scholarly journals SUN-641 Identifying Risk Factors Associated with Severe Maternal Morbidity Among Women with Gestational Diabetes Using Common Data Model

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Seo-Ho Cho ◽  
Kwangsoo Kim
Keyword(s):  
Risk Factors ◽  
Gestational Diabetes ◽  
Data Model ◽  
Maternal Morbidity ◽  
Severe Maternal Morbidity ◽  
Common Data Model ◽  
Logistic Regression Models ◽  
Factors Associated ◽  
Glucose And Lipid Metabolism ◽  
Tertiary Center

Abstract Objective: To identify the risk factors associated with severe maternal morbidity among women with gestational diabetes using common data model Background: Severe maternal morbidity is an unintended, adverse outcome of the pregnancy or the process of labor and delivery that causes short and long-term consequences to women’s and infants’ health. The prevalence of severe maternal morbidity has been increasing, from 5 to 14 cases per every 1,000 births from 1994 to 2014, and is estimated to increase over time. Previous studies have shown an association between gestational diabetes and pregnancy complications including hypertension, preeclampsia, and preterm birth. We assessed the association of representative biomarkers with severe maternal morbidity among women with gestational diabetes. Methods: This cohort study used data collected from common data model database at a single tertiary center in Seoul, Korea during 2004-2019. All patients with indication of gestational diabetes were included in the study. Cases were all women who experienced severe maternal morbidity using the ICD-10 codes identified by the Centers for Disease Control and Prevention. We assessed associations between representative biomarkers and severe maternal morbidity, using t-test and multivariable logistic regression models. Results: Among 15,096 women who gave birth, the prevalence of gestational diabetes was 9.19% (n=1,388). Among those, 329 (23.7%) developed severe maternal morbidity during pregnancy. HbA1c, triglyceride, and fasting blood sugar were higher among women with severe maternal morbidity (p<0.05) and younger age showed association (p<0.01) with severe maternal morbidity. Conclusion: This study showed that gestational diabetes was highly associated with severe maternal morbidity. Blood glucose and lipid metabolism were shown to be associated factors with severe maternal morbidity among women with gestational diabetes.

scholarly journals Maternal Nutritional Status and the Development of Gestational Diabetes Using Common Data Model

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 961-961
Author(s):  
Seo-Ho Cho ◽  
Jeesuk Yu ◽  
Kwangsoo Kim
Keyword(s):  
Gestational Diabetes ◽  
Nutritional Status ◽  
Data Model ◽  
Statistical Significance ◽  
Hdl Cholesterol ◽  
Maternal Serum ◽  
Common Data Model ◽  
Contributing Factors ◽  
Maternal Nutritional Status ◽  
Tertiary Center

Abstract Objectives To identify the association between maternal nutritional status and gestational diabetes using common data model. Methods This cohort study used data collected from common data model database at a single tertiary center in Seoul, Korea during 2004–2019. All patients with delivery record were included in this study. Women with diagnosis of gestational diagnosis were identified as cases. Maternal nutritional level including iron, cholesterol, triglyceride, and hemoglobin level was included in the analysis. We assessed associations between maternal serum nutritional levels and gestational diabetes using t-test and multivariable logistic regression models. Results Among 15,096 women who gave birth, the prevalence of gestational diabetes was 5.43% (n = 820). The mean (SD) maternal age was 35.09 (4.25) years among women with gestational diabetes and 32.96 (11.82) years among women without gestational diabetes (P < 0.01). Iron, HDL cholesterol, and hemoglobin levels were significantly higher among women with gestational diabetes compared to women without gestational diabetes (P = 0.03, P = 0.03, P < 0.01, consecutively). Total cholesterol, LDL cholesterol, and triglyceride levels were also higher among women with gestational diabetes, but did not show statistical significance between the two groups (P > 0.05). Conclusions This study showed iron, HDL cholesterol, and hemoglobin levels may not be contributing factors for the development of gestational diabetes. Funding Sources This work was supported by the Technology Innovation Program funded by the Ministry of Trade, Industry, and Energy (MOTIE, Republic of Korea).

Do Hospitals with a Higher Level of Maternal Care Designation Have Better Maternal Outcomes?

2018 ◽  
Vol 36 (06) ◽  
pp. 653-658 ◽  
Author(s):  
Sindhu Srinivas ◽  
Katy Kozhimannil ◽  
Peiyin Hung ◽  
Laura Attanasio ◽  
Judy Jou ◽  
...  
Keyword(s):  
High Risk ◽  
Maternal Care ◽  
Maternal Morbidity ◽  
Cross Sectional Study ◽  
Severe Maternal Morbidity ◽  
Maternal Outcomes ◽  
Cross Sectional ◽  
Discharge Data ◽  
Logistic Regression Models ◽  
The Impact

Background A recent document by the American Congress of Obstetricians and Gynecologists (ACOG) and the Society for Maternal-Fetal Medicine introduced the concept of uniform levels of maternal care (LMCs). Objective We assessed LMC across hospitals and measured their association with maternal morbidity, focusing on women with high-risk conditions. Study Design We collected data from hospitals from May to November 2015 and linked survey responses to Statewide Inpatient Databases (SID) hospital discharge data in a retrospective cross-sectional study of 247,383 births admitted to 236 hospitals. Generalized logistic regression models were used to examine the associations between hospitals' LMC and the risk of severe maternal morbidity. Stratified analyses were conducted among women with high-risk conditions. Results High-risk pregnancies were more likely to be managed in hospitals with higher LMC (p < 0.001). Women with cardiac conditions had lower odds of maternal morbidity when delivered in level I compared with level IV units (adjusted odds ratio: 0.29; 95% confidence interval: 0.08–0.99; p = 0.049). There were no other significant associations between the LMC and severe maternal morbidity. Conclusion A higher proportion of high-risk pregnancies were managed within level IV units, although there was no overall evidence that these births had superior outcomes. Further prospective evaluation of LMC designation with patient outcomes is necessary to determine the impact of regionalization on maternal outcomes.

scholarly journals Population-Based Study of Risk Factors for Severe Maternal Morbidity

2012 ◽  
Vol 26 (6) ◽  
pp. 506-514 ◽  
Author(s):  
Kristen E. Gray ◽  
Erin R. Wallace ◽  
Kailey R. Nelson ◽  
Susan D. Reed ◽  
Melissa A. Schiff
Keyword(s):  
Risk Factors ◽  
Maternal Morbidity ◽  
Population Based ◽  
Severe Maternal Morbidity ◽  
Population Based Study

scholarly journals Feasibility of Using Common Data Model for Orthopedic Research: Analysis of Risk Factors for Periprosthetic Joint Infection after Total Joint Arthroplasty

2020 ◽  
Author(s):  
Young Ju Chae ◽  
Jin Ho Shin ◽  
Sung Jae Jung ◽  
Hyun Sik Gong
Keyword(s):  
Risk Factors ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Social Factors ◽  
Data Model ◽  
Joint Infection ◽  
Joint Arthroplasty ◽  
Common Data Model ◽  
Laboratory Results

Abstract Background: Common data model (CDM) is a standardized data structure defined to efficiently use different sources in hospitals. A study using the CDM is scarce for orthopedic outcome researches due to the complexity of variables. We aimed to test the feasibility of applying CDM in the orthopedic field and analyzed risk factors for periprosthetic joint infection (PJI) after total joint arthroplasty (TJA) using CDM.Methods: We undertook a retrospective cohort study of all primary and revision hip and knee TJAs at our institution from January 2003 to October 2017. We identified potential risk factors for PJI after TJAs in the literatures, which included preoperative demographic/social factors, previous medical history, intraoperative factors, laboratory results and others. The data sourced from EMR was extracted, transformed, and loaded into CDM.Results: Variables such as demographic/social factors, medical history and laboratory results could be converted into CDM, but the other known risk factors could not. In total, 12,320 primary hip and knee TJAs and 120 revision arthroplasties were identified. Among them, 34 revisions were done because of PJI. Risk factors of PJI were hypertension and urinary tract infection after total hip arthroplasty, and age (70-79 years), male sex, anemia, steroid use, and urinary tract infection after total knee arthroplasty. Conclusions: This study demonstrates that orthopedic outcome researches using CDM is feasible although data converting to CDM was possible for limited factors. Further data transforming technologies need to be developed to analyze more factors relevant to orthopedic area, such as intraoperative factors and imaging findings.

scholarly journals Identifying women with gestational diabetes based on maternal characteristics: an analysis of four Norwegian prospective studies

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Anam Shakil Rai ◽  
Line Sletner ◽  
Anne Karen Jenum ◽  
Nina Cecilie Øverby ◽  
Signe Nilssen Stafne ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gestational Diabetes ◽  
Diagnostic Criteria ◽  
Predictive Accuracy ◽  
Screening Method ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Maternal Characteristics ◽  
Logistic Regression Models ◽  
European Women

Abstract Background There is still no worldwide agreement on the best diagnostic thresholds to define gestational diabetes (GDM) or the optimal approach for identifying women with GDM. Should all pregnant women perform an oral glucose tolerance test (OGTT) or can easily available maternal characteristics, such as age, BMI and ethnicity, indicate which women to test? The aim of this study was to assess the prevalence of GDM by three diagnostic criteria and the predictive accuracy of commonly used risk factors. Methods We merged data from four Norwegian cohorts (2002–2013), encompassing 2981 women with complete results from a universally offered OGTT. Prevalences were estimated based on the following diagnostic criteria: 1999WHO (fasting plasma glucose (FPG) ≥7.0 or 2-h glucose ≥7.8 mmol/L), 2013WHO (FPG ≥5.1 or 2-h glucose ≥8.5 mmol/L), and 2017Norwegian (FPG ≥5.3 or 2-h glucose ≥9 mmol/L). Multiple logistic regression models examined associations between GDM and maternal factors. We applied the 2013WHO and 2017Norwegian criteria to evaluate the performance of different thresholds of age and BMI. Results The prevalence of GDM was 10.7, 16.9 and 10.3%, applying the 1999WHO, 2013WHO, and the 2017Norwegian criteria, respectively, but was higher for women with non-European background when compared to European women (14.5 vs 10.2%, 37.7 vs 13.8% and 27.0 vs 7.8%). While advancing age and elevated BMI increased the risk of GDM, no risk factors, isolated or in combination, could identify more than 80% of women with GDM by the latter two diagnostic criteria, unless at least 70–80% of women were offered an OGTT. Using the 2017Norwegian criteria, the combination “age≥25 years or BMI≥25 kg/m2” achieved the highest sensitivity (96.5%) with an OGTT required for 93% of European women. The predictive accuracy of risk factors for identifying GDM was even lower for non-European women. Conclusions The prevalence of GDM was similar using the 1999WHO and 2017Norwegian criteria, but substantially higher with the 2013WHO criteria, in particular for ethnic non-European women. Using clinical risk factors such as age and BMI is a poor pre-diagnostic screening method, as this approach failed to identify a substantial proportion of women with GDM unless at least 70–80% were tested.

scholarly journals Frequency of and Factors Associated With Severe Maternal Morbidity

2015 ◽  
Vol 35 (1) ◽  
pp. 21-22
Author(s):  
W.A. Grobman ◽  
J.L. Bailit ◽  
M.M. Rice ◽  
R.J. Wapner ◽  
U.M. Reddy ◽  
...  
Keyword(s):  
Maternal Morbidity ◽  
Severe Maternal Morbidity ◽  
Factors Associated
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