DESIGN: GWG trajectories were identified using the latent class growth model. Binary logistic regression was performed to examine the associations between adverse pregnancy outcomes and these trajectories.
SETTING: Negeri Sembilan, Malaysia.
PARTICIPANTS: Two thousand one hundred ninety-three pregnant women.
RESULTS: Three GWG trajectories were identified: 'Group 1 - slow initial GWG but followed by drastic GWG', 'Group 2 - maintaining rate of GWG at 0·58 kg/week' and 'Group 3 - maintaining rate of GWG at 0·38 kg/week'. Group 1 had higher risk of postpartum weight retention (PWR) (adjusted OR (AOR) 1·02, 95 % CI 1·01, 1·04), caesarean delivery (AOR 1·03, 95 % CI 1·01, 1·04) and having low birth weight (AOR 1·04, 95 % CI 1·02, 1·05) compared with group 3. Group 2 was at higher risk of PWR (AOR 1·18, 95 % CI 1·16, 1·21), preterm delivery (AOR 1·03, 95 % CI 1·01, 1·05) and caesarean delivery (AOR 1·02, 95 % CI 1·01, 1·03), but at lower risk of having small-for-gestational-age infants (AOR 0·97, 95 % CI 0·96, 0·99) compared with group 3. The significant associations between group 1 and PWR were observed among non-overweight/obese women; between group 1 and caesarean delivery among overweight/obese women; group 2 with preterm delivery and caesarean delivery were only found among overweight/obese women.
CONCLUSIONS: Higher GWG as well as increasing GWG trajectories was associated with higher risk of adverse pregnancy outcomes. Promoting GWG within the recommended range should be emphasised in antenatal care to prevent the risk of adverse pregnancy outcomes.
METHODS: A retrospective study involving pregnant women with SLE who had antenatal follow-up and delivery in between 1 January 2007 and 1 January 2017. All participants were retrospectively enrolled and categorized into two groups based on hydroxychloroquine treatment during pregnancy.
RESULTS: There were 82 pregnancies included with 47 (57.3%) in the hydroxychloroquine group and 35 (42.7%) in the non-hydroxychloroquine group. Amongst hydroxychloroquine users, there were significantly more pregnancies with musculoskeletal involvement (p = 0.03), heavier mean neonatal birthweight (p = 0.02), and prolonged duration of pregnancy (p = 0.001). In non-hydroxychloroquine patients, there were significantly more recurrent miscarriages (p = 0.003), incidence of hypertension (p = 0.01) and gestational diabetes mellitus (p = 0.01) and concurrent medical illness (p = 0.005). Hydroxychloroquine use during pregnancy was protective against hypertension (p = 0.001), and the gestational age at delivery had significant effect on the neonatal birthweight (p = 0.001). However, duration of the disease had a significant negative effect on the neonatal birthweight (p = 0.016).
CONCLUSION: Hydroxychloroquine enhanced better neonatal outcomes and reduced adverse pregnancy outcomes and antenatal complications such as hypertension and diabetes.
METHODS AND ANALYSIS: A total of 294 eligible participants will be recruited and allocated into 3 groups comprising of mHealth intervention alone, mHealth intervention integrated with personal medical nutrition therapy and a control group. Pretested structured questionnaires are used to obtain the respondents' personal information, anthropometry data, prenatal knowledge, physical activity, psychosocial well-being, dietary intake, quality of life, sleep quality and GWG. There will be at least three time points of data collection, with all participants recruited during their first or second trimester will be followed up prospectively (after 3 months or/and after 6 months) until delivery. Generalised linear mixed models will be used to compare the mean changes of outcome measures over the entire study period between the three groups.
ETHICS AND DISSEMINATION: Ethical approvals were obtained from the ethics committee of human subjects research of Universiti Putra Malaysia (JKEUPM-2022-072) and medical research & ethics committee, Ministry of Health Malaysia: NMRR ID-22-00622-EPU(IIR). The results will be disseminated through journals and conferences targeting stakeholders involved in nutrition research.
TRIAL REGISTRATION NUMBER: Clinicaltrial.gov ID: NCT05377151.
OBJECTIVES: To compare techniques of blood glucose monitoring and their impact on maternal and infant outcomes among pregnant women with pre-existing diabetes.
SEARCH METHODS: We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 November 2016), searched reference lists of retrieved studies and contacted trial authors.
SELECTION CRITERIA: Randomised controlled trials (RCTs) and quasi-RCTs comparing techniques of blood glucose monitoring including SMBG, continuous glucose monitoring (CGM) or clinic monitoring among pregnant women with pre-existing diabetes mellitus (type 1 or type 2). Trials investigating timing and frequency of monitoring were also included. RCTs using a cluster-randomised design were eligible for inclusion but none were identified.
DATA COLLECTION AND ANALYSIS: Two review authors independently assessed study eligibility, extracted data and assessed the risk of bias of included studies. Data were checked for accuracy. The quality of the evidence was assessed using the GRADE approach.
MAIN RESULTS: This review update includes at total of 10 trials (538) women (468 women with type 1 diabetes and 70 women with type 2 diabetes). The trials took place in Europe and the USA. Five of the 10 included studies were at moderate risk of bias, four studies were at low to moderate risk of bias, and one study was at high risk of bias. The trials are too small to show differences in important outcomes such as macrosomia, preterm birth, miscarriage or death of baby. Almost all the reported GRADE outcomes were assessed as being very low-quality evidence. This was due to design limitations in the studies, wide confidence intervals, small sample sizes, and few events. In addition, there was high heterogeneity for some outcomes.Various methods of glucose monitoring were compared in the trials. Neither pooled analyses nor individual trial analyses showed any clear advantages of one monitoring technique over another for primary and secondary outcomes. Many important outcomes were not reported.1. Self-monitoring versus standard care (two studies, 43 women): there was no clear difference for caesarean section (risk ratio (RR) 0.78, 95% confidence interval (CI) 0.40 to 1.49; one study, 28 women) or glycaemic control (both very low-quality), and not enough evidence to assess perinatal mortality and neonatal mortality and morbidity composite. Hypertensive disorders of pregnancy, large-for-gestational age, neurosensory disability, and preterm birth were not reported in either study.2. Self-monitoring versus hospitalisation (one study, 100 women): there was no clear difference for hypertensive disorders of pregnancy (pre-eclampsia and hypertension) (RR 4.26, 95% CI 0.52 to 35.16; very low-quality: RR 0.43, 95% CI 0.08 to 2.22; very low-quality). There was no clear difference in caesarean section or preterm birth less than 37 weeks' gestation (both very low quality), and the sample size was too small to assess perinatal mortality (very low-quality). Large-for-gestational age, mortality or morbidity composite, neurosensory disability and preterm birth less than 34 weeks were not reported.3. Pre-prandial versus post-prandial glucose monitoring (one study, 61 women): there was no clear difference between groups for caesarean section (RR 1.45, 95% CI 0.92 to 2.28; very low-quality), large-for-gestational age (RR 1.16, 95% CI 0.73 to 1.85; very low-quality) or glycaemic control (very low-quality). The results for hypertensive disorders of pregnancy: pre-eclampsia and perinatal mortality are not meaningful because these outcomes were too rare to show differences in a small sample (all very low-quality). The study did not report the outcomes mortality or morbidity composite, neurosensory disability or preterm birth.4. Automated telemedicine monitoring versus conventional system (three studies, 84 women): there was no clear difference for caesarean section (RR 0.96, 95% CI 0.62 to 1.48; one study, 32 women; very low-quality), and mortality or morbidity composite in the one study that reported these outcomes. There were no clear differences for glycaemic control (very low-quality). No studies reported hypertensive disorders of pregnancy, large-for-gestational age, perinatal mortality (stillbirth and neonatal mortality), neurosensory disability or preterm birth.5.CGM versus intermittent monitoring (two studies, 225 women): there was no clear difference for pre-eclampsia (RR 1.37, 95% CI 0.52 to 3.59; low-quality), caesarean section (average RR 1.00, 95% CI 0.65 to 1.54; I² = 62%; very low-quality) and large-for-gestational age (average RR 0.89, 95% CI 0.41 to 1.92; I² = 82%; very low-quality). Glycaemic control indicated by mean maternal HbA1c was lower for women in the continuous monitoring group (mean difference (MD) -0.60 %, 95% CI -0.91 to -0.29; one study, 71 women; moderate-quality). There was not enough evidence to assess perinatal mortality and there were no clear differences for preterm birth less than 37 weeks' gestation (low-quality). Mortality or morbidity composite, neurosensory disability and preterm birth less than 34 weeks were not reported.6. Constant CGM versus intermittent CGM (one study, 25 women): there was no clear difference between groups for caesarean section (RR 0.77, 95% CI 0.33 to 1.79; very low-quality), glycaemic control (mean blood glucose in the 3rd trimester) (MD -0.14 mmol/L, 95% CI -2.00 to 1.72; very low-quality) or preterm birth less than 37 weeks' gestation (RR 1.08, 95% CI 0.08 to 15.46; very low-quality). Other primary (hypertensive disorders of pregnancy, large-for-gestational age, perinatal mortality (stillbirth and neonatal mortality), mortality or morbidity composite, and neurosensory disability) or GRADE outcomes (preterm birth less than 34 weeks' gestation) were not reported.
AUTHORS' CONCLUSIONS: This review found no evidence that any glucose monitoring technique is superior to any other technique among pregnant women with pre-existing type 1 or type 2 diabetes. The evidence base for the effectiveness of monitoring techniques is weak and additional evidence from large well-designed randomised trials is required to inform choices of glucose monitoring techniques.