Role of Hospital Connectedness in Brain Metastasis Outcomes.

Importance: Although patients with brain metastases receive interdisciplinary and multi-institutional care, the association between neuro-oncologic care networks and patient outcomes remains unknown. As patients often interact with multiple facilities, quantifying this association across a network of hospitals is critical to capture the complexity of the health care journey for patients with brain metastases. Objective: To evaluate how statewide health care network metrics are associated with inpatient mortality and hospital length of stay (LOS) for patients with brain metastases. Design, Setting, and Participants: This multicenter, statewide cohort study used data from the 2018 to 2019 Healthcare Cost and Utilization Project State Inpatient and Emergency Department Databases. Primary analyses were completed by August 2023. Participants included adults with a brain metastases receiving care in Massachusetts. Exposure: All inpatient and emergency department visits mapped for patients following the first diagnosis of brain metastasis. Main Outcomes and Measures: Inpatient mortality and hospital LOS were the main outcomes assessed. Hospital interdependence in brain metastases care was calculated using a connectedness score (weighted degree: weighted sum of ties to other care facilities). The association between hospital connectedness and clinical outcomes was analyzed using mixed-effects logistic and linear regression models, adjusting for hospital-level features. Results: In this cohort study, 4679 patients with brain metastases were identified with inpatient or ED encounters in Massachusetts (from 2018 to 2019). The median (IQR) age was 64 (57-73) years, and 2559 (55%) were female. There was interdependence in brain metastases care, with 993 patients (21%) visiting 2 or more unique hospitals. Highly connected hospitals were heterogeneous, with many being small and one-half lacking subspecialty neuro-oncologic care or teaching status. Increased hospital connectedness was significantly associated with improved inpatient mortality for patients with brain metastases, with the lowest connectedness quartile associated with more than double the risk of mortality compared with the highest quartile (odds ratio, 2.34; 95% CI, 1.33-4.11; P = .003). A stepwise increase in inpatient mortality risk was observed as hospital connectedness decreased, independently of hospital volume. Furthermore, intermediate hospital connectedness was associated with increased hospital LOS (coefficient, 1.08; 95% CI, 0.17-1.95; P = .006). Conclusions and Relevance: This study found that hospital-to-hospital interconnectedness was significantly associated with improved clinical outcomes for patients with brain metastases. The salience of network metrics highlights their potential role alongside other patient-level and hospital-level variables to evaluate and improve oncology care delivery.

Neighborhood Child Opportunity and Preterm Birth Rates by Race and Ethnicity.

Importance: In the US, infants born to non-Hispanic Black birthing parents are 50% more likely to be born preterm than those born to non-Hispanic White birthing parents, and individual-level factors do not fully account for this inequity. Neighborhood context, rooted in historic patterns of structural racism, may facilitate understanding patterns of inequity in preterm birth. Objective: To estimate the association between neighborhood opportunity level, measured by the Child Opportunity Index (COI), and preterm birth among infants in Massachusetts. Design, Setting, and Participants: In this cross-sectional, population-based study, Massachusetts birth certificates from 3 large metropolitan areas (Boston, Springfield, and Worcester) were linked to US Census tract-level data from the COI, and log binomial regression models and generalized estimating equations were fit to examine associations of different levels of opportunity with preterm birth. Singleton infants born in Massachusetts between February 1, 2011, and December 31, 2015, were included. Analyses were originally conducted in 2019 and updated in 2024. Exposure: Level of child opportunity (measured by the COI) at the US Census tract level. Race and ethnicity were ascertained from the birth certificate, as reported by the birthing parent. Main Outcomes and Measures: Live birth before 37 completed weeks' gestation. Results: The analytic dataset included 267 553 infants, of whom 18.9% were born to Hispanic, 10.1% to non-Hispanic Asian or Pacific Islander, 10.1% to non-Hispanic Black, and 61.0% to non-Hispanic White birthing parents. More than half of infants born to non-Hispanic Black and Hispanic birthing parents were born into very low opportunity neighborhoods, and in crude models, this was associated with greater prevalence of preterm birth relative to very high opportunity neighborhoods (prevalence ratio, 1.44; 95% CI, 1.37-1.52). After adjustment for covariates, infants born into very low opportunity neighborhoods still had a greater prevalence of preterm birth (prevalence ratio, 1.16; 95% CI, 1.10-1.23). Conclusions and Relevance: In this cross-sectional study of neighborhood opportunity and preterm birth, elevated risk associated with exposure to a very low opportunity neighborhood, coupled with the disproportionate exposure by race and ethnicity, points to a modifiable factor that may contribute to racial and ethnic inequities in preterm birth. Future research should investigate interventions that seek to address neighborhood opportunity.

HEALTH ASSESSMENT OF SPOTTED (CLEMMYS GUTTATA) AND PAINTED (CHRYSEMYS PICTA) TURTLES IN CAPE COD, MASSACHUSETTS, U.S.A, WITH DETECTION OF A NOVEL ADENOVIRUS.

Freshwater turtles face numerous anthropogenic threats worldwide. Health assessments are a key component of chelonian population assessment and monitoring but are under reported in many species. The purpose of this study was to characterize the health of spotted turtles (Clemmys guttata; n = 30) and painted turtles (Chrysemys picta; n = 24) at Camp Edwards, a military base in Cape Cod, Massachusetts, using physical examinations, hematology, plasma heavy metal analyses, and pathogen surveillance via PCR. Spotted turtles had a high prevalence of carapace (n = 27, 90%) and plastron (n = 14, 46.7%) lesions, and a previously undescribed adenovirus was detected in three animals (proposed as Clemmys adenovirus-1). Female painted turtles had lower plasma copper (p = 0.012) and higher strontium (p = 0.0003) than males, and appeared to be in a similar plane of health to previous reports. This initial health assessment effort provides useful baseline data for future comparison in these species. Conservation efforts on Camp Edwards should incorporate continued health surveillance of these populations to identify intervention opportunities and determine the conservation threats, if any, of the novel adenovirus.

A GPT-based EHR modeling system for unsupervised novel disease detection.

OBJECTIVE: To develop an Artificial Intelligence (AI)-based anomaly detection model as a complement of an "astute physician" in detecting novel disease cases in a hospital and preventing emerging outbreaks. METHODS: Data included hospitalized patients (n = 120,714) at a safety-net hospital in Massachusetts. A novel Generative Pre-trained Transformer (GPT)-based clinical anomaly detection system was designed and further trained using Empirical Risk Minimization (ERM), which can model a hospitalized patient's Electronic Health Records (EHR) and detect atypical patients. Methods and performance metrics, similar to the ones behind the recent Large Language Models (LLMs), were leveraged to capture the dynamic evolution of the patient's clinical variables and compute an Out-Of-Distribution (OOD) anomaly score. RESULTS: In a completely unsupervised setting, hospitalizations for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection could have been predicted by our GPT model at the beginning of the COVID-19 pandemic, with an Area Under the Receiver Operating Characteristic Curve (AUC) of 92.2 %, using 31 extracted clinical variables and a 3-day detection window. Our GPT achieves individual patient-level anomaly detection and mortality prediction AUC of 78.3 % and 94.7 %, outperforming traditional linear models by 6.6 % and 9 %, respectively. Different types of clinical trajectories of a SARS-CoV-2 infection are captured by our model to make interpretable detections, while a trend of over-pessimistic outcome prediction yields a more effective detection pathway. Furthermore, our comprehensive GPT model can potentially assist clinicians with forecasting patient clinical variables and developing personalized treatment plans. CONCLUSION: This study demonstrates that an emerging outbreak can be accurately detected within a hospital, by using a GPT to model patient EHR time sequences and labeling them as anomalous when actual outcomes are not supported by the model. Such a GPT is also a comprehensive model with the functionality of generating future patient clinical variables, which can potentially assist clinicians in developing personalized treatment plans.

Drug use practices and wound care experiences in the age of xylazine adulteration.

INTRODUCTION: Exposure to xylazine has been associated with wounds distinct from typical injection-related skin and soft tissue infections. We sought to understand drug use and wound care practices, and treatment experiences of people who use drugs (PWUD) in a high-prevalence area of xylazine adulteration. METHODS: In August 2023, we surveyed adult PWUD reporting at least one past-year drug use-related wound across three Massachusetts syringe service programs. Using a representative illustration, participants indicated if they had experienced a xylazine wound in the past 90 days. We compared demographic, drug use factors, wound care, and medical treatment experiences among those with and without xylazine wounds. We also conducted additional content analysis of open-ended responses. RESULTS: Of the 171 respondents, 87 % (n=148) had a xylazine wound in the past 90 days. There were no statistically significant demographic differences between those with and without xylazine wounds. Among those primarily injecting (n=155), subcutaneous injection was nearly ten times more likely among people with xylazine wounds. For those with xylazine wounds (n=148), many engaged in heterogeneous wound self-treatment practices, and when seeking medical care, 74 % experienced healthcare stigma and 58 % had inadequate pain and withdrawal management. CONCLUSION: People with self-identified xylazine wounds were more likely to engage in subcutaneous injection and faced several barriers seeking medical wound treatment. Programs serving people exposed to xylazine should work to support safer injection practices, including alternatives to injecting and improving access to high-quality, effective wound care. Further study is warranted to understand the causes, promoters, and prevention of xylazine-related wounds.

Pharmacy Naloxone Standing Order and Community Opioid Fatality Rates Over Time.

Importance: Despite the proliferation of pharmacy standing-order naloxone dispensing across many US states before the change to over-the-counter status, few policy analyses have evaluated the implementation of pharmacy naloxone standing orders in addressing opioid overdose fatality among communities. Objective: To determine whether the implementation of pharmacy standing-order naloxone was associated with lower opioid fatality rates compared with communities without pharmacies with standing-order naloxone. Design, Setting, and Participants: This retrospective multisite study was conducted with an interrupted time series analysis across 351 municipalities in Massachusetts over 24 quarters (from January 1, 2013, through December 31, 2018). Standing-order naloxone dispensing data were collected from 2 sources for all major chain pharmacies and many independent pharmacies, covering 70% of retail pharmacies in Massachusetts. Municipalities had various standing-order naloxone implementation inceptions during the study period. Data were analyzed from December 2021 to November 2023. Exposure: The main exposure was measured by the first quarter with standing-order naloxone dispensation as the actual implementation inception. Main Outcomes and Measures: The primary study outcome was municipal opioid fatality rate per 100 000 population obtained from the Massachusetts Registry of Vital Records and Statistics. Results: The median (IQR) population size across 351 municipalities was 10 314 (3635 to 21 781) people, with mean (SD) proportion of female individuals was 51.1% (2.8 percentage points). Pharmacies from 214 municipalities (60.9%) reported dispensing standing-order naloxone over the study period. At the baseline of the first quarter of 2013, municipalities that eventually had standing-order naloxone had greater quarterly opioid fatality rates compared with those that never implemented standing-order naloxone (3.51 vs 1.03 deaths per 100 000 population; P < .001). After adjusting for municipal-level sociodemographic and opioid prevention factors, there was significant slope decrease of opioid fatality rates (annualized rate ratio, 0.84; 95% CI, 0.78-0.91; P < .001) following standing-order naloxone dispensing, compared with the municipalities that did not implement standing-order naloxone. There were no significant level changes of opioid fatality rates in the adjusted models. Sensitivity analyses yielded similar and significant findings. Conclusions and Relevance: These findings suggest that community pharmacy dispensing of naloxone with standing orders was associated with a relative, gradual, and significant decrease in opioid fatality rates compared with communities that did not implement the standing-order naloxone program. These findings support the expansion of naloxone access, including over-the-counter naloxone as part of a multifaceted approach to address opioid overdose.

Preventing overdoses involving stimulants: the POINTS study protocol.

BACKGROUND: In recent years, overdoses involving illicit cocaine, methamphetamine, and other stimulants have increased in the U.S. The unintentional consumption of stimulants containing illicit fentanyl is a major risk factor for overdoses, particularly in Massachusetts and Rhode Island. Understanding the drug use patterns and strategies used by people who use stimulants (PWUS) to prevent overdose is necessary to identify risk and protective factors for stimulant and opioid-involved overdoses. Mixed-methods research with people who distribute drugs (PWDD) can also provide critical information into the mechanisms through which fentanyl may enter the stimulant supply, and the testing of drug samples can further triangulate PWUS and PWDD perspectives regarding the potency and adulteration of the drug supply. These epidemiological methods can inform collaborative intervention development efforts with community leaders to identify feasible, acceptable, and scalable strategies to prevent fatal and non-fatal overdoses in high-risk communities. METHODS: Our overall objective is to reduce stimulant and opioid-involved overdoses in regions disproportionately affected by the overdose epidemic. To meet this long-term objective, we employ a multi-pronged approach to identify risk and protective factors for unintentional stimulant and opioid-involved overdoses among PWUS and use these findings to develop a package of locally tailored intervention strategies that can be swiftly implemented to prevent overdoses. Specifically, this study aims to [1] Carry out mixed-methods research with incarcerated and non-incarcerated people who use or distribute illicit stimulants to identify risk and protective factors for stimulant and opioid-involved overdoses; [2] Conduct drug checking to examine the presence and relative quantity of fentanyl and other adulterants in the stimulant supply; and [3] Convene a series of working groups with community stakeholders involved in primary and secondary overdose prevention in Massachusetts and Rhode Island to contextualize our mixed-methods findings and identify multilevel intervention strategies to prevent stimulant-involved overdoses. DISCUSSION: Completion of this study will yield a rich understanding of the social epidemiology of stimulant and opioid-involved overdoses in addition to community-derived intervention strategies that can be readily implemented and scaled to prevent such overdoses in two states disproportionately impacted by the opioid and overdose crises: Massachusetts and Rhode Island.

A Dynamic Prognostic Model for Identifying Vulnerable COVID-19 Patients at High Risk of Rapid Deterioration.

PURPOSE: We aimed to validate and, if performance was unsatisfactory, update the previously published prognostic model to predict clinical deterioration in patients hospitalized for COVID-19, using data following vaccine availability. METHODS: Using electronic health records of patients ≥18 years, with laboratory-confirmed COVID-19, from a large care-delivery network in Massachusetts, USA, from March 2020 to November 2021, we tested the performance of the previously developed prediction model and updated the prediction model by incorporating data after availability of COVID-19 vaccines. We randomly divided data into development (70%) and validation (30%) cohorts. We built a model predicting worsening in a published severity scale in 24 h by LASSO regression and evaluated performance by c-statistic and Brier score. RESULTS: Our study cohort consisted of 8185 patients (Development: 5730 patients [mean age: 62; 44% female] and Validation: 2455 patients [mean age: 62; 45% female]). The previously published model had suboptimal performance using data after November 2020 (N = 4973, c-statistic = 0.60. Brier score = 0.11). After retraining with the new data, the updated model included 38 predictors including 18 changing biomarkers. Patients hospitalized after Jun 1st, 2021 (when COVID-19 vaccines became widely available in Massachusetts) were younger and had fewer comorbidities than those hospitalized before. The c-statistic and Brier score were 0.77 and 0.13 in the development cohort, and 0.73 and 0.14 in the validation cohort. CONCLUSION: The characteristics of patients hospitalized for COVID-19 differed substantially over time. We developed a new dynamic model for rapid progression with satisfactory performance in the validation set.

Sex, Atrial Fibrillation, and Long-Term Mortality After Cardiac Surgery.

Importance: There are limited data on the association of sex with the incidence of postoperative atrial fibrillation (poAF) and subsequent long-term mortality after cardiac surgery. Objective: To evaluate whether the incidence of poAF and associated long-term mortality after cardiac surgery differ by sex. Design, Setting, and Participants: This retrospective cohort study was conducted at 2 tertiary care centers in Massachusetts from January 1, 2002, until October 1, 2016, with follow-up until December 1, 2022. Adult (aged >20 years) women and men undergoing coronary artery bypass graft surgery, aortic valve surgery, mitral valve surgery, and combined procedures with cardiopulmonary bypass were examined using medical records. Patients who had data on poAF were included in data analyses. Exposures: Sex and poAF. Main Outcomes and Measures: Primary outcomes were the incidence of poAF and all-cause mortality. poAF was defined as any atrial fibrillation detected on electrocardiogram (EKG) during the index hospitalization in patients presenting for surgery in normal sinus rhythm. Data on poAF were obtained from EKG reports and supplemented by information from the Society of Thoracic Surgeons Adult Cardiac Surgery Database. All-cause mortality was assessed via hospital records. The hypotheses were formulated prior to data analysis. Results: Among 21 568 patients with poAF data (mean [SD] age, 66.5 [12.4] years), 2694 of 6601 women (40.8%) and 5805 of 14 967 men (38.8%) developed poAF. In a multivariable logistic regression model, women had lower risk of poAF (odds ratio [OR], 0.85; 95% CI, 0.79-0.91; P < .001). During the follow-up study period, 1294 women (50.4%) and 2376 men (48.9%) in the poAF group as well as 1273 women (49.6%) and 2484 men (51.1%) in the non-poAF group died. Cox proportional hazards analysis found that the association between poAF and mortality was significantly moderated (ie, effect modified) by sex. Compared with same-sex individuals without poAF, men with poAF had a 17% higher mortality hazard (hazard ratio [HR], 1.17; 95% CI, 1.11-1.25; P < .001), and women with poAF had a 31% higher mortality hazard (HR, 1.31; 95% CI, 1.21-1.42; P < .001). Conclusions and Relevance: In this retrospective cohort study of 21 568 patients who underwent cardiac surgery, women were less likely to develop poAF than men when controlling for other relevant characteristics; however, women who did develop poAF had a higher risk of long-term mortality than men who developed poAF. This observed elevated risk calls for a tailored approach to perioperative care in women undergoing cardiac surgery.

Case identification and healthcare utilization in the years prior to a first mania diagnosis.

BACKGROUND: There is limited evaluation of approaches to identify patients with new onset bipolar affective disorder (BPAD) when using administrative datasets. METHODS: Using the Massachusetts All-Payer Claims Database (APCD), we identified individuals with a 2016 diagnosis of bipolar disorder with mania and examined patterns of psychiatric and medical care over the preceding 48 months. RESULTS: Among 4806 individuals aged 15-35 years with a 2016 BPAD with mania diagnosis, 3066 had 48 months of historical APCD data, and of those, 75 % involved information from ≥2 payors. After excluding individuals with historical BPAD or mania diagnoses, there were 583 individuals whose 2016 BPAD with mania diagnosis appeared to be new (i.e., 34 new diagnoses per 100,000 individuals aged 15-35 years). Most individuals received medical care, e.g., 98 % had outpatient visits, 76 % had Emergency Department (ED) visits, and 50 % had mental health-related ED visits during the 48 months prior to their first mania diagnosis. One-third (37.2 %) had a depressive episode before their initial BPAD with mania diagnosis. LIMITATIONS: Study was conducted in one state among insured individuals. We used administrative data, which permits evaluation of large populations but lacks rigorous, well-validated claims-based definitions for BPAD. There could be diagnostic uncertainty during illness course, and clinicians may differ in their diagnostic thresholds. CONCLUSIONS: Careful examination of multiple years of patient history spanning all payors is essential for identifying new onset BPAD diagnoses presenting with mania, which in turn is critical to estimating population rates of new disease and understanding the early course of disease.

The association between intraoperative low driving pressure ventilation and perioperative healthcare-associated costs: A retrospective multicenter cohort study.

STUDY OBJECTIVE: A low dynamic driving pressure during mechanical ventilation for general anesthesia has been associated with a lower risk of postoperative respiratory complications (PRC), a key driver of healthcare costs. It is, however, unclear whether maintaining low driving pressure is clinically relevant to measure and contain costs. We hypothesized that a lower dynamic driving pressure is associated with lower costs. DESIGN: Multicenter retrospective cohort study. SETTING: Two academic healthcare networks in New York and Massachusetts, USA. PATIENTS: 46,715 adult surgical patients undergoing general anesthesia for non-ambulatory (inpatient and same-day admission) surgery between 2016 and 2021. INTERVENTIONS: The primary exposure was the median intraoperative dynamic driving pressure. MEASUREMENTS: The primary outcome was direct perioperative healthcare-associated costs, which were matched with data from the Healthcare Cost and Utilization Project-National Inpatient Sample (HCUP-NIS) to report absolute differences in total costs in United States Dollars (US$). We assessed effect modification by patients' baseline risk of PRC (score for prediction of postoperative respiratory complications [SPORC] ≥ 7) and effect mediation by rates of PRC (including post-extubation saturation < 90%, re-intubation or non-invasive ventilation within 7 days) and other major complications. MAIN RESULTS: The median intraoperative dynamic driving pressure was 17.2cmH2O (IQR 14.0-21.3cmH2O). In adjusted analyses, every 5cmH2O reduction in dynamic driving pressure was associated with a decrease of -0.7% in direct perioperative healthcare-associated costs (95%CI -1.3 to -0.1%; p = 0.020). When a dynamic driving pressure below 15cmH2O was maintained, -US$340 lower total perioperative healthcare-associated costs were observed (95%CI -US$546 to -US$132; p = 0.001). This association was limited to patients at high baseline risk of PRC (n = 4059; -US$1755;97.5%CI -US$2495 to -US$986; p < 0.001), where lower risks of PRC and other major complications mediated 10.7% and 7.2% of this association (p < 0.001 and p = 0.015, respectively). CONCLUSIONS: Intraoperative mechanical ventilation targeting low dynamic driving pressures could be a relevant measure to reduce perioperative healthcare-associated costs in high-risk patients.

Medication for Opioid Use Disorder After Serious Injection-Related Infections in Massachusetts.

Importance: Serious injection-related infections (SIRIs) cause significant morbidity and mortality. Medication for opioid use disorder (MOUD) improves outcomes but is underused. Understanding MOUD treatment after SIRIs could inform interventions to close this gap. Objectives: To examine rehospitalization, death rates, and MOUD receipt for individuals with SIRIs and to assess characteristics associated with MOUD receipt. Design, Setting, and Participants: This retrospective cohort study used the Massachusetts Public Health Data Warehouse, which included all individuals with a claim in the All-Payer Claims Database and is linked to individual-level data from multiple government agencies, to assess individuals aged 18 to 64 years with opioid use disorder and hospitalization for endocarditis, osteomyelitis, epidural abscess, septic arthritis, or bloodstream infection (ie, SIRI) between July 1, 2014, and December 31, 2019. Data analysis was performed from November 2021 to May 2023. Exposure: Demographic and clinical factors potentially associated with posthospitalization MOUD receipt. Main Outcomes and Measures: The main outcome was MOUD receipt measured weekly in the 12 months after hospitalization. We used zero-inflated negative binomial regression to examine characteristics associated with any MOUD receipt and rates of treatment in the 12 months after hospitalization. Secondary outcomes were receipt of any buprenorphine formulation, methadone, and extended-release naltrexone examined individually. Results: Among 8769 individuals (mean [SD] age, 43.2 [12.0] years; 5066 [57.8%] male) who survived a SIRI hospitalization, 4305 (49.1%) received MOUD, 5919 (67.5%) were rehospitalized, and 973 (11.1%) died within 12 months. Of those treated with MOUD in the 12 months after hospitalization, the mean (SD) number of MOUD initiations during follow-up was 3.0 (1.7), with 956 of 4305 individuals (22.2%) receiving treatment at least 80% of the time. MOUD treatment after SIRI hospitalization was significantly associated with MOUD in the prior 6 months (buprenorphine: adjusted odds ratio [AOR], 16.51; 95% CI, 13.81-19.74; methadone: AOR, 28.46; 95% CI, 22.41-36.14; or naltrexone: AOR, 2.05; 95% CI, 1.56-2.69). Prior buprenorphine (incident rate ratio [IRR], 1.17; 95% CI, 1.11-1.24) or methadone (IRR, 1.89; 95% CI, 1.79-2.01) use was associated with higher treatment rates after hospitalization, and prior naltrexone use (IRR, 0.86; 95% CI, 0.77-0.95) was associated with lower rates. Conclusions and Relevance: This study found that in the year after a SIRI hospitalization in Massachusetts, mortality and rehospitalization were common, and only half of patients received MOUD. Treatment with MOUD before a SIRI was associated with posthospitalization MOUD initiation and time receiving MOUD. Efforts are needed to initiate MOUD treatment during SIRI hospitalizations and subsequently retain patients in treatment.

Minding the margins: Evaluating the impact of COVID-19 among Latinx and Black communities with optimal qualitative serological assessment tools.

COVID-19 disproportionately affected minorities, while research barriers to engage underserved communities persist. Serological studies reveal infection and vaccination histories within these communities, however lack of consensus on downstream evaluation methods impede meta-analyses and dampen the broader public health impact. To reveal the impact of COVID-19 and vaccine uptake among diverse communities and to develop rigorous serological downstream evaluation methods, we engaged racial and ethnic minorities in Massachusetts in a cross-sectional study (April-July 2022), screened blood and saliva for SARS-CoV-2 and human endemic coronavirus (hCoV) antibodies by bead-based multiplex assay and point-of-care (POC) test and developed across-plate normalization and classification boundary methods for optimal qualitative serological assessments. Among 290 participants, 91.4% reported receiving at least one dose of a COVID-19 vaccine, while 41.7% reported past SARS-CoV-2 infections, which was confirmed by POC- and multiplex-based saliva and blood IgG seroprevalences. We found significant differences in antigen-specific IgA and IgG antibody outcomes and indication of cross-reactivity with hCoV OC43. Finally, 26.5% of participants reported lingering COVID-19 symptoms, mostly middle-aged Latinas. Hence, prolonged COVID-19 symptoms were common among our underserved population and require public health attention, despite high COVID-19 vaccine uptake. Saliva served as a less-invasive sample-type for IgG-based serosurveys and hCoV cross-reactivity needed to be evaluated for reliable SARS-CoV-2 serosurvey results. The use of the developed rigorous downstream qualitative serological assessment methods will help standardize serosurvey outcomes and meta-analyses for future serosurveys beyond SARS-CoV-2.

Insurance Instability for Patients With Opioid Use Disorder in the Year After Diagnosis.

Importance: Transitions in insurance coverage may be associated with worse health care outcomes. Little is known about insurance stability for individuals with opioid use disorder (OUD). Objective: To examine insurance transitions among adults with newly diagnosed OUD in the 12 months after diagnosis. Design, Setting, and Participants: Longitudinal cohort study using data from the Massachusetts Public Health Data Warehouse. The cohort includes adults aged 18 to 63 years diagnosed with incident OUD between July 1, 2014, and December 31, 2014, who were enrolled in commercial insurance or Medicaid at diagnosis; individuals diagnosed after 2014 were excluded from the main analyses due to changes in the reporting of insurance claims. Data were analyzed from November 10, 2022, to May 6, 2024. Exposure: Insurance type at time of diagnosis (commercial and Medicaid). Main Outcomes and Measures: The primary outcome was the cumulative incidence of insurance transitions in the 12 months after diagnosis. Logistic regression models were used to generate estimated probabilities of insurance transitions by insurance type and diagnosis for several characteristics including age, race and ethnicity, and whether an individual started medication for OUD (MOUD) within 30 days after diagnosis. Results: There were 20 768 individuals with newly diagnosed OUD between July 1, 2014, and December 31, 2014. Most individuals with newly diagnosed OUD were covered by Medicaid (75.4%). Those with newly diagnosed OUD were primarily male (67% in commercial insurance, 61.8% in Medicaid). In the 12 months following OUD diagnosis, 30.4% of individuals experienced an insurance transition, with adjusted models demonstrating higher transition rates among those starting with Medicaid (31.3%; 95% CI, 30.5%-32.0%) compared with commercial insurance (27.9%; 95% CI, 26.6%-29.1%). The probability of insurance transitions was generally higher for younger individuals than older individuals irrespective of insurance type, although there were notable differences by race and ethnicity. Conclusions and Relevance: This study found that nearly 1 in 3 individuals experience insurance transitions in the 12 months after OUD diagnosis. Insurance transitions may represent an important yet underrecognized factor in OUD treatment outcomes.

Using Parametric g-Computation for Time-to-Event Data and Distributed Lag Models to Identify Critical Exposure Windows for Preterm Birth: An Illustrative Example Using PM2.5 in a Retrospective Birth Cohort Based in Eastern Massachusetts (2011-2016).

BACKGROUND: Parametric g-computation is an attractive analytic framework to study the health effects of air pollution. Yet, the ability to explore biologically relevant exposure windows within this framework is underdeveloped. OBJECTIVES: We outline a novel framework for how to incorporate complex lag-responses using distributed lag models (DLMs) into parametric g-computation analyses for survival data. We call this approach "g-survival-DLM" and illustrate its use examining the association between PM2.5 during pregnancy and the risk of preterm birth (PTB). METHODS: We applied the g-survival-DLM approach to estimate the hypothetical static intervention of reducing average PM2.5 in each gestational week by 20% on the risk of PTB among 9,403 deliveries from Beth Israel Deaconess Medical Center, Boston, Massachusetts, 2011-2016. Daily PM2.5 was taken from a 1-km grid model and assigned to address at birth. Models were adjusted for sociodemographics, time trends, nitrogen dioxide, and temperature. To facilitate implementation, we provide a detailed description of the procedure and accompanying R syntax. RESULTS: There were 762 (8.1%) PTBs in this cohort. The gestational week-specific median PM2.5 concentration was relatively stable across pregnancy at ∼7µg/m3. We found that our hypothetical intervention strategy changed the cumulative risk of PTB at week 36 (i.e., the end of the preterm period) by -0.009 (95% confidence interval: -0.034, 0.007) in comparison with the scenario had we not intervened, which translates to about 86 fewer PTBs in this cohort. We also observed that the critical exposure window appeared to be weeks 5-20. DISCUSSION: We demonstrate that our g-survival-DLM approach produces easier-to-interpret, policy-relevant estimates (due to the g-computation); prevents immortal time bias (due to treating PTB as a time-to-event outcome); and allows for the exploration of critical exposure windows (due to the DLMs). In our illustrative example, we found that reducing fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5)] during gestational weeks 5-20 could potentially lower the risk of PTB. https://doi.org/10.1289/EHP13891.

PREVALENCE OF THE BOPYRID ISOPOD PROBOPYRUS PANDALICOLA IN DAGGERBLADE GRASS SHRIMP FROM SALT MARSH CREEKS AND PANNES OF CAPE COD, MASSACHUSETTS.

In salt marsh ecosystems, daggerblade grass shrimp, Palaemon (Palaemonetes) pugio, play a crucial role in food webs and serve as the definitive host for the bopyrid isopod Probopyrus pandalicola. These ectoparasites infest the branchial chambers of grass shrimp, which can lead to decreased energy availability and sterilization of infected hosts. Although bopyrid isopod infestation of daggerblade grass shrimp has been frequently reported in literature from coastal marshes of the southeastern United States, the prevalence of this parasite has not been recently documented in daggerblade grass shrimp from marshes of the northeastern United States. The goal of this project was to quantify the prevalence of Pr. pandalicola infestations in Pa. pugio across Cape Cod, Massachusetts. We evaluated bopyrid isopod prevalence from shrimp collected from 5 different salt marsh habitats along Cape Cod in August 2021. Bopyrid isopod infestations were found in shrimp at 4 of 5 salt marshes, with prevalence ranging from 0.04 to 14.1%. Seasonal resampling of one of the salt marshes revealed the highest average infestation prevalence in spring (<17.1%) and an isolated high of 30.3% prevalence in a single salt panne. A series of linear and multivariate models showed that panne area, shrimp abundance, and distance to shoreline were related to Pr. pandalicola shrimp infestations in salt pannes in summer. This study describes the prevalence of the bopyrid isopod infesting daggerblade grass shrimp in salt marshes in New England, with implications for how parasitized shrimp influence salt marsh food webs in which they are found.

Comparing the effect of two systems-level interventions on perinatal generalized anxiety disorder and posttraumatic stress disorder symptoms.

BACKGROUND: The Massachusetts Child Psychiatry Access Program for Moms and PRogram In Support of Moms are designed to help obstetric practices address perinatal depression. The PRogram in Support of Moms includes the statewide Massachusetts Child Psychiatry Access Program for Moms program, plus proactive implementation support. OBJECTIVE: The goal of this study was to understand the impact of these programs on perinatal generalized anxiety disorder and posttraumatic stress disorder symptoms among individuals screening positive for depression. STUDY DESIGN: We conducted a secondary analysis of 2017-2022 data from a cluster randomized controlled trial of Massachusetts Child Psychiatry Access Program for Moms vs PRogram In Support of Moms. We included participants completing a generalized anxiety disorder or posttraumatic stress disorder screen at baseline (n=254) with antenatal Edinburgh Postnatal Depression Scale scores ≥10. We assessed changes in generalized anxiety disorder and posttraumatic stress disorder symptoms from pregnancy (4-25 weeks of gestational age or 32-40 weeks of gestational age), 4-12 weeks postpartum, and 11-13 months postpartum. We conducted a difference-in-difference analysis to compare symptom change from pregnancy to postpartum. We used adjusted linear mixed models with repeated measures to examine the impact of the Massachusetts Child Psychiatry Access Program for Moms and PRogram In Support of Moms on changes in the Generalized Anxiety Disorder 7 and the Posttraumatic Stress Disorder Checklist. RESULTS: Mean Generalized Anxiety Disorder 7 scores decreased by 3.6 (Massachusetts Child Psychiatry Access Program for Moms) and 6.3 (PRogram In Support of Moms) points from pregnancy to 4-12 weeks postpartum. Mean Posttraumatic Stress Disorder Checklist scores decreased by 6.2 and 10.0 points, respectively, at 4-12 weeks postpartum among individuals scree ning positive on the Generalized Anxiety Disorder 7 (n=83) or Posttraumatic Stress Disorder Checklist (n=58) in pregnancy. Generalized Anxiety Disorder 7 and Posttraumatic Stress Disorder Checklist scores decreased among both groups at 11-13 months postpartum. These changes were clinically meaningful. PRogram In Support of Moms conferred a statistically significant greater decrease (2.7 points) on the Generalized Anxiety Disorder 7 than the Massachusetts Child Psychiatry Access Program for Moms at 4-12 weeks postpartum. No differences were found between the Massachusetts Child Psychiatry Access Program for Moms and PRogram In Support of Moms in Posttraumatic Stress Disorder Checklist or Generalized Anxiety Disorder 7 change at 11-13 months, although both were associated with a reduction in generalized anxiety disorder and posttraumatic stress disorder symptoms at 4-12 weeks and 11-13 months postpartum. CONCLUSION: Both the Massachusetts Child Psychiatry Access Program for Moms and PRogram In Support of Moms could help to improve symptoms for individuals experiencing co-occurring symptoms of depression, generalized anxiety disorder, or posttraumatic stress disorder. PRogram In Support of Moms may confer additional benefits in the early postpartum period, although this difference was not clinically significant.

Receipt of medications for opioid use disorder before and after incarceration in Massachusetts State prisons, 2014-2019.

BACKGROUND: Little is known about how use patterns of medications for opioid use disorder (MOUDs) evolve from pre-incarceration to post-incarceration among incarcerated individuals with opioid use disorder. This article describes pre- and post-incarceration MOUD receipt during a period when naltrexone was the only type of MOUD offered in a state prison system, the Massachusetts Department of Correction (MADOC). METHODS: A retrospective cohort study of individuals with opioid use disorder who had an incarceration episode in MADOC during January 2015 to March 2019. The data source was the Massachusetts Public Health Data Warehouse, a multi-sector data platform that links individual-level data from multiple statewide datasets. We described patterns of MOUD receipt during the four weeks prior to and after an incarceration episode. Multivariable logistic regression models characterized predictors of post-incarceration MOUD receipt. RESULTS: In the male sample (n=691 incarcerations), from the pre- to post-incarceration periods, receipt of buprenorphine increased (14.3 % to 18.3 %), naltrexone increased (5.0 % to 10.5 %), and methadone decreased (4.7 % to 1.7 %). Similarly, in the female sample (n=892 incarcerations), from the pre- to post-incarceration periods, receipt of buprenorphine increased (10.3 % to 12.3 %, naltrexone increased (4.5 % to 9.3 %), and methadone decreased (5.0 % to 2.9 %). Much of the post-release naltrexone receipt occurred among participants in MADOC's pre-release naltrexone program. CONCLUSIONS: MOUD receipt was low but increased slightly in the post-incarceration period. This change was driven by increases in buprenorphine and naltrexone and despite decreases in methadone.

Morbidity and Mortality of Hospital-Onset SARS-CoV-2 Infections Due to Omicron Versus Prior Variants : A Propensity-Matched Analysis.

BACKGROUND: Many hospitals have scaled back measures to prevent nosocomial SARS-CoV-2 infection given large decreases in the morbidity and mortality of SARS-CoV-2 infections for most people. Little is known, however, about the morbidity and mortality of nosocomial SARS-CoV-2 infections for hospitalized patients in the Omicron era. OBJECTIVE: To estimate the effect of nosocomial SARS-CoV-2 infection on hospitalized patients' outcomes during the pre-Omicron and Omicron periods. DESIGN: Retrospective matched cohort study. SETTING: 5 acute care hospitals in Massachusetts, December 2020 to April 2023. PATIENTS: Adults testing positive for SARS-CoV-2 on or after hospital day 5, after negative SARS-CoV-2 test results on admission and on hospital day 3, were matched to control participants by hospital, service, time period, days since admission, and propensity scores that incorporated demographics, comorbid conditions, vaccination status, primary diagnosis category, vital signs, and laboratory test values. MEASUREMENTS: Primary outcomes were hospital mortality and time to discharge. Secondary outcomes were intensive care unit (ICU) admission, need for advanced oxygen support, discharge destination, hospital-free days, and 30-day readmissions. RESULTS: There were 274 cases of hospital-onset SARS-CoV-2 infection during the pre-Omicron period and 1037 cases during the Omicron period (0.17 vs. 0.49 cases per 100 admissions). Patients with hospital-onset SARS-CoV-2 infection were older and had more comorbid conditions than those without. During the pre-Omicron period, hospital-onset SARS-CoV-2 infection was associated with increased risk for ICU admission, increased need for high-flow oxygen, longer time to discharge (median difference, 4.7 days [95% CI, 2.9 to 6.6 days]), and higher mortality (risk ratio, 2.0 [CI, 1.1 to 3.8]) versus matched control participants. During the Omicron period, hospital-onset SARS-CoV-2 infection remained associated with increased risk for ICU admission and increased time to discharge (median difference, 4.2 days [CI, 3.6 to 5.0 days]). The association with increased hospital mortality was attenuated but still significant (risk ratio, 1.6 [CI, 1.2 to 2.3]). LIMITATION: Residual confounding may be present. CONCLUSION: Hospital-onset SARS-CoV-2 infection during the Omicron period remains associated with increased morbidity and mortality. PRIMARY FUNDING SOURCE: Harvard Medical School Department of Population Medicine.

Risk factors for persistent fatal opioid-involved overdose clusters in Massachusetts 2011-2021: a spatial statistical analysis with socio-economic, accessibility, and prescription factors.

BACKGROUND: Fatal opioid-involved overdose rates increased precipitously from 5.0 per 100,000 population to 33.5 in Massachusetts between 1999 and 2022. METHODS: We used spatial rate smoothing techniques to identify persistent opioid overdose-involved fatality clusters at the ZIP Code Tabulation Area (ZCTA) level. Rate smoothing techniques were employed to identify locations of high fatal opioid overdose rates where population counts were low. In Massachusetts, this included areas with both sparse data and low population density. We used Local Indicators of Spatial Association (LISA) cluster analyses with the raw incidence rates, and the Empirical Bayes smoothed rates to identify clusters from 2011 to 2021. We also estimated Empirical Bayes LISA cluster estimates to identify clusters during the same period. We constructed measures of the socio-built environment and potentially inappropriate prescribing using principal components analysis. The resulting measures were used as covariates in Conditional Autoregressive Bayesian models that acknowledge spatial autocorrelation to predict both, if a ZCTA was part of an opioid-involved cluster for fatal overdose rates, as well as the number of times that it was part of a cluster of high incidence rates. RESULTS: LISA clusters for smoothed data were able to identify whether a ZCTA was part of a opioid involved fatality incidence cluster earlier in the study period, when compared to LISA clusters based on raw rates. PCA helped in identifying unique socio-environmental factors, such as minoritized populations and poverty, potentially inappropriate prescribing, access to amenities, and rurality by combining socioeconomic, built environment and prescription variables that were highly correlated with each other. In all models except for those that used raw rates to estimate whether a ZCTA was part of a high fatality cluster, opioid overdose fatality clusters in Massachusetts had high percentages of Black and Hispanic residents, and households experiencing poverty. The models that were fitted on Empirical Bayes LISA identified this phenomenon earlier in the study period than the raw rate LISA. However, all the models identified minoritized populations and poverty as significant factors in predicting the persistence of a ZCTA being part of a high opioid overdose cluster during this time period. CONCLUSION: Conducting spatially robust analyses may help inform policies to identify community-level risks for opioid-involved overdose deaths sooner than depending on raw incidence rates alone. The results can help inform policy makers and planners about locations of persistent risk.