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Browsing by Author "Raman, Subha"
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Item Clinical and Laboratory characteristics of patients with COVID-19 Infection and Deep Venous Thrombosis(Elsevier, 2020-10-22) Motaganahalli, Raghu L.; Kapoor, Rajat; Timsina, Lava R.; Gutwein, Ashley R.; Ingram, Michael D.; Raman, Subha; Roberts, Scott D.; Rahman, Omar; Rollins, David; Dalsing, Michael C.; Surgery, School of MedicineObjective: Early reports suggest that patients with novel coronavirus disease-2019 (COVID-19) infection carry a significant risk of altered coagulation with an increased risk for venous thromboembolic events. This report investigates the relationship of significant COVID-19 infection and deep venous thrombosis (DVT) as reflected in the patient clinical and laboratory characteristics. Methods: We reviewed the demographics, clinical presentation, laboratory and radiologic evaluations, results of venous duplex imaging and mortality of COVID-19-positive patients (18-89 years) admitted to the Indiana University Academic Health Center. Using oxygen saturation, radiologic findings, and need for advanced respiratory therapies, patients were classified into mild, moderate, or severe categories of COVID-19 infection. A descriptive analysis was performed using univariate and bivariate Fisher's exact and Wilcoxon rank-sum tests to examine the distribution of patient characteristics and compare the DVT outcomes. A multivariable logistic regression model was used to estimate the adjusted odds ratio of experiencing DVT and a receiver operating curve analysis to identify the optimal cutoff for d-dimer to predict DVT in this COVID-19 cohort. Time to the diagnosis of DVT from admission was analyzed using log-rank test and Kaplan-Meier plots. Results: Our study included 71 unique COVID-19-positive patients (mean age, 61 years) categorized as having 3% mild, 14% moderate, and 83% severe infection and evaluated with 107 venous duplex studies. DVT was identified in 47.8% of patients (37% of examinations) at an average of 5.9 days after admission. Patients with DVT were predominantly male (67%; P = .032) with proximal venous involvement (29% upper and 39% in the lower extremities with 55% of the latter demonstrating bilateral involvement). Patients with DVT had a significantly higher mean d-dimer of 5447 ± 7032 ng/mL (P = .0101), and alkaline phosphatase of 110 IU/L (P = .0095) than those without DVT. On multivariable analysis, elevated d-dimer (P = .038) and alkaline phosphatase (P = .021) were associated with risk for DVT, whereas age, sex, elevated C-reactive protein, and ferritin levels were not. A receiver operating curve analysis suggests an optimal d-dimer value of 2450 ng/mL cutoff with 70% sensitivity, 59.5% specificity, and 61% positive predictive value, and 68.8% negative predictive value. Conclusions: This study suggests that males with severe COVID-19 infection requiring hospitalization are at highest risk for developing DVT. Elevated d-dimers and alkaline phosphatase along with our multivariable model can alert the clinician to the increased risk of DVT requiring early evaluation and aggressive treatmentItem SCMR level II/independent practitioner training guidelines for cardiovascular magnetic resonance: integration of a virtual training environment(BMC, 2021-12-27) Patel, Amit R.; Kelle, Sebastian; Fontana, Marianna; Jacob, Ron; Stojanovska, Jadranka; Collins, Jeremy; Patel, Hena N.; Francone, Marco; Han, Yuchi; Bandettini, W. Patricia; Bucciarelli‑Ducci, Chiara; Raman, Subha; Weissman, Gaby; Medicine, School of MedicineItem Society for cardiovascular magnetic resonance recommendations for training and competency of CMR technologists(Elsevier, 2022-01) Darty, Stephen; Jenista, Elizabeth; Kim, Raymond J.; Dyke, Christopher; Simonetti, Orlando P.; Radike, Monika; Bryant, Jen; Lawton, Chris Benny; Freitag, Nicole; Shah, Dipan J.; Bucciarelli-Ducci, Chiara; Raman, Subha; Plein, Sven; Elliott, Michael D.; Medicine, School of MedicineThe Society for Cardiovascular Magnetic Resonance (SCMR) recommendations for training and competency of cardiovascular magnetic resonance (CMR) technologists document will define the knowledge, experiences and skills required for a technologist to be competent in CMR imaging. By providing a framework for CMR training and competency the overarching goal is to promote the performance of high-quality CMR and to foster the increased adoption of CMR into clinical care.Item Temporal Uncertainty Localization to Enable Human-in-the-loop Analysis of Dynamic Contrast-enhanced Cardiac MRI Datasets(ArXiv, 2023-11-13) Yalcinkaya, Dilek M.; Youssef, Khalid; Heydari, Bobak; Simonetti, Orlando; Dharmakumar, Rohan; Raman, Subha; Sharif, Behzad; Medicine, School of MedicineDynamic contrast-enhanced (DCE) cardiac magnetic resonance imaging (CMRI) is a widely used modality for diagnosing myocardial blood flow (perfusion) abnormalities. During a typical free-breathing DCE-CMRI scan, close to 300 time-resolved images of myocardial perfusion are acquired at various contrast "wash in/out" phases. Manual segmentation of myocardial contours in each time-frame of a DCE image series can be tedious and time-consuming, particularly when non-rigid motion correction has failed or is unavailable. While deep neural networks (DNNs) have shown promise for analyzing DCE-CMRI datasets, a "dynamic quality control" (dQC) technique for reliably detecting failed segmentations is lacking. Here we propose a new space-time uncertainty metric as a dQC tool for DNN-based segmentation of free-breathing DCE-CMRI datasets by validating the proposed metric on an external dataset and establishing a human-in-the-loop framework to improve the segmentation results. In the proposed approach, we referred the top 10% most uncertain segmentations as detected by our dQC tool to the human expert for refinement. This approach resulted in a significant increase in the Dice score (p < 0.001) and a notable decrease in the number of images with failed segmentation (16.2% to 11.3%) whereas the alternative approach of randomly selecting the same number of segmentations for human referral did not achieve any significant improvement. Our results suggest that the proposed dQC framework has the potential to accurately identify poor-quality segmentations and may enable efficient DNN-based analysis of DCE-CMRI in a human-in-the-loop pipeline for clinical interpretation and reporting of dynamic CMRI datasets.Item Underrepresentation in Cardiovascular Disease Clinical Trials(2023-07-28) Khan, Uzair; Raman, SubhaBackground: When it comes to inequalities in medicine, there are countless avenues through which barriers are placed that lead to worse health outcomes for marginalized groups. One inequality that isn't mentioned nearly as often is how difficult it is for marginalized groups to participate in clinical trials. As such, the results from these studies are most broadly applicable only to white men, the most common demographic to participate, as opposed to people from all races and backgrounds. The project for this summer is the first step in a longitudinal project meant to identify and address the barriers that preclude marginalized groups from participating. Methods: There are three steps to researching this underrepresentation. The first is a literature review. In this step, we searched for any existing literature about the presence of underrepresentation in cardiovascular disease (CVD) clinical trials as well as in other fields. From this literature, the results were analyzed, to ensure the validity of conducting our study, as well as the methodology of the studies, to ensure our own research will follow the established methods of other successful studies. The second is to interview experts in the field, such as others who research this topic as well as cardiologists and community leaders, to determine what barriers and solutions they believe decrease participation of POC patients. The final step is to conduct our own clinical trial that addresses those barriers by applying solutions discerned from the previous steps and creates a successful methodology to properly include underrepresented patients in the future. For this summer, we made it to the second step. Results: The literature review found that there indeed exists a discrepancy in participation of POC patients in clinical trials. Specifically, while the percent of overall nonwhite participation has increased, the number of black participants has remained the same since January of 2001, indicating that while there has been improvement in this inequality, there is still a need to improve recruitment for black participants specifically (Tahhan et al., 2020). Findings from the literature review also indicated potential barriers for underrepresented groups, including mistrust of clinical trials as a whole, time/resources constraints, and just a general lack of awareness of the existence of clinical trials (Clark et al., 2019). While determining solutions is part of the future directions of this study, Clark, et al. seems to suggest that the best solutions will address the interface between patients, physicians, and clinical trial teams on all 3 levels. One final conclusion from the literature review is the fact that there was “no price to pay for achieving diversity” (Batchelor et al., 2021). In looking at studies all over the country from 2 US National Coronary Stent Registries, a higher focus on increasing racial minority groups and women did not negatively influence research site performance, and possibly could lead to lower protocol deviation rates. While the interview portion of the study has yet to be completed, we have interviewed Francine Epperson, a researcher who has investigated barriers to black patient participation in Alzheimer’s clinical trials. Her study concluded that one facilitator to increase black participation is a “return of results to make informed decisions about their health” (Eliacin et al., 2023). Too often, clinical trials take results from participants and apply them elsewhere, with their participants being none the wiser as to what they helped accomplish. By applying and sharing the results of the studies to the communities that are recruited, we establish trust and a continued partnership, something that is desperately needed to help address the underrepresentation in cardiovascular disease clinical trials. Future Directions: The next steps in this project include conducting expert interviews, including cardiologists but also public health and community leaders, to determine barriers to participation and potential solutions. The final step involves consolidating the first two steps into solutions that can be used to conduct a clinical trial that minimizes barriers and increases rates of nonwhite participation. Citations: Batchelor, W. B., Damluji, A. A., Yong, C., Fiuzat, M., Barnett, S. D., Kandzari, D. E., Sherwood, M. W., Epps, K. C., Tehrani, B. N., Allocco, D. J., Meredith, I. T., Lindenfeld, J., O'Connor, C. M., & Mehran, R. (2021). Does study subject diversity influence cardiology research site performance?: Insights from 2 U.S. National Coronary Stent Registries. Am Heart J, 236, 37-48. https://doi.org/10.1016/j.ahj.2021.02.003 Clark, L. T., Watkins, L., Pina, I. L., Elmer, M., Akinboboye, O., Gorham, M., Jamerson, B., McCullough, C., Pierre, C., Polis, A. B., Puckrein, G., & Regnante, J. M. (2019). Increasing Diversity in Clinical Trials: Overcoming Critical Barriers. Curr Probl Cardiol, 44(5), 148-172. https://doi.org/10.1016/j.cpcardiol.2018.11.002 Eliacin, J., Polsinelli, A. J., Epperson, F., Gao, S., Van Heiden, S., Westmoreland, G., Richards, R., Richards, M., Campbell, C., Hendrie, H., Risacher, S. L., Saykin, A. J., & Wang, S. (2023). Barriers and facilitators to participating in Alzheimer's disease biomarker research in black and white older adults. Alzheimer's & Dementia: Translational Research & Clinical Interventions, 9(2). https://doi.org/10.1002/trc2.12399 Tahhan, A. S., Vaduganathan, M., Greene, S. J., Alrohaibani, A., Raad, M., Gafeer, M., Mehran, R., Fonarow, G. C., Douglas, P. S., Bhatt, D. L., & Butler, J. (2020). Enrollment of Older Patients, Women, and Racial/Ethnic Minority Groups in Contemporary Acute Coronary Syndrome Clinical Trials. JAMA Cardiology, 5(6), 714. https://doi.org/10.1001/jamacardio.2020.0359