Publications by authors named "J Plasek"
Background: Charcot-Marie-Tooth is the most common inherited neuromuscular disorder. Rarely, it can be associated with heart failure and various arrhythmic disturbances. This case illustrates the challenges of making decisions to prevent sudden cardiac death in a patient with Charcot-Marie-Tooth disease.
View Article and Find Full Text PDFBackground: Adverse drug events (ADEs) are understudied in the ambulatory care setting. We aim to estimate the prevalence and characteristics of ADEs in outpatient care using electronic health records (EHRs).
Methods: This cross-sectional study included EHR data for patients who had an outpatient encounter at an academic medical center from 1 October 2018 through 31 December 2019.
Induction of supraventricular tachycardias in patients undergoing pulmonary vein isolation for paroxysmal atrial fibrillation is safe and reasonable.
Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub
November 2024
Aims: Patients with atrial fibrillation (AF) may experience other supraventricular tachycardias (SVT) that can trigger AF and cause similar symptoms. The aim of this study was to assess the safety and effectivity of inducing SVT in patients undergoing catheter ablation (CA) for AF.
Methods: In 61 patients with paroxysmal AF undergoing CA between January 2022 and March 2023, an electrophysiological study was performed after pulmonary vein isolation (PVI) to induce SVT.
Article Synopsis
- Lung-protective ventilation is crucial for patients with ARDS, but adherence to guidelines is inadequate, prompting a study on contributing factors over a 5-year period.
- A cohort and qualitative research approach analyzed real-time data from 1,055 patients undergoing critical care, focusing on their tidal volume settings and subgroup analysis for COVID-19 cases.
- Findings revealed that male sex and COVID-19 status increased adherence to lung-protective ventilation, while older age, cancer, and hypertension led to decreased usage among critical-care providers.
- Focus groups provided additional insights into why guidelines were not consistently followed.
Article Synopsis
- The study investigates the effectiveness of large language models (LLMs) like GPT-4 and Llama 2 in identifying cognitive decline from real electronic health records (EHRs), comparing them with traditional models.
- Conducted at Mass General Brigham, researchers analyzed clinical notes from patients diagnosed with mild cognitive impairment, using various approaches to optimize LLM performance and create an ensemble model that combined different methods.
- The findings showed that while GPT-4 was more accurate than Llama 2, it still didn't surpass traditional models; however, an ensemble model significantly outperformed all others in key evaluation metrics.