Faculty Bibliography

BACKGROUND AND HYPOTHESIS/OBJECTIVE:New equations to estimate GFR based on creatinine (eGFRcr), cystatin C (eGFRcys) or both (eGFRcr-cys) have been developed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and the European Kidney Function Consortium (EKFC). There is a need to evaluate the performance of these equations in diverse European settings to inform implementation decisions, especially among people with key comorbid conditions. METHODS:We performed a cross-sectional study including 6174 adults referred for single-point plasma clearance of iohexol in Stockholm, Sweden, with 9579 concurrent measurements of creatinine and cystatin C. We assessed the performance of the CKD-EPI 2009/2012/2021, EKFC 2021/2023, revised Lund-Malmö (RLM) 2011 and CAPA 2014 equations against measured GFR (mGFR). RESULTS:Mean age was 56 years, mGFR was 62 mL/min/1.73m2 and 40% were female. Comorbid conditions were common: cardiovascular disease (30%), liver disease (28%), diabetes (26%) and cancer (26%). All eGFRcr-cys equations had small bias and P30 close to 90%, and performed better than eGFRcr or eGFRcys equations. Among eGFRcr equations, CKD-EPI 2009 and CKD-EPI 2021 showed larger bias and lower P30 than EKFC 2021 and RLM. There were no meaningful differences in performance across eGFRcys equations. Findings were consistent across comorbid conditions, and eGFRcr-cys equations showed good performance in patients with liver disease, cancer and heart failure. CONCLUSIONS:In conclusion, eGFRcr-cys equations performed best, with minimal variation among equations in this Swedish cohort. The lower performance of CKD-EPI eGFRcr equations compared with EKFC and Lund-Malmö may reflect differences in population characteristics and mGFR methods. Implementing eGFRcr equations will require a trade-off between accuracy and uniformity across regions.

BACKGROUND:Depression ranks as the foremost mental health concern among childbearing women. Within low- and middle-income countries (LMICs), between 20 and 25% of women encounter depression during pregnancy or soon after delivery. This condition impacts not only the mothers but also their offspring. Offspring of women suffering from postnatal depression (PND) exhibit suboptimal cognitive development and increased emotional and behavioural issues throughout their growth. This scenario becomes more pronounced in LMICs, where numerous adversities further jeopardise children's developmental progress. Despite antenatal services providing a pivotal platform to address women's mental health needs, PND treatment remains inaccessible in many LMICs. The World Health Organization advocates interpersonal psychotherapy (IPT) for treating depression. While research from high-income countries has established the efficacy of IPT and group-IPT (g-IPT) for PND, its effectiveness within the LMIC context and its potential benefits for child development remain uncharted. This study seeks to gauge the potency of g-IPT for women with PND in two LMICs. METHODS:This multi-site randomised controlled trial is a continuation of two preceding phases-conceptual mapping and a feasibility study executed in Lebanon and Kenya. Insights gleaned from these phases underpin this comprehensive RCT, which contrasts the efficacy and cost-effectiveness of high-quality standard care (HQ-SC) augmented with g-IPT against HQ-SC in isolation. The trial, characterised as an individually randomised superiority assessment, targets women with postnatal depression in Beirut, Lebanon, and Nairobi, Kenya. It aims to determine if culturally tailored g-IPT, administered within community settings in both countries, outperforms HQ-SC in influencing child developmental outcomes, maternal depression, and the quality of the mother-child bond. DISCUSSION/CONCLUSIONS:The SUMMIT trial, designed with pragmatism, possesses the magnitude to evaluate g-IPT within two LMIC frameworks. It seeks to enlighten policymakers, service commissioners, professionals, and users about g-IPT's potential to alleviate maternal PND and bolster child developmental outcomes in LMICs. Additionally, the trial will generate valuable data on the clinical and economic merits of high-quality standard care. TRIAL REGISTRATION/BACKGROUND:ISRCTN, ISRCTN15154316. Registered on 27 September 2023, https://doi.org/10.1186/ISRCTN15154316.

OBJECTIVES/UNASSIGNED:The destruction of the World Trade Center (WTC) towers in New York City on September 11, 2001 (9/11), released approximately 1 million tons of pulverized particulate matter throughout southern Manhattan and areas in Brooklyn, exposing community members and responders to high levels of potentially toxic environmental particles. Asbestos exposure was a health concern because of its use in certain sections of the WTC towers. Malignant mesothelioma, originating from the lining cells (mesothelium) of the peritoneal and pleural cavities, is one complication associated with asbestos exposure. METHODS/UNASSIGNED:The WTC Environmental Health Center (WTC EHC) is a treatment and surveillance program for community members (Survivors) exposed to WTC dust and fumes. RESULTS/UNASSIGNED:In this report, we describe four cases of mesothelioma in the WTC EHC as of July 1st, 2023. Two of our patients have been diagnosed with peritoneal mesothelioma and two patients have been diagnosed with pleural mesothelioma. CONCLUSION/UNASSIGNED:Given the known delay in the development of mesotheliomas after asbestos exposure, we provide information on these early mesothelioma cases to enhance the understanding of the adverse health effects of WTC exposures on the local community.

The Family Health Centers at New York University Langone (FHC), a federally qualified health center network in New York City, created a novel clinical decision support (CDS) tool that alerts primary health care providers to patients"™ gaps in care and triggers a dynamic, individualized order set on the basis of unique patient factors, enabling providers to readily act on each patient"™s specific gaps in care. FHC implemented this tool in 2017, starting with 15 protocols for quality measures; as of February 2024, there are 30 such protocols. During a patient visit with a provider, when there is a gap in care, a best-practice alert (BPA) fires, which includes an order set unique to the patient and visit. The provider can bypass the alert (not open it) or acknowledge the alert (open it). The provider may review the content of the order set and accept it as is or with modifications, or they can decline its recommendations if they believe it is not appropriate or plan to address the gap in care another way during the visit. To accept the dynamic order set is the intended workflow. The authors present data from September 2019 to January 2023 totaling 171,319 patient visits with at least one open gap in care among providers in pediatrics, family medicine, and internal medicine. The rate at which providers acknowledged the BPA in the first 6 months was 45% and steadily increased. In the last 6 months of the period, providers acknowledged the BPA 78% (19,281 of 24,575) of the time. Similarly, in the first 6 months, in all encounters in which a BPA was fired, 28.8% (8,585 of 29,829) had an order placed via the dynamic order set (accepted); that rate increased to 49.7% (12,210 of 24,575) during the last 6 months. This order set completion rate is notable given that most CDS use rates are low. Gap closure was higher when providers acknowledged the alert. In an analysis of all encounters with at least one open gap, spanning 2019"“2023, 46% (48,431 of 105,371) of the time, at least one gap was closed when the alert was acknowledged compared with 33% (21,993 of 65,948) when the alert was bypassed (and the recommendations of the dynamic order set were never followed). The authors show that CDS tools can be successfully implemented in a high-volume, low-resource setting if designed with efficiency in mind, ensuring provider utilization and clinical impact through closing care gaps. CDS tools that are dynamically patient specific can help improve quality of care if they are part of a broader culture of quality improvement.

INTRODUCTION/BACKGROUND:Concurrent electronic nicotine delivery system (ENDS) and cigarette (dual) use is harmful. Identifying longitudinal trajectories of ENDS and cigarette use among dual users can help to determine the public health impact of ENDS and inform tobacco control policies and interventions. OBJECTIVES/OBJECTIVE:(1) To identify independent and joint trajectories of ENDS and cigarette use among wave (W) 1 adult dual users across W1 to W5 of the Population Assessment of Tobacco and Health (PATH) Study; and (2) identify W1 predictors of ENDS and cigarette joint trajectory group membership. METHODS:We used group-based trajectory modelling to estimate independent and joint trajectories of ENDS and cigarette use from wave 1 (W1; 2013-2014) to wave 5 (W5; 2018-2019) among W1 adult established dual users of ENDS and cigarettes (n=545) from the PATH Study. We used multinomial logistic regression to identify W1 predictors of joint trajectories. RESULTS:Two ENDS (early quitters=66.0%, stable users=34.0%) and three cigarette (stable users=55.2%, gradual quitters=27.3%, early quitters=17.5%) trajectories of W1 were identified. In joint trajectory analysis, 41.6% of participants were early ENDS quitters and stable cigarette users; 14.8% early ENDS quitters and gradual cigarette quitters; 14.6% stable ENDS users and stable cigarette users; 11.2% stable ENDS users and gradual cigarette quitters; 10.3% early ENDS quitters and early cigarette quitters; and 7.4% stable ENDS users and early cigarette quitters. Cigarette and ENDS use frequency, nicotine dependence, cannabis use and other non-combusted tobacco product use predicted trajectory group membership (p values <0.05). CONCLUSIONS:Most dual users maintained long-term cigarette smoking or dual use, highlighting the need to address cessation of both products. Continued monitoring of trajectories and their predictors is needed, given ongoing changes to the ENDS marketplace.

BACKGROUND/UNASSIGNED:(p-tau), as well as the trajectories of these CSF measures obtained longitudinally. RESULTS/UNASSIGNED:A total of 111 ADNI and 190 NYU participants classified as CU with available NLR, CSF, and covariate data were included. Compared to NYU, ADNI participants were older (73.79 vs. 61.53, p < 0.001), had a higher proportion of males (49.5% vs. 36.8%, p = 0.042), higher BMIs (27.94 vs. 25.79, p < 0.001), higher prevalence of hypertensive history (47.7% vs. 16.3%, p < 0.001), and a greater percentage of Aβ-positivity (34.2% vs. 20.0%, p = 0.009). In the ADNI cohort, we found cross-sectional associations between the NLR and CSF Aβ42 (β=-12.193, p = 0.021), but not t-tau or p-tau. In the NYU cohort, we found cross-sectional associations between the NLR and CSF t-tau (β = 26.812, p = 0.019) and p-tau (β = 3.441, p = 0.015), but not Aβ42. In the NYU cohort alone, subjects classified as Aβ+ (n = 38) displayed a stronger association between the NLR and t-tau (β = 100.476, p = 0.037) compared to Aβ- subjects or the non-stratified cohort. In both cohorts, the same associations observed in the cross-sectional analyses were observed after incorporating longitudinal CSF data. CONCLUSIONS/UNASSIGNED:in the younger NYU cohort. Associations persisted after adjusting for comorbidities, suggesting a direct link between the NLR and AD. However, changes in associations between the NLR and specific AD biomarkers may occur as part of immunosenescence.

BACKGROUND:Generative artificial intelligence has the potential to revolutionize health technology product development by improving coding quality, efficiency, documentation, quality assessment and review, and troubleshooting. OBJECTIVE:This paper explores the application of a commercially available generative artificial intelligence tool (ChatGPT) to the development of a digital health behavior change intervention designed to support patient engagement in a commercial digital diabetes prevention program. METHODS:We examined the capacity, advantages, and limitations of ChatGPT to support digital product idea conceptualization, intervention content development, and the software engineering process, including software requirement generation, software design, and code production. In total, 11 evaluators, each with at least 10 years of experience in fields of study ranging from medicine and implementation science to computer science, participated in the output review process (ChatGPT vs human-generated output). All had familiarity or prior exposure to the original personalized automatic messaging system intervention. The evaluators rated the ChatGPT-produced outputs in terms of understandability, usability, novelty, relevance, completeness, and efficiency. RESULTS:Most metrics received positive scores. We identified that ChatGPT can (1) support developers to achieve high-quality products faster and (2) facilitate nontechnical communication and system understanding between technical and nontechnical team members around the development goal of rapid and easy-to-build computational solutions for medical technologies. CONCLUSIONS:ChatGPT can serve as a usable facilitator for researchers engaging in the software development life cycle, from product conceptualization to feature identification and user story development to code generation. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500.