In some studies, the dose of intravenous soybean oil (SO) has been associated with a decreased incidence of intestinal failure-associated liver disease. The effect of lipid sparing on neurodevelopment (ND) and growth remains unknown. This study investigated the impact of SO dose on ND and growth over the first 2 years of age in preterm neonates.
We develop a novel extension of Oaxaca decomposition methods for non-linear random effects models to investigate the decline of infant mortality in 42 low and middle income countries. We analyze micro data from 84 Demographic and Health Surveys where surveys from two time periods were available. We predict mortality at the birth level with a Bayesian hierarchical probit regression models. We use the predictions from these models as input for our new Oaxaca method. Our novel approach accounts for uncertainty in the decompostion results, and allows for point estimates, stan- dard deviations, and posterior distributions of the Oaxaca conclusions. Further, our approach does not depend on assumptions such as matched samples between two surveys and and marginalizes ran- dom effects for variables that are not comparable between surveys, such as location effects. For most countries, declines in infant mortality are due to changes in the regression coefficients, not on covari- ate distributions. However, our decomposition results show that there is considerable heterogeneity between countries and uncertainty on which variable matter the most within countries.
Background: Neonates with gastrointestinal disorders (GDs) are at high risk for parenteral nutrition–associated liver disease (PNALD). Soybean‐based intravenous lipid emulsions (S‐ILE) have been associated with PNALD. This study's objective was to determine if a lower dose compared with a higher dose of S‐ILE prevents cholestasis without compromising growth. Materials and Methods: This multicenter randomized controlled pilot study enrolled patients with GDs who were ≤5 days of age to a low dose (~1 g/kg/d) (LOW) or control dose of S‐ILE (~3 g/kg/d) (CON). The primary outcome was cholestasis (direct bilirubin [DB] >2 mg/dL) after the first 7 days of age. Secondary outcomes included growth, PN duration, and late‐onset sepsis. Results: Baseline characteristics were similar between the LOW (n = 20) and CON groups (n = 16). When the LOW group was compared with the CON group, there was no difference in cholestasis (30% vs 38%, P = .7) or secondary outcomes. However, mean ± SE DB rate of change over the first 8 weeks (0.07 ± 0.04 vs 0.3 ± 0.09 mg/dL/wk, P = .01) and entire study (0.008 ± 0.03 vs 0.2 ± 0.07 mg/dL/wk, P = .02) was lower in the LOW group compared with the CON group. Conclusion: In neonates with GDs who received a lower dose of S‐ILE, DB increased at a slower rate in comparison to neonates who received a higher dose of S‐ILE. Growth was comparable between the groups. This study demonstrates a need for a larger, randomized controlled trial comparing 2 different S‐ILE doses for cholestasis prevention in neonates at risk for PNALD.
Melanocytic tumors are often challenging and constitute almost one in four skin biopsies. Immunohistochemical (IHC) studies may assist diagnosis; however, indications for their use are not standardized.A test set of 240 skin biopsies of melanocytic tumors was examined by 187 pathologists from 10 US states, interpreting 48 cases in Phase I and either 36 or 48 cases in Phase II. Participant and diagnosis characteristics were compared between those who reported they would have ordered, or who would have not ordered IHC on individual cases. Intraobserver analysis examined consistency in the intent to order when pathologists interpreted the same cases on two occasions.Of 187 participants interpreting 48 cases each, 21 (11%) did not request IHC tests for any case, 85 (45%) requested testing for 1 to 6 cases, and 81 (43%) requested testing for ≥6 cases. Of 240 cases, 229 had at least one participant requesting testing. Only 2 out of 240 cases had more than 50% of participants requesting testing. Increased utilization of testing was associated with younger age of pathologist, board-certification in dermatopathology, low confidence in diagnosis, and lesions in intermediate MPATH-Dx classes 2 to 4. The median intraobserver concordance for requesting tests among 72 participants interpreting the same 48 cases in Phases I and II was 81% (IQR 73%-90%) and the median Kappa statistic was 0.20 (IQR 0.00, 0.39).Substantial variability exists among pathologists in utilizing IHC.
Rates of abnormal visual inspection with acetic acid and prevalence of high-risk human papillomavirus (HPV) subtypes have not been well characterized in HIV-infected women in Malawi. We performed a prospective cohort study of visual inspection with acetic acid (N = 440) in HIV-infected women aged 25--59 years, with a nested study of HPV subtypes in first 300 women enrolled. Of 440 women screened, 9.5% (N = 42) had abnormal visual inspection with acetic acid with 69.0% (N = 29) having advanced disease not amenable to cryotherapy. Of 294 women with HPV results, 39% (N = 114) of women were positive for high-risk HPV infection. Only lower CD4 count (287 cells/mm 3 versus 339 cells/mm 3 , p = 0.03) and high-risk HPV (66.7% versus 35.6%, p < 0.01) were associated with abnormal visual inspection with acetic acid. The most common high-risk HPV subtypes in women with abnormal visual inspection with acetic acid were 35 (33.3%), 16 (26.7%), and 58 (23.3%). Low CD4 cell count was associated with abnormal visual inspection with acetic acid and raises the importance of early antiretroviral therapy and expanded availability of visual inspection with acetic acid. HPV vaccines targeting additional non-16/18 high-risk HPV subtypes may have greater protective advantages in countries such as Malawi.
Abstract Objectives “Assurance behaviors,” a type of defensive medicine, involve physicians’ utilization of additional patient services to avoid adverse legal outcomes. We aim to compare the use of clinical behaviors (such as ordering additional tests, services, and consultations) due to malpractice concerns with the same behaviors due to patient safety concerns. Methods A national sample of dermatopathologists (n = 160) completed an online survey. Results Participants reported using one or more of five clinical behaviors due to concerns about medical malpractice (95%) and patient safety (99%). Self-reported use of clinical behaviors due to malpractice concerns and patient safety concerns was compared, including ordering additional immunohistochemistry/molecular tests (71% vs 90%, respectively, P < .0001), recommending additional surgical sampling (78% vs 91%, P < .0001), requesting additional slides (81% vs 95%, P < .0001), obtaining second reviews (78% vs 91%, P < .0001), and adding caveats into reports regarding lesion difficulty (85% vs 89%, P > .05). Conclusions Dermatopathologists use many clinical behaviors both as assurance behaviors and due to patient safety concerns, with a higher proportion reporting patient safety concerns as a motivation for specific behaviors.
Author(s): Flores, Martiniano Jose | Advisor(s): Weiss, Robert E | Abstract: We analyze data from the Los Angeles LGBT Center, a community-based healthcare organization. When patients visit the clinic, they are given a comprehensive risk-assessment questionnaire. We develop three methods that allow us to identify the risk factors associated with HIV seroconversion and predict who is most likely to become HIV positive. First, we construct a two-stage multivariate logistic regression model, where stage one models a patient's history of illicit drug use and their history of STIs other than HIV, and stage two models their risk of contracting HIV. Each stage of the model has ZIP code random effects that are correlated over space. We propose a statistic called the geometric mean ratio (GMR), which measures how much of the variability in the ZIP code random effects for HIV is explained by the stage one random effects. We find that the stage one random effects are negligible in the HIV model and that where a person lives is not predictive of their risk of contracting HIV. Next, we jointly model a patient's time until HIV seroconversion with their clinic visit frequency through shared frailties. We show that if clinic visit frequency is correlated with survival, then the censoring is informative. We examine how the informativeness of the censoring depends on the frailty distributions. We find that patients who visit the clinic more frequently tend to have a higher probability of contracting HIV, suggesting that patients are accurately assessing that they have a higher risk of disease.Finally, we reduce the items from the risk assessment questionnaire into a set of latent measures of patient riskiness with a factor analysis model. Because patients come to the clinic multiple times, we allow the factors to be correlated within a patient over time, and between patients over space. We then use the factor scores from one visit to predict whether or not a patient will seroconvert by their next visit. We show that this model is equivalent to a larger longitudinal factor model and that the factor scores are predictive of future risk of HIV.
Abstract Background Goal 3.2 from the Sustainable Development Goals (SDG) calls for reductions in national averages of Under-5 Mortality. However, it is well known that within countries these reductions can coexist with left behind populations that have mortality rates higher than national averages. To measure inequality in under-5 mortality and to identify left behind populations, mortality rates are often disaggregated by socioeconomic status within countries. While socioeconomic disparities are important, this approach does not quantify within group variability since births from the same socioeconomic group may have different mortality risks. This is the case because mortality risk depends on several risk factors and their interactions and births from the same socioeconomic group may have different risk factor combinations. Therefore mortality risk can be highly variable within socioeconomic groups. We develop a comprehensive approach using information from multiple risk factors simultaneously to measure inequality in mortality and to identify left behind populations. Methods We use Demographic and Health Surveys (DHS) data on 1,691,039 births from 182 different surveys from 67 low and middle income countries, 51 of which had at least two surveys. We estimate mortality risk for each child in the data using a Bayesian hierarchical logistic regression model. We include commonly used risk factors for monitoring inequality in early life mortality for the SDG as well as their interactions. We quantify variability in mortality risk within and between socioeconomic groups and describe the highest risk sub-populations. Findings For all countries there is more variability in mortality within socioeconomic groups than between them. Within countries, socioeconomic membership usually explains less than 20% of the total variation in mortality risk. In contrast, country of birth explains 19% of the total variance in mortality risk. Targeting the 20% highest risk children based on our model better identifies under-5 deaths than targeting the 20% poorest. For all surveys, we report efficiency gains from 26% in Mali to 578% in Guyana. High risk births tend to be births from mothers who are in the lowest socioeconomic group, live in rural areas and/or have already experienced a prior death of a child. Interpretation While important, differences in under-5 mortality across socioeconomic groups do not explain most of overall inequality in mortality risk because births from the same socioeconomic groups have different mortality risks. Similarly, policy makers can reach the highest risk children by targeting births based on several risk factors (socioeconomic status, residing in rural areas, having a previous death of a child and more) instead of using a single risk factor such as socioeconomic status. We suggest that researchers and policy makers monitor inequality in under-5 mortality using multiple risk factors simultaneously, quantifying inequality as a function of several risk factors to identify left behind populations in need of policy interventions and to help monitor progress toward the SDG.
Abstract The effects of democracy on living conditions among the poor are disputed. Previous studies have addressed this question by estimating the average effect of democracy on early-life mortality across all countries. We revisit this debate using a research design that distinguishes between the aggregated effects of democracy across all countries and their individual effects within countries. Using Interrupted Time Series methodology and estimating model parameters in a Bayesian framework, we find the average effect of democracy on early-life mortality to be close to zero, but with considerable variation at the country-level. Democratization was followed by fewer child deaths in 21 countries, an increase in deaths in eight, and no measurable changes in the remaining 32 cases. Transitions were usually beneficial in Europe, neutral or beneficial in Africa and Asia, and neutral or harmful in Latin America. The distribution of country-level effects is not consistent with common arguments about the conditional effects of democratic transitions. Our results open a new line of research into the sources of theses heterogeneous effects.
