scholarly journals Trends and Risk Factors Associated with Severe Maternal Morbidity in Texas Women

2018 ◽  
Vol 21 ◽  
pp. S147
Author(s):  
CN Truong ◽  
S Pathak ◽  
C Ganduglia Cazaban
2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Seo-Ho Cho ◽  
Kwangsoo Kim

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.


2012 ◽  
Vol 26 (6) ◽  
pp. 506-514 ◽  
Author(s):  
Kristen E. Gray ◽  
Erin R. Wallace ◽  
Kailey R. Nelson ◽  
Susan D. Reed ◽  
Melissa A. Schiff

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

2021 ◽  
Vol 4 (2) ◽  
pp. e2036148 ◽  
Author(s):  
Jiajia Chen ◽  
Shanna Cox ◽  
Elena V. Kuklina ◽  
Cynthia Ferre ◽  
Wanda Barfield ◽  
...  

Author(s):  
Lisa M. Korst ◽  
Kimberly D. Gregory ◽  
Lisa A. Nicholas ◽  
Samia Saeb ◽  
David J. Reynen ◽  
...  

Abstract Background Current interest in using severe maternal morbidity (SMM) as a quality indicator for maternal healthcare will require the development of a standardized method for estimating hospital or regional SMM rates that includes adjustment and/or stratification for risk factors. Objective To perform a scoping review to identify methodological considerations and potential covariates for risk adjustment for delivery-associated SMM. Search methods Following the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews, systematic searches were conducted with the entire PubMed and EMBASE electronic databases to identify publications using the key term “severe maternal morbidity.” Selection criteria Included studies required population-based cohort data and testing or adjustment of risk factors for SMM occurring during the delivery admission. Descriptive studies and those using surveillance-based data collection methods were excluded. Data collection and analysis Information was extracted into a pre-defined database. Study design and eligibility, overall quality and results, SMM definitions, and patient-, hospital-, and community-level risk factors and their definitions were assessed. Main results Eligibility criteria were met by 81 studies. Methodological approaches were heterogeneous and study results could not be combined quantitatively because of wide variability in data sources, study designs, eligibility criteria, definitions of SMM, and risk-factor selection and definitions. Of the 180 potential risk factors identified, 41 were categorized as pre-existing conditions (e.g., chronic hypertension), 22 as obstetrical conditions (e.g., multiple gestation), 22 as intrapartum conditions (e.g., delivery route), 15 as non-clinical variables (e.g., insurance type), 58 as hospital-level variables (e.g., delivery volume), and 22 as community-level variables (e.g., neighborhood poverty). Conclusions The development of a risk adjustment strategy that will allow for SMM comparisons across hospitals or regions will require harmonization regarding: a) the standardization of the SMM definition; b) the data sources and population used; and c) the selection and definition of risk factors of interest.


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