Background: It is unclear whether the use of clinical prediction rules is sufficient to rule out infective endocarditis (IE) in patients with bacteremia (SAB) without an echocardiogram evaluation, either transthoracic (TTE) and/or transesophageal (TEE). Our primary purpose was to test the usefulness of PREDICT, POSITIVE, and VIRSTA scores to rule out IE without echocardiography. Our secondary purpose was to evaluate whether not performing an echocardiogram evaluation is associated with higher mortality.
Methods: We conducted a unicentric retrospective cohort including all patients with a first SAB episode from January 2015 to December 2020. IE was defined according to modified Duke criteria. We predefined threshold cutoff points to consider that IE was ruled out by means of the mentioned scores. To assess 30-day mortality, we used a multivariable regression model considering performing an echocardiogram as covariate.
Results: Out of 404 patients, IE was diagnosed in 50 (12.4%). Prevalence of IE within patients with negative PREDICT, POSITIVE, and VIRSTA scores was: 3.6% (95% CI 0.1-6.9%), 4.9% (95% CI 2.2-7.7%), and 2.2% (95% CI 0.2-4.3%), respectively. Patients with negative VIRSTA and negative TTE had an IE prevalence of 0.9% (95% CI 0-2.8%). Performing an echocardiogram was independently associated with lower 30-day mortality (OR 0.24 95% CI 0.10-0.54, = 0.001).
Conclusion: PREDICT and POSITIVE scores were not sufficient to rule out IE without TEE. In patients with negative VIRSTA score, it was doubtful if IE could be discarded with a negative TTE. Not performing an echocardiogram was associated with worse outcomes, which might be related to presence of occult IE. Further studies are needed to assess the usefulness of clinical prediction rules in avoiding echocardiographic evaluation in SAB patients.
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http://dx.doi.org/10.3390/jcm11061502 | DOI Listing |
J Clin Med
January 2025
Guthrie Cortland Medical Center, Cortland, NY 13045, USA.
Artificial intelligence (AI) in echocardiography represents a transformative advancement in cardiology, addressing longstanding challenges in cardiac diagnostics. Echocardiography has traditionally been limited by operator-dependent variability and subjective interpretation, which impact diagnostic reliability. This study evaluates the role of AI, particularly machine learning (ML), in enhancing the accuracy and consistency of echocardiographic image analysis and its potential to complement clinical expertise.
View Article and Find Full Text PDFAnimals (Basel)
January 2025
Veterinary Teaching Hospital, Tokyo University of Agriculture and Technology, Tokyo 183-8538, Japan.
A 2-month-old Shiba Inu was presented to an emergency veterinary clinic with decreased activity and was diagnosed with pulmonary hypertension secondary to a ventricular septal defect. The dog was referred to the TUAT Veterinary Medical Center for further evaluation. During treatment, a diverticulum was incidentally identified at the apex of the left ventricle.
View Article and Find Full Text PDFBiomedicines
January 2025
Department of Emergency Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
Background/objectives: Autoimmune inflammation enhances the electrical instability of the atrial myocardium in patients with systemic sclerosis (SSc); thus, atrial arrhythmia risk is increased, which might be predicted by evaluating the P wave interval and dispersion of a 12-lead surface electrocardiogram (ECG).
Methods: We examined 26 SSc patients and 36 healthy controls and measured the P wave interval and P wave dispersion of the 12-lead surface ECG in each patient. Furthermore, echocardiography and 24-h Holter ECG were performed and levels of inflammatory laboratory parameters, including serum progranulin (PGRN), sVCAM-1, sICAM-1, leptin and C-reactive protein (CRP), were determined.
Respir Med
January 2025
Department of Anaesthesiology, Pain Medicine and Critical Care, All India Institute of Medical Sciences, New Delhi, India.
Purpose: Acute Kidney Injury (AKI) has an incidence of 20-50% in patients admitted in Intensive Care Unit. As weaning failure is associated with increased morbidity, its prediction and understanding of its physiological basis holds extreme importance in guided management and prognostication of these patients. We conducted this prospective, observational, single - center study to evaluate the efficacy of transthoracic echocardiography (TTE) and lung ultrasonography (LUS) in predicting weaning failure in patients with AKI requiring mechanical ventilation.
View Article and Find Full Text PDFJ Electrocardiol
January 2025
University of Rochester School of Nursing, NY, USA; University of Rochester Medical Center, NY, USA.
Background: Identifying patients with low left ventricular ejection fraction (LVEF) in the emergency department using an electrocardiogram (ECG) may optimize acute heart failure (AHF) management. We aimed to assess the efficacy of 527 automated 12‑lead ECG features for estimating LVEF among patients with AHF.
Method: Medical records of patients >18 years old and AHF-related ICD codes, demographics, LVEF %, comorbidities, and medication were analyzed.
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