Simone Redaelli MD

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Simone Redaelli MD

Simone Redaelli MD

@SimonRedaelliMD

Anesthesia and Critical Care physician - Postdoc @BIDMCHealth @harvardmed - @unimib alumni - Interests: #ARDS #cooking👨‍🍳 - Milan 🇮🇹 & Boston 🇺🇸

Boston, MA شامل ہوئے Kasım 2017
351 فالونگ248 فالوورز
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ATS Blue Journal
ATS Blue Journal@ATSBlueEditor·
The Blue Journal thanks Simone Redaelli, MD, for his contribution to the March 1 issue Adjustments of Ventilator Parameters during Operating Room–to–ICU Transition and 28-Day Mortality @SimonRedaelliMD @maxsebschaefer bit.ly/4bWz2CE
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ATS Blue Journal
ATS Blue Journal@ATSBlueEditor·
The Blue Journal thanks Dario von Wedel for his contribution to the March 1 issue Adjustments of Ventilator Parameters during Operating Room–to–ICU Transition and 28-Day Mortality @dariovonwedel @maxsebschaefer bit.ly/4bWz2CE
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ATS Blue Journal
ATS Blue Journal@ATSBlueEditor·
Adjustments of Ventilator Parameters during Operating Room–to–ICU Transition and 28-Day Mortality When adjustments of ventilator settings lead to increased ventilation intensity, they might precipitate higher 28-day mortality @maxsebschaefer 🔗 bit.ly/3P59DN9
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JAMA
JAMA@JAMA_current·
In this study of abstracts, addition of affiliations was significantly associated with acceptance rates by a commonly used large language model, with higher tiers of institutions being associated with higher acceptance rates. ja.ma/48wzR2z
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Simone Redaelli MD
Simone Redaelli MD@SimonRedaelliMD·
I’m glad to share that our work on inflammatory subphenotypes in patients at risk of #ARDS has just been published in @yourICM Thank you to all the people that made this achievement possible @BIDMCAnesthesia @unimib
Intensive Care Medicine@yourICM

🫁 Inflammatory subphenotypes in pts at risk of #ARDS: potential predictive/prognostic strategy? Hyper & non-hyper-inflammatory subphenotypes may precede development, identifiable in ED & remain identifiable. Worse outcomes if hyper-inflammatory type. 🖇️ rdcu.be/dp0z0

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MIT Critical Data
MIT Critical Data@MITCriticalData·
AI for prediction of treatment outcomes in breast cancer: 1. Despite the exponential increase in the number of algorithms published in breast oncology, very few are prospectively evaluated in clinical practice. 2. Using the PROBAST tool, 72% have high risk of bias.
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