Faculty Bibliography

IMPORTANCE/UNASSIGNED:Hurricanes are associated with increased cardiovascular disease (CVD) risk, yet little is known about whether these risks extend into the long term and for how long. OBJECTIVE/UNASSIGNED:To examine the association between hurricane-related flooding and CVD risk up to 5 years after landfall. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cohort study included a 20% national sample of continuously enrolled Medicare fee-for-service beneficiaries from New Jersey, New York City, and Connecticut from January 1, 2010, to December 31, 2017. Data were analyzed from December 14, 2023, to June 20, 2025. EXPOSURE/UNASSIGNED:Residence in zip code tabulation areas (ZCTAs) impacted by flooding from Hurricane Sandy throughout the study period. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was the rate of ZCTA-level adjusted CVD events (including myocardial infarction [MI], heart failure [HF], and stroke), defined per 1000 beneficiary-years, with associated 95% bayesian credible intervals (bCrIs). Secondary outcomes included the rate of events for each CVD subtype (MI, HF, and stroke). RESULTS/UNASSIGNED:In the matched cohort, 121 395 beneficiaries resided in 690 ZCTAs, of which 441 (63.9%) flooded. In nonflooded vs flooded ZCTAs, mean (SD) age (74.2 [1.4] vs 74.1 [1.2] years; P = .16), proportion of female beneficiaries (61.4% [8.4%] vs 61.3% [6.6%]; P = .89), and proportion of White beneficiaries (74.3% [28.7%] vs 76.7% [26.8%]; P = .27) were similar, but ZCTA-level median income ($81 168 [$33 410] vs $69 650 [$27 594]; P < .001) and median National Area Deprivation Index rank (17.1 [IQR, 10.2-27.6] vs 21.0 [IQR, 10.9-32.5]; P = .02) differed; prevalence of CVD and CVD subtypes was similar at baseline. Flooding was associated with an increase in adjusted 5-year CVD risk post landfall (relative risk, 1.05; 95% bCrI, 1.01-1.08) and HF rates overall (relative risk, 1.03; 95% bCrI, 1.00-1.08). No significant difference was found in rates of MI or stroke in adjusted analyses. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this cohort study of Medicare fee-for-service beneficiaries, hurricane-related flooding was associated with increases in CVD event rates as long as 5 years after landfall and increased HF rates in New Jersey. These findings highlight the importance of place-based vulnerability from hurricane exposure to mitigate longer-term CVD risk and the need to consider long-term outcomes in hurricane mitigation efforts.

OBJECTIVE:The authors sought to identify predictors of and trends in the incidence of above (AKA) and below (BKA) knee amputations in a nationwide sample. BACKGROUND:Recently available major lower extremity amputation incidence estimates are drawn from earlier data and may benefit from an update. There is a potential for significant reductions given an increasing emphasis on structured amputation prevention programs and widespread adoption of sophisticated revascularization techniques. METHODS:Inpatient admissions with a diagnosis of atherosclerosis and/or related amputation were identified from the National Inpatient Sample. The primary outcome was the trend in BKA and AKA incidence. Multilevel logistic regression, stratified by landmark periods, was used to identify amputation predictors over time by comparing amputees to patients admitted with a diagnosis of atherosclerosis who did not undergo amputation. Population attributable fractions were used to estimate the proportion of each outcome due to a specific risk factor. RESULTS:Between January 1993 and December 2021, we identified 197,018 patients who underwent BKA and 151,018 who underwent AKA. BKA incidence decreased from 12/100,000 people in 1993 to 8/100,000 in 2010 (2.2% reduction per year). This trend reversed after 2010, ending in 13/100,000 in 2021 (9% increase per year; P <0.001). AKA incidence decreased from 11/100,000 people in 1993 to 6/100,000 in 2012 (2.1% reduction per year). This trend reversed in 2012, ending in 8/100,000 in 2021 (4% increase per year; P <0.001). The mean age for BKA decreased from 68 years in 1993 to 61.6 years in 2021, and for AKA, from 75 years to 66.7 years ( P <0.001 for both). We compared admissions for major amputation to 2,421,352 admissions for atherosclerosis without amputation. After 2010, BKA patients were more likely to be younger [odds ratio (OR)=1.0 vs. 0.97], White (OR=0.73 vs. 1.02), obese (OR=0.91 vs. 1.24), and hypertensive (OR=0.97 vs. 1.07; ORs presented for pre-2010 and post-2010 periods, respectively). After 2012, AKA patients were younger (OR=1.04 vs. 0.99), less likely to be female (OR=1.04 vs. 0.75), and showed shifts in effect size but not direction of important risk factors such as White race (OR=0.61 vs. 0.9), hypertension (OR=0.79 vs. 0.92), and obesity (OR=0.73 vs. 0.91). The population attributable fractions confirmed a progressive shift in the effect of risk factors on the changing incidence of both BKA and AKA. The effect of other risk factors such as diabetes (OR=4.3 and 1.6 for BKA and AKA, respectively) and dialysis (OR=2.4 and 2.1 for BKA and AKA, respectively) remained unchanged over time. CONCLUSION/CONCLUSIONS:Major amputation incidence has steadily increased since 2010, accompanied by a substantial shift in the associated comorbidity and demographic profile. This shift is particularly striking among patients with BKA who, after 2010, are more likely to be younger, White, obese, and hypertensive. Treatment paradigms to address this serious public health issue will need to be reconsidered to reflect increasing attribution to metabolic syndrome.

PURPOSE/OBJECTIVE:Artificial intelligence (AI) promises to significantly impact medical education, yet its implementation raises important questions about educational effectiveness, ethical use, and equity. In the second part of a 2-part innovation report, which was commissioned by the Josiah Macy Jr. Foundation to inform discussions at a conference on AI in medical education, the authors explore the perspectives of innovators actively integrating AI into medical education, examining their perceptions regarding the impacts, opportunities, challenges, and strategies for successful AI adoption and risk mitigation. METHOD/METHODS:Semi-structured interviews were conducted with 25 medical education AI innovators-including learners, educators, institutional leaders, and industry representatives-from June to August 2024. Interviews explored participants' perceptions of AI's influence on medical education, challenges to integration, and strategies for mitigating challenges. Transcripts were analyzed using thematic analysis to identify themes and synthesize participants' recommendations for AI integration. RESULTS:Innovators' responses were synthesized into 2 main thematic areas: (1) AI's impact on teaching, learning, and assessment, and (2) perceived threats and strategies for mitigating them. Participants identified AI's potential to enact precision education through virtual tutors and standardized patients, support active learning formats, enable centralized teaching, and facilitate cognitive offloading. AI-enhanced assessments could automate grading, predict learner trajectories, and integrate performance data from clinical interactions. Yet, innovators expressed concerns over threats to transparency and validity, potential propagation of biases, risks of over-reliance and deskilling, and institutional disparities. Proposed mitigation strategies emphasized validating AI outputs, establishing foundational competencies, fostering collaboration and open-source sharing, enhancing AI literacy, and maintaining robust ethical standards. CONCLUSIONS:AI innovators in medical education envision transformative opportunities for individualized learning and precision education, balanced against critical threats. Realizing these benefits requires proactive, collaborative efforts to establish rigorous validation frameworks; uphold foundational medical competencies; and prioritize ethical, equitable AI integration.

BACKGROUND:One hypothesis for the respiratory syncytial virus (RSV) surge in 2022 was suppression of immune responses following SARS-CoV-2 infection. Our objective was to compare the risk of subsequent RSV and other infections among children with and without SARS-CoV-2 infection. METHODS:We conducted a retrospective cohort study using electronic health record data from 27 US health systems analyzing children aged under 5 years with SARS-CoV-2 infection (test/coded) between March and July 2022. The comparison groups were children with (a) influenza infection and (b) respiratory tract infection with no evidence of SARS-CoV-2/influenza infection. The primary and secondary outcomes were RSV infection and respiratory or any infection in the subsequent 15 to 180 days, respectively. We applied inverse probability of treatment weighting and performed weighted logistic regression modeling. RESULTS:Our primary and secondary cohorts consisted of 18 767 and 114 414 children with SARS-CoV-2 infection, and 6697 and 30 424 with influenza infection, respectively, and 46 697 with another acute respiratory tract infection. The odds of subsequent RSV were lower in the SARS-CoV-2 group compared with the influenza group (adjusted odds ratio [aOR] 0.73, 95% CI 0.61-0.86) and compared with the group with any respiratory tract infection (aOR 0.78, 95% CI 0.7-0.87). The odds of a respiratory tract infection and any infection were lower in the SARS-CoV-2 group than the influenza group (aOR 0.62, 95% CI 0.59-0.64 and aOR 0.67, 95% CI 0.65-0.7, respectively). CONCLUSIONS:We did not find an increased risk of RSV or a respiratory or any type of infection within 6 months of SARS-CoV-2 infection, compared with influenza and other respiratory illnesses.

Multiple myeloma evolution is characterized by the accumulation of genomic drivers over time. To unravel this timeline and its impact on clinical outcomes, we analyzed 421 whole-genome sequences from 382 patients. Using clock-like mutational signatures, we estimated a time lag of two to four decades between the initiation of events and diagnosis. We demonstrate that odd-numbered chromosome trisomies in patients with hyperdiploidy can be acquired simultaneously with other chromosomal gains (for example, 1q gain). We show that hyperdiploidy is acquired after immunoglobulin heavy chain translocation when both events co-occur. Finally, patients with early 1q gain had adverse outcomes similar to those with 1q amplification (>1 extra copy), but fared worse than those with late 1q gain. This finding underscores that the 1q gain prognostic impact depends more on the timing of acquisition than on the number of copies gained. Overall, this study contributes to a better understanding of the life history of myeloma and may have prognostic implications.

BACKGROUND/UNASSIGNED:Social determinants of health (SDoH) contribute to disparities in SARS-CoV-2 infection, but their associations with long COVID are unknown. OBJECTIVE/UNASSIGNED:To determine associations between SDoH at the time of SARS-CoV-2 infection and risk for long COVID. DESIGN/UNASSIGNED:Prospective observational cohort study. SETTING/UNASSIGNED:33 states plus Washington, DC, and Puerto Rico. PARTICIPANTS/UNASSIGNED:Adults (aged ≥18 years) enrolled in RECOVER-Adult (Researching COVID to Enhance Recovery) between October 2021 and November 2023 who were within 30 days of SARS-CoV-2 infection; completed baseline SDoH, comorbidity, and pregnancy questionnaires; and were followed prospectively. MEASUREMENTS/UNASSIGNED:Social risk factors from SDoH baseline questionnaires, ZIP code poverty and household crowding measures, and a weighted score of 11 or higher on the Long COVID Research Index 6 months after infection. RESULTS/UNASSIGNED:Among 3787 participants, 418 (11%) developed long COVID. After adjustment for demographic characteristics, pregnancy, disability, comorbidities, SARS-CoV-2 severity, and vaccinations, financial hardship (adjusted marginal risk ratio [ARR], 2.36 [95% CI, 1.97 to 2.91]), food insecurity (ARR, 2.36 [CI, 1.83 to 2.98]), less than a college education (ARR, 1.60 [CI, 1.30 to 1.97]), experiences of medical discrimination (ARR, 2.37 [CI, 1.94 to 2.83]), skipped medical care due to cost (ARR, 2.87 [CI, 2.22 to 3.70]), and lack of social support (ARR, 1.79 [CI, 1.50 to 2.17]) were associated with increased risk for long COVID. Living in ZIP codes with the highest (vs. lowest) household crowding was also associated with greater risk (ARR, 1.36 [CI, 1.05 to 1.71]). LIMITATION/UNASSIGNED:Selection bias may influence observed associations and generalizability. CONCLUSION/UNASSIGNED:Participants with social risk factors at the time of SARS-CoV-2 infection had greater risk for subsequent long COVID than those without. Future studies should determine whether social risk factor interventions mitigate long-term effects of SARS-CoV-2 infection. PRIMARY FUNDING SOURCE/UNASSIGNED:National Institutes of Health.

BACKGROUND:Nonattendance at new patient appointments leads to missed opportunities for engagement in care, lost revenue, and suboptimal resource utilization. OBJECTIVE:To assess the effectiveness of outreach calls to new patients, prioritized by a no-show predictive algorithm and conducted by volunteers, on visit attendance. DESIGN/METHODS:Rapid randomized quality improvement project. PARTICIPANTS/METHODS:Patients with new patient appointments at an urban safety-net adult primary care clinic scheduled to occur between August 1, 2024 and September 30, 2024. INTERVENTION/METHODS:Estimated probability of visit no-show for patients was calculated using a predictive algorithm embedded in the electronic health record and used to sort lists of patients with upcoming appointments. Every other patient received an outreach call from a trained volunteer within 3 business days of their appointment plus usual automated reminder messages versus usual automated reminder messages alone. MAIN MEASURES/METHODS:New patient visit attendance compared between intervention and control groups. We conducted subgroup analyses of attendance by visit modality (in-person vs. telehealth), preferred language, and quartile of predicted no-show probability. KEY RESULTS/RESULTS:Patients in the intervention group (n = 281) had higher visit attendance than those in the control group (n = 280): 68.0% versus 54.1% (p < 0.01). There was a significant difference in attendance for in-person (70.7% vs. 51.7%; p < 0.01) but not telehealth (60.6% vs. 61.2%; p = 0.94) visits. Patients who preferred English had the biggest increase in attendance (17.2%; p < 0.01). Patients in the second and third quartiles of predicted no-show probability (31%-38% and 39%-45% predicted probability) had the biggest increases in attendance (22.2% [p = 0.01] and 15.4% [p = 0.05]). CONCLUSIONS:Outreach calls for new patients, prioritized by a no-show predictive algorithm and conducted by volunteers, can be a feasible and effective approach to improving visit attendance in a targeted fashion. Further investigation is needed to understand how to better support non-English preferring patients and patients with telehealth appointments.

Guideline-directed medical therapy is the backbone of heart failure treatment. However, patients continue to experience heart failure symptoms, impaired quality of life, and reduced functional status despite guideline-directed medical and device treatment. There is a void in treatment alternatives between guideline-directed therapy and the advanced heart failure surgical options of heart transplant (HT) and left ventricular assist device (LVAD). Cardiac contractility modulation and baroreceptor activation therapies are shown to improve heart failure symptoms, quality of life, and exertional capacity in select patients and complement our current treatment paradigm. The purpose of this paper is to review these novel Food and Drug Administration (FDA)-approved heart failure therapies and facilitate the identification of appropriate candidates.