Atreya Mishra

Beyond LDL-C: Modern Lipid Management for ASCVD Prevention in Primary Care

Adis journals on behalf of:, A. C. Carlson, Zaid Zayyad, Stefanie Driesenga et autres

The above infographic represents the opinions of the authors. For a full list of declarations, including funding and author disclosure statements, and copyright information, please see the full text online (see “read the peer-reviewed publication” opposite).

Beyond LDL-C: Modern Lipid Management for ASCVD Prevention in Primary Care

Adis journals on behalf of:, A. C. Carlson, Zaid Zayyad, Stefanie Driesenga et autres

The above infographic represents the opinions of the authors. For a full list of declarations, including funding and author disclosure statements, and copyright information, please see the full text online (see “read the peer-reviewed publication” opposite).

Beyond LDL-C: Modern Lipid Management for ASCVD Prevention in Primary Care

Andrew Carlson, Zaid Zayyad, Stefanie Driesenga, Peter Boxley et autres

Prevention of atherosclerotic cardiovascular disease (ASCVD) is fundamental for both cardiologists and primary care physicians. From risk estimation to medical therapy for primary and secondary prevention, management is evolving with increasing evidence. Risk estimation is moving toward a model that emphasizes lifetime …

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C-55 | A Challenge to the Obesity Paradox: The Correlation Between BMI and Frailty in TAVR Outcomes

Zachary Natsheh, David Tiu, Rohan Bhattaram, Andrew M. Carlson et autres

Frailty increases risk after Transcatheter Aortic Valve Replacement (TAVR). While elevated body mass index (BMI) is a health risk, prior studies found that higher BMI experienced better outcomes post-TAVR, demonstrating an obesity paradox. We investigated the combined impact of frailty and BMI …

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E-71 | Does the Obesity Paradox Hold its Shape? Cardiac Remodeling Post-TAVR in the Context of Body Mass Index and Frailty

Zachary Natsheh, David Tiu, Rohan Bhattaram, Andrew M. Carlson et autres

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F-98 | Using the Past to Plan for the Future: A Machine Learning Model for Forecasting Post-TAVR Length of Stay

Arvind Draffen, Adriana Ene, Andrew M. Carlson, Azmer Khan et autres

Accurate prediction of length of stay (LOS) post-transcatheter aortic valve replacement (TAVR) is important for optimizing resources, improving patient outcomes, and reducing costs. Machine learning (ML) can be used to uncover patterns and offer predictive insight from large or complex datasets. This …

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C-3 | New Valve, Old Problem: Predicting HF admissions following TAVR

Pooja Acharya, Azmer Khan, Andrew M. Carlson, Pal Shah et autres

Heart failure with preserved ejection fraction (HFpEF) is common among patients undergoing Transcatheter Aortic Valve Replacement (TAVR), yet predictors of post-procedural heart failure (HF) hospitalization remain undercharacterized.

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C-16 | Shared Care, Shared Outcomes: TAVR Performance Across Veterans Affairs and Academic Partner Institutions

Cynthia Chen, Bayan Hammad, Andrew M. Carlson, Azmer Khan et autres

Though transcatheter aortic valve replacement (TAVR) is widely used for treating severe aortic stenosis, many VA hospitals lack in-house programs, requiring referral to academic medical centers (AMCs), though outcomes data from this model are limited. We compared clinical outcomes between VA and …

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C-85 | How Much Contrast Is Too Much? Use of the Mehran Risk Score in Transcatheter Aortic Valve Replacement

Omar Uraizee, Andrew M. Carlson, Vidur Gurbuxani, Rohan Bhattaram et autres

Contrast-induced nephropathy (CIN) is the third most common cause of hospital acquired renal failure. Risk stratification tools, such as the Mehran risk score and the contrast volume: maximum allowable contrast dose (MACD) ratio, are used to predict contrast-induced acute kidney injury (CI-AKI) …

C-46 | Time to TAVR: Investigating the Impact of Prolonged Wait Times

Laura Navarro, Runze Zhang, Sofiy Lougin, Rohan Bhattaram et autres

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C-84 | Weighing the Evidence: Impact of Body Mass Index on Short- and Long-Term Outcomes Following Transcatheter Aortic Valve Replacement

David Tiu, Pal Shah, Zachary Natsheh, Andrew M. Carlson et autres

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C-11 | Predicting the Future: Using Machine Learning to Predict Adverse Outcomes after TAVR

Rohan Bhattaram, Suhas Seshadri, Andrew M. Carlson, Azmer Khan et autres

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