Browsing by Subject "Delivery, Obstetric"

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    Acute infectious morbidity in multiple gestation.
    (Infect Dis Obstet Gynecol, 2015) Dotters-Katz, Sarah K; Patel, Emily; Grotegut, Chad A; Heine, R Phillips
    OBJECTIVES: Physiologic and immunologic changes in pregnancy result in increased susceptibility to infection. These shifts are more pronounced in pregnancies complicated by multiple gestation. The objective of this study was to determine the association between multiple gestation and risk of infectious morbidity. STUDY DESIGN: The Nationwide Inpatient Sample for the years 2008-2010 was used to identify pregnant women during admission for delivery with International Classification of Diseases codes. Logistic regression was used to compute odds ratios and 95% confidence intervals for demographic data, preexisting medical conditions, and acute medical and infectious complications for women with multiple versus singleton gestations. RESULTS: Among women with multiple gestation, 38.4 per 1,000 women had an infectious complication compared to 12.8 per 1,000 women with singletons. The most significant infectious morbidity associated with multiple gestation was intestinal infections, pyelonephritis, influenza, and pneumonia. After controlling for confounding variables, infectious complications at delivery persisted for women with multiples, though the association was dependent on mode of delivery. CONCLUSIONS: Women with multiple gestations are at increased risk for infectious morbidity identified at the time of delivery. This association was diminished among women who had a cesarean suggesting that operative delivery is not responsible for this association.
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    Prevalence and predictors of giving birth in health facilities in Bugesera District, Rwanda.
    (BMC Public Health, 2012-12-05) Joharifard, Shahrzad; Rulisa, Stephen; Niyonkuru, Francine; Weinhold, Andrew; Sayinzoga, Felix; Wilkinson, Jeffrey; Ostermann, Jan; Thielman, Nathan M
    BACKGROUND: The proportion of births attended by skilled health personnel is one of two indicators used to measure progress towards Millennium Development Goal 5, which aims for a 75% reduction in global maternal mortality ratios by 2015. Rwanda has one of the highest maternal mortality ratios in the world, estimated between 249-584 maternal deaths per 100,000 live births. The objectives of this study were to quantify secular trends in health facility delivery and to identify factors that affect the uptake of intrapartum healthcare services among women living in rural villages in Bugesera District, Eastern Province, Rwanda. METHODS: Using census data and probability proportional to size cluster sampling methodology, 30 villages were selected for community-based, cross-sectional surveys of women aged 18-50 who had given birth in the previous three years. Complete obstetric histories and detailed demographic data were elicited from respondents using iPad technology. Geospatial coordinates were used to calculate the path distances between each village and its designated health center and district hospital. Bivariate and multivariate logistic regressions were used to identify factors associated with delivery in health facilities. RESULTS: Analysis of 3106 lifetime deliveries from 859 respondents shows a sharp increase in the percentage of health facility deliveries in recent years. Delivering a penultimate baby at a health facility (OR = 4.681 [3.204 - 6.839]), possessing health insurance (OR = 3.812 [1.795 - 8.097]), managing household finances (OR = 1.897 [1.046 - 3.439]), attending more antenatal care visits (OR = 1.567 [1.163 - 2.112]), delivering more recently (OR = 1.438 [1.120 - 1.847] annually), and living closer to a health center (OR = 0.909 [0.846 - 0.976] per km) were independently associated with facility delivery. CONCLUSIONS: The strongest correlates of facility-based delivery in Bugesera District include previous delivery at a health facility, possession of health insurance, greater financial autonomy, more recent interactions with the health system, and proximity to a health center. Recent structural interventions in Rwanda, including the rapid scale-up of community-financed health insurance, likely contributed to the dramatic improvement in the health facility delivery rate observed in our study.
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    Risk of obstetric anal sphincter injuries at the time of admission for delivery: A clinical prediction model.
    (BJOG : an international journal of obstetrics and gynaecology, 2022-11) Luchristt, Douglas; Meekins, Ana Rebecca; Zhao, Congwen; Grotegut, Chad; Siddiqui, Nazema Y; Alhanti, Brooke; Jelovsek, John Eric

    Objective

    To develop and validate a model to predict obstetric anal sphincter injuries (OASIS) using only information available at the time of admission for labour.

    Design

    A clinical predictive model using a retrospective cohort.

    Setting

    A US health system containing one community and one tertiary hospital.

    Sample

    A total of 22 873 pregnancy episodes with in-hospital delivery at or beyond 21 weeks of gestation.

    Methods

    Thirty antepartum risk factors were identified as candidate variables, and a prediction model was built using logistic regression predicting OASIS versus no OASIS. Models were fit using the overall study population and separately using hospital-specific cohorts. Bootstrapping was used for internal validation and external cross-validation was performed between the two hospital cohorts.

    Main outcome measures

    Model performance was estimated using the bias-corrected concordance index (c-index), calibration plots and decision curves.

    Results

    Fifteen risk factors were retained in the final model. Decreasing parity, previous caesarean birth and cardiovascular disease increased risk of OASIS, whereas tobacco use and black race decreased risk. The final model from the total study population had good discrimination (c-index 0.77, 95% confidence interval [CI] 0.75-0.78) and was able to accurately predict risks between 0 and 35%, where average risk for OASIS was 3%. The site-specific model fit using patients only from the tertiary hospital had c-stat 0.74 (95% CI 0.72-0.77) on community hospital patients, and the community hospital model was 0.77 (95%CI 0.76-0.80) on the tertiary hospital patients.

    Conclusions

    OASIS can be accurately predicted based on variables known at the time of admission for labour. These predictions could be useful for selectively implementing OASIS prevention strategies.