. 2019;27:76\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.19621/j.cnki.11-3555/r.2019.1638\u003c/span\u003e\u003cspan address=\"10.19621/j.cnki.11-3555/r.2019.1638\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao-li XIAO. -l. Application of Continuation Nursing in Specialist Outpatients in Clinical Nursing of Pregnant Women with Gestational Diabetes. China \u0026amp;Foreign Med Treat. 2019;38:166\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.16662/j.cnki.1674-0742.2019.20.166\u003c/span\u003e\u003cspan address=\"10.16662/j.cnki.1674-0742.2019.20.166\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWei LJYYC. H.-x. S. X.-h. Z. Y. S. Application study of online and face to face mode in continuing nursing care of gestational diabetes. CHINA Mod Med. 2021;28:237\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhouhui ZLZHJFZRG. R. H. B. L. Application of continuous nursing under the mode of hospital nursing team guiding community nursing staff in gestational diabetes. CHINA Mod DOCTOR. 2019;57:152\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSung JH, Lee DY, Min KP, Park CY. Peripartum Management of Gestational Diabetes Using a Digital Health Care Service: A Pilot, Randomized Controlled Study. Clin Ther. 2019;41:2426\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.clinthera.2019.09.005\u003c/span\u003e\u003cspan address=\"10.1016/j.clinthera.2019.09.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYew TW, et al. A Randomized Controlled Trial to Evaluate the Effects of a Smartphone Application-Based Lifestyle Coaching Program on Gestational Weight Gain, Glycemic Control, and Maternal and Neonatal Outcomes in Women With Gestational Diabetes Mellitus: The SMART-GDM Study. Diabetes Care. 2021;44:456\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2337/dc20-1216\u003c/span\u003e\u003cspan address=\"10.2337/dc20-1216\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarolan-Olah M, Sayakhot P. A randomized controlled trial of a web-based education intervention for women with gestational diabetes mellitus. Midwifery. 2019;68:39\u0026ndash;47. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.midw.2018.08.019\u003c/span\u003e\u003cspan address=\"10.1016/j.midw.2018.08.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChan RS, et al. Randomized trial examining effectiveness of lifestyle intervention in reducing gestational diabetes in high risk Chinese pregnant women in Hong Kong. Sci Rep. 2018;8:13849. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-018-32285-6\u003c/span\u003e\u003cspan address=\"10.1038/s41598-018-32285-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhenzhen G. Analysis of the Influence of Continuous Nursing on the Treatment Compliance and Pregnancy Outcome of Gestational Diabetes Patients. DIABETES NEW WORLD. 2021;24:155\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.16658/j.cnki.1672-4062.2021.09.155\u003c/span\u003e\u003cspan address=\"10.16658/j.cnki.1672-4062.2021.09.155\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao-li Y, \u0026amp; LR. -b. The Effect of Medical and Nursing Integration\u0026thinsp;+\u0026thinsp;WeChat Interactive Continuous Nursing Intervention on the Self-management Level and Nursing Service Satisfaction of Patients with Gestational Diabetes. DIABETES NEW WORLD. 2021;24:1\u0026ndash;3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.16658/j.cnki.1672-4062.2021.04.001\u003c/span\u003e\u003cspan address=\"10.16658/j.cnki.1672-4062.2021.04.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWei-feng C. -n. The Value of Continuous Nursing in Patients with Gestational Diabetes and the Observation of Nursing Measures and Satisfaction. DIABETES NEW WORLD. 2020;23:128\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.16658/j.cnki.1672-4062.2020.20.128\u003c/span\u003e\u003cspan address=\"10.16658/j.cnki.1672-4062.2020.20.128\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDing B, et al. WeChat-assisted dietary and exercise intervention for prevention of gestational diabetes mellitus in overweight/obese pregnant women: a two-arm randomized clinical trial. Arch Gynecol Obstet. 2021;304:609\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00404-021-05984-1\u003c/span\u003e\u003cspan address=\"10.1007/s00404-021-05984-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChahed S, et al. Impact of a tailored-care education programme on maternal and neonatal outcomes in pregnant women with gestational diabetes: a randomized controlled trial. Pan Afr Med J. 2022;43:128. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.11604/pamj.2022.43.128.34084\u003c/span\u003e\u003cspan address=\"10.11604/pamj.2022.43.128.34084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRasekaba TM, et al. Using technology to support care in gestational diabetes mellitus: Quantitative outcomes of an exploratory randomised control trial of adjunct telemedicine for gestational diabetes mellitus (TeleGDM). Diabetes Res Clin Pract. 2018;142:276\u0026ndash;85. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.diabres.2018.05.049\u003c/span\u003e\u003cspan address=\"10.1016/j.diabres.2018.05.049\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTian Y, Zhang S, Huang F, Ma L. Comparing the Efficacies of Telemedicine and Standard Prenatal Care on Blood Glucose Control in Women With Gestational Diabetes Mellitus: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2021;9:e22881. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/22881\u003c/span\u003e\u003cspan address=\"10.2196/22881\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBorgen I, et al. Effect of the Pregnant\u0026thinsp;+\u0026thinsp;smartphone application in women with gestational diabetes mellitus: a randomised controlled trial in Norway. BMJ Open. 2019;9:e030884. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2019-030884\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2019-030884\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSadiya A, Jakapure V, Shaar G, Adnan R, Tesfa Y. Lifestyle intervention in early pregnancy can prevent gestational diabetes in high-risk pregnant women in the UAE: a randomized controlled trial. BMC Pregnancy Childbirth. 2022;22:668. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12884-022-04972-w\u003c/span\u003e\u003cspan address=\"10.1186/s12884-022-04972-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMunda A, Mlinaric Z, Jakin PA, Lunder M. Pongrac Barlovic, D. Effectiveness of a comprehensive telemedicine intervention replacing standard care in gestational diabetes: a randomized controlled trial. Acta Diabetol. 2023;60:1037\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00592-023-02099-8\u003c/span\u003e\u003cspan address=\"10.1007/s00592-023-02099-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQi S, Dong Y. Effect of Multidisciplinary Team Continuous Nursing on Glucose and Lipid Metabolism, Pregnancy Outcome, and Neonatal Immune Function in Gestational Diabetes Mellitus. \u003cem\u003eDis Markers\u003c/em\u003e 2022, 7285639. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2022/7285639\u003c/span\u003e\u003cspan address=\"10.1155/2022/7285639\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCumpston M, et al. Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions. Cochrane Database Syst Rev. 2019;10(Ed000142). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/14651858.Ed000142\u003c/span\u003e\u003cspan address=\"10.1002/14651858.Ed000142\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCaissutti C, Berghella V. Scientific Evidence for Different Options for GDM Screening and Management: Controversies and Review of the Literature. \u003cem\u003eBiomed Res Int\u003c/em\u003e 2017, 2746471. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2017/2746471\u003c/span\u003e\u003cspan address=\"10.1155/2017/2746471\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJuan J, Yang H, Prevalence. Prevention, and Lifestyle Intervention of Gestational Diabetes Mellitus in China. Int J Environ Res Public Health. 2020;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph17249517\u003c/span\u003e\u003cspan address=\"10.3390/ijerph17249517\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOgunwole SM, et al. Interconception Care for Primary Care Providers: Consensus Recommendations on Preconception and Postpartum Management of Reproductive-Age Patients With Medical Comorbidities. Mayo Clin Proc Innov Qual Outcomes. 2021;5:872\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.mayocpiqo.2021.08.004\u003c/span\u003e\u003cspan address=\"10.1016/j.mayocpiqo.2021.08.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYeh T, Yeung M, Mendelsohn Curanaj FA. Inpatient Glycemic Management of the Pregnant Patient. Curr Diab Rep. 2018;18:73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11892-018-1045-x\u003c/span\u003e\u003cspan address=\"10.1007/s11892-018-1045-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrtiz FM, Jimenez EY, Boursaw B, Huttlinger K. Postpartum Care for Women with Gestational Diabetes. MCN Am J Matern Child Nurs. 2016;41:116\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/nmc.0000000000000215\u003c/span\u003e\u003cspan address=\"10.1097/nmc.0000000000000215\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeng X, et al. Information-based continuous nursing on pregnant women with gestational diabetes mellitus. Eur Rev Med Pharmacol Sci. 2023;27:8762\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.26355/eurrev_202309_33798\u003c/span\u003e\u003cspan address=\"10.26355/eurrev_202309_33798\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUgwudike B, Kwok M. Update on gestational diabetes and adverse pregnancy outcomes. Curr Opin Obstet Gynecol. 2023;35:453\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/gco.0000000000000901\u003c/span\u003e\u003cspan address=\"10.1097/gco.0000000000000901\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRudner N. Nursing is a health equity and social justice movement. Public Health Nurs. 2021;38:687\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/phn.12905\u003c/span\u003e\u003cspan address=\"10.1111/phn.12905\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKyt\u0026ouml; M, et al. Supporting the Management of Gestational Diabetes Mellitus With Comprehensive Self-Tracking: Mixed Methods Study of Wearable Sensors. JMIR Diabetes. 2023;8:e43979. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/43979\u003c/span\u003e\u003cspan address=\"10.2196/43979\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Continuous Care, Pregnancy, Gestational Diabetes Mellitus, Meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-7893643/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7893643/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThis study aimed to investigate the effects of continuous care on blood glucose and pregnancy outcomes in patients with gestational diabetes mellitus (GDM) through meta-analysis.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e\u003cp\u003eSearches were conducted in PubMed, Web of Science, OVID-Embase, The Cochrane Library, Sinomed, ScienceDirect, IEEE, ProQuest, SpringerLink, EBSCO, JSTOR, BMJ, Taylor, UpToDate, JAMA (Journal of the American Medical Association), CNKI (China National Knowledge Infrastructure), WanFang Data, VIP Database for Chinese Technical Periodicals, China Biology Medicine disc (CBMdisc), Chinese Medical Association Journal Database were systematically searched for randomized controlled trials on the effects of continuous care on blood glucose and pregnancy outcomes in GDM patients from inception to June 2023. Data were then pooled and analyzed using Stata 18.0 software.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe meta-analysis included 22 randomized controlled trials, comprising 12 English and 10 Chinese publications, involving 2808 patients, with 1410 in the continuous care group and 1398 in the dietary intervention group. Meta-analysis results showed that compared with routine care, continuous care had statistically significant differences in fasting blood glucose [WMD=-0.37, 95%CI (-0.63,-0.11), P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001], average blood glucose at 2 hours after meals [WMD=-1.34, 95%CI=(-1.93,-0.76), P\u0026thinsp;=\u0026thinsp;0.0000], HbA1c levels [WMD=-0.78, 95%CI=(-0.89, -0.67), P\u0026thinsp;=\u0026thinsp;0.353], preterm birth rate [RR\u0026thinsp;=\u0026thinsp;0.39, 95%CI=(0.26, 0.59), P\u0026thinsp;=\u0026thinsp;0.085], cesarean section rate [RR\u0026thinsp;=\u0026thinsp;0.60, 95%CI=(0.52,0.68), P\u0026thinsp;\u0026lt;\u0026thinsp;0.01], macrosomia rate [RR\u0026thinsp;=\u0026thinsp;0.42, 95%CI=(0.30,0.59), P\u0026thinsp;=\u0026thinsp;0.040], postpartum hemorrhage rate [RR\u0026thinsp;=\u0026thinsp;0.20, 95%CI=(0.10,0.41), P\u0026thinsp;=\u0026thinsp;0.910], neonatal hypoglycemia rate [RR\u0026thinsp;=\u0026thinsp;0.17, 95%CI(0.08,0.34), P\u0026thinsp;=\u0026thinsp;0.291], neonatal asphyxia rate [RR\u0026thinsp;=\u0026thinsp;0.29, 95%CI=(0.10,0.85), P\u0026thinsp;=\u0026thinsp;0.996], and low birth weight rate [RR\u0026thinsp;=\u0026thinsp;0.53, 95%CI=(0.24, 1.20), P\u0026thinsp;=\u0026thinsp;0.400].\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur study systematically evaluates the effects of continuous care on GDM outcomes, affirming its positive impact on blood glucose levels and some adverse pregnancy outcomes in patients with GDM.\u003c/p\u003e","manuscriptTitle":"Effects of Continuous Care on Gestational Diabetes Mellitus Patients: A Systematic Review and Meta-analysis of 22 RCTs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 06:38:37","doi":"10.21203/rs.3.rs-7893643/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a5908c8c-f4ef-4f60-8802-0eb6561c89af","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-29T06:38:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-29 06:38:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7893643","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7893643","identity":"rs-7893643","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}