Objective: This study aimed to evaluate whether the addition of heart rate-corrected QT inter- val prolongation to the Global Registry of Acute Coronary Events risk score improves the pre- dictive value for early mortality in patients with non-ST segment elevation acute coronary syndrome.
Methods: We retrospectively screened our database for consecutive non-ST-segment eleva- tion acute coronary syndrome patients between January 2017 and July 2019. The demographic and clinical parameters were acquired via chart review. All electrocardiograms were reviewed by 2 physicians. QT interval was measured using the tangent method. Early mortality was defined as all-cause death observed during the hospital stay or within 30 days after discharge.
Results: The final study population consisted of 283 patients, there were 17 early deaths. Ten of 59 patients with prolonged corrected QT intervals died (16.9%, P < .001). Both the Global Registry of Acute Coronary Events risk score (odds ratio: 1.032; 95% CI: 1.012-1.053; P = .002) and corrected QT interval (odds ratio: 1.026; 95% CI: 1.007-1.045; P = 0.007) independently predicted early mortality. The area under value was 0.769 (95% CI: 0.674-0.863, P < .001) for the corrected QT interval and 0.780 (95% CI:0.681-0.878; P < .001) for the Global Registry of Acute Coronary Events risk score alone. However, when the corrected QT interval and the Global Registry of Acute Coronary Events risk score were combined, it was found to be 0.808 (95% CI: 0.713-0.904, P < .001).
Conclusion: This study is the first to report that prolonged corrected QT and the Global Registry of Acute Coronary Events risk score independently predict early mortality and a combina- tion of these 2 factors may improve the predictive value for early mortality in patients with ST-segment elevation acute coronary syndrome.
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http://dx.doi.org/10.5543/tkda.2022.21198 | DOI Listing |
JAMA Pediatr
January 2025
Department of Cardiology, Harvard Medical School and Boston Children's Hospital, Boston, Massachusetts.
Importance: Multisystem inflammatory syndrome in children (MIS-C) is a life-threatening complication of COVID-19 infection. Data on midterm outcomes are limited.
Objective: To characterize the frequency and time course of cardiac dysfunction (left ventricular ejection fraction [LVEF] <55%), coronary artery aneurysms (z score ≥2.
J Asthma
January 2025
Division of Pediatric Allergy and Immunology, Department of Pediatrics, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey.
Objective: It is well known that children who suffer from obesity and asthma may also have exercise-induced bronchospasm. Exhaled nitric oxide is an indicator of airway inflammation, and could be affected by exercise. This study looked at how exercise, which is a typical cause of acute airway obstruction, affects the levels of FeNO and in obese and asthmatic children.
View Article and Find Full Text PDFEgypt Heart J
January 2025
Department of Cardiology, Division of Heart & Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
Background: Hyponatremia is one of the complicating findings in acute decompensated heart failure. Decrease in cardiac output and systemic blood pressure triggers activation of renin-angiotensin-aldosterone system, antidiuretic hormone, and norepinephrine due to the perceived hypovolemia. Fluid-overloaded heart failure patients are commonly treated with loop diuretics, acutely decompensated heart failure patients tend to be less responsive to conventional oral doses of a loop diuretic, while other different diuretics could work in different part of nephron circulation system.
View Article and Find Full Text PDFClin Transl Med
January 2025
State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Background And Aims: The importance of risk stratification in patients with chest pain extends beyond diagnosis and immediate treatment. This study sought to evaluate the prognostic value of electrocardiogram feature-based machine learning models to risk-stratify all-cause mortality in those with chest pain.
Methods: This was a prospective observational cohort study of consecutive, non-traumatic patients with chest pain.
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