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Richa Agarwal

Richa Agarwal

· Associate Professor of MedicineVerified

Duke University · Medicine

Active 2007–2026

h-index15
Citations876
Papers12365 last 5y
Funding
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Research topics

  • Physical therapy
  • Medicine
  • Internal medicine
  • Nursing

Selected publications

  • From Awareness to Advantage: A Study of Green HRM

    Springer proceedings in business and economics · 2026-01-01

    book-chapter1st authorCorresponding
  • Analyzing employee attrition of research and development firms using mixed methods

    Cogent Business & Management · 2025-10-01

    articleOpen access

    Employees are the assets of an organization as they are the source of an indispensable and sustainable competitive advantage. Employee attrition is critical to the knowledge-intensive Research and Development (R&D) industry due to information loss. When employee joins the competing organization, and he transfer his key expertise/ competencies to competing organization. The present study collected empirical data from 457 samples through a survey. Grounded in Herzberg’s motivation-hygiene theory, this study employs a mixed-method approach, integrating logistic regression with semi-structured interviews, to examine attrition drivers in Indian R&D firms. By synthesizing fairness, tangible benefits, workplace relationships, and workplace stress, the study offers novel insights into retention challenges specific to knowledge-intensive environments. The study is distinct as we did not find significant studies that discuss the concerns and expectations of highly skilled employees to improve retention rates. The present study also addresses methodological gaps, as we did not find significant studies that used both logistic regression using machine learning and semi-structured interviews to analyze employee attrition of R&D firms. The findings of the study reveal that both intrinsic and extrinsic factors are accountable for employee attrition in R&D firms.

  • Abstract 4367166: A Multicenter Study of Detection of Pulmonary Hypertension Based on Point-of-Care 12- Lead ECG Data

    Circulation · 2025-11-03

    article

    Background: Pulmonary hypertension (PH) is a life-threatening disease affecting up to 1% of the global population. Diagnosis can be challenging and is often delayed due to the need for advanced imaging and invasive procedures. The use of artificial intelligence applied to ECGs (ECG-AI) has been shown to detect subtle patterns in voltage-time data and may be a valuable tool for the early detection of PH. Hypothesis and Purpose: To evaluate the performance of a previously trained, ECG-AI algorithm to detect PH (ECG-AI PH) using real-world data (RWD) collected in a multicenter, validation study. A joint primary hypothesis required sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) to exceed the null values of 76%, 70%, 10% and 90%. Study Design and Methods: This retrospective validation study was conducted at 5 geographically diverse U.S. health systems. Adult subjects were eligible for inclusion if they had a 12-lead ECG paired with an echocardiogram (Echo) in which tricuspid regurgitation velocity (TRV) was recorded, following presentation with dyspnea. Patients were classified according to echocardiographic criteria as either PH (PH+, TRV >3.4 m/s) or controls (PH-, TRV ≤2.8 m/s) to simulate the real-world use of ECG-AI, where a positive result could lead to a follow-up Echo. The study database was locked before processing the digital ECGs with ECG-AI PH. Performance was also estimated in a subset of subjects that later had a right heart catheterization using mPAP ≥ 20mmHg as the definition of PH. Results: A total of 14281 subjects (53% female, 63% aged 50+ years) met the inclusion criteria, including 3019 PH+ cases and 11262 PH- controls (Figure). Sn and Sp were 84.0% (95% CI: 82.6%, 85.3%) and 71.7% (95% CI: 70.9%, 72.6%), respectively. The positive and negative predictive values were 18.9% (95% CI: 18.4%, 19.4%) and 98.3% (95% CI: 98.1%, 98.4%), respectively, at 7.3% prevalence. Each endpoint met pre-defined performance criteria. In the subset of 1683 subjects with a follow up RHC, performance remained robust (Sn 85% (1155/1358); Sp 46% (151/325)). Conclusion: While ECG-AI PH was first developed as an investigational tool to detect PH, continued development as software as a medical device for clinical use demonstrated that the algorithm retained strong performance to detect PH in diverse, non-overlapping clinical settings and patient populations.

  • Pregnancy and Delivery Care for a Patient With a HeartMate 3

    JACC Case Reports · 2025-06-01 · 1 citations

    articleOpen access

    BACKGROUND: The limited available data on pregnancies among patients with left ventricular assist devices (LVADs) in situ shows elevated rates of maternal and fetal/neonatal morbidity and mortality. The first fully magnetically levitated device providing centrifugal continuous flow, HeartMate 3 (HM3, Abbott), is the only LVAD available in the United States since 2018 and has fewer adverse patient outcomes compared with previous devices. CASE SUMMARY: A 32-year-old G5P2113 woman became pregnant 19 months after destination-therapy HM3 LVAD placement. Uncomplicated antepartum care and a cesarean delivery at 34 weeks under neuraxial anesthesia was facilitated by our institution's pregnancy heart team. DISCUSSION: This represents the second reported HM3-supported pregnancy resulting in a live birth. Various barriers to care guided a shared anticoagulation plan, and no hemorrhagic or thrombotic complications occurred. Our intrapartum monitoring strategy facilitated a patient-centered delivery and postpartum experience while maintaining excellent patient safety.

  • Combined heart-lung organ allocation: A glitch in the system

    The Journal of Heart and Lung Transplantation · 2025-09-09 · 2 citations

    article
  • 59P Development and validation of a simple scoring system to identify patients with poor outcomes from resection of colorectal liver metastases (CRLM) despite technical resectability

    Annals of Oncology · 2025-07-01

    articleOpen accessSenior author
  • Withdrawal of aspirin in patients with left ventricular assist device treated with vitamin K antagonists: impact of anticoagulation quality in the randomized ARIES-HM3 trial

    European Heart Journal · 2025-11-07 · 5 citations

    articleOpen access

    BACKGROUND AND AIMS: Left ventricular assist devices (LVADs), including the HeartMate 3 (HM3), have improved outcomes in patients with advanced heart failure. Use of vitamin K antagonists (VKA) is mandated to reduce the risk of thrombotic events, but there is heterogeneity in management. Time in therapeutic range (TTR) is a crucial metric for assessing the quality of VKA management. The ARIES-HM3 trial demonstrated that aspirin can be safely omitted from the antithrombotic regimen, resulting in reduced bleeding without increased thrombosis. This pre-specified trial analysis explores the relationship of quality of VKA management assessed by TTR with haemocompatibility-related outcomes. METHODS: ARIES-HM3 was an international, randomized, double-blind, placebo-controlled study of aspirin (100 mg/day) or placebo (1:1) with VKA therapy in patients with de-novo HM3 placement. Participants were stratified into low TTR or high TTR groups based on median levels (n = 554). Primary endpoint success and secondary endpoint rates were stratified based on TTR groups. Bleeding rates at 12 months were estimated using an Andersen-Gill model with TTR as a single continuous variable, and multivariable regression analysis was performed. RESULTS: The percentage of patients with a TTR above or below the median of 56 was similar between the aspirin and placebo groups. More participants achieved primary endpoint success with TTR ≥56% (77% vs 66.9%, P = .01). Higher TTR was associated with lower bleeding rates at 12 months (26.4 vs 49.2 events per 100 participant-years; rate ratio 1.84, 95% confidence interval [CI] 1.37-2.53) without stroke increase (3.2 vs 2.8 events per 100 participant-years; rate ratio 0.88 [95% CI: 0.30-2.53]). No interaction was observed between the assigned treatment group and TTR. Modelling demonstrated a constant decrease in bleeding as a function of increasing TTR. Female sex and Black race were independent predictors of low TTR (odds ratio: 1.70 [95% CI: 1.12-2.57]; 1.62 [95% CI: 1.11-2.35], respectively), with more frequent INRs below the therapeutic range. Multivariable modelling identified age ≥65 years, aspirin use, TTR <56%, and blood urea nitrogen ≥30 mg/dL as predictors of non-surgical bleeding. CONCLUSIONS: The quality of VKA management as measured by TTR correlates with the occurrence of non-surgical bleeding in patients with the HM3 LVAD, with a lower TTR associated with an increased bleeding risk. These data provide new clinical direction to define a benchmark TTR to achieve further mitigation of residual risk of bleeding and enhance haemocompatibility with the HM3 LVAD.

  • Adiposity-related anthropometrics, cardiovascular outcomes, and finerenone in heart failure and chronic kidney disease with type 2 diabetes: a FINE-HEART analysis

    European Heart Journal · 2025-11-01

    article

    Abstract Background Excess/dysfunctional adiposity is a core pathophysiological mechanism intersecting cardiovascular (CV), kidney, and metabolic (CKM) disorders. However, the association between different adiposity-related anthropometrics and CV outcomes has not been rigorously explored in this population. Purpose To explore CV outcomes and treatment effects of finerenone according to baseline body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and waist-hip ratio (WHR). Methods In this prespecified participant-level FINE-HEART pooled analysis of FIDELIO-DKD, FIGARO-DKD, and FINEARTS-HF, CV outcomes and treatment effects of finerenone according to BMI, WC, WHtR, and WHR were evaluated using multivariable-adjusted Cox proportional hazards regression models and Poisson regression with restricted cubic splines. Independent and combined effects of BMI and WHtR were also assessed. Results Among 18,759 participants with available data for all anthropometrics, 52% had a BMI ≥30 kg/m2 (8% with BMI ≥40 kg/m2), 77% had an elevated WC, 64% had an elevated WHtR, and 91% had an elevated WHR. Among those with BMI &amp;lt;30 kg/m2, WC and WHtR were elevated in 62% and 35%, respectively. Female and older participants were more likely to have elevated WC and WHtR. Higher BMI, WC, WHtR, and WHR were each significantly associated with a wide range of CV outcomes, including CV death or heart failure (HF) hospitalization (Figure) and its individual components, major adverse cardiovascular events, and new-onset atrial fibrillation. A U-shaped association was observed between BMI and CV death, but not WC, WHtR, or WHR, for which more linear associations were observed. BMI-adjusted WHtR (adjusted hazard ratio [aHR], 1.09 per 0.05 increase; 95% CI, 1.03 to 1.11) and WHtR-adjusted BMI (aHR, 1.13 per 5 kg/m2 increase above 30 kg/m2; 95% CI, 1.04 to 1.22) were each associated with a higher rate of CV death or HF hospitalization, and participants with elevated BMI and WHtR experienced a higher rate of CV death or HF hospitalization compared with those with elevated BMI or WHtR alone (Table). Benefits of finerenone on CV death or HF hospitalization were consistent irrespective of baseline BMI (Pinteraction=0.27) or WHtR (Pinteraction=0.26), with greater absolute benefits among participants with higher BMI (absolute rate reduction [ARR] for BMI ≥40 kg/m2, 1.3 per 100 person-years; ARR for BMI 18.5-25 kg/m2, 0.6 per 100 person-years) and WC (ARR for elevated WC, 0.7 per 100 person-years; ARR for non-elevated WC, 0.5 per 100 person-years). Conclusions These findings support assessment of anthropometrics capturing abdominal adiposity, in addition to BMI, to enhance risk stratification among individuals with CKM conditions. Higher BMI and abdominal adiposity may additionally identify individuals with potential to derive greater absolute CV benefits with finerenone.Figure Table

  • Appropriate and inappropriate ICD shocks in patients with LVADs: Prevalence, associated factors, and etiologies

    Heart Rhythm · 2024-07-23 · 3 citations

    article
  • Patient Perceptions and Knowledge Surrounding Pregnancy After Heart Transplantation: A Multicenter Study

    Circulation Heart Failure · 2024-08-01 · 1 citations

    articleOpen access

    BACKGROUND: More women of childbearing age are surviving after heart transplantation (HT), many of whom have a desire to become pregnant. Limited data exist evaluating patients' perspectives, receipt of counseling, and knowledge surrounding contraception, pregnancy, breastfeeding, and medication safety after HT. METHODS: We conducted a voluntary, confidential, web-based cross-sectional survey of women who were childbearing age (defined as 18-45 years) at the time of HT. Transplants occurred between January 2005 and January 2020. Surveys were conducted across 6 high-volume HT centers in the United States. RESULTS: There were 64 responses from women who were of childbearing age at the time of HT. Twenty-five women (39.1%) were pregnant before HT, and 6 (9.4%) women reported at least 1 pregnancy post-transplant. Fifty-three percent (n=34) reported they did not receive enough information on post-HT pregnancy before listing for HT, and 26% (n=16) did not discuss their ability to become pregnant with their care team before proceeding with HT. Following HT, 44% (n=28) still felt that they had not received enough information regarding pregnancy. The majority of women (n=49, 77%) had discussed contraception to prevent unplanned pregnancy with their transplant team. Twenty percent (n=13) reported that pregnancy was never safe after transplantation based on the information they had received from their transplant providers. CONCLUSIONS: Many women feel they are not receiving adequate counseling with regard to posttransplant reproductive health. This survey highlights an opportunity to improve both provider education and patient communication to better support women with HT desiring posttransplant pregnancy.

Frequent coauthors

  • Chetan B. Patel

    24 shared
  • Raymond L. Benza

    University of Pittsburgh

    23 shared
  • Lauren K. Truby

    The University of Texas Southwestern Medical Center

    22 shared
  • Robert J. Mentz

    Duke University

    19 shared
  • Adam D. DeVore

    Duke University

    18 shared
  • Carmelo A. Milano

    17 shared
  • Amresh Raina

    Allegheny Health Network

    16 shared
  • Mardi Gomberg‐Maitland

    George Washington University

    15 shared
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