Faculty Bibliography

Wastewater-based surveillance (WBS) is valuable for monitoring antimicrobial resistance (AMR). Staphylococci are key targets, as wastewater can facilitate gene transfer and resistance emergence. Data on WBS for population-level AMR in the Arabian-Gulf remain limited. This study assessed Staphylococcus diversity and resistance in Dubai wastewater. Samples were collected over eight months from nine community sites, two hospital nodes, and two wastewater treatment plants (WWTPs) and were analysed by culture-based method. Ninety-six Staphylococcus isolates were recovered from community, hospital, and WWTP influent, with no growth in effluent. Most isolates (n/N = 88/96) were coagulase-negative Staphylococcus (CoNS), spanning 15 species, dominated by S. saprophyticus, S. cohnii and S. sciuri. The only coagulase-positive Staphylococcus was S. aureus (n = 8) and the only species detected across all wastewater sources. Resistance was highest to benzylpenicillin (88%) and fusidic acid (82%), whereas all isolates remained susceptible to glycopeptides, tigecycline, and linezolid. Fusidic acid resistance was higher in community-wastewater isolates, whereas β-lactam resistance predominated in hospital-wastewater isolates. Sixty percent of CoNS were multidrug-resistant; methicillin resistance occurred in 37.5% of CoNS and 50% of S. aureus. Wastewater is a reservoir of diverse multidrug-resistant staphylococci, underscoring One Health relevance reflecting the potential for circulation between humans, animals, and the shared environment. WBS can support population-level AMR monitoring to inform public health and veterinary interventions.

BACKGROUND:Social disruptions (e.g., loss of stable housing, employment, income) during the COVID-19 pandemic have been associated with greater mental healthcare and substance use treatment needs in the general population. People with HIV (PWH) may have experienced greater social disruptions during the COVID-19 pandemic due to pre-existing social vulnerabilities and may have experienced greater interruptions in healthcare during the pandemic due to the co-management of chronic and co-morbid conditions, including mental health and substance use disorder diagnoses, which are prevalent among PWH. METHODS:Between April and September 2020, surveys assessing social disruption and healthcare interruption were conducted among Multicenter AIDS Cohort Study/Women’s Interagency HIV Study Combined Cohort Study participants. Descriptive statistics and multivariable logistic regression models were used to characterize and examine the relationships between social disruptions and interruptions in general, mental health, and substance use care, adjusting for sociodemographic characteristics (age, race and ethnicity, region, income, and employment) and HIV status. Qualitative interviews were conducted to add depth and context to quantitative analysis. RESULTS:Among 3,665 survey participants (2,238 PWH, 1,427 PWoH), 54% (1214 PWH, 733 PWoH) reported social disruptions and 42% reported healthcare interruptions (972 PWH, 578 PWoH). PWH experiencing ≥ 2 social disruptions had higher odds of missed healthcare appointments (aOR = 1.92, 95%CI:1.56, 2.36) and interrupted mental healthcare (aOR = 2.54, 95%CI:1.83, 3.53) compared to those experiencing < 2. PWoH experiencing ≥ 2 social disruptions had higher odds of missed healthcare appointments, (aOR = 1.65, 95%CI:1.26, 2.17), interrupted mental healthcare (aOR = 2.24, 95%CI:1.38, 3.64), and interrupted substance use treatment (aOR = 2.58, 95%CI:1.15, 5.75) compared to those experiencing < 2. Qualitative interviews elucidated the following reasons for healthcare interruptions: Interruptions in medication and supplies, reduced access to quality healthcare services, self-imposed interruptions related to perceived COVID risk, increased interruptions related to comorbid care needs, reduced access to mental healthcare, and delays in HIV-care. CONCLUSION:Healthcare interruptions during the pandemic inequitably affected vulnerable individuals, especially those experiencing greater social disruptions and those with specialized health care needs. Understanding the impact of pandemic related social disruptions on vulnerable individuals provides an opportunity to address disparities and build a more capable health care system. SUPPLEMENTARY INFORMATION:The online version contains supplementary material available at 10.1186/s12913-025-13690-w.

OBJECTIVES/OBJECTIVE:Metal artifact reduction MRI can exceed specific absorption rate (SAR) limits due to high-bandwidth radiofrequency pulses, causing scan interruptions and prolonged acquisition times. The aim of the current study is to reduce SAR and potentially scan time in metal artifact reduction MRI using an optimized variable refocusing flip angle (VRFA) scheme compared with the standard constant refocusing flip angle (CRFA). MATERIALS AND METHODS/METHODS:Three VRFA variants (VRFA1 to VRFA3) were developed to maximize tissue signal and contrast while minimizing SAR and image blur. The optimal variant was selected through quantification of metal artifacts and image blur in phantoms and tissue signal in a volunteer. Patients with hip arthroplasty underwent CRFA and optimal VRFA imaging using high-bandwidth turbo-spin-echo (HBW-TSE) and compressed-sensing slice-encoding-for-metal-artifact-correction (CS-SEMAC) sequences. Three readers ranked paired CRFA and VRFA scans for quality. Analyses included repeated measures ANOVA, noninferiority testing, and paired t/Wilcoxon signed-rank tests. RESULTS:CRFA and VRFA1 to VRFA3 showed no significant differences in image blur (full-width-at-half-maximum, mean ± SD, 1.9 ± 0.2 vs 1.9 ± 0.2 vs 1.9 ± 0.3 vs 1.9 ± 0.3 pixels, P = 0.06) or metal artifacts (8.2 ± 2.8 vs 8.4 ± 2.7 vs 8.4 ± 2.6 vs 8.4 ± 2.7 pixels, P = 0.57). The optimal VRFA variant (VRFA3) preserved 81% of CRFA fat-muscle contrast at 77% SAR and 70% scan time on proton-density (PD), and 94% of fluid-muscle contrast at 80% SAR and 67% scan time on short-tau-inversion-recovery (STIR). In 23 patients [mean age, 67.3 y ± 12.2 (SD); 14 females], the optimal VRFA was noninferior to CRFA in all quality metrics (all 95% CI < noninferiority margin = 0.1) and significantly reduced SAR (mean, PD-HBW-TSE/STIR-HBW-TSE/PD-CS-SEMAC/STIR-CS-SEMAC: 1.11/1.35/1.17/1.18 vs 1.85/1.83/1.49/1.46 W/kg, all P ≤ 0.001). In HBW-TSE, reduced SAR allowed longer echo trains and 15% to 32% shorter scan times. CONCLUSION/CONCLUSIONS:Metal artifact reduction MRI with VRFA reduces SAR without compromising image quality. It allows shorter acquisitions in HBW-TSE.

BACKGROUND:Electrophysiologic care is increasingly a critical element of cardiovascular care, especially among older adults. OBJECTIVE:We investigated access to common electrophysiologic procedures among Medicare beneficiaries in the United States (US). METHODS:We used US Medicare Physician and Other Practitioners data (2013-2020) to identify centers providing pacemaker implantation and atrial fibrillation (AF) ablation, and linked it to county and zip code-level demographic data from the Agency for Healthcare Research and Quality to evaluate the density and trends in the number of centers across states and counties. For each US zip code, we determined the closest center where electrophysiologic procedures were performed and the travel duration using the Google Maps application programming interface. We also examined the association between sociodemographic factors and travel time to the nearest clinician using multivariable logistic regression models. RESULTS:In 2020, 3022 Medicare providers performed pacemaker implantations across 1392 centers, and 1661 providers performed AF ablations across 852 centers. However, only 20% of US counties had facilities performing pacemaker implantation, and just 16% had sites offering AF ablation. In 45% of counties, individuals needed to drive ≥1 hour to reach a site for pacemaker implantation. For AF ablation, this number increased to 50%. Longer travel times were associated with non-urban zip codes, higher percentage of Hispanic residents, less than high school education, and median annual income <$59,000. CONCLUSION/CONCLUSIONS:There are demographic and geographic disparities in access to interventional electrophysiologic care among Medicare beneficiaries in the US, with lower access among residents of rural areas and socio-economically disadvantaged groups.

BACKGROUND:Wearable accelerometers, which continuously record physical activity metrics, are commonly used in mobile health-enabled cardiac rehabilitation (mHealth-CR). The association between adherence to accelerometer use during mHealth-CR and improvement in clinical outcomes, such as functional capacity, is understudied. The emergence of artificial intelligence (AI) technology provides novel opportunities to investigate accelerometry use patterns in relation to mHealth-CR outcomes. OBJECTIVE:In this study, we sought to use an AI clustering framework to identify distinct behavioral phenotypes of adherence to accelerometer use. We then aimed to quantify the association of these adherence phenotypes with functional capacity improvements in older adults undergoing mHealth-CR. METHODS:We analyzed data from the RESILIENT (Rehabilitation at Home Using Mobile Health in Older Adults After Hospitalization for Ischemic Heart Disease) trial, the largest randomized clinical study to date comparing mHealth-CR versus usual care in older adults (aged ≥65 years). Intervention arm participants were instructed to wear a Fitbit accelerometer for the 3-month study duration. Adherence to accelerometer use was quantified as overall adherence (percentage of days worn) via k-means clustering AI-derived measures and compared with changes in 6-minute walk distance (6-MWD), adjusted for demographic and clinical covariates. RESULTS:Among 271 participants with a mean age of 71 years (SD 8), of whom 198 (73%) were male, accelerometers were worn for an average of 76 days (95% confidence limits 73,78) over 3 months. Adjusted analyses showed a weak association between days of wear and improvement in 6-MWD, with every 30 additional days associated with an 11-meter improvement (P=.08). Our k-means clustering framework identified adherence phenotypes at two resolutions: low resolution (k=2 clusters) and high resolution (k=8 clusters). The consistently high adherence cluster trended toward a 24.6-meter improvement in 6-MWD compared to the low and declining adherence clusters (n=39; 95% CI 0.7-49.9; P=.06). The 8-cluster phenotyping revealed a richer set of adherence patterns, with the consistently high adherence cluster in this analysis having a 38.5-meter (95% CI 2.2-74.7; P=.04) improvement in 6-MWD than the low adherence cluster, as well as greater average daily steps over the 3-month intervention (mean 7518, SD 3415 vs mean 4800, SD 2920 steps; P=.008). CONCLUSIONS:A time-series AI clustering framework identified a range of behavioral phenotypes representing different degrees of adherence to accelerometer use. Regression analysis identified a weak association between the higher adherence phenotype and functional capacity improvement in older adults undergoing mHealth-CR. Our AI-derived accelerometry adherence phenotypes may offer a new approach to tailor mHealth-CR regimens to individual patients, potentially leading to better outcomes in this high-risk population. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT03978130; https://clinicaltrials.gov/study/NCT03978130. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:RR2-10.2196/32163.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Impaired consciousness in epilepsy negatively affects quality of life. Previous work has focused on temporal lobe seizures, where cortical slow waves are associated with depressed subcortical arousal and impaired consciousness. However, it is unknown whether frontal lobe seizures also show cortical slow waves or a different activity pattern with impaired consciousness. METHODS:Intracranial EEG (icEEG) recordings from patients at 3 centers were retrospectively assessed to identify seizures originating in the frontal lobe. Seizures were classified as focal preserved consciousness (FPC), focal impaired consciousness (FIC), or focal to bilateral tonic-clonic (FBTC) based on video review. Changes in icEEG power from preictal baseline were calculated in different cortical regions and across frequency ranges in these 3 seizure categories. RESULTS:< 0.001, 95% CI 330.1-781.9 and 375.3-818.2, respectively). DISCUSSION/CONCLUSIONS:The widespread power increases across frequencies in frontal lobe FIC seizures contrast with those in focal temporal lobe epilepsy, where impaired consciousness is associated with cortical slow waves. These findings suggest that different focal seizure types produce impaired consciousness by affecting widespread cortical regions but through different physiologic mechanisms. Insights gained by studying the physiology of impaired consciousness may be the first step toward developing novel treatments to prevent this significant negative consequence of epilepsy and improve quality of life.

INTRODUCTION/UNASSIGNED:The potential buffering role of benefit finding, a cognitive and behavior adaptation process, in the relationship between financial concerns and psychological distress is not well understood among Asian American populations. Our study examined how financial concerns impacted Asian Americans' mental health, specifically in the presence of benefit finding and received pay during the COVID-19 pandemic. METHODS/UNASSIGNED:Survey-weighted data from the 2021 Asian American and Native Hawaiian/Pacific Islander COVID-19 Needs Assessment Project was analyzed to test the associations between financial concerns and psychological distress among Asian American adults 18 years or older (unweighted N = 3,152). Multivariable linear regression models included an interaction term for benefit finding, financial concerns, and received pay to test the moderation effect of benefit finding on psychological distress. RESULTS/UNASSIGNED:: 1.24, 95% CI: 0.91, 1.56). Asian Americans who reported greater levels of benefit finding had lower psychological distress, but benefit finding alone did not moderate the relationship between financial concerns and psychological distress. However, having both greater levels of benefit finding and received pay protected Asian American participants the most from psychological distress when experiencing financial concerns. DISCUSSION/UNASSIGNED:Our findings suggest that benefit finding and received pay combined may have important implications for interventions and policy-level changes targeting financial concerns among Asian Americans. Future research should explore the relationships between benefit finding and health outcomes over the life course, other protective coping responses for Asian Americans, and potential differences by Asian ethnicity or specific subgroups.

Despite rapid advances in artificial intelligence (AI) across sectors, health care remains one of the least transformed domains. This stagnation is not due to lack of data, clinical need, or innovation, but rather to persistent regulatory and economic misalignment. Even AI tools cleared by the U.S. Food and Drug Administration that meet clinical efficacy standards often face major barriers to adoption, largely driven by outdated reimbursement frameworks and fragmented incentives among stakeholders. The result is a systemic failure to deploy technologies that could meaningfully reduce clinician workload, shorten wait times, and improve patient lives. In this article, we examine the reimbursement landscape for health AI, focusing first on tools that fit existing regulatory pathways, outlining payment barriers and proposing policy reforms. These include resolving Current Procedural Terminology adoption bottlenecks, addressing integration overhead, and aligning pricing models with AI cost structures. We then extend the discussion to the emerging domain of generative AI in health care, highlighting the urgent need for prospective regulatory frameworks to ensure patient benefits. (Funded by the National Institutes of Health and the Leukemia and Lymphoma Society.).