[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100584076":3},{"organization":4,"outcomesModule":7,"designInfo":17,"detailedDescription":19,"studyPopulation":20,"armGroups":21,"interventions":16,"overallOfficials":16,"centralContacts":25,"locations":34,"responsibleParty":313,"collaborators":316,"id":376,"slug":16,"hasResults":377,"nctId":378,"briefTitle":379,"officialTitle":380,"acronym":381,"eligibilityCriteria":382,"healthyVolunteers":377,"sex":383,"minAge":384,"maxAge":16,"enrollmentInfo":385,"targetDuration":388,"studyType":389,"phases":16,"briefSummary":390,"conditions":391,"keywords":393,"overallStatus":36,"whyStopped":16,"lastUpdateSubmitDate":399,"lastUpdatePostDateStruct":400,"startDateStruct":403,"completionDateStruct":405,"leadSponsor":407,"locationsCount":408},{"fullName":5,"class":6},"Centro Cardiologico Monzino","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":16,"otherOutcomes":16},[9,13],{"measure":10,"description":11,"timeFrame":12},"Risk score","Expand and update the patient dataset to further develop the Metabolic Exercise test data combined with Cardiac and Kidney Indexes (MECKI) score, optimizing its application in specific patient subgroups and aligning it with newly introduced therapies and treatments in clinical practice.","From enrollment to endpoint occurence (death, LVAD implantation, heart transplant) within 15 years",{"measure":14,"description":15,"timeFrame":12},"End point","Time to Cardiovascular death or LVAD implantation or heart transplant",null,{"allocation":16,"interventionModel":16,"interventionModelDescription":16,"primaryPurpose":16,"observationalModel":18,"timePerspective":6,"maskingInfo":16},"COHORT","Heart failure is a complex condition affecting multiple organs beyond the cardiovascular system, influencing disease progression and prognosis. It has become increasingly evident that accurate risk assessment requires considering multiple variables, as no single parameter alone is sufficient for prognosis.\n\nThese findings have led to the identification and study of prognostic parameters that, when combined, allow for a more precise risk estimation and identification of high-risk patients. Various prognostic scores have been developed, utilizing algorithms that integrate multiple variables to estimate an individual's mortality risk. Some scores are based on clinical evaluation and comorbidities, others on laboratory findings, baroreflex sensitivity, heart rate, sleep abnormalities, echocardiographic imaging, or cardiopulmonary exercise testing (CPET), either alone or in combination with other factors.\n\nCPET provides several parameters strongly correlated with prognosis. Since the 1990s, its use-alongside clinical data-has been recommended in heart failure management guidelines. More recently, in addition to peak oxygen consumption, the VE\u002FVCO₂ slope has been recognized as a key prognostic marker, reflecting ventilatory efficiency and ventilation-perfusion mismatch, and has been included in heart transplant assessment criteria.\n\nCurrent risk models in heart failure often omit important prognostic parameters, such as ventilatory indices from CPET, renal function, and hemoglobin levels. Among the numerous prognostic scores available, only the HF Survival Score (HFSS) and the HF Action Predictive Risk Score Model incorporate exercise-related parameters (peak VO₂ in the former and exercise duration in the latter), yet both neglect ventilatory aspects. Even the widely used Seattle Score does not include exercise-related variables.\n\nIn 2012, the researchers developed the MECKI (Metabolic Exercise test data combined with Cardiac and Kidney Indexes) score, integrating oxygen consumption, ventilatory efficiency, and easily accessible biochemical and echocardiographic parameters. Unlike previous models requiring extensive data collection, MECKI is based on just six key variables, making it both practical and effective.\n\nRecent studies indicate the need to review and update the cutoff values and parameters used in prognostic models, as the introduction of new therapies and treatment strategies may significantly impact their predictive power in specific patient populations.\n\nStudy Objectives and Purpose The aim of this study is to expand and update the patient dataset to further develop the MECKI score, optimizing its application in patient subgroups and adapting it to new therapies and treatments introduced in clinical practice.\n\nAdditionally, the researchers seek to determine whether risk prediction accuracy varies in advanced-stage patients, those with comorbidities, or those receiving different treatments. This could lead to the development of correction factors for the MECKI score, improving its predictive power and applicability across different clinical scenarios.\n\nStudy Population Patients with systolic heart failure, consecutively enrolled and followed at multiple Heart Failure Units across Italy.\n\nPatients undergo assessment through medical history collection, physical examination, laboratory tests, ECG, transthoracic echocardiography, and cardiopulmonary exercise testing (CPET).\n\nFollow-up will be conducted according to the protocol of the respective Heart Failure Unit. The follow-up period ends at the last evaluation at the reference center, or upon the patient's death or heart transplantation.","Patients with past or present heart failure (with previous documentation of left ventricular systolic dysfunction (LVEF \\\u003C40%)), in stable clinical conditions, who underwent a cardiopulmonary exercise test, with no scheduled cardiovascular treatment.",[22],{"label":23,"type":16,"description":24,"interventionNames":16},"Heart failure patients","Patients with systolic heart failure, able to exercise",[26,31],{"name":27,"role":28,"phone":29,"phoneExt":16,"email":30},"Piergiuseppe Agostoni, Professor","CONTACT","+390258002010","piergiuseppe.agostoni@ccfm.it",{"name":32,"role":28,"phone":29,"phoneExt":16,"email":33},"Elisabetta Salvioni, PhD","elisabetta.salvioni@ccfm.it",[35,50,63,76,89,102,111,123,132,141,150,159,168,180,189,198,206,218,230,242,251,259,268,280,292,301],{"facility":5,"status":36,"city":37,"state":38,"zip":39,"country":38,"countryCode":40,"cosmosGeoPoint":41,"geoPoint":46,"contacts":47},"RECRUITING","Milan","Italy","20138","IT",{"type":42,"coordinates":43},"Point",[44,45],12.59836,42.78235,{"lat":45,"lon":44},[48],{"name":49,"role":28,"phone":29,"phoneExt":16,"email":33},"Piergiuseppe Agostoni",{"facility":51,"status":36,"city":52,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":53,"geoPoint":57,"contacts":58},"Ospedali Riuniti di Ancona","Ancona",{"type":42,"coordinates":54},[55,56],13.5103,43.60717,{"lat":56,"lon":55},[59],{"name":60,"role":28,"phone":61,"phoneExt":16,"email":62},"Maria Vittoria Matassini","000","mavimatassini@gmail.com",{"facility":64,"status":36,"city":65,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":66,"geoPoint":70,"contacts":71},"Istituti Clinici Scientifici Maugeri Bari","Bari",{"type":42,"coordinates":67},[68,69],16.86982,41.12066,{"lat":69,"lon":68},[72],{"name":73,"role":28,"phone":74,"phoneExt":16,"email":75},"Andrea Passantino","00000","andrea.passantino@icsmaugeri.it",{"facility":77,"status":36,"city":78,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":79,"geoPoint":83,"contacts":84},"Ospedale papa Giovanni XXIII","Bergamo",{"type":42,"coordinates":80},[81,82],9.66721,45.69601,{"lat":82,"lon":81},[85],{"name":86,"role":28,"phone":87,"phoneExt":16,"email":88},"Annamaria Iorio","0000","anita.iorio@hotmail.it",{"facility":90,"status":91,"city":92,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":93,"geoPoint":97,"contacts":98},"Spedali Civili Brescia","NOT_YET_RECRUITING","Brescia",{"type":42,"coordinates":94},[95,96],10.21472,45.53558,{"lat":96,"lon":95},[99],{"name":100,"role":28,"phone":87,"phoneExt":16,"email":101},"Savina Nodari","studi.clinici@asst-spedalicivili.it",{"facility":103,"status":36,"city":92,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":104,"geoPoint":106,"contacts":107},"Spedali Civili",{"type":42,"coordinates":105},[95,96],{"lat":96,"lon":95},[108],{"name":109,"role":28,"phone":110,"phoneExt":16,"email":101},"Marco Metra","000000",{"facility":112,"status":36,"city":113,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":114,"geoPoint":118,"contacts":119},"Università di Foggia","Foggia",{"type":42,"coordinates":115},[116,117],15.55188,41.45845,{"lat":117,"lon":116},[120],{"name":121,"role":28,"phone":110,"phoneExt":16,"email":122},"Michele Correale","michele.correale@libero.it",{"facility":124,"status":36,"city":37,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":125,"geoPoint":127,"contacts":128},"I.R.C.C.S. Ospedale San Raffaele",{"type":42,"coordinates":126},[44,45],{"lat":45,"lon":44},[129],{"name":130,"role":28,"phone":74,"phoneExt":16,"email":131},"Rosa Raimondo","RAIMONDO.ROSA@hsr.it",{"facility":133,"status":36,"city":37,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":134,"geoPoint":136,"contacts":137},"IRCCS Istituto Auxologico Italiano",{"type":42,"coordinates":135},[44,45],{"lat":45,"lon":44},[138],{"name":139,"role":28,"phone":74,"phoneExt":16,"email":140},"Gianfranco Parati","trials@auxologico.it",{"facility":142,"status":36,"city":37,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":143,"geoPoint":145,"contacts":146},"IRCCS Multimedica- Ospedale San Giuseppe",{"type":42,"coordinates":144},[44,45],{"lat":45,"lon":44},[147],{"name":148,"role":28,"phone":74,"phoneExt":16,"email":149},"Gaia Cattadori","gaia.cattadori@multimedica.it",{"facility":151,"status":91,"city":37,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":152,"geoPoint":154,"contacts":155},"Istituti Clinici Scientifici Maugeri Milano",{"type":42,"coordinates":153},[44,45],{"lat":45,"lon":44},[156],{"name":157,"role":28,"phone":61,"phoneExt":16,"email":158},"Maurizio Bussotti","maurizio.bussotti@icsmaugeri.it",{"facility":160,"status":91,"city":37,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":161,"geoPoint":163,"contacts":164},"Ospedale Cà Granda- A.O. Niguarda",{"type":42,"coordinates":162},[44,45],{"lat":45,"lon":44},[165],{"name":166,"role":28,"phone":74,"phoneExt":16,"email":167},"Enrico Perna","enrico.perna@ospedaleniguarda.it",{"facility":169,"status":36,"city":170,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":171,"geoPoint":175,"contacts":176},"Azienda Ospedaliera dei Colli - Ospedale Monaldi","Naples",{"type":42,"coordinates":172},[173,174],14.26811,40.85216,{"lat":174,"lon":173},[177],{"name":178,"role":28,"phone":110,"phoneExt":16,"email":179},"Giuseppe Limongelli","limongelligiuseppe@libero.it",{"facility":181,"status":36,"city":170,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":182,"geoPoint":184,"contacts":185},"Federico II hospital",{"type":42,"coordinates":183},[173,174],{"lat":174,"lon":173},[186],{"name":187,"role":28,"phone":87,"phoneExt":16,"email":188},"Antonio Cittadini","antonio.cittadini@unina.it",{"facility":190,"status":36,"city":170,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":191,"geoPoint":193,"contacts":194},"Università degli Studi di Napoli Federico II",{"type":42,"coordinates":192},[173,174],{"lat":174,"lon":173},[195],{"name":196,"role":28,"phone":87,"phoneExt":16,"email":197},"Pasquale Perrone Filardi","paolilloste@gmail.com",{"facility":199,"status":91,"city":200,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":201,"geoPoint":205,"contacts":16},"Istituto Mediterraneo per i Trapianti e Terapie ad alta specializzazione","Palermo",{"type":42,"coordinates":202},[203,204],13.3636,38.1166,{"lat":204,"lon":203},{"facility":207,"status":36,"city":208,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":209,"geoPoint":213,"contacts":214},"Ospedale Guglielmo da Saliceto","Piacenza",{"type":42,"coordinates":210},[211,212],9.69342,45.05242,{"lat":212,"lon":211},[215],{"name":216,"role":28,"phone":74,"phoneExt":16,"email":217},"Francesco Di Spigno","F.DiSpigno@ausl.pc.it",{"facility":219,"status":36,"city":220,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":221,"geoPoint":225,"contacts":226},"Fondazione Gabriele Monasterio","Pisa",{"type":42,"coordinates":222},[223,224],10.4036,43.70853,{"lat":224,"lon":223},[227],{"name":228,"role":28,"phone":87,"phoneExt":16,"email":229},"Michele Emdin","emdin@ftgm.it",{"facility":231,"status":36,"city":232,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":233,"geoPoint":237,"contacts":238},"Azienda Ospedaliera San Camillo-Forlanini","Roma",{"type":42,"coordinates":234},[235,236],11.10642,44.99364,{"lat":236,"lon":235},[239],{"name":240,"role":28,"phone":87,"phoneExt":16,"email":241},"Federica Re","federica.re@sancamilloforlanini.rm.it",{"facility":243,"status":36,"city":232,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":244,"geoPoint":246,"contacts":247},"Azienda Ospedaliera Sant'Andrea",{"type":42,"coordinates":245},[235,236],{"lat":236,"lon":235},[248],{"name":249,"role":28,"phone":87,"phoneExt":16,"email":250},"Damiano Magrì","damiano.magri@uniroma1.it",{"facility":252,"status":91,"city":253,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":254,"geoPoint":258,"contacts":16},"Azienda Ospedaliero-Universitaria Policinico Umberto I","Rome",{"type":42,"coordinates":255},[256,257],12.51133,41.89193,{"lat":257,"lon":256},{"facility":260,"status":36,"city":253,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":261,"geoPoint":263,"contacts":264},"Santo Spirito Hospital",{"type":42,"coordinates":262},[256,257],{"lat":257,"lon":256},[265],{"name":266,"role":28,"phone":74,"phoneExt":16,"email":267},"Angela B Scardovi","angela.scardovi@aslroma1.it",{"facility":269,"status":36,"city":270,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":271,"geoPoint":275,"contacts":276},"IRCCS Policlinico San Donato","San Donato Milanese",{"type":42,"coordinates":272},[273,274],9.26838,45.41047,{"lat":274,"lon":273},[277],{"name":278,"role":28,"phone":87,"phoneExt":16,"email":279},"Massimo Piepoli","massimo.piepoli@unimi.it",{"facility":281,"status":91,"city":282,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":283,"geoPoint":287,"contacts":288},"S. Maria alle Scotte Hospital UOC cardiologia clinico-chirurgica (UTIC)","Siena",{"type":42,"coordinates":284},[285,286],11.33064,43.31822,{"lat":286,"lon":285},[289],{"name":290,"role":28,"phone":74,"phoneExt":16,"email":291},"Francesca Righini","righini.francescamaria@gmail.com",{"facility":293,"status":91,"city":282,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":294,"geoPoint":296,"contacts":297},"S. Maria alle Scotte Hospital UOSA malattie cardiovascolari",{"type":42,"coordinates":295},[285,286],{"lat":286,"lon":285},[298],{"name":299,"role":28,"phone":61,"phoneExt":16,"email":300},"Alberto Palazzuoli","palazzuoli2@unisi.it",{"facility":302,"status":36,"city":303,"state":16,"zip":16,"country":38,"countryCode":40,"cosmosGeoPoint":304,"geoPoint":308,"contacts":309},"Azienda sanitaria universitaria Giuliano Isontina (ASUGI)","Trieste",{"type":42,"coordinates":305},[306,307],13.77678,45.64953,{"lat":307,"lon":306},[310],{"name":311,"role":28,"phone":87,"phoneExt":16,"email":312},"Gianfranco SInagra","gianfranco.sinagra@asugi.sanita.fvg.it",{"type":314,"investigatorFullName":49,"investigatorTitle":315,"investigatorAffiliation":5,"oldNameTitle":16,"oldOrganization":16},"PRINCIPAL_INVESTIGATOR","Professor",[317,319,321,324,326,328,330,332,334,336,338,340,342,344,346,348,350,352,354,356,358,360,362,364,366,368,370,372,374],{"name":318,"class":6},"Santo Spirito Hospital, Italy",{"name":320,"class":6},"Fondazione Toscana Gabriele Monasterio",{"name":322,"class":323},"Spedali Civili, University of Brescia, Italy","UNKNOWN",{"name":325,"class":6},"Monaldi Hospital",{"name":327,"class":323},"Azienda Sanitaria Universitaria Giuliano Isontina (ASU GI)",{"name":329,"class":6},"San Raffaele University Hospital, Italy",{"name":331,"class":6},"University of Foggia",{"name":333,"class":6},"Azienda Ospedaliera Niguarda Cà Granda",{"name":335,"class":6},"Azienda Policlinico Umberto I",{"name":337,"class":323},"Federico II University of Naples, Department of Clinical Medicine and Surgery, Naples, Italy",{"name":339,"class":323},"Città di Lecce Hospital",{"name":341,"class":323},"Policlinico G . Martino, Messina Italy",{"name":343,"class":6},"Azienda Ospedaliera Universitaria Senese",{"name":345,"class":6},"Azienda Sanitaria di Firenze",{"name":347,"class":323},"Ospedale San Luca, Istituto Auxologico Italiano, Milano",{"name":349,"class":323},"Casa di Cura Mater Dei",{"name":351,"class":6},"University of Bari",{"name":353,"class":6},"Azienda Ospedaliera di Perugia",{"name":355,"class":323},"I.R.C.C.S. Policlinico San Donato, San Donato Milanese, Italy",{"name":357,"class":6},"IRCCS Multimedica",{"name":359,"class":6},"Ospedali Riuniti Ancona",{"name":361,"class":6},"A.O. Ospedale Papa Giovanni XXIII",{"name":363,"class":6},"S. Andrea Hospital",{"name":365,"class":6},"Istituti Clinici Scientifici Maugeri SpA",{"name":367,"class":323},"Istituto Auxologico Italiano - IRCCS - Ospedale San Luca - Milano",{"name":369,"class":323},"Azienda Ospedaliero-Universitaria Senese",{"name":371,"class":6},"The Mediterranean Institute for Transplantation and Advanced Specialized Therapies",{"name":373,"class":6},"Federico II University",{"name":375,"class":323},"Ospedale Guglielmo da Saliceto, Piacenza","100584076",false,"NCT06884631","Metabolic Exercise Test Data Combined with Cardiac and Kidney Indexes (MECKI) Score Evolution: Identification of Cardiovascular Risk in Patients with Heart Failure","Metabolic Exercise Test Data Combined with Cardiac and Kidney Indexes (MECKI) Score Evolution: Study of Cardiovascular Risk in Patients with Heart Failure","MECKI","Inclusion Criteria:\n\n* age \\>18 past or present heart failure (NYHA functional class I-III, stage C of the ACC\u002FAHA classification)\n* documentation of left ventricular systolic dysfunction (LVEF \\\u003C40%)\n* stable clinical conditions\n* previous or concomitant cardiopulmonary exercise test\n\nExclusion Criteria:\n\n* scheduled cardiovascular treatment\n* clinical unstable condition\n* History of pulmonary embolism, significant valvular disease, pericardial disease, severe COPD, exercise-induced angina, exercise-induced ECG changes, severe brady- or tachyarrhythmias, or the presence of comorbidities that interfere with exercise performance.","ALL","18 Years",{"count":386,"type":387},10000,"ESTIMATED","10 Years","OBSERVATIONAL","Heart failure is a complex condition involving multiple organs beyond the cardiovascular system, all influencing disease progression and prognosis. Accurate risk assessment requires considering multiple variables, as no single parameter alone provides a complete prognostic picture.\n\nThis has led to the development of prognostic models combining clinical and laboratory parameters. Some of these models incorporate cardiopulmonary exercise testing (CPET), which provides key prognostic indicators. Since the 1990s, CPET has been recommended in heart failure management guidelines due to its strong prognostic value when combined with clinical data.\n\nHowever, existing risk models often exclude important predictors such as ventilatory parameters from CPET (VE\u002FVCO₂), renal function, and hemoglobin levels. To address this gap, in 2012 the investigators developed the MECKI (Metabolic Exercise test data combined with Cardiac and Kidney Indexes) score, integrating oxygen consumption, ventilatory efficiency, and easily accessible biochemical and echocardiographic parameters. Unlike previous models requiring extensive data collection, MECKI is based on only six variables, making it practical and effective.\n\nRecent studies suggest the need to update the cutoff values and parameters used for risk stratification, as new therapies and treatment strategies may significantly alter prognostic accuracy in different patient populations.\n\nThis study aims to expand and refine the MECKI score by updating the patient dataset, optimizing its performance in specific subgroups, and aligning it with emerging therapeutic approaches.\n\nAdditionally, the investigators will evaluate whether the model's risk accuracy varies in advanced-stage patients, those with comorbidities, or under different treatment regimens. This could lead to correction factors that enhance the score's predictive power across diverse clinical scenarios, further improving its applicability and reliability in heart failure management.",[392],"Heart Failure",[394,395,396,397,398],"prognosis","risk score","heart failure","cardiopulmonary exercise test","exercise","2025-03-18",{"date":401,"type":402},"2025-03-19","ACTUAL",{"date":404,"type":402},"2021-02-10",{"date":406,"type":387},"2028-12-31",{"name":5,"class":6},26]