Dataset Information

Impact of a telemedicine system with automated reminders on outcomes in women with gestational diabetes mellitus.

ABSTRACT: Health information technology has been proven to be a successful tool for the management of patients with multiple medical conditions. The purpose of this study was to examine the impact of an enhanced telemedicine system on glucose control and pregnancy outcomes in women with gestational diabetes mellitus (GDM).We used an Internet-based telemedicine system to also allow interactive voice response phone communication between patients and providers and to provide automated reminders to transmit data. Women with GDM were randomized to either the telemedicine group (n=40) or the control group (n=40) and asked to monitor their blood glucose levels four times a day. Women in the intervention group transmitted those values via the telemedicine system, whereas women in the control group maintained paper logbooks, which were reviewed at prenatal visits. Primary outcomes were infant birth weight and maternal glucose control. Data collection included blood glucose records, transmission rates for the intervention group, and chart review.There were no significant differences between the two groups (telemedicine vs. controls) in regard to maternal blood glucose values or infant birth weight. However, adding telephone access and reminders increased transmission rates of data in the intervention group compared with the intervention group in our previous study (35.6±32.3 sets of data vs.17.4±16.9 sets of data; P<0.01).Our enhanced telemedicine monitoring system increased system utilization and contact between women with GDM and their healthcare providers but did not impact upon pregnancy outcomes.

SUBMITTER: Homko CJ

PROVIDER: S-EPMC3389380 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Impact of a telemedicine system with automated reminders on outcomes in women with gestational diabetes mellitus.

Homko Carol J CJ Deeb Larry C LC Rohrbacher Kimberly K Mulla Wadia W Mastrogiannis Dimtrios D Gaughan John J Santamore William P WP Bove Alfred A AA

Diabetes technology & therapeutics 20120418 7

<h4>Background</h4>Health information technology has been proven to be a successful tool for the management of patients with multiple medical conditions. The purpose of this study was to examine the impact of an enhanced telemedicine system on glucose control and pregnancy outcomes in women with gestational diabetes mellitus (GDM).<h4>Subjects and methods</h4>We used an Internet-based telemedicine system to also allow interactive voice response phone communication between patients and providers ...[more]

PMID: 22512287

Similar Datasets

Project description:OBJECTIVES: To assess the maternal and fetal complications of pregnancy in mothers with gestational diabetes mellitus (GDM) compared with non-diabetic patients who delivered in the hospital during the study period. METHODS: The outcome of pregnancy in 220 Saudi patients with GDM identified from the delivery register/hospital database and matched for age, parity and body mass index with 220 non-diabetic controls were studied retrospectively from their case files. Patients with multiple pregnancies and abnormal presentation of the fetus were excluded from the study. RESULTS: The GDM patients were treated with either diet alone or with additional insulin in some patients who required better control of their blood sugar levels. Patients with GDM had a significantly higher incidence of pre-eclampsia (p<0.0001); preterm delivery (p=0.0226); induction of labor (p<0.0001); cesarean section (p=0.0019); higher mean birth weight (p<0.0001) of babies; large for gestational age infants (p=0.0011); macrosomia (p=0.0186); and admission to the neonatal intensive care unit (p=0.0003), compared with the control group. However, the rates of Apgar score <7 at 5 minutes, respiratory distress syndrome, neonatal hypoglycemia, hyperbilirubinemia and the need for phototherapy were similar in both groups of patients. Congenital anomalies and perinatal mortality rates were not significantly different in the two groups. CONCLUSION: GDM is recognized to be associated with increased rates of adverse maternal and neonatal outcomes, which are supported by the findings of this study. Even the mild form of GDM seems to have significant consequences for women and their offspring and is recommended to be aggressively treated. Evidence suggests that early diagnosis and strict control of blood sugar levels throughout the pregnancy can significantly reduce maternal and fetal complications. A multicenter, randomized controlled trial, based on universally accepted criteria for GDM screening test, standardized diagnostic OGTT and management of all patients with GDM versus the standard obstetric management of the control is warranted.

Project description:AimsTo explore the association between higher serum ferritin (SF) levels in mid-pregnancy and adverse pregnancy outcomes in gestational diabetes mellitus (GDM) pregnancies, then develop a predictive cut-off value that might effectively predict the risk of adverse pregnancy outcomes in future clinical.MethodsThe study involved 201 pregnant women with GDM. 201 gestational age and parity matched normoglycemic pregnant women were taken as control group. The differences in clinical data were compared by the Mann-Whitney U test and Chi-square tests. Multivariate logistic regression was used to determine the relationship between SF and GDM-relate adverse pregnancy outcomes. The predicted value of SF level was determined through receiver operating characteristic (ROC) curve analysis.ResultsSF level was significantly higher in women with GDM [16.10 (27.30-9.50) (ng/mL) vs. 12.04 (18.11-7.06) (ng/mL), (p < 0.001)]. Meanwhile, higher levels of SF were also discovered in GDM women with preeclampsia and neonatal hypoglycemia and respiratory distress (all p < 0.05). In the adjusted model, a positive association was shown between SF and preeclampsia [adjusted odds ratio (AOR) = 1.032, 95%CI = 1.004-1.060, p = 0.024], neonatal hypoglycemia [adjusted odds ratio (AOR) = 1.047, 95%CI = 1.022-1.072, p < 0.001] and respiratory distress outcomes (AOR = 1.034, 95%CI = 1.011-1.058, p = 0.004) respectively. The area under ROC curve (AUC) for prediction of preeclampsia by SF combined with serum calcium, age, pre-pregnancy BMI and gestational weight gain (GWG) was 0.658 (95% CI = 50.8-80.8%, p = 0.028) with the cut-off value of 24.45 ng/mL, and the sensitivity and specificity were 58.8.0% and 64.3%, respectively. To predict neonatal hypoglycemia, the clinical point value of SF was 27.43 ng/mL with AUC was 0.800, sensitivity and specificity was 90.5% and 68.0% respectively. Predicting neonatal respiratory distress, the AUC value of the SF level was 0.730, with a cut-off value of 27.37 ng/mL and the sensitivity and specificity were 52.0% and 86.5%, respectively.ConclusionsHigher level of SF in mid-pregnancy was significantly associated with the risk of GDM and GDM-relate adverse pregnancy outcomes. Moreover, SF levels have moderate clinical value in predicting the adverse outcomes of maternal preeclampsia, neonatal hypoglycemia and respiratory distress.

Project description:Objectives To perceive the temporal features of breast milk proteome between women with gestational diabetes mellitus (GDM) and healthy controls across various lactation periods, as well as to explore the potential impacts of these differences on the growth of offspring. Methods The study cohort included twenty mothers with GDM and twenty healthy mothers. Human milk samples were obtained at four distinct time points: colostrum (4-6 days postpartum), transitional milk (12-14 days postpartum), early mature milk (42 days postpartum) and mature milk (4 months postpartum). Shotgun proteomics with label free quantification was applied to analyze the milk proteome. Gene Ontology (GO) enrichment analysis, alongside other bioinfomatic tools were conducted to elucidate the function of differentially expressed proteins. Subsequently, a random forest model was utilized to discern proteins that could reliably differentiate milk samples from mothers with gestational diabetes mellitus (GDM) from those of healthy counterparts. Furthermore, correlative analysis was employed to investigate the association between these proteins and the anthropometric indices of infants. Results Principal coordinate analysis (PCoA) revealed distinct separations in the milk proteome of GDM and healthy mothers during the initial lactation stages, with these differences diminishing over time. The up-regulated proteins in GDM were predominantly associated with the innate immune system, complement and coagulation cascades, cellular secretion, enzymatic and binding activity, and platelet activation. Six proteins were identified as effective markers for distinguishing milk samples from the two groups, with an average area under the curve (AUC) value of 0.91. Twenty-eight proteins exhibited consistent changes between GDM and healthy groups across at least two lactation stages, many of which were significantly correlated to the anthropometric indices of the offsprings. Conclusions GDM significantly influences the milk proteome, with the extent of alteration diminishing as lactation progresses into the mature milk phase.

Dataset Information

Impact of a telemedicine system with automated reminders on outcomes in women with gestational diabetes mellitus.

Publications

Impact of a telemedicine system with automated reminders on outcomes in women with gestational diabetes mellitus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets