Trends and outcomes of delivery hospitalizations with unstable housing, 2000-2018.

Purpose: Data on trends in and implications of unstable housing during pregnancy are limited. The purpose of this study was to address these knowledge gaps.Methods: This repeat cross-sectional study using the National Inpatient Sample analyzed unstable housing diagnoses among 2000-2018 delivery hospitalizations. Joinpoint regression was used to estimate trends in unstable housing by calculating the average annual percent change.Results: From 2000 to 2018, 27,984 delivery hospitalizations had associated diagnoses of unstable housing (0.03%). There was a significant increase in the unstable housing rates, from 0.72 per 10,000 deliveries in 2000 to 12.8 per 10,000 deliveries in 2018. Delivery hospitalizations with unstable housing were at significantly higher risk of antepartum hemorrhage, preterm delivery, hypertensive disorders of pregnancy, postpartum hemorrhage, and severe maternal morbidity than those without.Conclusions: This serial cross-sectional analysis of delivery hospitalizations found that the reported prevalence of unstable housing is low but increasing and associated with adverse outcomes.

Deliveries Among Patients Aged 11-19 Years and Risk for Adverse Pregnancy Outcomes.

OBJECTIVE: To characterize delivery hospitalization trends of patients aged 11-19 years and associated comorbidities and outcomes. METHODS: For this repeated cross-sectional analysis, deliveries to patients aged 11-54 years were identified in the 2000-2018 National Inpatient Sample. Temporal trends in deliveries to patients aged 11-14 years and 15-19 years were analyzed using joinpoint regression to estimate average annual percent change with 95% CIs. The association of deliveries among patients aged 11-19 years with other comorbid conditions was analyzed. The relationship between delivery among patients aged 11-19 years and adverse maternal outcomes was analyzed with unadjusted and adjusted logistic regression models, with unadjusted and adjusted odds ratios (aORs) as measures of effect. RESULTS: An estimated 73,198,153 delivery hospitalizations from 2000 to 2018 were included, of which 88,363 were to patients aged 11-14 years and 6,359,331 were to patients aged 15-19 years. The proportion of delivery hospitalizations among patients aged 11-14 years decreased from 2.1 to 0.4 per 1,000 from 2000 to 2018 (average annual percent change -7.8%, 95% CI -8.5% to -7.2%). Deliveries to patients aged 15-19 years decreased from 2000 to 2018, from 11.5% to 4.8% of all deliveries (average annual percent change -4.9%, 95% CI -5.6% to -4.3%). For deliveries among patients aged 11-19 years, rates of obesity, mental health conditions, substance use disorder, asthma, and pregestational and gestational diabetes all significantly increased over the study period. From 2000 to 2018, rates of severe maternal morbidity (average annual percent change 2.4%, 95% CI 1.6-3.1%), postpartum hemorrhage (average annual percent change 2.4%, 95% CI 1.4-3.4%), cesarean delivery (average annual percent change 1.3%, 95% CI 0.9-1.7%), and hypertensive disorders of pregnancy (average annual percent change 3.3%, 95% CI 2.8-3.8%) all increased significantly among deliveries to patients aged 11-19 years. Compared with deliveries to patients aged 20-54 years, deliveries to patients aged 11-14 years were associated with increased risk for severe maternal morbidity (aOR 1.73, 95% CI 1.49-2.00), hypertensive disorders of pregnancy (aOR 1.79, 95% CI 1.71-1.88), and postpartum hemorrhage (aOR 1.37, 95% CI 1.27-1.49). CONCLUSION: Deliveries among patients aged 11-19 years have decreased, but both comorbidity and risk for adverse outcomes increased among this age group.

Clinical and Demographic Risk Factors for COVID-19 during Delivery Hospitalizations in New York City.

OBJECTIVE: This study was aimed to review 4 weeks of universal novel coronavirus disease 2019 (COVID-19) screening among delivery hospitalizations, at two hospitals in March and April 2020 in New York City, to compare outcomes between patients based on COVID-19 status and to determine whether demographic risk factors and symptoms predicted screening positive for COVID-19. STUDY DESIGN: This retrospective cohort study evaluated all patients admitted for delivery from March 22 to April 18, 2020, at two New York City hospitals. Obstetrical and neonatal outcomes were collected. The relationship between COVID-19 and demographic, clinical, and maternal and neonatal outcome data was evaluated. Demographic data included the number of COVID-19 cases ascertained by ZIP code of residence. Adjusted logistic regression models were performed to determine predictability of demographic risk factors for COVID-19. RESULTS: Of 454 women delivered, 79 (17%) had COVID-19. Of those, 27.9% (n = 22) had symptoms such as cough (13.9%), fever (10.1%), chest pain (5.1%), and myalgia (5.1%). While women with COVID-19 were more likely to live in the ZIP codes quartile with the most cases (47 vs. 41%) and less likely to live in the ZIP code quartile with the fewest cases (6 vs. 14%), these comparisons were not statistically significant (p = 0.18). Women with COVID-19 were less likely to have a vaginal delivery (55.2 vs. 51.9%, p = 0.04) and had a significantly longer postpartum length of stay with cesarean (2.00 vs. 2.67days, p < 0.01). COVID-19 was associated with higher risk for diagnoses of chorioamnionitis and pneumonia and fevers without a focal diagnosis. In adjusted analyses, including demographic factors, logistic regression demonstrated a c-statistic of 0.71 (95% confidence interval [CI]: 0.69, 0.80). CONCLUSION: COVID-19 symptoms were present in a minority of COVID-19-positive women admitted for delivery. Significant differences in obstetrical outcomes were found. While demographic risk factors demonstrated acceptable discrimination, risk prediction does not capture a significant portion of COVID-19-positive patients. KEY POINTS: · COVID-19 symptoms were present in a minority of COVID-19-positive women admitted.. · COVID-19 symptomatology did not appear to differ before or after the apex of infection in New York.. · Demographic risk factors are unlikely to capture a significant portion of COVID-19-positive patients..