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Rachael Cusack

Researcher at Mater Misericordiae University Hospital

Publications -  9
Citations -  21

Rachael Cusack is an academic researcher from Mater Misericordiae University Hospital. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 1, co-authored 1 publications receiving 4 citations.

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Hypotension during hip fracture surgery and postoperative morbidity

TL;DR: In this exploratory retrospective analysis, the cumulative time of hypotension during hip fracture surgery correlated with extensive postoperative morbidity when adjusting to other known predictors.
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Novel investigational treatments for ventilator-associated pneumonia and critically ill patients in the intensive care unit

TL;DR: Novel approaches such as monoclonal antibody treatments for P. aeruginosa and S. aureus and phage antibiotic synthesis are highlighted and mechanisms of resistance in Gram-negative bacteria, virulence factors, and inhaled antibiotics are examined.
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Effects of Fluids on the Sublingual Microcirculation in Sepsis

TL;DR: A systematic review of the evidence for using handheld intra vital microscopes to guide fluid resuscitation and the effect of fluid bolus on the sublingual microcirculation in patients with sepsis and septic shock is presented in this paper .
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Endothelial Damage and the Microcirculation in Critical Illness

TL;DR: In this paper , the authors reviewed the evidence for a relationship between clinically evaluable microcirculation and biological signal of glycocalyx disruption in various diseases in ICU, but results are highly variable.
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An artificial neural network classification method employing longitudinally monitored immune biomarkers to predict the clinical outcome of critically ill COVID-19 patients

TL;DR: In this paper , a dimensionality reduction analysis was performed to determine meaningful biomarkers for explaining the data variability, and the biomarkers were used as input of artificial neural network, random forest, classification and regression trees, k-nearest neighbors and support vector machines.