Residential particulate matter, proximity to major roads, traffic density and traffic volume as risk factors for preterm birth in California.

BACKGROUND: While pollution from vehicle sources is an established risk factor for preterm birth, it is unclear whether distance of residence to the nearest major road or related measures like major road density represent useful measures for characterising risk. OBJECTIVE: To determine whether major road proximity measures (including distance to major road, major road density and traffic volume) are more useful risk factors for preterm birth than other established vehicle-related measures (including particulate matter <2.5 µm in diameter (PM2.5 ) and diesel particulate matter (diesel PM)). METHODS: This retrospective cohort study included 2.7 million births across the state of California from 2011-2017; each address at delivery was geocoded. Geocoding was used to calculate distance to the nearest major road, major road density within a 500 m radius and major road density weighted by truck volume. We measured associations with preterm birth using risk ratios adjusted for target demographic, clinical, socioeconomic and environmental covariates (aRRs). We compared these to the associations between preterm birth and PM2.5 and diesel PM by census tract of residence. RESULTS: Findings showed that whereas higher mean levels of PM2.5 and diesel PM by census tract were associated with a higher risk of preterm birth, living closer to roads or living in higher traffic density areas was not associated with higher risk. Residence in a census tract with a mean PM2.5 in the top quartile compared with the lowest quartile was associated with the highest observed risk of preterm birth (aRR 1.04, 95% CI 1.04, 1.05). CONCLUSIONS: Over a large geographical region with a diverse population, PM2.5 and diesel PM were associated with preterm birth, while measures of distance to major road were not, suggesting that these distance measures do not serve as a proxy for measures of particulate matter in the context of preterm birth.

Mortality and Major Neonatal Morbidity in Preterm Infants with Serious Congenital Heart Disease.

OBJECTIVE: To investigate the trends of 1-year mortality and neonatal morbidities in preterm infants with serious congenital heart disease (CHD). STUDY DESIGN: This cohort study used a population-based administrative dataset of all liveborn infants of 26-36 weeks gestational age with serious CHD born in California between 2011 and 2017. We assessed 1-year mortality and major neonatal morbidities (ie, retinopathy of prematurity, bronchopulmonary dysplasia, necrotizing enterocolitis, intraventricular hemorrhage grade >2, and periventricular leukomalacia) across the study period and compared these outcomes with those in infants without CHD. RESULTS: We identified 1921 preterm infants with serious CHD. The relative risk (RR) of death decreased by 10.6% for each year of the study period (RR, 0.89; 95% CI, 0.84-0.95), and the RR of major neonatal morbidity increased by 8.3% for each year (RR, 1.08; 95% CI, 1.02-1.15). Compared with preterm neonates without any CHD (n = 234 522), the adjusted risk difference (ARD) for mortality was highest at 32 weeks of gestational age (9.7%; 95% CI, 8.3%-11.2%), that for major neonatal morbidity was highest at 28 weeks (21.9%; 95% CI, 17.0%-26.9%), and that for the combined outcome was highest at 30 weeks (26.7%; 95% CI, 23.3%-30.1%). CONCLUSIONS: Mortality in preterm neonates with serious CHD decreased over the last decade, whereas major neonatal morbidities increased. Preterm infants with a gestational age of 28-32 weeks have the highest mortality or morbidity compared with their peers without CHD. These results support the need for specialized and focused medical neonatal care in preterm neonates with serious CHD.

Cohort study of respiratory hospital admissions, air quality and sociodemographic factors in preterm infants born in California.

BACKGROUND: Preterm infants suffer from respiratory morbidity especially during the first year of life. OBJECTIVE: To investigate the association of air quality and sociodemographic indicators on hospital admission rates for respiratory causes. METHODS: This is a retrospective cohort study. We identified all live-born preterm infants in California from 2007 to 2012 in a population-based administrative data set and linked them to a data set measuring several air quality and sociodemographic indicators at the census tract level. All sociodemographic and air quality predictors were divided into quartiles (first quartile most favourable to the fourth quartile least favourable). Mixed effect logistic models to account for clustering at the census tract level were used to investigate associations between chronic air quality and sociodemographic indicators respiratory hospital admission during the first year of life. RESULTS: Of 205 178 preterm infants, 5.9% (n = 12 033) were admitted to the hospital for respiratory causes during the first year. In the univariate analysis, comparing the first to the fourth quartile of chronic ozone (risk ratio [RR] 1.29, 95% confidence interval [CI] 1.21, 1.37), diesel (RR 1.10, 95% CI 1.02, 1.17) and particulate matter 2.5 (RR 1.07, 95% CI 1.01, 1.14) exposure were associated with hospital admission during the first year. Following adjustment for confounders, the risk ratios for hospital admission during the first year were 1.53 (95% CI 1.37, 1.72) in relation to educational attainment (per cent of the population over age 25 with less than a high school education) and 1.23 (95% CI 1.09, 1.38) for poverty (per cent of the population living below two times the federal poverty level). CONCLUSIONS: Among preterm infants, respiratory hospital admissions in the first year in California are associated with socioeconomic characteristics of the neighbourhood an individual is living in.

Applying Logic to the Healthcare Journey.

Cross-disciplinary approaches to remediate complex healthcare service delivery issues may have merit. This study aims to establish the potential benefits of applying service design and evaluative research concepts in healthcare. Specifically, this study aims to demonstrate how a Customer Journey Map and a Logic Model could be used in unison to identify and remedy service delivery gaps to reduce barriers to care. This study provides systems thinking approach to solving operational issues in healthcare.

Developing a resiliency model for survival without major morbidity in preterm infants.

OBJECTIVE: Develop and validate a resiliency score to predict survival and survival without neonatal morbidity in preterm neonates <32 weeks of gestation using machine learning. STUDY DESIGN: Models using maternal, perinatal, and neonatal variables were developed using LASSO method in a population based Californian administrative dataset. Outcomes were survival and survival without severe neonatal morbidity. Discrimination was assessed in the derivation and an external dataset from a tertiary care center. RESULTS: Discrimination in the internal validation dataset was excellent with a c-statistic of 0.895 (95% CI 0.882-0.908) for survival and 0.867 (95% CI 0.857-0.877) for survival without severe neonatal morbidity, respectively. Discrimination remained high in the external validation dataset (c-statistic 0.817, CI 0.741-0.893 and 0.804, CI 0.770-0.837, respectively). CONCLUSION: Our successfully predicts survival and survival without major morbidity in preterm babies born at <32 weeks. This score can be used to adjust for multiple variables across administrative datasets.

Prevalence of cannabis use disorder among individuals using medical cannabis at admission to inpatient treatment for substance use disorders.

INTRODUCTION: Cannabis is used for medical and recreational purposes and may result in cannabis use disorder (CUD). This study explored the prevalence of cannabis use disorder and other psychiatric comorbidities among inpatients undergoing treatment for substance use disorder who reported medical cannabis use at admission. METHODS: We assessed CUD and other substance use disorders based on DSM-5 symptoms, anxiety with the Generalized Anxiety Disorder scale (GAD-7), depression with the Patient Health Questionnaire (PHQ-9), and post-traumatic stress disorder with the PTSD Checklist for DSM-5 (PCL-5). We compared the prevalence of CUD and other psychiatric comorbidities between inpatients who endorsed the use of cannabis for medical purposes only vs those endorsing use for medical and recreational purposes. RESULTS: Among 125 inpatients, 42% reported medical use only, and 58% reported medical and recreational use (dual motives). For CUD, 28% of Medical-Only and 51% of Dual-Use motives patients met the diagnostic criteria for CUD (p = 0.016). High psychiatric comorbidities were present: 79% and 81% screened positive for an anxiety disorder, 60% and 61% screened positive for depression, and 66% and 57% screened positive for PTSD for the Medical-Only and Dual-Use inpatients, respectively. CONCLUSIONS: Many treatment-seeking individuals with substance use disorder who report medical cannabis use meet criteria for CUD, particularly those reporting concurrent recreational use.

Associations with spontaneous and indicated preterm birth in a densely phenotyped EHR cohort.

Background: Preterm birth (PTB) is the leading cause of infant mortality and follows multiple biological pathways, many of which are poorly understood. Some PTBs result from medically indicated labor following complications from hypertension and/or diabetes, while many others are spontaneous with unknown causes. Previously, investigation of potential risk factors has been limited by lack of data on maternal medical history and the difficulty of classifying PTBs as indicated or spontaneous. Here, we leverage electronic health record (EHR) data (patient health information including demographics, diagnoses, and medications) and a supplemental curated pregnancy database to overcome these limitations. Novel associations may provide new insight into the pathophysiology of PTB as well as help identify individuals who would be at risk of PTB. Methods: We quantified associations between maternal diagnoses and preterm birth using logistic regression controlling for maternal age and socioeconomic factors within a University of California, San Francisco (UCSF), EHR cohort with 10,643 births ( nterm = 9692, nspontaneous_preterm = 449, nindicated_preterm = 418) and maternal pre-conception diagnosis phenotypes derived from International Classification of Diseases (ICD) 9 and 10 codes. Results: Eighteen conditions significantly and robustly (False Discovery Rate (FDR)<0.05) associated with PTBs compared to term. We discovered known (hypertension, diabetes, and chronic kidney disease) and less established (blood, cardiac, gynecological, and liver conditions) associations. Type 1 diabetes was the most significant overall association (adjusted p = 1.6×10 -14 , adjusted OR = 7 (95% CI 5, 12)), and the odds ratios for the significant phenotypes ranged from 3 to 13. We further carried out analysis stratified by spontaneous vs. indicated PTB. No phenotypes significantly associated with spontaneous PTB; however, the results for indicated PTB largely recapitulated the phenotype associations with all PTBs. Conclusions: Our study underscores the limitations of approaches that combine indicated and spontaneous births together. When combined, significant associations were almost entirely driven by indicated PTBs, although our spontaneous and indicated groups were of a similar size. Investigating the spontaneous population has the potential to reveal new pathways and understanding of the heterogeneity of PTB.

Leveraging electronic health records to identify risk factors for recurrent pregnancy loss across two medical centers: a case-control study.

Recurrent pregnancy loss (RPL), defined as 2 or more pregnancy losses, affects 5-6% of ever-pregnant individuals. Approximately half of these cases have no identifiable explanation. To generate hypotheses about RPL etiologies, we implemented a case-control study comparing the history of over 1,600 diagnoses between RPL and live-birth patients, leveraging the University of California San Francisco (UCSF) and Stanford University electronic health record databases. In total, our study included 8,496 RPL (UCSF: 3,840, Stanford: 4,656) and 53,278 Control (UCSF: 17,259, Stanford: 36,019) patients. Menstrual abnormalities and infertility-associated diagnoses were significantly positively associated with RPL in both medical centers. Age-stratified analysis revealed that the majority of RPL-associated diagnoses had higher odds ratios for patients <35 compared with 35+ patients. While Stanford results were sensitive to control for healthcare utilization, UCSF results were stable across analyses with and without utilization. Intersecting significant results between medical centers was an effective filter to identify associations that are robust across center-specific utilization patterns.

Estimating stillbirth and neonatal mortality rate among Rohingya refugees in Bangladesh, September 2017 to December 2018: a prospective surveillance.

INTRODUCTION: There is limited literature on neonatal mortality in humanitarian emergencies. We estimated neonatal mortality and stillbirth rates; determined whether an association exists between proximity to a secondary health facility and neonatal mortality or stillbirth; and tested the correlation between the number of health facilities in a camp and neonatal mortality or stillbirth rates in Rohingya refugee camps in Bangladesh. METHODS: We conducted a prospective community-based mortality surveillance in 29 out of 34 Rohingya refugee camps between September 2017 and December 2018, covering approximately 811 543 Rohingya refugees with 19 477 estimated live births. We linked mortality surveillance data with publicly available information on camp population, number of functional health facilities and camp and health facility geospatial coordinates. Using descriptive statistics and spatial analyses, we estimated the mortality rate and tested for correlations. RESULTS: Overall, the estimated neonatal mortality rate was 27.0 (95% CI: 22.3 to 31.8) per 1000 live births, and the stillbirth rate was 15.2 (95% CI: 10.8 to 19.6) per 1000 total births. The majority of neonatal deaths (76.3%, n=405/531) and stillbirths (72.1%, n=202/280) occurred at home or in the community. A positive correlation existed between the camp population size and number of health facilities inside the camp (Spearman's rho=0.56, p value<0.01). No statistically significant correlation existed between the camp neonatal mortality rate or stillbirth rate and number of health facilities inside the camp. Camps that were located closer to a secondary health facility as compared with a labour room/sexual and reproductive health unit had a lower neonatal mortality rate (p value<0.01). CONCLUSIONS: The results provide insight into the neonatal mortality and stillbirth rates in Rohingya refugees camps in Bangladesh during 2017-2018. Prospective community-based mortality surveillance may be a feasible method to evaluate the effectiveness of humanitarian responses in improving neonatal survival and preventing stillbirths.

Barriers and Facilitators to the Implementation of an Integrated Youth Services Network in Ontario.

Introduction: In response to the challenges of the traditional mental health system for youth both in Canada and abroad, models of integrated youth services (IYS) that span the integration of mental health, health, substance use, eucation, employment, peer support, and navigation into 'one-stop shops' are being established nationally and internationally. IYS models, however, need to be better described and evaluated to inform the replicability of this approach in other jurisdictions. Description: This paper describes the implementation of an IYS in a small urban city and rural county in Ontario, Canada, including insights from key informants into barriers, facilitators, and lessons learned. Discussion: This evaluation identified a number of barriers and facilitators to the implementation of the IYS model in this specific context. Implementation facilitators included youth and family engagement, network partner collaboration, leadership, governance structure, community enthusiasm and support, and collaborative funding models. Barriers to implementation included the COVID-19 pandemic and related public health restrictions, the diverse needs of youth, change management, sustainable funding, and transportation. Lessons learned: By establishing a shared vision of delivering youth services across the integrated network, and engaging youth early in the process of model development, IYS have the potential to transform the service system for youth and their families. Meeting the diverse needs and challenges of youth who live in rural or small urban communities will enhance service delivery and experience for young people.

The association of COVID-19 infection in pregnancy with preterm birth: A retrospective cohort study in California.

INTRODUCTION: Our understanding of the association between coronavirus disease 19 (COVID-19) and preterm or early term birth among racially and ethnically diverse populations and people with chronic medical conditions is limited. METHODS: We determined the association between COVID-19 and preterm (PTB) birth among live births documented by California Vital Statistics birth certificates between July 2020 and January 2021 (n=240,147). We used best obstetric estimate of gestational age to classify births as very preterm (VPTB, <32 weeks), PTB (< 37 weeks), early term (37 and 38 weeks), and term (39-44 weeks), as each confer independent risks to infant health and development. Separately, we calculated the joint effects of COVID-19 diagnosis, hypertension, diabetes, and obesity on PTB and VPTB. FINDINGS: COVID-19 diagnoses on birth certificates increased for all racial/ethnic groups between July 2020 and January 2021 and were highest for American Indian/Alaska Native (12.9%), Native Hawaiian/Pacific Islander (11.4%), and Latinx (10.3%) birthing people. COVID-19 diagnosis was associated with an increased risk of VPTB (aRR 1.6, 95% CI [1.4, 1.9]), PTB (aRR 1.4, 95% CI [1.3, 1.4]), and early term birth (aRR 1.1, 95% CI [1.1, 1.2]). There was no effect modification of the overall association by race/ethnicity or insurance status. COVID-19 diagnosis was associated with elevated risk of PTB in people with hypertension, diabetes, and/or obesity. INTERPRETATION: In a large population-based study, COVID-19 diagnosis increased the risk of VPTB, PTB, and early term birth, particularly among people with medical comorbidities. Considering increased circulation of COVID-19 variants, preventative measures, including vaccination, should be prioritized for birthing persons. FUNDING: UCSF-Kaiser Department of Research Building Interdisciplinary Research Careers in Women's Health Program (BIRCWH) National Institute of Child Health and Human Development (NICHD) and the Office of Research on Women's Health (ORWH) [K12 HD052163] and the California Preterm Birth Initiative, funded by Marc and Lynn Benioff.

Predictors of premature treatment termination in a large residential addiction medicine program.

BACKGROUND: While inpatient programs are a common setting for addiction treatment, patients' premature termination is a major concern. Predicting premature treatment termination has the potential to substantially improve patient outcomes by identifying high-risk profiles and suggesting care paths that might reduce dropout. The current study examined the predictors of premature termination from an inpatient addiction medicine service. METHODS: In 1082 patients admitted to a large inpatient addiction medicine service, we used intake assessments of severity of alcohol use disorder, illicit drug use disorder, post-traumatic stress disorder (PTSD), anxiety disorders, and major depressive disorder to predict planned termination (n = 922) or premature termination (n = 160). We used two complementary analytic approaches-traditional binary logistic regression and a data-driven latent profile analysis (LPA). RESULTS: Binary logistic regression revealed that alcohol use severity, illicit drug use severity, and PTSD severity significantly predicted termination status, although alcohol use severity notably exhibited an inverse relationship. The LPA revealed four distinct profiles, with one profile exhibiting a significantly higher rate of premature termination and another exhibiting a significantly lower rate of premature termination. The high-risk profile was characterized by high drug severity, high comorbid psychopathology (PTSD, depression, and anxiety symptoms), but low alcohol severity. The low-risk profile was characterized by high alcohol severity, but low drug use and low comorbid psychopathology. CONCLUSIONS: These results provide converging evidence that illicit drug severity and psychiatric severity, and particularly PTSD, were associated with premature termination. Moreover, the LPA revealed distinct latent subgroups of patients with meaningfully higher and lower risk of premature termination, suggesting that addiction services should develop strategies for identifying high-risk individuals or develop care paths for high-risk symptom clusters. Approaches that are trauma-informed or otherwise focus on the management of comorbid psychiatric conditions may be particularly appropriate for reducing premature termination.

Robust Sequence Determinants of α-Synuclein Toxicity in Yeast Implicate Membrane Binding.

Protein conformations are shaped by cellular environments, but how environmental changes alter the conformational landscapes of specific proteins in vivo remains largely uncharacterized, in part due to the challenge of probing protein structures in living cells. Here, we use deep mutational scanning to investigate how a toxic conformation of α-synuclein, a dynamic protein linked to Parkinson's disease, responds to perturbations of cellular proteostasis. In the context of a course for graduate students in the UCSF Integrative Program in Quantitative Biology, we screened a comprehensive library of α-synuclein missense mutants in yeast cells treated with a variety of small molecules that perturb cellular processes linked to α-synuclein biology and pathobiology. We found that the conformation of α-synuclein previously shown to drive yeast toxicity-an extended, membrane-bound helix-is largely unaffected by these chemical perturbations, underscoring the importance of this conformational state as a driver of cellular toxicity. On the other hand, the chemical perturbations have a significant effect on the ability of mutations to suppress α-synuclein toxicity. Moreover, we find that sequence determinants of α-synuclein toxicity are well described by a simple structural model of the membrane-bound helix. This model predicts that α-synuclein penetrates the membrane to constant depth across its length but that membrane affinity decreases toward the C terminus, which is consistent with orthogonal biophysical measurements. Finally, we discuss how parallelized chemical genetics experiments can provide a robust framework for inquiry-based graduate coursework.