Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001919', 'term': 'Bradycardia'}], 'ancestors': [{'id': 'D001145', 'term': 'Arrhythmias, Cardiac'}, {'id': 'D006331', 'term': 'Heart Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 300}, 'targetDuration': '10 Years', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2021-11-30', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-09', 'completionDateStruct': {'date': '2041-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-09-29', 'studyFirstSubmitDate': '2021-10-27', 'studyFirstSubmitQcDate': '2021-11-08', 'lastUpdatePostDateStruct': {'date': '2025-10-03', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2021-11-19', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2041-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': '3P-MACE', 'timeFrame': 'after 3 years', 'description': 'death, myocardial infarction and/or stroke'}, {'measure': '3P-MACE', 'timeFrame': 'after 5 years', 'description': 'death, myocardial infarction and/or stroke'}, {'measure': '3P-MACE', 'timeFrame': 'after 10 years', 'description': 'death, myocardial infarction and/or stroke'}, {'measure': 'Atrial high rate episodes', 'timeFrame': 'after 3 years', 'description': 'in patients with sinus rhythm and implanted DDDR pacemaker; \\> 6 min duration'}, {'measure': 'Atrial high rate episodes', 'timeFrame': 'after 5 years', 'description': 'in patients with sinus rhythm and implanted DDDR pacemaker; \\> 6 min duration'}, {'measure': 'Atrial high rate episodes', 'timeFrame': 'after 10 years', 'description': 'in patients with sinus rhythm and implanted DDDR pacemaker; \\> 6 min duration'}, {'measure': 'Ventricular tachyarrhythmia', 'timeFrame': 'after 3 years', 'description': 'cycle length \\< 320 ms; ≥ 40 beats'}, {'measure': 'Ventricular tachyarrhythmia', 'timeFrame': 'after 5 years', 'description': 'cycle length \\< 320 ms; ≥ 40 beats'}, {'measure': 'Ventricular tachyarrhythmia', 'timeFrame': 'after 10 years', 'description': 'cycle length \\< 320 ms; ≥ 40 beats'}], 'secondaryOutcomes': [{'measure': 'Progression of subclinical coronary atherosclerosis assessed by CTA', 'timeFrame': 'after 5 years', 'description': 'Agatston-Score stratified to 0, 1-10, 11-100, 101-400, \\>400. Coronary lesions will be graded according to the CADSRAD classification (minimal \\< 10%, mild \\< 50%, moderate 50-70%, severe \\> 70%). Coronary plaques will be classified as T1 = calcified, T2 = mixed, T3 = mixed, primarily calcified, T4 = non-calcified). "High risk plaque"-criteria will include: low attenuation plaque, napkin-ring, spotty calcification \\< 3mm, remodelling index.'}, {'measure': 'Deterioration of lung function', 'timeFrame': 'after 5 years', 'description': 'conventional lung function testing'}, {'measure': 'Progression of subclinical peripheral artery disease', 'timeFrame': 'after 5 years', 'description': 'sonography'}, {'measure': 'Progression of subclinical peripheral artery disease', 'timeFrame': 'after 5 years', 'description': 'ABI'}, {'measure': 'QoL assessment', 'timeFrame': 'after 5 years', 'description': 'EQ-5D-5L'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Bradycardia']}, 'referencesModule': {'references': [{'pmid': '20625114', 'type': 'BACKGROUND', 'citation': "Gottlieb DJ, Yenokyan G, Newman AB, O'Connor GT, Punjabi NM, Quan SF, Redline S, Resnick HE, Tong EK, Diener-West M, Shahar E. Prospective study of obstructive sleep apnea and incident coronary heart disease and heart failure: the sleep heart health study. Circulation. 2010 Jul 27;122(4):352-60. doi: 10.1161/CIRCULATIONAHA.109.901801. Epub 2010 Jul 12."}, {'pmid': '25307200', 'type': 'BACKGROUND', 'citation': 'Luyster FS, Kip KE, Aiyer AN, Reis SE, Strollo PJ Jr. Relation of obstructive sleep apnea to coronary artery calcium in non-obese versus obese men and women aged 45-75 years. Am J Cardiol. 2014 Dec 1;114(11):1690-4. doi: 10.1016/j.amjcard.2014.08.040. Epub 2014 Sep 16.'}, {'pmid': '25515104', 'type': 'BACKGROUND', 'citation': 'Hla KM, Young T, Hagen EW, Stein JH, Finn LA, Nieto FJ, Peppard PE. Coronary heart disease incidence in sleep disordered breathing: the Wisconsin Sleep Cohort Study. Sleep. 2015 May 1;38(5):677-84. doi: 10.5665/sleep.4654.'}, {'pmid': '24561163', 'type': 'BACKGROUND', 'citation': 'Defaye P, de la Cruz I, Marti-Almor J, Villuendas R, Bru P, Senechal J, Tamisier R, Pepin JL. A pacemaker transthoracic impedance sensor with an advanced algorithm to identify severe sleep apnea: the DREAM European study. Heart Rhythm. 2014 May;11(5):842-8. doi: 10.1016/j.hrthm.2014.02.011. Epub 2014 Feb 19.'}, {'pmid': '31493591', 'type': 'BACKGROUND', 'citation': 'Marti-Almor J, Marques P, Jesel L, Garcia R, Di Girolamo E, Locati F, Defaye P, Venables P, Dompnier A, Barcelo A, Nagele H, Burri H. Incidence of sleep apnea and association with atrial fibrillation in an unselected pacemaker population: Results of the observational RESPIRE study. Heart Rhythm. 2020 Feb;17(2):195-202. doi: 10.1016/j.hrthm.2019.09.001. Epub 2019 Sep 4.'}, {'pmid': '27890735', 'type': 'BACKGROUND', 'citation': "Moubarak G, Bouzeman A, de Geyer d'Orth T, Bouleti C, Beuzelin C, Cazeau S. Variability in obstructive sleep apnea: Analysis of pacemaker-detected respiratory disturbances. Heart Rhythm. 2017 Mar;14(3):359-364. doi: 10.1016/j.hrthm.2016.11.033. Epub 2016 Nov 23."}, {'pmid': '33179808', 'type': 'BACKGROUND', 'citation': 'Mazza A, Bendini MG, Leggio M, De Cristofaro R, Valsecchi S, Boriani G. Continuous monitoring of sleep-disordered breathing with pacemakers: Indexes for risk stratification of atrial fibrillation and risk of stroke. Clin Cardiol. 2020 Dec;43(12):1609-1615. doi: 10.1002/clc.23489. Epub 2020 Nov 12.'}, {'pmid': '31221356', 'type': 'BACKGROUND', 'citation': 'Linz D, Brooks AG, Elliott AD, Nalliah CJ, Hendriks JML, Middeldorp ME, Gallagher C, Mahajan R, Kalman JM, McEvoy RD, Lau DH, Sanders P. Variability of Sleep Apnea Severity and Risk of Atrial Fibrillation: The VARIOSA-AF Study. JACC Clin Electrophysiol. 2019 Jun;5(6):692-701. doi: 10.1016/j.jacep.2019.03.005. Epub 2019 May 1.'}, {'pmid': '28073884', 'type': 'BACKGROUND', 'citation': 'Mazza A, Bendini MG, De Cristofaro R, Lovecchio M, Valsecchi S, Boriani G. Pacemaker-detected severe sleep apnea predicts new-onset atrial fibrillation. Europace. 2017 Dec 1;19(12):1937-1943. doi: 10.1093/europace/euw371.'}]}, 'descriptionModule': {'briefSummary': 'This is a prospective, non-interventional cohort study. It tests the hypothesis that\n\n* Pacemaker-derived monitoring of sleep-related breathing disorders and/or daily physical activity predicts clinical outcome.\n* Autonomic imbalance defined by an increased periodic repolarisation dynamics (PRD) predicts clinical outcome in pacemaker patients.\n* Autonomic imbalance defined by an increased periodic repolarisation dynamics (PRD) predicts the occurrence of AHRE in SR patients implanted with a DDDR pacemaker.', 'detailedDescription': 'All forms of arrhythmias, sleep apnea during sleeping hours and physical activity using sensors in modern implanted pacemakers as well as autonomic imbalance measures will be correlated with the incidence and progression (within 5 years of follow-up) of common co-morbidities such as arterial hypertension, coronary artery disease, heart failure, COPD, peripheral artery disease, iron insufficiency. In a long follow up perspective major adverse cardiovascular events will be recorded and new risk scores will be developed, incorporating machine learning techniques.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Patients with pacemakers are usually above the age of 65 years, and suffer from common co-morbidities such as arterial hypertension, coronary artery disease, heart failure, COPD, peripheral artery disease, iron insufficiency, sleep disordered breathing, obesity and/or physical inactivity / de-conditioning.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* implanted Microport TEO SR/DR or BOREA SR/DR pacemaker device\n* signed informed consent\n\nExclusion Criteria:\n\n* any contraindication to perform a cardiac CT examination\n* eGFR \\< 30 ml/min/1.73 m2\n* allergy against CT contrast medium\n* hyperthyreoism\n* inability of the patient to understand the study purpose and plan\n* inability of the patient to perform baseline examinations\n* pregnancy or breast-feeding; women with childbearing potential\n* estimated life expectancy below one year'}, 'identificationModule': {'nctId': 'NCT05127720', 'acronym': 'ACaSA', 'briefTitle': 'Pacemaker-based Long-term Monitoring of Sleep Apnea', 'organization': {'class': 'OTHER', 'fullName': 'Medical University Innsbruck'}, 'officialTitle': 'Schrittmacher-basiertes Schlafapnoe Langzeit-Monitoring', 'orgStudyIdInfo': {'id': '1322/2020'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'patients with severe sleep apnea', 'description': 'defined by a pacemaker-derived mean RDI ≥ 20/h in the first 12 months after enrollment'}, {'label': 'patients with autonomic imbalance', 'description': 'defined by PRD ≥ 5.75deg2 assessed within the first 12 months of enrollment'}, {'label': 'patients with a sedentary lifestyle', 'description': 'defined by a pacemaker-derived mean daily physical activity level \\< 2h in the first 12 months after enrollment'}]}, 'contactsLocationsModule': {'locations': [{'zip': '6020', 'city': 'Innsbruck', 'state': 'Tyrol', 'status': 'RECRUITING', 'country': 'Austria', 'contacts': [{'name': 'Wolfgang Dichtl, MD PhD', 'role': 'CONTACT', 'email': 'dichtl@me.com', 'phone': '004351250481388'}, {'name': 'Agne Adukauskaite, MSc PhD', 'role': 'CONTACT', 'email': 'agne.adukauskaite@tirol-kliniken.at', 'phone': '004351250483447'}, {'name': 'Philipp Spitaler', 'role': 'SUB_INVESTIGATOR'}, {'name': 'Andrea Rubatscher', 'role': 'SUB_INVESTIGATOR'}], 'facility': 'Medical University Innsbruck', 'geoPoint': {'lat': 47.26266, 'lon': 11.39454}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Medical University Innsbruck', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}