Lauren Ferrante
@lferrantemd
Intensivist, ICU outcomes researcher bridging Critical Care Medicine & Geriatrics @YalePCCSM, ATS 2024 Critical Care Program Chair, mom. Views my own
ID: 724603024220557314
25-04-2016 14:16:38
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Proud of Snigdha Jain MD, MHS and Yale School of Medicine medical student Julia Stevenson who rocked their presentations at #ATS2024! ๐๐ป๐๐ป๐๐ป ATS Crit Care Yale PCCSM Yale Pepper Center Geriatrics at Yale
Thatโs a wrap #ATS2024! Thank you ATS Crit Care Program Committee for your hard work, all of the CCA speakers, moderators, & attendees, Nuala Meyer for being a great partner/Chair-Elect to work with, & David Furfaro for leading the SECC. See you at #ATS2025!
NEW EVIDENCE Pre-post pilot study by Lauren Ferrante & Yale School of Medicine team shows Occupational therapy (within a 3-part bundle) has added value over PT/mobility for reducing delirium in older adults in ICU atsjournals.org/doi/abs/10.151โฆ See thread below #ICUrehab AOTA Kelly OT
Interested in outcomes among middle-aged & older adults after LTCH hospitalization? See new article below by Snigdha Jain MD, MHS and UCSF Geriatrics collaborators! Yale PCCSM Yale Pepper Center
โฆHelp shape ATS 2025 San Francisco - submit Scientific Proposals, Meet the Expert, and Post-Grad proposals this week! ATS Crit Careโฉ โฆATS Early Careerโฉ โฆAmerican Thoracic Society (ATS)โฉ Due 6/26!
1/n #olderadults who are hospitalized forย #Covid_19 are at โฌ๏ธrisk for delirium. In our study in JAMA Network Open , we evaluated the association between In-hospital #delirium โก๏ธ#FunctionalImpairment & #CognitiveImpairment over 6 months after hospitalization.
2๏ธโฃ J Stevenson, Lauren Ferrante, et alโs pilot study of in-hospital use of a #PICS risk prediction tool to older adult ICU survivorsโฆ showing: โญ๏ธ feasibility โญ๏ธ good calibration for the tool chestcc.org/article/S2949-โฆ Margaret Pisani CHESTยฎ Journal CHEST
Can we PREDICT the development of post-ICU functional impairment? In #journal_ChestCritCare led by Lauren Ferrante, a feasibility study demonstrating ๐ >90% completion rate of the risk prediction tool by participants ๐ Improved model discrimination with in-hospital factors