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Objectives: This study aims to investigate the relationship between serum calcium (SC) levels and the incidence of postoperative atrial fibrillation (POAF) in patients undergoing coronary artery bypass graft surgery.
Methods: This retrospective, observational cohort study consecutively enrolled patients undergoing isolated coronary artery bypass grafting in Beijing Anzhen Hospital from January 2018 to December 2021. Patients with a previous history of atrial fibrillation or atrial flutter or requiring concomitant cardiac surgery were excluded. A logistic regression model was used to determine predictors of POAF. Multivariable adjustment, inverse probability of treatment weighting and propensity score matching were used to adjust for confounders. Moreover, we conducted univariable and multivariable logistic regression analyses on preoperative and postoperative SC and ionized SC levels.
Results: The analysis encompassed 12 293 patients. The POAF rate was significantly higher in patients with low SC level than those without (1379 [33.9%] vs 2375 [28.9%], P < 0.001). Low SC level was associated with an increased odds ratio of POAF (odds ratio [95% confidence interval]: 1.27 [1.18-1.37], P < 0.001). Inverse probability of treatment weighting and propensity score matching analyses confirmed the results. The increased POAF rate in low SC level group still existed among subgroup analysis based on different age, sex, body mass index, hypertension, hyperlipidaemia, CHA2DS2-VASc and magnesium.
Conclusions: Low SC level indicates elevated POAF risk in patients undergoing isolated coronary artery bypass graft surgery even after the adjustment for age, sex, cardiovascular risk factors, echocardiographic parameters and laboratory markers.
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http://dx.doi.org/10.1093/icvts/ivae077 | DOI Listing |
Am J Med Sci
September 2025
The Ruth and Bruce Rappaport Faculty of Medicine, Technion, Israel Institute of Technology, Haifa, Israel; Department of Internal Medicine, Lady Davis Carmel Medical Center, Haifa, Israel.
Objective: Multifocal atrial tachycardia (MAT), characterized by an irregularly irregular rhythm, is often regarded as a clinical imitator of atrial fibrillation (AF). We aimed to evaluate the prevalence of MAT misclassification as AF in the emergency department (ED) setting.
Methods: A retrospective analysis of 1,828 ECGs from patients discharged with AF diagnoses over five years.
Environ Res
September 2025
Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.
Background: Fine particulate matter (PM) has been previously linked to cardiovascular diseases (CVDs). PM is a mixture of components, each of which has its own toxicity profile which are not yet well understood. This study explores the relationship between long-term exposure to PM components and hospital admissions with CVDs in the Medicare population.
View Article and Find Full Text PDFClin Neurol Neurosurg
September 2025
Department of Neurology, UPMC, Pittsburgh, PA, USA. Electronic address:
Background: Final infarct volume (FIV) is a strong predictor of stroke outcomes. Although smaller FIV are associated with better outcomes, many patients fail to achieve functional independence. We aimed to identify poor outcome predictors in patients with anterior large vessel occlusion stroke (LVOS) who underwent mechanical thrombectomy (MT) and had small FIV.
View Article and Find Full Text PDFJ Physiol
September 2025
Undergraduate Medical Education, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
J Am Coll Cardiol
August 2025
Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Cardiology, Kaiser Permanente Santa Clara Medical Center, Santa Clara, California, USA. Electronic address:
Background: Accurate measurement of echocardiographic parameters is crucial for the diagnosis of cardiovascular disease and tracking of change over time; however, manual assessment requires time-consuming effort and can be imprecise. Artificial intelligence has the potential to reduce clinician burden by automating the time-intensive task of comprehensive measurement of echocardiographic parameters.
Objectives: The purpose of this study was to develop and validate open-sourced deep learning semantic segmentation models for the automated measurement of 18 anatomic and Doppler measurements in echocardiography.