The triglyceride-glucose (TyG) index and the triglyceride-to-HDL cholesterol (TG/HDL) ratio have emerged as surrogate markers of insulin resistance, but their predictive value for gestational diabetes mellitus (GDM) remains uncertain. This retrospective cohort study included 4,239 pregnant women, among whom 919 developed GDM and 3,320 had normal glucose tolerance. Demographic, anthropometric, and biochemical parameters were collected during early pregnancy, specifically at 8–13 gestational weeks (first trimester), OGTT-related glucose and insulin measurements (FIN, 1hPIN, 2hPIN) were obtained later at 24–28 weeks during the routine 75-g OGTT, after at least 8 hours of overnight fasting. Logistic regression, restricted cubic spline models, correlation analysis, age-stratified analyses, and mediation analysis were performed to evaluate associations of TyG and TG/HDL ratio with GDM. A nomogram model was constructed and internally validated using a random training/validation split. Higher TyG and TG/HDL ratio levels were independently associated with increased GDM risk (TyG: aOR 4.07, 95

Early identification of gestational diabetes mellitus (GDM) is critical for mitigating adverse maternal and neonatal outcomes. Existing prediction models face limitations in clinical utility due to inconsistent variable selection and reliance on impractical biomarkers. This study aimed to develop and validate a resource-efficient GDM prediction model using routinely available first-trimester clinical indicators and deploy it as an open-access web tool. A retrospective cohort of 1818 pregnancies from a Shanghai tertiary hospital (2023) was randomly divided into training (70 https://wangxiao0922.shinyapps.io/20250309/ ) were developed for risk stratification. This resource-efficient tool enables early GDM risk stratification using routine clinical variables, supporting timely intervention in diverse healthcare settings.

BackgroundGestational Diabetes Mellitus (GDM) poses severe health risks to mother and child, yet effective, non-invasive preventive strategies remain elusive. While the gut microbiota is known to influence glucose metabolism, its potential as a therapeutic target and predictive biomarker in high-risk pregnancies is underexplored. This study investigated whether soluble dietary fiber supplementation could remodel the gut microbiome to prevent GDM and improve pregnancy outcomes.MethodsWe performed a single-center, randomized controlled trial with 98 pregnant women at elevated risk for GDM. For 5 weeks, from 20 to 24+6 weeks of pregnancy, participants were randomly assigned to either a fiber group (getting soluble fiber supplements every day) or a control group (getting normal care). Clinical outcomes encompassed OGTT results, gestational weight gain (GWG), and delivery outcomes. We used 16S rRNA sequencing to look at changes in gut flora. Furthermore, we developed a novel nomogram integrating clinical variables with microbial signatures to predict GDM risk.ResultsAlthough GDM incidence did not statistically differ, the fiber group exhibited significantly improved glycemic excursions (predominantly lower 1h-PG, and reduced whole-OGTT glucose AUC and iAUC), reduced GWG during the 5-week intervention period (1.83 vs. 2.54 kg; P = 0.016), and a complete absence of preterm births (0% vs. 12.0%; P = 0.040). Microbiome analysis revealed that fiber intake enriched Bifidobacterium and Limosilactobacillus while suppressing Phascolarctobacterium. Functional prediction indicated a downregulation of inflammation-related pathways (HIF-1, AMPK) in the Fiber group. Crucially, a prediction model combining clinical factors with a specific “micro-balance” (Bifidobacterium ratio) achieved superior predictive accuracy (AUC 0.821) compared to clinical factors alone.ConclusionsPreliminary findings suggest that dietary fiber supplementation serves as a potent “biotic” intervention in high-risk pregnancies, improving 1-hour postprandial glucose homeostasis and eliminating preterm birth in this cohort. The mechanism appears associated with the specific enrichment of Bifidobacterium. Additionally, we validated a novel clinical-microbial nomogram, suggesting that integrating gut microbiome data can significantly enhance GDM risk stratification. Future extensive research is need to confirm these results.

Platinum resistance remains a major obstacle to effective treatment and improved prognosis in ovarian cancer. Although 5-methylcytosine (m5C) RNA modification has been implicated in chemoresistance, its precise functional role in ovarian cancer remains unclear. In this study, we integrated RNA-Seq and single-cell transcriptomic data from cisplatin-resistant ovarian cancer cell lines and patient samples, identifying the m5C reader protein ALYREF as a key regulator of platinum resistance. Functional studies using ALYREF and NSUN2 knockdown, overexpression, and mutant constructs—combined with multi-omics analyses (RNA-Seq, m5C-BIS-Seq, and RIP-Seq)—revealed that ALYREF binds to m5C-modified LGR4 mRNA, enhancing its stability and promoting activation of the Wnt/β-catenin signaling pathway. Critically, this regulatory mechanism is dependent on NSUN2-mediated m5C modification of LGR4 mRNA. Together, our findings demonstrate that the NSUN2/ALYREF/LGR4 axis mediates platinum resistance through m5C-dependent stabilization of LGR4 and downstream Wnt signaling activation. Thus, targeting ALYREF may represent a promising strategy to overcome platinum resistance in ovarian cancer.

OBJECTIVE:This study aimed to examine the association between isolated maternal hypothyroxinemia (IMH) during the first and second trimesters and the risk of gestational diabetes mellitus (GDM), as well as its association with adverse perinatal outcomes. METHODS:The study included 2,741 pregnant women who visited the obstetric outpatient clinic at Shanghai General Hospital and underwent routine obstetric examinations between January 2020 and June 2021. Participants diagnosed with IMH in the first trimester were categorized as H1(+), while those without as H1(-). Similarly, those diagnosed with IMH in the second trimester were categorized as H2(+), and those without as H2(-). Based on these classification, four groups were formed: group A H1(-) H2(-), (n = 1,886); group B H1(+) H2(-), (n = 99); group C H1(-) H2(+), (n = 613); and group D H1(+) H2(+), (n = 143). Retrospective analysis was performed to examine clinical data, including pregnancy complications, across all four groups. RESULTS:The incidence of GDM was significantly higher in groups B, C, and D compared to group A (all p < 0.001), with the following trend: group D > group C > group B > group A. Specifically, group D exhibited the highest incidence of GDM [n% = 93.01 %, p3 < 0.001]). Logistic regression analysis, adjusted for confounding factors identified IMH during the first trimester, IMH during the second trimester, and persistent IMH across both trimesters as significant risk factors for GDM. Notably, the risk of GDM in cases of persistent IMH was 73.97 times higher than the normal risk (aOR = 73.97, p < 0.001). The study also found that isolated maternal hypothyroxinemia (IMH) was significantly associated with adverse perinatal outcomes. CONCLUSION:IMH during either the first or second trimester, and particularly persistent IMH across both trimesters, is strongly associated with a higher risk of GDM and insulin resistance. Our findings highlight the importance of monitoring and managing IMH during pregnancy to mitigate the risk of adverse perinatal outcomes. Early intervention may improve both maternal and neonatal health.

Context Large-for-gestational-age (LGA), one of the most common complications of gestational diabetes mellitus (GDM), has become a global concern. The predictive performance of common continuous glucose monitoring (CGM) metrics for LGA is limited.Objective We aimed to develop and validate an artificial intelligence (AI)-based model to determine the probability of women with GDM giving birth to LGA infants during pregnancy using CGM measurements together with demographic data and metabolic indicators.Methods A total of 371 women with GDM from a prospective cohort at a university hospital were included. CGM was performed during 20 to 34 gestational weeks, and glycemic fluctuations were evaluated and visualized in women with GDM who gave birth to LGA and non-LGA infants. A convolutional neural network (CNN)-based fusion model was developed to predict LGA. Comparisons among the novel fusion model and 3 conventional models were made using the area under the receiver operating characteristic curve (AUCROC) and accuracy.Results Overall, 76 (20.5%) out of 371 GDM women developed LGA neonates. The visualized 24-hour glucose profiles differed at midmorning. This difference was consistent among subgroups categorized by pregestational body mass index, therapeutic protocol, and CGM administration period. The AI-based fusion prediction model using 24-hour CGM data and 15 clinical variables for LGA prediction (AUCROC 0.852; 95% CI, 0.680-0.966; accuracy 84.4%) showed superior discriminative power compared with the 3 classic models.Conclusion We demonstrated better performance in predicting LGA infants among women with GDM using the AI-based fusion model. The characteristics of the CGM profiles allowed us to determine the appropriate window for intervention.

Microplastic (MP) pollution is an emerging environmental concern with potential health risks, yet its impact on pregnancy remains largely unexplored. This study investigated the effects of polystyrene microplastic (PS-MP) exposure on placental function and its role in preeclampsia (PE) pathogenesis. Pregnant rats were exposed to PS-MP, which induced PE-like symptoms including elevated blood pressure, increased proteinuria, and altered expression of angiogenic factors. Transcriptomic and molecular analyses revealed PS-MP triggered ferroptosis in placental trophoblast cells by activating the HIF-1α/TFRC axis, resulting in iron overload and oxidative stress. PS-MP exposure impaired trophoblast migration, invasion, and angiogenesis; these effects were ameliorated by ferroptosis inhibition. These findings identified PS-MP-induced ferroptosis as a critical mechanism underlying placental dysfunction, highlighting PS-MP as a potential environmental risk factor for PE. Understanding the impact of MP on pregnancy provides crucial insights into their reproductive toxicity and underscores the need for further research on mitigating their effects.

This retrospective cohort study examined the association between first-trimester triglyceride-to-HDL cholesterol (TG/HDL-C) ratio and gestational diabetes mellitus (GDM) risk among 2,356 pregnant women from Shanghai General Hospital between October 2019, and June 2021. Using logistic regression and restricted cubic spline models, we found the TG/HDL-C ratio was an independent GDM predictor (OR:1.37, 95%CI:1.16-1.62, p<0.001), persisting after adjustment (aOR:1.65, 95%CI:1.27-2.13, p<0.001). Nonlinear dose-response relationships were observed (p-interaction<0.05), with stronger associations in women >35 years (OR:1.60, 95%CI:1.12-2.28) and those with BMI≥25kg/m² (OR:1.78, 95%CI:1.25-2.54). First-trimester TG/HDL-C ratio elevation significantly increases GDM risk, suggesting its potential for early risk stratification and targeted prevention.

AIM:We investigated the relationship between the complexity of the glucose time series index (CGI) during pregnancy and adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM). MATERIALS AND METHODS:In this retrospective cohort study, 388 singleton pregnant women with GDM underwent continuous glucose monitoring (CGM) at a median of 26.86 gestational weeks. CGI was calculated using refined composite multiscale entropy based on CGM data. The participants were categorized into tertiles according to their baseline CGI (CGI <2.32, 2.32-3.10, ≥3.10). Logistic regression was used to assess the association between CGI and composite adverse outcomes or large for gestational age (LGA). The discrimination performance of CGI was estimated using receiver operating characteristic analysis. RESULTS:Of the 388 participants, 71 (18.3%) had LGA infants and 63 (16.2%) had composite adverse outcomes. After adjustments were made for confounders, compared with those with a high CGI (CGI ≥3.10), participants with a low CGI (CGI <2.32) had a higher risk of composite adverse outcomes (odds ratio: 12.10, 95% confidence interval: 4.41-33.18) and LGA (odds ratio: 12.68, 95% confidence interval: 4.04-39.75). According to the receiver operating characteristic analysis, CGI was significantly better than glycated haemoglobin and conventional CGM indicators for the prediction of adverse pregnancy outcomes (all p < .05). CONCLUSION:A lower CGI during pregnancy was associated with composite adverse outcomes and LGA. CGI, a novel glucose homeostasis predictor, seems to be superior to conventional glucose indicators for the prediction of adverse pregnancy outcomes in women with GDM.

Objective: To investigate the relationship between triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and gestational diabetes mellitus (GDM) in the first trimester. Method(s): We followed 2,356 pregnant women who visited the obstetric outpatient clinic of Shanghai General Hospital and underwent regular obstetric examinations from October 1st, 2019 to June 1st, 2021. A 75 g oral glucose tolerance test (OGTT) was performed, and lipid levels were measured in the first trimester. Logistic regressionand restricted cubic spline (RCS) were applied to evaluate the association between the TG/HDL-C ratio and GDM. Result(s): Among 2,356 pregnant women, 425 women(18.04 %) were diagnosed with GDM. Logistic regression analysis showed that the TG/HDL-C ratio was an independent risk factor for GDM (OR=1.37 (95% CI: 1.16-1.62), p<0.001). After adjusting for potential confounding factors, we observed that a high TG/HDL-C ratio promoted GDM (OR: 1.65, 95% CI: 1.27–2.13, p<0.001). The RCS analysis revealed a signifcant nonlinear association. (P-interaction < 0.05). Conclusion(s): In this study, we found a significant correlation between TG/HDL-C ratio and GDM, and high TG/HDL-C ratio can be regarded as a significant risk factor for the development of gestational diabetes. Early detection of elevated TG/HDL-C may serve in early detection of GDM and help physicians in framing primary preventive strategies.

AbstractBackground Although the association between inadequate or excessive gestational weight gain (GWG) and adverse pregnancy outcomes has been investigated in China, most studies use the Institute of Medicine (IOM) guidelines, which might not be suitable for Chinese women characteristics. Besides, studies exploring association between GWG in the second trimester and pregnancy outcomes are relatively few. Methods A total of 976 cases of live-birth singleton pregnancies at the Shanghai General Hospital were included in this retrospective observational study. Patients were classified into three groups including GWG during 24 gestational weeks (G24WG) within, below and above the Standard of Recommendation for Weight Gain during Pregnancy Period published by Maternal and Child Health Standards Professional Committee of National Health Commission (NHC), China PR in 2022 (2022 Chinese GWG guidelines), which specifies the recommended value of weight gain of natural singleton pregnancy in China. Binary logistic regression was used to estimate the adjusted odds ratio (OR) and 95% confidence intervals (CIs) of adverse pregnancy outcomes among three G24WG groups. Results Of the 976 women analyzed, 12.6% had G24WG below the 2022 Chinese GWG guidelines, while 37.2% had G24WG above the 2022 Chinese GWG guidelines. Women with G24WG below the 2022 Chinese GWG guidelines had a higher risk of Small for Gestational Age (SGA, Adjusted OR = 2.690, 95% CI: 1.334–5.427, P = 0.006) and a lower risk of Large for Gestational Age (LGA, Adjusted OR = 0.435, 95% CI: 0.228–0.829, P = 0.011) than women who had G24WG within the 2022 Chinese GWG guidelines. Conclusions G24WG is a strong predictor of newborn anthropometric outcomes and help doctors provide appropriate nutritional counseling for pregnant women in China.

Aims Previous studies showed conflicting results linking body iron stores to the risk of gestational diabetes mellitus (GDM) and dyslipidemia. We aim to investigate the relationship between serum ferritin, and the prevalence of GDM, insulin resistance (IR) and hypertriglyceridemia. Methods A total of 781 singleton pregnant women of gestation in Shanghai General Hospital took part in the retrospective cohort study conducted. The participants were divided into four groups by quartiles of serum ferritin levels (Q1–4). Binary logistic regressions were used to examine the strength of association between the different traits and the serum ferritin (sFer) quartiles separately, where Q1 (lowest ferritin quartile) was taken as the base reference. One-way ANOVA was adopted to compare the averages of the different variables across Sfer quartiles. Results Compared with the lowest serum ferritin quartile (Q1), the ORs for Q3, and Q4 in our population were 1.79 (1.01–2.646), and 2.07 (1.089-2.562) respectively and this trend persisted even after adjusted for age and pre-BMI. Women with higher serum ferritin quartile including Q3 (OR=2.182, 95%CI=1.729-5.527, P=0.003) and Q4(OR=3.137, 95%CI=3.137-8.523, P<0.01)are prone to develop insulin resistance disorders. No significant difference was observed between sFer concentrations and gestational hypertriglyceridemia(GTG) in the comparison among these 4 groups across logistic regressions but TG was found positively correlated with increased ferritin values in the second trimester. Conclusions Increased concentrations of plasma ferritin in early pregnancy are significantly and positively associated with insulin resistance and incidence of GDM but not gestational dyslipidemia. Further clinical studies are warranted to determine whether it is necessary to encourage pregnant women to take iron supplement as a part of routine antenatal care.

Aim: Preeclampsia (PE) and intrauterine growth restriction (IUGR) are two significant obstetrical diseases that cause serious harm to maternal and infant health. Worldwide, PE is the most frequent cause of IUGR; The latter is regarded as a serious complication of PE but its underlying mechanism and molecular biological changes are poorly understood. Thus, few effective medical therapies for its treatment are available. PE and IUGR share the same etiological background but their connections at the molecular level were rarely known. Consequently, it is of urgency to create an effective method to evaluate their molecular signature. The objective of this study was to identify the hub genes related to PE with IUGR (PE-IUGR) by conducting a weighted gene co-expression network analysis (WGCNA). Methods: The GSE147776 data set containing 28 samples of placental tissue (n = 6 with PE-IUGR) was downloaded from the Gene Expression Omnibus database. The gene expression profile was correlated with phenotypic data and analyzed using a WGCNA. Additionally, a WGCNA was used to construct a gene co-expression network, and hub genes were further identified by identifying modules related to the clinical traits of PE-IUGR. Results: Nine genes, i.e., TDRKH, XPOT, AMACR, NBN, ALS2, CLYBL, CENPQ, PCGF6 and COQ3 were obtained by the WGCNA. These were considered the key genes that were likely involved in IUGR in PE. Conclusions: We constructed a co-expression network of PE-IUGR and identified 9 hub genes related to the condition.

甲状腺功能亢进(Hyperthyroidism,以下简称甲亢)在妊娠期比较少见,其发病率为0.1％-0.4％[1].其中,妊娠一过性甲状腺毒症(gestational transient thyro-toxicosis,GTT)占10％,Graves病占85％,其他少见的包括甲状腺高功能腺瘤、结节性甲状腺肿、甲状腺破坏以及外源性补充甲状腺素过量等[2].妊娠期甲亢最常见的种类是Graves病.血清中是否存在促甲状腺素受体自 身抗体(thyrotropin receptor autoantibody,TRAb)是鉴别Graves病与其他类型甲亢的一种方法.

Pregnant women with a high triglyceride-glucose (TyG) index during early pregnancy may increase the risk of gestational diabetes mellitus (GDM), and dietary fiber could play an important role in glucose and lipid metabolism. However, no trials have tested the effects of dietary fiber on preventing GDM in women with a high TyG index. This study aims to investigate whether GDM can be prevented by dietary fiber supplementation in women with a TyG index ≥8.5 during early pregnancy (<20 weeks). A randomized clinical trial was performed among 295 women with a TyG index ≥8.5 before 20 weeks of gestation, divided into a fiber group (24 g dietary fiber powder/day) or a control group (usual care). The intervention was conducted from 20 to 24+6 gestational weeks, and both groups received guidance on exercise and diet. The primary outcomes were the incidence of GDM diagnosed by a 75 g oral glucose tolerance test at 25–28 gestational weeks, and levels of maternal blood glucose, lipids. Secondary outcomes include gestational hypertension, postpartum hemorrhage, preterm birth, and other maternal and neonatal complications. GDM occurred at 11.2

目的:探讨妊娠期糖尿病与妊娠合并高脂血症的肠道菌群构成特点,寻找两种妊娠代谢性疾病的肠道菌群相关的潜在致病机制.方法:收集妊娠期糖尿病孕妇24例、妊娠合并高脂血症孕妇23例、健康产检孕妇17名,采集粪便并借助16S rDNA扩增子测序技术进行测序,借助QIIME及R语言软件平台,分析三类样本中肠道的菌群在Alpha多样性、Beta多样性、LEfSe的差异性方面的生物学信息.结果:妊娠期糖尿病组Alpha多样性较妊娠合并高脂血症组偏低(Shannon的指数值为3.78±0.73、4.38±0.75,t=3.001,P=0.005;Chao1指数为815.38±376.43,1107.56±489.52,t=2.676,P=0.008);妊娠期糖尿病组的Alpha多样性低于对照组(P<0.05),高脂血症组与对照组的Alpha多样性比较,差异无统计学意义(P>0.05).妊娠期糖尿病组与高脂血症组的Beta多样性比较,差异有统计学意义(R2=0.03,P=0.001),妊娠期糖尿病组与对照组的Beta多样性比较,差异有统计学意义(R2=0.04,P=0.034),高脂血症组与对照组相比Beta多样性比较,差异有统计学意义(R2=0.04,P=0.018).妊娠期糖尿病组、高脂血症组在属水平的肠道菌群差异:Firmicutes、Bacteroidetes、Proteobacteria是相对丰度最高的三大菌群,两组间的相对丰度比较,差异无统计学意义(P>0.05);在属水平,Blautia、Dorea、Akkermansia、Bifidobacterium的相对丰度比较,差异无统计学意义(P>0.05).结论:与妊娠期糖尿病组相比,高脂血症组与正常对照组的菌群组成和构成更相似,而妊娠期糖尿病患者与妊娠中期高脂血症患者在菌属构成和相对丰度有关键菌群的重合,预示着二者可能存在共同的菌群代谢机制,参与介导糖代谢、脂代谢及胰岛素抵抗.

Background: The relationship of iron deficiency and thyroid hormone has been researched a lot among pregnant or other healthy population. However, invisible iron deficiency, namely shortage of serum ferritin (sFer) level, has been barely investigated among Chinese pregnant women. This study aimed to explore the effects of sFer status on thyroid function and pregnancy outcomes in a population-based upper first-class hospital.Methods: A total of 781 singleton pregnant women of gestation in Shanghai General Hospital took part in this retrospective cohort study. The participants were divided into four groups by quartiles of serum ferritin levels (Q1-4). Binary logistic regressions were used to examine the strength of association between the different traits and the serum ferritin (sFer) quartiles separately, where Q1 (lowest ferritin quartile) was taken as the base reference. One-way ANOVA was adopted to compare the averages of the different variables across sFer quartiles. Categorical measures were compared by Fisher exact test or chi-square test.Results: As the sFer concentration rises, incidence of premature birth (15.8%vs 12.3% vs 9.20% vs 6.20% p = 0.016) as well as threatened miscarriage (14.8% vs 7.2% vs 8.70% vs 6.70% p = 0.021) presented a downward trend. Compared with the other sFer group, subjects of the low sFer group were older, more often to be found to have lower serum gamma T3 and FT4 levels in early pregnancy but not in middle pregnancy.Conclusion: sFer concentration in the first trimester can affect thyroid function. The correction of invisible iron deficiency with inadequate sFer status prior to pregnancy or during early pregnancy is imperative, not only to prevent anemia, but also for maintaining optimum thyroid function and normal fetal development. For clinicians, sFer status of pregnant women should be attached great importance apart from attention to iron level.

脊髓血管畸形是指脊髓血管先天发育异常引起的血管病变,以胸腰段多见,常导致急性、亚急性或慢性脊髓功能障碍.妊娠合并脊髓血管畸形的病例极为少见,其发病率尚不清楚,此次报道一例妊娠合并脊髓血管畸形伴出血的病例,目的是加强对此罕见病的认识,以及探讨妊娠期脊髓血管畸形病人的管理及治疗.

ObjectiveThis study evaluated the effect of continuous glucose monitoring (CGM) versus self-monitored blood glucose (SMGB) in gestational diabetes mellitus (GDM) with hemoglobin A1c (HbA1c) <6%.MethodsFrom January 2019 to February 2021, 154 GDM patients with HbA1c<6% at 24–28 gestational weeks were recruited and assigned randomly to either SMBG only or CGM in addition to SMBG, with 77 participants in each group. CGM was used in combination with fingertip blood glucose monitoring every four weeks until antepartum in the CGM group, while in the SMBG group, fingertip blood glucose monitoring was applied. The CGM metrics were evaluated after 8 weeks, HbA1c levels before delivery, gestational weight gain (GWG), adverse pregnancy outcomes and CGM medical costs were compared between the two groups.ResultsCompared with patients in the SMBG group, the CGM group patients had similar times in range (TIRs) after 8 weeks (100.00% (93.75-100.00%) versus 99.14% (90.97-100.00%), p=0.183) and HbA1c levels before delivery (5.31 ± 0.06% versus 5.35 ± 0.06%, p=0.599). The proportion with GWG within recommendations was higher in the CGM group (59.7% versus 40.3%, p=0.046), and the newborn birth weight was lower (3123.79 ± 369.58 g versus 3291.56 ± 386.59 g, p=0.015). There were no significant differences in prenatal or obstetric outcomes, e.g., cesarean delivery rate, hypertensive disorders, preterm births, macrosomia, hyperbilirubinemia, neonatal hypoglycemia, respiratory distress, and neonatal intensive care unit admission >24 h, between the two groups. Considering glucose monitoring, SMBG group patients showed a lower cost than CGM group patients.ConclusionsFor GDM patients with HbA1c<6%, regular SMBG is a more economical blood glucose monitoring method and can achieve a similar performance in glycemic control as CGM, while CGM is beneficial for ideal GWG.