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Clinical Outcomes For Impella Patients Associated With Hyperlipidemia: An Analysis Of The National Inpatient Sample, Tony Elias, Sonika Vatsa, Kyrillos Gamal, Taha Syed, Rafail Beshai
Clinical Outcomes For Impella Patients Associated With Hyperlipidemia: An Analysis Of The National Inpatient Sample, Tony Elias, Sonika Vatsa, Kyrillos Gamal, Taha Syed, Rafail Beshai
Rowan-Virtua Research Day
The Impella, a ventricular assist device, is crucial for managing severe heart failure and cardiogenic shock. Despite its widespread use, there's scant information on how hyperlipidemia affects Impella patients. To address this gap, we delved into the National Inpatient Sample Database from 2019 and 2020. Our aim was to scrutinize in-hospital outcomes among these patients. We identified 8233 Impella patients, among whom 1012 (12.3%) had hyperlipidemia. Those with hyperlipidemia displayed higher rates of hypertension, diabetes mellitus, and chronic kidney disease compared to their counterparts without hyperlipidemia. Shockingly, in-hospital mortality was notably elevated in the hyperlipidemia group, emphasizing its clinical significance. …
Cardiovascular Disease Prediction Modelling: A Machine Learning Approach, Usmaan Al-Shehab, Maduka Gunasinghe, Yousuf Elkhoga, Nimay Patel, Juliana Yang
Cardiovascular Disease Prediction Modelling: A Machine Learning Approach, Usmaan Al-Shehab, Maduka Gunasinghe, Yousuf Elkhoga, Nimay Patel, Juliana Yang
Rowan-Virtua Research Day
The objective of this project is to utilize the UCI Heart Disease dataset to identify physiological biomarkers that are highly correlated with heart disease incidence. A predictive model can then be developed using these biomarkers to estimate the likelihood of someone having or developing a heart-related condition. This study compares the efficacy of predicting cardiovascular disease as an outcome using three machine learning algorithms: Support Vector Machine, Gaussian Naive Bayes, and logistic regression. Support Vector Machine works by creating hyperplanes between data points to conduct classification. Gaussian Naive Bayes works by using the conditional probabilities of events to classify the …