0000000000345159

AUTHOR

Paul Clopton

showing 3 related works from this author

Machine Learning–Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes

2022

Background: Machine learning is a promising approach to personalize atrial fibrillation management strategies for patients after catheter ablation. Prior atrial fibrillation ablation outcome prediction studies applied classical machine learning methods to hand-crafted clinical scores, and none have leveraged intracardiac electrograms or 12-lead surface electrocardiograms for outcome prediction. We hypothesized that (1) machine learning models trained on electrograms or electrocardiogram (ECG) signals can perform better at predicting patient outcomes after atrial fibrillation ablation than existing clinical scores and (2) multimodal fusion of electrogram, ECG, and clinical features can furt…

MaleEnginyeria elèctricaUrgències cardiovascularsMachine LearningTreatment OutcomePredictive Value of TestsRecurrencePhysiology (medical)Atrial FibrillationCatheter AblationHumansFemaleHeart AtriaCardiology and Cardiovascular MedicineCirculation: Arrhythmia and Electrophysiology
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Neutrophil Gelatinase-Associated Lipocalin for Acute Kidney Injury During Acute Heart Failure Hospitalizations

2016

AbstractBackground: Worsening renal function (WRF) often occurs during acute heart failure (AHF) and can portend adverse outcomes; therefore, early identification may help mitigate risk. Neutrophil...

medicine.medical_specialtymedicine.drug_class030232 urology & nephrologyRenal functionCardiorenal syndrome030204 cardiovascular system & hematologyLipocalin03 medical and health scienceschemistry.chemical_compound0302 clinical medicineInternal medicinemedicineNatriuretic peptideIntensive care medicineProspective cohort studyCreatininebusiness.industryAcute kidney injuryfood and beveragesmedicine.disease3. Good healthchemistryHeart failureCardiologyCardiology and Cardiovascular MedicinebusinessJournal of the American College of Cardiology
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Utility of Urine Neutrophil Gelatinase-Associated Lipocalin for Worsening Renal Function during Hospitalization for Acute Heart Failure: Primary Find…

2019

ABSTRACT Background: Worsening renal function (WRF) during acute heart failure (AHF) occurs frequently and has been associated with adverse outcomes, though this association has been questioned. WRF is now evaluated by function and injury. We evaluated whether urine neutrophil gelatinase-associated lipocalin (uNGAL) is superior to creatinine for prediction and prognosis of WRF in patients with AHF. Methods and Results: We performed a multicenter, international, prospective cohort of patients with AHF requiring IV diuretics. The primary outcome was whether uNGAL predicted development of WRF, defined as a sustained increase in creatinine of 0.5 mg/dL or ≥50% above first value or initiation of…

MalePROGNOSISInternationalitymedicine.medical_treatmentUrine030204 cardiovascular system & hematologyKidneyKidney Function TestsGastroenterologyTHERAPYCohort Studieschemistry.chemical_compound0302 clinical medicine030212 general & internal medicineProspective StudiesProspective cohort studyDAMAGERISKAged 80 and overAcute kidney injuryIMPAIRMENTAcute Kidney InjuryMiddle Aged3. Good healthHospitalizationbiomarkerAcute heart failure; biomarker; worsening renal functionFemaleCardiology and Cardiovascular MedicineGlomerular Filtration Ratemedicine.medical_specialtyRenal functionDIAGNOSIS03 medical and health sciencesLipocalin-2Internal medicineSTRATIFICATIONmedicineMANAGEMENTHumansRenal replacement therapyAdverse effectAgedHeart FailureCreatininebusiness.industryMORTALITYAcute heart failuremedicine.diseasechemistryHeart failureworsening renal functionbusinessBiomarkersJournal of cardiac failure
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