The relationship between neighborhood economic deprivation and community-acquired pneumonia related admissions in Maryland.

Introduction: Community-acquired pneumonia (CAP) is a major health concern in the United States (US), with its incidence, severity, and outcomes influenced by social determinants of health, including socioeconomic status. The impact of neighborhood socioeconomic status, as measured by the Distressed Communities Index (DCI), on CAP-related admissions remains understudied in the literature. Objective: To determine the independent association between DCI and CAP-related admissions in Maryland. Methods: We conducted a retrospective study using the Maryland State Inpatient Database (SID) to collate data on CAP-related admissions from January 2018 to December 2020. The study included adults aged 18-85 years. We explored the independent association between community-level economic deprivation based on DCI quintiles and CAP-related admissions, adjusting for significant covariates. Results: In the study period, 61,467 cases of CAP-related admissions were identified. The patients were predominantly White (49.7%) and female (52.4%), with 48.6% being over 65 years old. A substantive association was found between the DCI and CAP-related admissions. Compared to prosperous neighborhoods, patients living in economically deprived communities had 43% increased odds of CAP-related admissions. Conclusion: Residents of the poorest neighborhoods in Maryland have the highest risk of CAP-related admissions, emphasizing the need to develop effective public health strategies beneficial to the at-risk patient population.

Patient perspectives on cancer care during COVID-19: A qualitative study.

PURPOSE: The COVID-19 pandemic posed unique challenges to cancer-related care as health systems balanced competing risks of timely delivery of care and minimizing exposure to infection in a high-risk, immunocompromised patient population. This study aimed to better understand how pandemic-related factors affected the patient experience of cancer care during this time. METHODS: We conducted fifteen semi-structured interviews with adults from rural counties in Maryland who were diagnosed with and/or actively treated for cancer at the TidalHealth healthcare network between January 2020 and October 2022. RESULTS: Interviews from fifteen participants were analyzed. Two major themes emerged including COVID Impact on Care, and COVID Impact on Mental Health. Subthemes under COVID Impact on Care include Staffing Shortages, Hospital Regulations, Visitation, Importance of Advocacy, and Telehealth Utilization, and subthemes under COVID Impact on Mental Health include Loneliness, Support Networks, and Perceptions of COVID and Personal Protection. Overall, participants described positive care experiences despite notable delays, disruptions to continuity of care, difficult transitions to telemedicine, visitation policies that limited patient support, increased mental health struggles related to social distancing measures, and greater desire for patient advocacy. CONCLUSION: Our findings reveal significant impacts of the COVID-19 pandemic on experiences of cancer treatment and survivorship in a more vulnerable, rural patient population with lower healthcare access and income level. Our findings suggest areas for targeted interventions to limit disruptions to quality care in future public health emergencies.

Quantification of referrals received at two emergency-capable hyperbaric medicine centers.

Emergency hyperbaric oxygen treatment capability is limited in the United States, and there is little documentation of calls received by centers available 24 hours a day, seven days a week, 365 days a year. Our study aimed to calculate the number of calls received for urgent hyperbaric oxygen (HBO2). We logged calls from two HBO2 chambers on the East Coast of the United States that serve a densely populated region in 2021. The total number of emergency calls was 187 at the University of Maryland (UMD) and 127 at the University of Pennsylvania (UPenn). There were calls on 180/365 (46%) days during the study period at UMD and 239/365 (63%) days at UPenn. The most common indication was carbon monoxide toxicity. The peak month of calls was March. Emergency HBO2 calls are common, and more centers must accept emergency cases. Data from geographically diverse centers would add generalizability to these results and capture more diving-related emergencies.

Neighborhood Disadvantage and Prostate Tumor RNA Expression of Stress-Related Genes.

Importance: African American men experience greater prostate cancer incidence and mortality than White men. Growing literature supports associations of neighborhood disadvantage, which disproportionately affects African American men, with aggressive prostate cancer; chronic stress and downstream biological impacts (eg, increased inflammation) may contribute to these associations. Objective: To examine whether several neighborhood disadvantage metrics are associated with prostate tumor RNA expression of stress-related genes. Design, Setting, and Participants: This cross-sectional study leveraged prostate tumor transcriptomic data for African American and White men with prostate cancer who received radical prostatectomy at the University of Maryland Medical Center between August 1992 and January 2021. Data were analyzed from May 2023 to April 2024. Exposures: Using addresses at diagnosis, 2 neighborhood deprivation metrics (Area Deprivation Index [ADI] and validated bayesian Neighborhood Deprivation Index) as well as the Racial Isolation Index (RI) and historical redlining were applied to participants' addresses. Self-reported race was determined using electronic medical records. Main Outcomes and Measures: A total of 105 stress-related genes were evaluated with each neighborhood metric using linear regression, adjusting for race, age, and year of surgery. Genes in the Conserved Transcriptional Response to Adversity (CTRA) and stress-related signaling genes were included. Results: A total of 218 men (168 [77%] African American, 50 [23%] White) with a median (IQR) age of 58 (53-63) years were included. African American participants experienced greater neighborhood disadvantage than White participants (median [IQR] ADI, 115 [100-130] vs 92 [83-104]; median [IQR] RI, 0.68 [0.34-0.87] vs 0.11 [0.06-0.14]). ADI was positively associated with expression for 11 genes; HTR6 (serotonin pathway) remained significant after multiple-comparison adjustment (ß = 0.003; SE, 0.001; P < .001; Benjamini-Hochberg q value = .01). Several genes, including HTR6, were associated with multiple metrics. We observed higher expression of 5 proinflammatory genes in the CTRA with greater neighborhood disadvantage (eg, CXCL8 and ADI, ß = 0.008; SE, 0.003; P = .01; q value = .21). Conclusions and Relevance: In this cross-sectional study, the expression of several stress-related genes in prostate tumors was higher among men residing in disadvantaged neighborhoods. This study is one of the first to suggest associations of neighborhood disadvantage with prostate tumor RNA expression. Additional research is needed in larger studies to replicate findings and further investigate interrelationships of neighborhood factors, tumor biology, and aggressive prostate cancer to inform interventions to reduce disparities.

Air or Ground Transport to the Critical Care Resuscitation Unit: Does It Really Matter?

OBJECTIVE: Critically ill patients requiring urgent interventions or subspecialty care often require transport over significant distances to tertiary care centers. The optimal method of transportation (air vs. ground) is unknown. We investigated whether air transport was associated with lower mortality for patients being transferred to a specialized critical care resuscitation unit (CCRU). METHODS: This was a retrospective study of all adult patients transferred to the CCRU at the University of Maryland Medical Center in 2018. Our primary outcome was hospital mortality. The secondary outcomes included the length of stay and the time to the operating room (OR) for patients undergoing urgent procedures. We performed optimal 1:2 propensity score matching for each patient's need for air transport. RESULTS: We matched 198 patients transported by air to 382 patients transported by ground. There was no significant difference between demographics, the initial Sequential Organ Failure Assessment score, or hospital outcomes between groups. One hundred sixty-four (83%) of the patients transported via air survived to hospital discharge compared with 307 (80%) of those transported by ground (P = .46). Patients transported via air arrived at the CCRU more quickly (127 [100-178] vs. 223 [144-332] minutes, P < .001) and were more likely (60 patients, 30%) to undergo urgent surgical operation within 12 hours of CCRU arrival (30% vs. 17%, P < .001). For patients taken to the OR within 12 hours of arriving at the CCRU, patients transported by air were more likely to go to the OR after 200 minutes since the transfer request (P = .001). CONCLUSION: The transportation mode used to facilitate interfacility transfer was not significantly associated with hospital mortality or the length of stay for critically ill patients.

A Framework for Developing and Assessing Custom Case Definitions: A Demonstration Applied to Opioid Overdose in Maryland.

CONTEXT: Public health epidemiologists monitor data sources for disease outbreaks and other events of public health concern, but manual review of records to identify cases of interest is slow and labor-intensive and may not reflect evolving data practices. To automatically identify cases from electronic data sources, epidemiologists must use "case definitions" or formal logic that captures the criteria used to identify a record as a case of interest. OBJECTIVE: To establish a methodology for development and evaluation of case definitions. A logical evaluation framework to approach case definitions will allow jurisdictions the flexibility to implement a case definition tailored to their goals and available data. DESIGN: Case definition development is explained as a process with multiple logical components combining free-text and categorical data fields. The process is illustrated with the development of a case definition to identify emergency medical services (EMS) call records related to opioid overdoses in Maryland. SETTING: The Maryland Department of Health (MDH) installation of the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE), which began capturing EMS call records in ESSENCE in 2019 to improve statewide coverage of all-hazards health issues. RESULTS: We describe a case definition evaluation framework and demonstrate its application through development of an opioid overdose case definition to be used in MDH ESSENCE. We show the iterative process of development, from defining how a case can be identified conceptually to examining each component of the conceptual definition and then exploring how to capture that component using available data. CONCLUSION: We present a framework for developing and qualitatively assessing case definitions and demonstrate an application of the framework to identifying opioid overdose incidents from MDH EMS data. We discuss guidelines to support jurisdictions in applying this framework to their own data and public health challenges to improve local surveillance capability.

Infant Feeding Support for Pregnant and Postpartum Parents With Intellectual and Developmental Disabilities: Perspectives of WIC Staff.

OBJECTIVE: To describe the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) staff experiences, perceptions, and training needs surrounding the provision of infant feeding support for parents with intellectual and developmental disabilities (IDD). METHODS: We conducted in-depth semistructured interviews between October and November 2021 with Maryland WIC staff (N = 10) who provide infant feeding counseling and support. We analyzed interviews using conventional content analysis. RESULTS: Three themes were identified: identifying and documenting IDD, facilitating effective communication and infant feeding education, and assessing WIC staff competence and readiness. CONCLUSIONS AND IMPLICATIONS: The interviews suggested the need to explore the risks and benefits of routine and compassionate processes for identifying and documenting disability, create accessible teaching materials that facilitate understanding and engagement, and educate and train staff to provide tailored support in WIC. Engaging parents with IDD to better understand their perspectives and experiences should guide future efforts to improve inclusivity and accessibility.

Blue and red tides in the Chesapeake Bay watershed: Examining political and environmental framings of collective action during the 2016 and 2020 elections.

Watersheds require collective care and management at local and regional levels to maintain their ecological health. The Chesapeake Bay's last several decades of stagnantly poor ecological health presents a distinctive case study for explicating the challenges of motivating collective action across a diverse regional natural resource. Our study uses county- and individual-level descriptive analysis to examine interrelated framings of environmental quality, environmental sentiment, and political action at two critical moments in time-the 2016 and 2020 presidential elections. We find that demographic, environmental, and political characteristics vary with distance to the Chesapeake Bay and that linked environmental and political characteristics appeared to become more polarized between 2016 and 2020. We found no evidence that local environmental quality influenced new political actions such as voting; however, people already likely to vote were influenced by their pro-environmental values such as priorities around climate change.

Increasing Access to Cardiac Rehabilitation Services Among Disadvantaged Populations.

The Prince George's County Health Department encountered several challenges to increasing access to cardiac rehabilitation (CR) services among disadvantaged populations. They include excessive patient out-of-pocket costs; requirements that CR orders must be signed by a physician; provider reluctance to refer patients to CR, with most primary care providers preferring to refer clients to cardiologists for the latter to determine whether the patient needs CR referral; limited availability of CR programs; and difficulty identifying patients eligible for CR services. Discussions with other local health departments and public health practitioners indicate that these challenges are not unique to Maryland but are indicative of policy and system barriers that prevent the optimal delivery of cardiovascular health services. This practice report documents the challenges and the Prince George's County Health Department's efforts to resolve them and provides recommendations for decision-makers seeking to make CR programs more accessible to disadvantaged populations.

Assessing racial bias in healthcare predictive models: Practical lessons from an empirical evaluation of 30-day hospital readmission models.

OBJECTIVE: Despite increased availability of methodologies to identify algorithmic bias, the operationalization of bias evaluation for healthcare predictive models is still limited. Therefore, this study proposes a process for bias evaluation through an empirical assessment of common hospital readmission models. The process includes selecting bias measures, interpretation, determining disparity impact and potential mitigations. METHODS: This retrospective analysis evaluated racial bias of four common models predicting 30-day unplanned readmission (i.e., LACE Index, HOSPITAL Score, and the CMS readmission measure applied as is and retrained). The models were assessed using 2.4 million adult inpatient discharges in Maryland from 2016 to 2019. Fairness metrics that are model-agnostic, easy to compute, and interpretable were implemented and apprised to select the most appropriate bias measures. The impact of changing model's risk thresholds on these measures was further assessed to guide the selection of optimal thresholds to control and mitigate bias. RESULTS: Four bias measures were selected for the predictive task: zero-one-loss difference, false negative rate (FNR) parity, false positive rate (FPR) parity, and generalized entropy index. Based on these measures, the HOSPITAL score and the retrained CMS measure demonstrated the lowest racial bias. White patients showed a higher FNR while Black patients resulted in a higher FPR and zero-one-loss. As the models' risk threshold changed, trade-offs between models' fairness and overall performance were observed, and the assessment showed all models' default thresholds were reasonable for balancing accuracy and bias. CONCLUSIONS: This study proposes an Applied Framework to Assess Fairness of Predictive Models (AFAFPM) and demonstrates the process using 30-day hospital readmission model as the example. It suggests the feasibility of applying algorithmic bias assessment to determine optimized risk thresholds so that predictive models can be used more equitably and accurately. It is evident that a combination of qualitative and quantitative methods and a multidisciplinary team are necessary to identify, understand and respond to algorithm bias in real-world healthcare settings. Users should also apply multiple bias measures to ensure a more comprehensive, tailored, and balanced view. The results of bias measures, however, must be interpreted with caution and consider the larger operational, clinical, and policy context.

Using machine learning models to estimate Escherichia coli concentration in an irrigation pond from water quality and drone-based RGB imagery data.

The rapid and efficient quantification of Escherichia coli concentrations is crucial for monitoring water quality. Remote sensing techniques and machine learning algorithms have been used to detect E. coli in water and estimate its concentrations. The application of these approaches, however, is challenged by limited sample availability and unbalanced water quality datasets. In this study, we estimated the E. coli concentration in an irrigation pond in Maryland, USA, during the summer season using demosaiced natural color (red, green, and blue: RGB) imagery in the visible and infrared spectral ranges, and a set of 14 water quality parameters. We did this by deploying four machine learning models - Random Forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), and K-nearest Neighbor (KNN) - under three data utilization scenarios: water quality parameters only, combined water quality and small unmanned aircraft system (sUAS)-based RGB data, and RGB data only. To select the training and test datasets, we applied two data-splitting methods: ordinary and quantile data splitting. These methods provided a constant splitting ratio in each decile of the E. coli concentration distribution. Quantile data splitting resulted in better model performance metrics and smaller differences between the metrics for both the training and testing datasets. When trained with quantile data splitting after hyperparameter optimization, models RF, GBM, and XGB had R2 values above 0.847 for the training dataset and above 0.689 for the test dataset. The combination of water quality and RGB imagery data resulted in a higher R2 value (>0.896) for the test dataset. Shapley additive explanations (SHAP) of the relative importance of variables revealed that the visible blue spectrum intensity and water temperature were the most influential parameters in the RF model. Demosaiced RGB imagery served as a useful predictor of E. coli concentration in the studied irrigation pond.

Behavioral Weight Loss Programs for Cancer Survivors Throughout Maryland: Protocol for a Pragmatic Trial and Participant Characteristics.

BACKGROUND: Clinical trials examining lifestyle interventions for weight loss in cancer survivors have been demonstrated to be safe, feasible, and effective. However, scalable weight loss programs are needed to support their widespread implementation. The ASPIRE trial was designed to evaluate real-world, lifestyle-based, weight loss programs for cancer survivors throughout Maryland. OBJECTIVE: The objectives of this protocol paper are to describe the design of a nonrandomized pragmatic trial, study recruitment, and baseline characteristics of participants. METHODS: Participants were aged ≥18 years, residing in Maryland, with a BMI ≥25 kg/m2, who reported a diagnosis of a malignant solid tumor, completed curative treatment, and had no ongoing or planned cancer treatment. Enrollment criteria were minimized to increase generalizability. The primary recruitment source was the Johns Hopkins Health System electronic health records (EHRs). Participants selected 1 of 3 remotely delivered weight loss programs: self-directed, app-supported, or coach-supported program. RESULTS: Participants were recruited across all 5 geographic regions of Maryland. Targeted invitations using EHRs accounted for 287 (84.4%) of the 340 participants enrolled. Of the 5644 patients invited through EHR, 5.1% (287/5644) enrolled. Participants had a mean age of 60.7 (SD 10.8) years, 74.7% (254/340) were female, 55.9% (190/340) identified as non-Hispanic Black, 58.5% (199/340) had a bachelor's degree, and the average BMI was 34.1 kg/m2 (SD 5.9 kg/m2). The most common types of cancers were breast (168/340, 49.4%), prostate (72/340, 21.2%), and thyroid (39/340, 8.5%). The self-directed weight loss program (n=91) included 25 participants who agreed to provide weights through a study scale; the app-supported program (n=142) included 108 individuals who agreed to provide their weight measurements; and the coach-supported weight loss program included 107 participants. We anticipate final analysis will take place in the fall of 2024. CONCLUSIONS: Using EHR-based recruitment efforts, this study took a pragmatic approach to reach and enroll cancer survivors into remotely delivered weight loss programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04534309; https://clinicaltrials.gov/study/NCT04534309. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54126.

The efficacy of 1-allyloxy-4-propoxybenzene (3c{3,6}) against Varroa destructor mites in honey bee colonies from Maryland, USA.

Varroa destructor Oud (Acari: Varroidae) is a harmful ectoparasite of Apis mellifera L. honey bees causing widespread colony losses in Europe and North America. To control populations of these mites, beekeepers have an arsenal of different treatments, including both chemical and nonchemical options. However, nonchemical treatments can be labor intensive, and Varroa has gained resistance to some conventional pesticides, and the use of other chemical treatments is restricted temporally (e.g., cannot be applied during periods of honey production). Thus, beekeepers require additional treatment options for controlling mite populations. The compound 1-allyloxy-4-propoxybenzene (3c{3,6}) is a diether previously shown to be a strong feeding deterrent against Lepidopteran larvae and a repellent against mosquitoes and showed promise as a novel acaricide from laboratory and early field trials. Here we test the effect of the compound, applied at 8 g/brood box on wooden release devices, on honey bees and Varroa in field honey bee colonies located in Maryland, USA, and using a thymol-based commercial product as a positive control. 3c{3,6} had minimal effect on honey bee colonies, but more tests are needed to determine whether it affected egg production by queens. Against Varroa3c{3,6} had an estimated efficacy of 78.5%, while the positive control thymol product showed an efficacy of 91.3%. 3c{3,6} is still in the development stage, and the dose or application method needs to be revisited.

Mapping the distribution of Lyme disease at a mid-Atlantic site in the United States using electronic health data.

Lyme disease is a spatially heterogeneous tick-borne infection, with approximately 85% of US cases concentrated in the mid-Atlantic and northeastern states. Surveillance for Lyme disease and its causative agent, including public health case reporting and entomologic surveillance, is necessary to understand its endemic range, but currently used case detection methods have limitations. To evaluate an alternative approach to Lyme disease surveillance, we have performed a geospatial analysis of Lyme disease cases from the Johns Hopkins Health System in Maryland. We used two sources of cases: a) individuals with both a positive test for Lyme disease and a contemporaneous diagnostic code consistent with a Lyme disease-related syndrome; and b) individuals referred for a Lyme disease evaluation who were adjudicated to have Lyme disease. Controls were individuals from the referral cohort judged not to have Lyme disease. Residential address data were available for all cases and controls. We used a hierarchical Bayesian model with a smoothing function for a coordinate location to evaluate the probability of Lyme disease within 100 km of Johns Hopkins Hospital. We found that the probability of Lyme disease was greatest in the north and west of Baltimore, and the local probability that a subject would have Lyme disease varied by as much as 30-fold. Adjustment for demographic and ecological variables partially attenuated the spatial gradient. Our study supports the suitability of electronic medical record data for the retrospective surveillance of Lyme disease.

Polysubstance Use among Maryland High School Students: Variations across County-Level School Districts.

BACKGROUND: Polysubstance use is a highly prevalent public health issue, particularly among adolescents, and decisions on prevention programming and policies are often made at the local level. While there is a growing literature examining patterns of polysubstance use among adolescents, little is known about differences in those patterns across geographic regions. METHODS: Using a large, representative sample of high school students from the state of Maryland (n = 41,091) from the 2018 Maryland Youth Risk Behavior Survey, we conducted a latent class analysis (LCA) of adolescent substance use along nine binary indicators, including past 30-day combustible tobacco, e-cigarette, alcohol, and cannabis use, as well as lifetime use of prescription opioids, cocaine, heroin, methamphetamine, and injection drug use. Measurement invariance across counties was examined using the Multiple Indicators and Multiple Causes (MIMIC) procedure. RESULTS: The results of the LCA show three classes of adolescent substance use for the total sample: (1) low substance use, (2) commonly used substances (i.e., e-cigarette, alcohol, and cannabis use), and (3) polysubstance use. The results from the MIMIC procedure demonstrated geographic differences in students' endorsement of specific indicators and their class membership. CONCLUSIONS: These differences demonstrate the need for an examination of local trends in adolescent polysubstance use to inform multi-tiered prevention programming and policy.

Causal inference approaches reveal both positive and negative unintended effects of agricultural and urban management practices on instream biological condition.

Agricultural and urban management practices (MPs) are primarily designed and implemented to reduce nutrient and sediment concentrations in streams. However, there is growing interest in determining if MPs produce any unintended positive effects, or co-benefits, to instream biological and habitat conditions. Identifying co-benefits is challenging though because of confounding variables (i.e., those that affect both where MPs are applied and stream biota), which can be accounted for in novel causal inference approaches. Here, we used two causal inference approaches, propensity score matching (PSM) and Bayesian network learning (BNL), to identify potential MP co-benefits in the Chesapeake Bay watershed portion of Maryland, USA. Specifically, we examined how MPs may modify instream conditions that impact fish and macroinvertebrate indices of biotic integrity (IBI) and functional and taxonomic endpoints. We found evidence of positive unintended effects of MPs for both benthic macroinvertebrates and fish indicated by higher IBI scores and specific endpoints like the number of scraper macroinvertebrate taxa and lithophilic spawning fish taxa in a subset of regions. However, our results also suggest MPs have negative unintended effects, especially on sensitive benthic macroinvertebrate taxa and key instream habitat and water quality metrics like specific conductivity. Overall, our results suggest MPs offer co-benefits in some regions and catchments with largely degraded conditions but can have negative unintended effects in some regions, especially in catchments with good biological conditions. We suggest the number and types of MPs drove these mixed results and highlight carefully designed MP implementation that incorporates instream biological data at the catchment scale could facilitate co-benefits to instream biological conditions. Our study underscores the need for more research on identifying effects of individual MP types on instream biological and habitat conditions.

Aggressive interactions among white-tailed deer (Artiodactyla: Cervidae) at 4-poster devices for host-targeted tick control.

White-tailed deer, Odocoileus virginianus Zimmermann (Artiodactyla: Cervidae), are the primary wildlife host for adult stages of blacklegged ticks (Acari: Ixodidae: Ixodes scapularis Say) and an important host for lone star ticks (Acari: Ixodidae: Amblyomma americanum Linnaeus), both of which are vectors of numerous tick-borne pathogens. The 4-poster passive deer treatment device is a topical, host-targeted method to control free-living tick populations and has been proven to successfully reduce tick abundance in several states. Aggressive behavior of white-tailed deer at concentrated feeding stations is hypothesized to interfere with the effective use of 4-poster devices and deer contact with acaricide applicators. We analyzed images collected by camera traps at 4-poster feeding stations deployed at 3 sites in Maryland and found a negative relationship between some aggressive interactions and contact with applicators. Our results emphasize the need for further investigation into whether deer social dynamics can impact 4-poster efficacy for tick control. This study serves as a reminder that intraspecific interactions are important to consider when using host-targeted acaricide approaches.

Antibiotic resistance trends among Vibrio vulnificus and Vibrio parahaemolyticus isolated from the Chesapeake Bay, Maryland: a longitudinal study.

Antibiotics are often used to treat severe Vibrio infections, with third-generation cephalosporins and tetracyclines combined or fluoroquinolones alone being recommended by the US Centers for Disease Control and Prevention. Increases in antibiotic resistance of both environmental and clinical vibrios are of concern; however, limited longitudinal data have been generated among environmental isolates to inform how resistance patterns may be changing over time. Hence, we evaluated long-term trends in antibiotic resistance of vibrios isolated from Chesapeake Bay waters (Maryland) across two 3-year sampling periods (2009-2012 and 2019-2022). Vibrio parahaemolyticus (n = 134) and Vibrio vulnificus (n = 94) toxR-confirmed isolates were randomly selected from both sampling periods and tested for antimicrobial susceptibility against eight antibiotics using the Kirby-Bauer disk diffusion method. A high percentage (94%-96%) of V. parahaemolyticus isolates from both sampling periods were resistant to ampicillin and only 2%-6% of these isolates expressed intermediate resistance or resistance to third-generation cephalosporins, amikacin, tetracycline, and trimethoprim-sulfamethoxazole. Even lower percentages of resistant V. vulnificus isolates were observed and those were mostly recovered from 2009 to 2012, however, the presence of multiple virulence factors was observed. The frequency of multi-drug resistance was relatively low (6%-8%) but included resistance against antibiotics used to treat severe vibriosis in adults and children. All isolates were susceptible to ciprofloxacin, a fluoroquinolone, indicating its sustained efficacy as a first-line agent in the treatment of severe vibriosis. Overall, our data indicate that antibiotic resistance patterns among V. parahaemolyticus and V. vulnificus recovered from the lower Chesapeake Bay have remained relatively stable since 2009.IMPORTANCEVibrio spp. have historically been susceptible to most clinically relevant antibiotics; however, resistance and intermediate-resistance have been increasingly recorded in both environmental and clinical isolates. Our data showed that while the percentage of multi-drug resistance and resistance to antibiotics was relatively low and stable across time, some Vibrio isolates displayed resistance and intermediate resistance to antibiotics typically used to treat severe vibriosis (e.g., third-generation cephalosporins, tetracyclines, sulfamethoxazole-trimethoprim, and aminoglycosides). Also, given the high case fatality rates observed with Vibrio vulnificus infections, the presence of multiple virulence factors in the tested isolates is concerning. Nevertheless, the continued susceptibility of all tested isolates against ciprofloxacin, a fluoroquinolone, is indicative of its use as an effective first-line treatment of severe Vibrio spp. infections stemming from exposure to Chesapeake Bay waters or contaminated seafood ingestion.

"Maybe if we weren't in the pandemic, I would have reconsidered": Experiences of abortion care-seeking during the COVID-19 pandemic in Maryland.

OBJECTIVE: To understand the COVID-19 pandemic's impact on abortion care-seeking in Maryland, a state with Medicaid coverage for abortion, high service availability, and laws supporting abortion rights. METHODS: We conducted semi-structured telephone interviews with 15 women who had an abortion between January 2021 and March 2022 at a hospital-based clinic in a mid-sized Maryland city. We purposively recruited participants with varied pandemic financial impacts. Interview questions prompted participants to reflect on how the pandemic affected their lives, pregnancy decisions, and experiences seeking abortion care. We analyzed our data for themes. RESULTS: All participants had some insurance coverage for their abortion; over half paid using Medicaid. Many participants experienced pandemic financial hardship, with several reporting job, food, and housing insecurity as circumstances influencing their decision to have an abortion. Most women who self-reported minimal financial hardship caused by the pandemic indicated they sought an abortion for reasons unrelated to COVID-19. In contrast, women with economic hardship viewed their pregnancies as unsupportable due to COVID-19 exacerbating financial instability, even when they desired to continue the pregnancy. All participants expressed that having an abortion was the best decision for their lives. Yet, when making decisions about their pregnancy, the most financially disadvantaged women weighed their desires against the pandemic's constraints on their reproductive self-determination. CONCLUSIONS: The pandemic changed abortion care-seeking circumstances even in a setting with minimal access barriers. Financial hardship influenced some women to have an abortion for a pregnancy that-while unplanned-they may have preferred to continue.

The influence of primary language on postoperative stroke outcomes.

BACKGROUND: Language barriers have the potential to influence acute stroke outcomes. Thus, we examined postoperative stroke outcomes among non-English primary language speakers. METHODS: Utilizing the Healthcare Cost and Utilization Project State Inpatient Database (2016-2019), we conducted a retrospective cohort study of adults diagnosed with a postoperative stroke in Michigan, Maryland, and New Jersey. Patients were classified by primary language spoken: English (EPL) or non-English (n-EPL). The primary outcome was hospital length-of-stay. Secondary outcomes included stroke intervention, feeding tube, tracheostomy, mortality, cost, disposition, and readmission. Propensity-score matching and post-match regression were used to quantify outcomes. RESULTS: Among 3078 postoperative stroke patients, 6.2 â€‹% were n-EPL. There were no differences in length-of-stay or secondary outcomes, except for higher odds of feeding tube placement (OR 1.95, 95 â€‹% CI 1.10-3.47, p â€‹= â€‹0.0227) in n-EPL. CONCLUSIONS: Postoperative stroke outcomes were comparable by primary language spoken. However, higher odds of feeding tube placement in n-EPL may suggest differences in patient-provider communication.