Literature DB >> 19909212

Risk factors for a prolonged length of stay in women hospitalized for preeclampsia in Texas.

Zuber D Mulla1, Bahij S Nuwayhid, K Michelle Garcia, Kellie Flood-Shaffer, James W Van Hook, R Moss Hampton.   

Abstract

OBJECTIVES: To identify correlates of a prolonged length of stay (PLOS) in women hospitalized for preeclampsia/eclampsia in Texas, USA.
METHODS: Statewide hospital data were obtained, and the records of women who were discharged in 2004 and/or 2005 with a principal discharge diagnosis of preeclampsia or eclampsia were extracted using ICD-9-CM codes. PLOS was defined as a stay greater than 5 days. Odds ratios (OR) for PLOS were calculated. Generalized estimating equations were used to account for a small group of women who were hospitalized multiple times during the study period for preeclampsia. A total of 21,203 records were analyzed.
RESULTS: The crude incidence of PLOS was 17.5%. Advancing maternal age was positively associated with PLOS: for every 10-year increase, there was a 20% increase in the odds of PLOS (adjusted OR = 1.20,95% confidence interval (CI): 1.13, 1.28). The strongest risk factor for PLOS was the presence of renal disease: adjusted OR 5.81 (95% CI: 3.97, 8.50). Protective factors included Medicaid beneficiary status, and being admitted from the emergency department.
CONCLUSIONS: The strongest correlate of PLOS in a large cohort of women hospitalized for preeclampsia was the presence of renal disease.

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Year:  2010        PMID: 19909212     DOI: 10.3109/10641950902777754

Source DB:  PubMed          Journal:  Hypertens Pregnancy        ISSN: 1064-1955            Impact factor:   2.108


  3 in total

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Authors:  Z D Mulla; V Annavajjhala; J L Gonzalez-Sanchez; M R Simon; B S Nuwayhid
Journal:  Epidemiol Infect       Date:  2012-07-20       Impact factor: 4.434

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

Authors:  Eva Williford; Valerie Haley; Louise-Anne McNutt; Victoria Lazariu
Journal:  PLoS One       Date:  2020-04-20       Impact factor: 3.240

3.  An imbalance-aware deep neural network for early prediction of preeclampsia.

Authors:  Rachel Bennett; Zuber D Mulla; Pavan Parikh; Alisse Hauspurg; Talayeh Razzaghi
Journal:  PLoS One       Date:  2022-04-06       Impact factor: 3.240

  3 in total

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