Faculty Bibliography

OBJECTIVE:To investigate the relationship between platelet indices (count, size and production/immaturity) and hypertensive disorders of pregnancy. STUDY DESIGN/METHODS:This was a secondary analysis of a prospective cohort of pregnant individuals followed from first trimester through delivery at an academic tertiary care institution. Routine platelet indices obtained prospectively during prenatal care and delivery were compared between those who developed a hypertensive disorder of pregnancy and those who did not. We assessed platelet count (by trimester), mean platelet volume, and immature platelet fraction measured as percent (%) and absolute count. Data were analyzed using Fisher's Exact test, chi-square test, and multivariable logistic regression. P < 0.05 was considered statistically significant. RESULTS: = 0.01) compared to those without a hypertensive disorder of pregnancy, after adjusting for age, race/ethnicity, obesity, nulliparity, and chronic hypertension. The prevalence and likelihood of a hypertensive disorder of pregnancy increased with increasing mean platelet volume, as well as with both the percent and absolute immature platelet fraction. There was no difference between groups in platelet count in the first trimester, second trimester, or at delivery. CONCLUSIONS:An increase in platelet size and immaturity was observed in those with a hypertensive disorder of pregnancy. These data support further investigation of platelets in the mechanisms of the development of hypertensive disorders of pregnancy and the use of platelet indices to better identify high risk groups in pregnancy.

BACKGROUND:Loneliness is a quality-of-life (QoL) concern for patients facing serious, life-limiting illnesses. Discerning risk factors of loneliness in palliative care patients allows providers to take preventative action and develop holistic treatment plans. METHODS:A planned sub-study of patients who completed the previously developed Three-Item Loneliness Scale upon enrollment into the multicenter, randomized clinical trial Emergency Medicine Palliative Care Access (EMPallA) with the objective of investigating the association of multimorbidity with loneliness in patients with late-stage illnesses. The EMPallA study included patients who were at least 50 years old and diagnosed with at least one end-stage illness (advanced cancer, advanced congestive heart failure (CHF), end-stage renal disease (ESRD), or advanced chronic obstructive pulmonary disease (COPD)). RESULTS:We analyzed 1,212 surveys using a mixed-effects logistic regression model. Our findings suggest those with a single illness are less likely to be lonely than those with multimorbidity (odds ratio [OR] = 0.5, 95% CI 0.3 to 0.8). Additionally, older age was associated with less loneliness (OR comparing age by 10-year increments is 0.7 [95% CI: 0.6 to 0.9]), after adjusting for disease type, education level, race, sex, immigrant status, having a caregiver, COVID-19 period, language, and site geographic location. CONCLUSIONS:Patients suffering from multimorbidity self-report being "very lonely" more often than patients with a single advanced illness; furthermore, advanced illness patients who were middle-aged (versus elderly) were 25% more likely to report being "very lonely." TRIAL REGISTRATION/BACKGROUND:Clinicaltrials.gov identifier: NCT03325985. Registered October 30, 2017.

BACKGROUND:Smoking among adults in substance use disorder (SUD) treatment programs is common with limited success in quitting. Given e-cigarettes' potential for smoking harm reduction, it is important to examine e-cigarette use among people in SUD treatment. METHODS:We analyzed data from adults who have received SUD treatment in the past year, from the 2020-2021 National Survey on Drug Use and Health (N = 1,246). We delineated correlates of lifetime and current (past-month) use e-cigarette use. RESULTS:Among adults receiving SUD treatment, an estimated 39.4 % (95 % CI: 34.1, 45.1) have used e-cigarettes in their lifetime and 19.5 % (95 % CI: 16.1, 23.6) of those currently vape. Among those reporting current vaping, an estimated 57.3 % (95 % CI: 44.9-68.8) currently smoke cigarettes and half (54.2 % [95 % CI: 41.1-66.7]) currently use cannabis. Compared to those who only received treatment for alcohol use disorder, those receiving treatment for drug use (aPR = 1.47, 95 % CI: 1.09-1.99) and alcohol and drug use (aPR = 1.60, 95 % CI: 1.16-2.22) had higher prevalence of lifetime e-cigarette use, and those reporting treatment for drug use only (aPR = 2.60, 95 % CI: 1.52-4.46) and alcohol and drug use (aPR = 2.82, 95 % CI: 1.63-4.87) also had higher prevalence of current e-cigarette use. CONCLUSIONS:The prevalence of e-cigarette use was higher among those in treatment for both drug or alcohol and drugs only than those receiving treatment for only alcohol use. Smoking harm reduction interventions can potentially include e-cigarette among those receiving drug treatment. There is also a need to address challenges of dual e-cigarette and cigarette use, as well as dual e-cigarette use with cannabis.

The benefits and challenges of electronic health records (EHRs) as data sources for clinical and epidemiologic research have been well described. However, several factors are important to consider when using EHR data to study novel, emerging, and multifaceted conditions such as postacute sequelae of SARS-CoV-2 infection or long COVID. In this article, we present opportunities and challenges of using EHR data to improve our understanding of long COVID, based on lessons learned from the National Institutes of Health (NIH)-funded RECOVER (REsearching COVID to Enhance Recovery) Initiative, and suggest steps to maximize the usefulness of EHR data when performing long COVID research.

BACKGROUND:Current guidelines recommend the resection of main duct- (MD) and mixed-type (MT) intraductal papillary mucinous neoplasms (IPMN) based on specific risk criteria to prevent or treat pancreatic cancer in selected patients. This paradigm follows high rates of malignancy observed in published surgical series. The aim of this systematic review and meta-analysis was to provide robust, pooled rates of invasive carcinoma (IC) and high-grade dysplasia (HGD) in resected MD- and MT-IPMNs of the pancreas. METHODS:The PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL databases were systematically searched. Studies that reported rates of IC or HGD, diagnosed by histopathology of surgical specimens, in MD- or MT-IPMNs were included. Pooled prevalence with 95 % confidence interval (95 % CI) was calculated using a random effects model. Galbraith plots were used to evaluate heterogeneity. Risk of bias was assessed using the National Institutes of Health Quality Assessment Tool. RESULTS:Based on 51 studies, 59 % (95 % CI: 54 %, 64 %) of resected MD- and MT-IPMN had IC or HGD, with IC in up to 39 % (95 % CI: 33 %, 44 %) of lesions and HGD in 20 % (95 % CI: 16 %, 25 %). Most studies were deemed to be of good quality and Galbraith plots demonstrated high concordance. CONCLUSIONS:These results confirm the rates of IC and HGD in resected MD/MT-IPMNs. However, a significant proportion of patients have benign lesions, and future research is needed to develop precise diagnostics to distinguish between patients with and without high-risk or cancerous disease.

BACKGROUND:Results from national surveys indicate that many older adults reported delayed medical care during the acute phase of the COVID-19 pandemic, yet few studies have used objective data to characterize healthcare utilization among vulnerable older adults in that period. In this study, we characterized healthcare utilization during the acute pandemic phase (March 7-October 6, 2020) and examined risk factors for total disruption of care among older adults with multiple chronic conditions (MCC) in New York City. METHODS:This retrospective cohort study used electronic health record data from NYC patients aged ≥ 50 years with a diagnosis of either hypertension or diabetes and at least one other chronic condition seen within six months prior to pandemic onset and after the acute pandemic period at one of several major academic medical centers contributing to the NYC INSIGHT clinical research network (n=276,383). We characterized patients by baseline (pre-pandemic) health status using cutoffs of systolic blood pressure (SBP) < 140mmHg and hemoglobin A1C (HbA1c) < 8.0% as: controlled (below both cutoffs), moderately uncontrolled (below one), or poorly controlled (above both, SBP > 160, HbA1C > 9.0%). Patients were then assessed for total disruption versus some care during shutdown using recommended care schedules per baseline health status. We identified independent predictors for total disruption using logistic regression, including age, sex, race/ethnicity, baseline health status, neighborhood poverty, COVID infection, number of chronic conditions, and quartile of prior healthcare visits. RESULTS:Among patients, 52.9% were categorized as controlled at baseline, 31.4% moderately uncontrolled, and 15.7% poorly controlled. Patients with poor baseline control were more likely to be older, female, non-white and from higher poverty neighborhoods than controlled patients (P < 0.001). Having fewer pre-pandemic healthcare visits was associated with total disruption during the acute pandemic period (adjusted odds ratio [aOR], 8.61, 95% Confidence Interval [CI], 8.30-8.93, comparing lowest to highest quartile). Other predictors of total disruption included self-reported Asian race, and older age. CONCLUSIONS:This study identified patient groups at elevated risk for care disruption. Targeted outreach strategies during crises using prior healthcare utilization patterns and disease management measures from disease registries may improve care continuity.

BACKGROUND:Given the cardiovascular, renal, and survival benefits of GLP-1 receptor agonists for diabetes, these agents could be effective among kidney transplant recipients. However, kidney transplant recipients are distinct from GLP-1 receptor agonist trial participants, with longer diabetes duration and severity, greater end-organ damage, increased cardiovascular risk, and multimorbidity. We examined GLP-1 receptor agonist real-world effectiveness and safety in kidney transplant recipients with diabetes. METHODS:This USA-based retrospective cohort study included kidney transplant recipients with type 2 diabetes at transplantation and Medicare as their primary insurance from a national registry linked with Medicare claims. Post-transplantation GLP-1 receptor agonist use was identified through Medicare claims. Death-censored graft loss was estimated using the Fine-Gray sub-distribution hazard model and extended Cox models were used for mortality and safety endpoints. Models incorporated inverse probability of treatment weights. To further test whether bias could affect the main results, a cohort was created in which each GLP-1 receptor agonist user was matched with a kidney transplant recipient who had not started a GLP-1 receptor agonist, was alive with a functioning graft, and had accrued the same amount of post-transplant survival time. FINDINGS/RESULTS:Between Jan 1, 2013 and Dec 31, 2020, we identified 44 536 first time kidney transplant recipients with Medicare as primary payer in the 6 months before and at transplantation. 24 192 patients were excluded as they did not have type 2 diabetes. 2328 patients were ineligible (1916 had missing values and 412 used GLP-1 receptor agonists before transplantation). The primary cohort thus consisted of 18 016 kidney transplant recipients with diabetes. Of these patients, 1969 (10·9%) had at least one GLP-1 receptor agonist prescription filled post-transplant. Compared with patients who had not received a GLP-1 receptor agonist, GLP-1 receptor agonist users were younger (median age at transplant 57 years [IQR 49-64] vs 60 years [51-66], p<0·0001) and more likely to be female (786 [39·9%] vs 5645 [35·2%], p<0·0001). Among GLP-1 receptor agonist users, 552 [28·0%] were non-Hispanic White, 703 [35·7%] were non-Hispanic Black, and 568 [28·8%] were Hispanic. The 5-year unadjusted cumulative incidence of death-censored graft loss from a cohort matched on survival time before GLP-1 receptor agonist initiation was 6·0% for GLP-1 receptor agonist users and 10·7% for non-users (Gray's test p=0·004). The 5-year unadjusted cumulative incidence for mortality from a cohort matched on survival time before GLP-1 receptor agonist initiation was 17·0% for GLP-1 receptor agonist users and 25·8% for non-users (log-rank p=0·0006). The 5-year unadjusted cumulative incidence for mortality was 13·5% for GLP-1 receptor agonist users and 19·9% for non-users (log-rank p<0·0001). GLP-1 receptor agonist use was associated with a 49% lower incidence of death-censored graft loss (adjusted subhazard ratio [aSHR] 0·51, 95% CI 0·36-0·71; p=0·0001) and 31% lower mortality (adjusted hazard ratio [aHR] 0·69, 95% CI 0·55-0·86; p=0·001). Inferences were robust when matched on survival time (death-censored graft loss aSHR 0·53, 95% CI 0·37-0·75; p=0·0005; mortality aHR 0·70, 95% CI 0·55-0·88; p=0·003). Safety endpoints were rare and not associated with GLP-1 receptor agonists, with the exception of diabetic retinopathy (aHR 1·49, 1·11-2·00; p=0·008). INTERPRETATION/CONCLUSIONS:GLP-1 receptor agonists were associated with better graft and patient survival. Clinical trials are needed to confirm these findings. FUNDING/BACKGROUND:National Institutes of Health.

IMPORTANCE/UNASSIGNED:The US health care sector accounts for about 8.5% of national greenhouse gas (GHG) emissions. Reliable estimates of emissions associated with health care-related travel are essential for informing policy changes. OBJECTIVE/UNASSIGNED:To generate a comprehensive national estimate of carbon emissions due to patient health care-related travel in the US. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cross-sectional study used data from the 2022 National Household Travel Survey (NHTS), conducted from January 2022 to January 2023. Participants were selected using an address-based sample from the US Postal Service Delivery Sequence File. Participating households reported all trips taken within 24 hours by all household members aged 5 years or older. Approximate emissions per mile were obtained from typical vehicle emissions data provided by US government institutions. Data were analyzed between March 11 and May 29, 2024. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Estimated annual CO2 equivalent (CO2e) emissions from patient health care-related travel per year, per patient, per trip, and per mile. A survey-weighted λ regression analysis was used to identify factors associated with higher CO2e emissions per trip. An alternative scenario analysis estimated reductions if 30% or 50% of private vehicle users switched to electric vehicles. RESULTS/UNASSIGNED:The sample included 16 997 participants with a weighted total of 3 506 325 536 US health care trips. Of these trips, 52.0% were reported by female travelers, 80.1% were made in urban areas, and 19.9% were made in rural areas. These trips accounted for 84 057 963 340 miles, resulting in weighted annual estimated emissions of 35.7 megatons (Mt) (95% CI, 27.5-43.9 Mt) CO2e. Each mile traveled generated an estimated 424 g (95% CI, 418-428 g) CO2e. Emissions per trip were higher (exponentiated coefficient [exp(β)], 2.19; 95% CI, 1.51-2.86; P < .001) for rural patients compared with urban patients. However, 69.3% of emissions were attributable to urban patients and 30.7% to rural patients. Patients with annual median household incomes of $50 000 to $99 999 generated higher trip emissions (exp[β], 1.92; 95% CI, 1.09-2.76; P = .003) compared with those with incomes of $25 000 or less. A 30% shift to electric vehicles was estimated to reduce health care-related carbon emissions to 27.6 Mt (95% CI, 20.7-34.6 Mt) CO2e, and a 50% shift was estimated to lower emissions to 22.3 Mt (95% CI, 16.0-28.6 Mt) CO2e. CONCLUSIONS AND RELEVANCE/UNASSIGNED:This cross-sectional study estimated that annual patient health care-related travel in the US generated 35.7 Mt CO2e, which accounts for a small but important proportion of total health care-related emissions in the US. These findings are essential for informing health care policy decisions and suggest that strategies such as telehealth and the adoption of electric vehicles may contribute to a small but significant reduction in health care-related GHG emissions.

BACKGROUND:Visual symptoms are common after concussion. Rapid automatized naming (RAN) tasks are simple performance measures that demonstrate worse time scores in the setting of acute or more remote injury. METHODS:We evaluated the capacity for the Mobile Universal Lexicon Evaluation System (MULES) and Staggered Uneven Number (SUN) testing to be feasibly administered during preseason testing in a cohort of youth ice hockey athletes using a novel computerized app, the Mobile Integrated Cognitive Kit (MICK). Participants from a youth hockey league underwent preseason testing. RESULTS:Among 60 participants, the median age was 13 years (range 6-17). The median best time for the MULES was 49.8 seconds (range = 34.2-141.0) and the median best time for the SUN was 70.1 (range = 36.6-200.0). As is characteristic of timed performance measures, there were learning effects between the first and second trials for both the MULES (median improvement = 10.6 seconds, range = -32.3 to 92.0, P < 0.001, Wilcoxon signed-rank test) and SUN (median improvement = 2.4 seconds, range= -8.0 to 15.1, P = 0.001, Wilcoxon signed-rank test). Age was a predictor of best baseline times, with longer (worse) times for younger participants for MULES (P < 0.001, rs = -0.67) and SUN (P < 0.001, rs = -0.54 Spearman rank correlation). Degrees of learning effect did not vary with age (P > 0.05, rs = -0.2). CONCLUSIONS:Vision-based RAN tasks, such as the MULES and SUN, can be feasibly administered using the MICK app during preseason baseline testing in youth sports teams. The results suggest that more frequent baseline tests are necessary for preadolescent athletes because of the relation of RAN task performance to age.