Risk Factors for a Prolonged Length of Stay in Women Hospitalized for Preeclampsia in Texas

Mulla, Zuber D.; Nuwayhid, B.; Garcia, Kristian M.; Flood-Shaffer, Kellie F.; Hook, James W. Van; Hampton, R. Moss

doi:10.3109/10641950902777754

Cited by 6 publications

(4 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several recent investigations have used the Texas and Florida hospital inpatient discharge databases to explore the epidemiology of pre-eclampsia [35][36][37][38]. Misclassification of the presence of pre-eclampsia in these previous studies and in the current investigation is possible.…”

Section: Discussionmentioning

confidence: 99%

Group B streptococcal colonization and the risk of pre-eclampsia

et al. 2012

View full text Add to dashboard Cite

SUMMARYTo determine if there was an association between recto-vaginal group B streptococcus (GBS) colonization and pre-eclampsia, two cross-sectional studies were conducted using statewide hospital databases. The first study analysed data from the state of Florida, USA, and included 190 645 women who were discharged in 2001. This dataset was used to generate the hypothesis that GBS colonization is associated with pre-eclampsia. The second study tested the GBS hypothesis using the records of 577 153 women who delivered in 2004 or 2005 in Texas, USA. Adjusted odds ratios (aOR) for the outcome of pre-eclampsia comparing GBS-positive to GBS-negative women were calculated using logistic regression. The aOR for the association between GBS carriage and pre-eclampsia was 0·71 [95% confidence interval (CI) 0·65–0·77] in the Florida dataset. In the Texas dataset, the overall prevalence of GBS carriage was 14·1% while the overall prevalence of pre-eclampsia was 4·0%. GBS carriers were 31% less likely than non-carriers to have pre-eclampsia (aOR 0·69, 95% CI 0·66–0·72) in Texas. In two large statewide analyses, GBS carriage was inversely associated with pre-eclampsia. A sensitivity analysis revealed that misclassification of GBS status is not a likely explanation of our findings.

show abstract

Section: Discussionmentioning

confidence: 99%

Group B streptococcal colonization and the risk of pre-eclampsia

et al. 2012

View full text Add to dashboard Cite

show abstract

“…The limitation in the choice of covariates and not being able to include health status information likely lead to the underestimation of the mean LOS. Individual patient comorbidities are unlikely to substantially change prediction of components (shorter LOS and longer LOS distributions) [40,41]. As with modeling in general the effect of a parameter changes depending on the other covariates in the model.…”

Section: Plos Onementioning

confidence: 99%

Dealing with highly skewed hospital length of stay distributions: The use of Gamma mixture models to study delivery hospitalizations

et al. 2020

View full text Add to dashboard Cite

The increased focus on addressing severe maternal morbidity and maternal mortality has led to studies investigating patient and hospital characteristics associated with longer hospital stays. Length of stay (LOS) for delivery hospitalizations has a strongly skewed distribution with the vast majority of LOS lasting two to three days in the United States. Prior studies typically focused on common LOSs and dealt with the long LOS distribution tail in ways to fit conventional statistical analyses (e.g., log transformation, trimming). This study demonstrates the use of Gamma mixture models to analyze the skewed LOS distribution. Gamma mixture models are flexible and, do not require data transformation or removal of outliers to accommodate many outcome distribution shapes, these models allow for the analysis of patients staying in the hospital for a longer time, which often includes those women experiencing worse outcomes. Random effects are included in the model to account for patients being treated within the same hospitals. Further, the role and influence of differing placements of covariates on the results is discussed in the context of distinct model specifications of the Gamma mixture regression model. The application of these models shows that they are robust to the placement of covariates and random effects. Using New York State data, the models showed that longer LOS for childbirth hospitalizations were more common in hospitals designated to accept more complicated deliveries, across hospital types, and among Black women. Primary insurance also was associated with LOS. Substantial variation between hospitals suggests the need to investigate protocols to standardize evidence-based medical care.

show abstract

“…First, it imposes the risk for birth between 37 and 39 weeks' gestation, which turns out to confer substantial increased morbidity and mortality, compared with births occurring after 39 weeks' gestation. 29 Third, as stated, health care costs for treating lateonset preeclampsia and infants born in the late preterm period are increasing because of extended hospital stay before delivery 30 and subsequent rehospitalization in the neonatal period. 27 These babies tend to stay in the hospital somewhat longer than babies receiving usual care.…”

Section: Late-onset Preeclampsiamentioning

confidence: 99%

A Risk Reduction Model for Late-Onset Preeclampsia

Yeo

2011

Advances in Nursing Science

View full text Add to dashboard Cite

Viewing late-onset preeclampsia as an autonomic dysregulation is a new approach. It is one that will provide nurses and other clinicians with theory-based prenatal care choices that focus on enhancing homeostasis rather than prediction. The dominant prediction model manages the disease based on one biomedical pathway even though the disease is believed to be heterogeneous. Unlike early-onset preeclampsia, which involves severe placental pathophysiology and thus should be left for medical research, late-onset preeclampsia--intact placenta with maternal cardiovascular dysregulation--may be prevented with a lifestyle intervention, in particular, low-intensity exercise. This article discusses a nursing approach to promote health and reduce risks even when the etiology of the disease remains unknown.

show abstract

Risk Factors for a Prolonged Length of Stay in Women Hospitalized for Preeclampsia in Texas

Abstract: The strongest correlate of PLOS in a large cohort of women hospitalized for preeclampsia was the presence of renal disease.

Cited by 6 publications

References 17 publications

Group B streptococcal colonization and the risk of pre-eclampsia

Group B streptococcal colonization and the risk of pre-eclampsia

Dealing with highly skewed hospital length of stay distributions: The use of Gamma mixture models to study delivery hospitalizations

A Risk Reduction Model for Late-Onset Preeclampsia

Contact Info

Product

Resources

About