Evaluating the effect of care around labor and delivery practices on early neonatal mortality in the Global Network's Maternal and Newborn Health Registry

BACKGROUND

Neonatal deaths in first 28-days of life represent 47% of all deaths under the age of five years globally and are a focus of the United Nation's (UN's) Sustainable Development Goals. Pregnant women are delivering in facilities but that does not indicate quality of care during delivery and the postpartum period. The World Health Organization's Essential Newborn Care (ENC) package reduces neonatal mortality, but lacks a simple and valid composite index that measures its effectiveness.

METHODS

Data on 5 intra-partum and 3 post-partum practices (indicators) recommended as part of ENC, routinely collected in NICHD's Global Network's (GN) Maternal Newborn Health Registry (MNHR) between 2010 and 2013, were included. We evaluated if all 8 practices (Care around Delivery - CAD), combined as an index was associated with reduced early neonatal mortality rates (days 0-6 of life).

RESULTS

A total of 150,848 live births were included in the analysis. The individual indicators varied across sites. All components were present in 19.9% births (range 0.4 to 31% across sites). Present indicators (8 components) were associated with reduced early neonatal mortality [adjusted RR (95% CI):0.81 (0.77, 0.85); p < 0.0001]. Despite an overall association between CAD and early neonatal mortality (RR < 1.0 for all early mortality): delivery by skilled birth attendant; presence of fetal heart and delayed bathing were associated with increased early neonatal mortality.

CONCLUSIONS

Present indicators (8 practices) of CAD were associated with a 19% reduction in the risk of neonatal death in the diverse health facilities where delivery occurred within the GN MNHR. These indicators could be monitored to identify facilities that need to improve compliance with ENC practices to reduce preventable neonatal deaths. Three of the 8 indicators were associated with increased neonatal mortality, due to baby being sick at birth. Although promising, this composite index needs refinement before use to monitor facility-based quality of care in association with early neonatal mortality. Trial registration The identifier of the Maternal Newborn Health Registry at ClinicalTrials.gov is NCT01073475.

Assessing coverage of essential maternal and child health interventions using health-facility data in Uganda

BACKGROUND

Nationally representative household surveys are the gold standard for tracking progress in coverage of life-saving maternal and child interventions, but often do not provide timely information on coverage at the local and health facility level. Electronic routine health information system (RHIS) data could help provide this information, but there are currently concerns about data quality. This analysis seeks to improve the usability of and confidence in electronic RHIS data by using adjustments to calculate more accurate numerators and denominators for essential interventions.

METHODS

Data from three sources (Ugandan Demographic and Health (UDHS) survey, electronic RHIS, and census) were used to provide estimates of essential maternal (> 4 antenatal care visits (ANC), skilled delivery, and postnatal care visit (PNC)) and child health interventions (diphtheria, pertussis, tetanus, and hepatitis B and Haemophilus influenzae type b and polio vaccination series, measles vaccination, and vitamin A). Electronic RHIS data was checked for quality and both numerators and denominators were adjusted to improve accuracy. Estimates were compared between the three sources.

RESULTS

Estimates of maternal health interventions from adjusted electronic RHIS data were lower than those of the UDHS, while child intervention estimates were typically higher. Adjustment of electronic RHIS data generally improved accuracy compared with no adjustment. There was considerable agreement between estimates from adjusted, electronic RHIS data, and UDHS for skilled delivery and first dose of childhood vaccination series, but lesser agreement for ANC visits and second and third doses of childhood vaccinations.

CONCLUSIONS

Nationally representative household surveys will likely continue being the gold standard of coverage estimates of maternal and child health interventions, but this analysis shows that current approaches to adjusting health facility estimate works better for some indications than others. Further efforts to improve accuracy of estimates from RHIS sources are needed.

Colorectal cancer screening: language is a greater barrier for Latino men than Latino women

Colorectal cancer screening (CRC) disparities between non-Latino Whites and Latinos remain, and may have increased. The goal of this analysis was to examine the association between Latino race/ethnicity, gender, and English-proficiency and CRC screening. Analysis of the CDC's BRFSS 2008 survey. We estimated crude and adjusted screening rates and odds ratios of respondents' reported CRC test receipt stratified by self-reported Latino ethnicity, gender, and limited English proficiency (LEP) as determined by language of survey response (English vs Spanish). Of 99,883 respondents included in the study populations, LEP Latino men had the lowest adjusted screening rates (48.2%) which were lower that all other Latinos subgroups including Latina women with LEP (56.2%). Compared to non-Latino White men, LEP Latino men were 0.47 times as likely to report receiving CRC screening tests (AOR 0.47; 95% CI 0.35-0.63). Disparities in CRC screening are most dramatic for LEP Latino men.

Kernel machine SNP-set testing under multiple candidate kernels

Joint testing for the cumulative effect of multiple single-nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large-scale genetic association studies. The kernel machine (KM)-testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori because this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest P-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power vs. using the best candidate kernel.

Dumbbell granulomatous abscess of the chest wall following needle biopsy of the pleura

A 38-year-old woman who had a Cope needle biopsy of the pleura was treated for plural tuberculosis on the basis of a positive PPD-S skin test and presence of caseating granulomas in the pleural biopsy. Ten months later she developed a tender, subcutaneous nodule in the area of the previous needle biopsy. Surgical exploration revealed a dumbbell abscess through the chest wall communicating with an area of consolidation in the right middle lobe. En bloc surgical resection of the abscess and peripheral portion of the right middle lobe was curative, although all pathologic and cultural studies of the resected tissue were non-diagnostic.