Mitchel L. Zoler, PhD
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News
Imaging recommendations issued for COVID-19 patients
April 16, 2020
An expert panel organized by the Fleischner Society made recommendations on using chest radiography or CT in hospitalized COVID-19 patients.
News
Evidence suggests possible RAS-blocker benefit in COVID-19 patients
April 16, 2020
Animal findings and physiologic mechanisms suggest RAS system inhibitors may benefit COVID-19 patients, another reason not to stop these drugs.
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Wuhan data link COVID-19 with myocardial damage
March 27, 2020
Findings from 603 COVID-19 patients at two Wuhan hospitals showed a high incidence of myocardial damage that predisposes to higher mortality.
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COVID-19 critical care guideline offers support for frontline clinicians
March 25, 2020
The target users of this guideline are frontline clinicians, allied health professionals, and policy makers involved in the care of patients with COVID-19 in the ICU.
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COVID-19: U.S. cardiology groups reaffirm continued use of RAAS-active drugs
March 18, 2020
Experts give ACE inhibitors and ARBs, cornerstones of cardiology therapy, a thumbs up despite a hypothetical adverse COVID-19 effect.
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ICH survival lags in the community setting
March 17, 2020
LOS ANGELES – An observed 6-month mortality of 64% in a Dutch study contrasts with better survival in interventional trials.
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Get With the Guidelines – Stroke targets ICH
March 17, 2020
A 17-year old U.S. program for quality improvement of ischemic stroke care will start to include ICH patients.
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AUGUSTUS: Apixaban surpassed warfarin despite prior stroke or thromboembolism
March 7, 2020
LOS ANGELES – Secondary AUGUSTUS analysis showed ACS/PCI patients with AFib plus prior stroke, TIA, or thromboembolism did better on apixaban.
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AFib patients do best on a DOAC started 7-10 days post stroke
March 4, 2020
LOS ANGELES – Observational data hints at the best time to start oral anticoagulation in AFib patients after a cardioembolic stroke.
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AI algorithm finds diagnostic AFib signatures in normal ECGs
February 26, 2020
NATIONAL HARBOR, MD. – Machine learning created software that can reliably detect a signal of past or impending AFib in a normal-appearing ECG recording.
