Feature Identification Using Interpretability Machine Learning Predicting Risk Factors for Disease Severity of In-Patients with COVID-19 in South Florida.

The objective of the study was to establish an AI-driven decision support system by identifying the most important features in the severity of disease for ntensive are nit (ICU) with echanical entilation (MV) requirement, ICU, and nterediate are nit (IMCU) admission for hospitalized patients with COVID-19 in South Florida. The features implicated in the risk factors identified by the model interpretability can be used to forecast treatment plans faster before critical conditions exacerbate. We analyzed eHR data from 5371 patients diagnosed with COVID-19 from South Florida Memorial Healthcare Systems admitted between March 2020 and January 2021 to predict the need for ICU with MV, ICU, and IMCU admission.

Using machine learning to identify patient characteristics to predict mortality of in-patients with COVID-19 in south Florida.

Introduction: The SARS-CoV-2 (COVID-19) pandemic has created substantial health and economic burdens in the US and worldwide. As new variants continuously emerge, predicting critical clinical events in the context of relevant individual risks is a promising option for reducing the overall burden of COVID-19. This study aims to train an AI-driven decision support system that helps build a model to understand the most important features that predict the "mortality" of patients hospitalized with COVID-19.

The muscle sparing latissimus dorsi (MSLD) flap for secondary breast reconstruction based on reverse flow from intercostal vessels.

The muscle-sparing latissimus dorsi (MSLD) flap is a modification by Saint Cyr of the traditional latissimus dorsi flap. While the flap is commonly based on the thoracodorsal artery pedicle, flap design based on reversed flow from the serratus branch has also been well documented. Uncertainty over the availability of adequate arterial inflow to support a pedicled MSLD flap is a potential concern in secondary breast reconstruction for previous surgery may have compromised the thoracodorsal pedicle and/or its branches.

Thrombectomy 6 to 24 Hours after Stroke with a Mismatch between Deficit and Infarct.

Background: The effect of endovascular thrombectomy that is performed more than 6 hours after the onset of ischemic stroke is uncertain. Patients with a clinical deficit that is disproportionately severe relative to the infarct volume may benefit from late thrombectomy.

Methods: We enrolled patients with occlusion of the intracranial internal carotid artery or proximal middle cerebral artery who had last been known to be well 6 to 24 hours earlier and who had a mismatch between the severity of the clinical deficit and the infarct volume, with mismatch criteria defined according to age (<80 years or ≥80 years).

Long-Term Outcomes of Patent Foramen Ovale Closure or Medical Therapy after Stroke.

Background: Whether closure of a patent foramen ovale reduces the risk of recurrence of ischemic stroke in patients who have had a cryptogenic ischemic stroke is unknown.

Methods: In a multicenter, randomized, open-label trial, with blinded adjudication of end-point events, we randomly assigned patients 18 to 60 years of age who had a patent foramen ovale (PFO) and had had a cryptogenic ischemic stroke to undergo closure of the PFO (PFO closure group) or to receive medical therapy alone (aspirin, warfarin, clopidogrel, or aspirin combined with extended-release dipyridamole; medical-therapy group). The primary efficacy end point was a composite of recurrent nonfatal ischemic stroke, fatal ischemic stroke, or early death after randomization.