Jeffery Michael Szychowski

Objective: The United States (US) reports disparities in maternal health outcomes across states, regions, and racial/ethnic groups. Few studies in the US South have sought to understand the perspectives of Non-Hispanic Black (NHB) women about their experiences of maternity care. This study examines NHB women's maternity care experiences in three Southern states. Methods: Through in-depth interviews (February—September 2023), we explored maternity care experiences of NHB women experiencing adverse maternal outcomes ( n = 18), and family members of deceased NHB women or infants ( n = 2), in Alabama, Georgia and North Carolina. Grounded in the World Health Organization’s Quality of Care Framework for Maternal and Newborn Health Care, our study elucidated the experiences of these NHB women and family members with racial and other discrimination, and their preferences for treatment during maternity care. We adopted a mixed deductive and inductive thematic approach to analyze the data using NVivo software. Results: Three major themes emerged: 1) experience of care, 2) perceptions of racial and other discrimination during maternity care, and 3) preferred manner of treatment in maternity services. Perceptions about discrimination due to race and other identities were shared. Issues related to provider-patient communication, respect, and emotional support were identified as main factors that influenced NHB women’s experiences of maternity care. Conclusion: Both positive and negative maternity care experiences, including instances of overt racism and discrimination were reported by NHB women and families who had experienced adverse pregnancy outcomes. Our findings highlight the need to prioritize respectful maternity care through targeted quality measures.

No tool currently exists to predict the cumulative risk of suboptimal clinical outcomes among pregnant and postpartum women with HIV (PPWH). This study sought to develop and validate a parsimonious risk calculator capable of predicting disengagement from care and HIV treatment failure among PPWH. We created the risk calculator using data from 1,331 PPWH from Southwestern Kenya (Homabay, Migori, and Kisumu Counties) in the Mother Infant Visit Adherence and Treatment Engagement Trial. Least absolute shrinkage and selection operator logistic regression retained the most predictive variables from 16 candidate factors to estimate the probability of treatment failure or disengagement from care. Three risk quintiles were calculated. We assessed external validation with an independent dataset (Opt4Mamas; N = 820). Cross-validated area under the curve of receiver operating characteristic (AUROC) and calibration measures assessed model performance. Two unique risk calculators were created - one for PPWH with known HIV diagnosis prior to pregnancy and one for PPWH with new HIV diagnoses. The combined outcome of care disengagement or treatment failure occurred in 43% of PPWH with known diagnosis and 40% with new diagnosis in the development dataset; and 37% with known diagnosis and 13% with new diagnosis in the validation dataset. The calculators included demographic (age, parity, marital status), clinical (virological failure, missed visits, regimen line, gestation age), and psychosocial variables (intimate partner violence, stigma, depression, partner support, disclosure, food insecurity). The model for PPWH with known diagnosis demonstrated better calibration and discrimination (AUROC 0.843 [95% CI 0.805, 0.866]) than the model for PPWH with a new HIV diagnosis (AUROC 0.463 [95% CI 0.347, 0.597]). Mean predicted risk probabilities among PPWH with known HIV diagnosis were: low (6%), moderate (56%), and high (70%). Mean predicted risk probabilities among those with a new HIV diagnosis were: low (31%), moderate (48%), and high (65%). The novel risk calculator for PPWH with a known HIV diagnosis has the potential to identify those who are at risk of sub-optimal HIV treatment and care outcomes for targeted interventions to prevent treatment failure and loss to follow-up.

Background: Accurate longitudinal modelling of cognitive decline is a major goal of Alzheimer’s disease and related dementia (ADRD) research. However, the impact of subject-specific effects is not well characterized and may have implications for data generation and prediction. Objective: This study seeks to address the impact of subject-specific effects, which are a less well-characterized aspect of ADRD cognitive decline, as measured by the Alzheimer’s Disease Assessment Scale’s Cognitive Subscale (ADAS-Cog). Methods: Prediction errors and biases for the ADAS-Cog subscale were evaluated when using only population-level effects, robust imputation of subject-specific effects using model covariances, and directly known individual-level effects fit during modelling as a natural control. Evaluated models included pre-specified parameterizations for clinical trial simulation, analogous mixed-effects regression models parameterized directly, and random forest ensemble models. Assessment used a meta-database of Alzheimer’s disease studies with validation in simulated synthetic cohorts. Results: All models observed increases in variance under imputation leading to increased prediction error. Bias decreased with imputation except under the pre-specified parameterization, which increased in the meta-database, but was attenuated under simulation. Known fitted subject effects gave the best prediction results. Conclusion: Subject-specific effects were found to have a profound impact on predicting ADAS-Cog. Reductions in bias suggest imputing random effects assists in calculating results on average, as when simulating clinical trials. However, reduction in error emphasizes population-level effects when attempting to predict outcomes for individuals. Forecasting future observations greatly benefits from using known subject-specific effects.

Aim To characterize symptom‐specific distress and impact on quality of life (QOL) among women with urge, passive, and combined urge/passive fecal incontinence (FI) phenotypes. A secondary aim was to characterize FI symptom‐specific distress and impact on women with a novel fourth phenotype, stress FI. Methods Women with at least monthly FI from 2003 to 2017 were included. Participants completed the Modified Manchester Health Questionnaire (MMHQ) including MHQ and Fecal Incontinence Severity Index (FISI). Anorectal manometry (ARM) and endoanal ultrasound (EAUS) testing was performed. Total MHQ and FISI scores were compared across FI subtypes controlling for pertinent baseline covariates. Results The cohort included 404 subjects, 220 meeting criteria for urge FI, 67 passive FI, and 117 combined urge/passive FI. On MHQ, women with combined urge/passive FI were most impacted (p < 0.01). FISI scores were significantly different from combined urge/passive FI having the greatest impact (38.1 ± 12.5) and urge FI (31.1 ± 11.3), p < 0.01 having the least. No differences were observed in ARM measurements or anal sphincter defects among the three groups (all p > 0.05). Twenty‐nine subjects were identified with stress FI. There were no differences in overall MHQ or FISI scores or anal sphincter evaluation among the urge, passive, and stress FI groups (all p > 0.05). Conclusion Women with combined urge/passive FI have higher symptom distress and impact on QOL than urge or passive FI alone. Further research is needed to determine the significance of stress FI as a subtype and response to treatment.

OBJECTIVE: To compare perinatal and maternal outcomes in low-risk multiparous women who underwent elective induction of labor in the 39th week of gestation with those who were expectantly managed. METHODS: We performed a single center retrospective cohort study of low-risk multiparous women delivering nonanomalous singletons between 39 and 42 completed weeks of gestation from 2014 to 2018. The primary outcome was a perinatal composite of death, neonatal respiratory support, a 5-minute Apgar score of 3 or less, and shoulder dystocia. Groups were compared using χ², Fisher exact, two sample t-test, and Wilcoxon rank sum tests, as appropriate. Multivariable logistic regression models were used to adjust for potential confounders. RESULTS: Of the 3,703 low-risk multiparous women meeting inclusion criteria, 453 (12%) delivered between 39 0/7 and 39 4/7 after an elective induction of labor. Women who underwent elective induction of labor were more likely to be privately insured, non-Hispanic, and weigh more at their first prenatal visit (all P<.01) compared with expectant management. An elective induction of labor was associated with decreased frequency of the perinatal composite morbidity (4.0% vs 7.1%; adjusted odds ratio [aOR] 0.57, 95% CI 0.34–0.96) compared with expectant management. Fewer cesarean deliveries occurred among women in the elective induction of labor group (5.1% vs 6.6%; aOR 0.60, 95% CI 0.37–0.97). Other maternal outcomes (hypertensive disorders, chorioamnionitis, and operative vaginal deliveries) as well as neonatal intensive care unit admissions were not different between groups. CONCLUSION: Elective induction of labor in low-risk multiparous women in the 39th week of gestation was associated with decreased perinatal morbidity and a lower frequency of cesarean delivery compared with expectant management.

Hospitals experiencing financial pressures are seeking to gain efficiencies through innovation. One solution is to engage hospitalists to help reduce the average length of stay (ALOS). This study considers whether and to what extent hospitalists affect ALOS and whether an association exists between the number of hospitalists per occupied bed (density) and ALOS. We examined 2,858 hospitals nationwide, including 20,180 hospital-years of data from 2007 through 2015 derived from the American Hospital Association Annual Survey database. Key findings showed that hospitals using hospitalists reported a statistically significant shorter ALOS than hospitals without hospitalists. The results also indicated a statistically significant decrease in ALOS for an increase in hospitalist full-time equivalent per occupied bed. This study is important because of the generalizability of its results and suggests that hospitals may form partnerships with hospitalists to improve hospital efficiency.