Biomarker Phenotypes in Heart Failure with Preserved Ejection Fraction Using Hierarchical Clustering: A Pilot Study

Objectives: We hypothesized the existence of distinct phenotype-based groups within the very heterogeneous population of patients of heart failure with preserved ejection fraction (HFpEF) and using an unsupervised hierarchical clustering applied to plasma concentration of various biomarkers. We soug...

Full description

Saved in:
Bibliographic Details
Published inMedical principles and practice Vol. 32; no. 4-5; pp. 297 - 307
Main Authors Mitic, Valentina, Stojanovic, Dijana, Deljanin Ilic, Marina, Petrovic, Dejan, Ignjatovic, Aleksandra, Milenkovic, Jelena
Format Journal Article
LanguageEnglish
Published Basel, Switzerland S. Karger AG 01.11.2023
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Objectives: We hypothesized the existence of distinct phenotype-based groups within the very heterogeneous population of patients of heart failure with preserved ejection fraction (HFpEF) and using an unsupervised hierarchical clustering applied to plasma concentration of various biomarkers. We sought to characterize them as “biomarker phenotypes” and to conclude differences in their overall characteristics. Subjects and Methods: A cross-sectional study was conducted on 75 patients with HFpEF. An agglomerative hierarchical clustering was performed using the concentrations of cardiac remodeling biomarkers, BNP, and cystatin C. Results: According to the obtained heat map of this analysis, we concluded two distinctive biomarker phenotypes within the HFpEF. The “remodeled phenotype” presented with significantly higher concentrations of cardiac remodeling biomarkers and cystatin C (p < 0.001), higher prevalence of myocardial infarction (p = 0.047), STEMI (p = 0.045), atrial fibrillation (p = 0.047), and anemia: lower erythrocytes count (p = 0.037), hemoglobin concentration (p = 0.034), and hematocrit (p = 0.046), compared to “non-remodeled phenotype.” Echocardiography showed that patients within “remodeled phenotype” had significantly increased parameters of left ventricular remodeling: left ventricular mass index (p < 0.001), left ventricular mass (p = 0.001), diameters of the interventricular septum (p = 0.027), posterior wall (p = 0.003), and function alterations, intermediate pauses duration >2.0 s (p < 0.006). Conclusion: Unsupervised hierarchical clustering applied to plasma concentration of various biomarkers in patients with HFpEF enables the identification of two biomarker phenotypes, significantly different in clinical characteristics and cardiac structure and function, whereas one phenotype particularly relates to patients with reduced ejection fraction. These findings imply distinct underlying pathophysiology within a unique cohort of HFpEF.
AbstractList We hypothesized the existence of distinct phenotype-based groups within the very heterogeneous population of patients of heart failure with preserved ejection fraction (HFpEF) and using an unsupervised hierarchical clustering applied to plasma concentration of various biomarkers. We sought to characterize them as "biomarker phenotypes" and to conclude differences in their overall characteristics.OBJECTIVESWe hypothesized the existence of distinct phenotype-based groups within the very heterogeneous population of patients of heart failure with preserved ejection fraction (HFpEF) and using an unsupervised hierarchical clustering applied to plasma concentration of various biomarkers. We sought to characterize them as "biomarker phenotypes" and to conclude differences in their overall characteristics.A cross-sectional study was conducted on 75 patients with HFpEF. An agglomerative hierarchical clustering was performed using the concentrations of cardiac remodeling biomarkers, BNP and cystatin C.SUBJECTS AND METHODSA cross-sectional study was conducted on 75 patients with HFpEF. An agglomerative hierarchical clustering was performed using the concentrations of cardiac remodeling biomarkers, BNP and cystatin C.According to the obtained heat map of this analysis, we concluded two distinctive biomarker phenotypes within the HFpEF. The "remodeled phenotype" presented with significantly higher concentrations of cardiac remodeling biomarkers and cystatin C (p < 0.001), higher prevalence of myocardial infarction (p = 0.047), STEMI (p = 0.045), atrial fibrillation (p = 0.047) and anemia: lower erythrocytes count (p=0.037), hemoglobin concentration (p = 0.034) and hematocrit (p = 0.046), compared to "non-remodeled phenotype". Echocardiography showed that patients within "remodeled phenotype" had significantly increased parameters of left ventricular remodeling: left ventricular mass index (p < 0.001), left ventricular mass (p = 0.001), diameters of the interventricular septum (p = 0.027) and posterior wall (p = 0.003) and function alterations, intermediate pauses duration >2.0 seconds (p < 0.006).RESULTSAccording to the obtained heat map of this analysis, we concluded two distinctive biomarker phenotypes within the HFpEF. The "remodeled phenotype" presented with significantly higher concentrations of cardiac remodeling biomarkers and cystatin C (p < 0.001), higher prevalence of myocardial infarction (p = 0.047), STEMI (p = 0.045), atrial fibrillation (p = 0.047) and anemia: lower erythrocytes count (p=0.037), hemoglobin concentration (p = 0.034) and hematocrit (p = 0.046), compared to "non-remodeled phenotype". Echocardiography showed that patients within "remodeled phenotype" had significantly increased parameters of left ventricular remodeling: left ventricular mass index (p < 0.001), left ventricular mass (p = 0.001), diameters of the interventricular septum (p = 0.027) and posterior wall (p = 0.003) and function alterations, intermediate pauses duration >2.0 seconds (p < 0.006).Unsupervised hierarchical clustering applied to plasma concentration of various biomarkers in patients with HFpEF enables the identification of two biomarker phenotypes, significantly different in clinical characteristics and cardiac structure and function, whereas one phenotype particularly relates to patients with reduced ejection fraction. These findings imply distinct underlying pathophysiology within a unique cohort of HFpEF.CONCLUSIONUnsupervised hierarchical clustering applied to plasma concentration of various biomarkers in patients with HFpEF enables the identification of two biomarker phenotypes, significantly different in clinical characteristics and cardiac structure and function, whereas one phenotype particularly relates to patients with reduced ejection fraction. These findings imply distinct underlying pathophysiology within a unique cohort of HFpEF.
Objectives: We hypothesized the existence of distinct phenotype-based groups within the very heterogeneous population of patients of heart failure with preserved ejection fraction (HFpEF) and using an unsupervised hierarchical clustering applied to plasma concentration of various biomarkers. We sought to characterize them as “biomarker phenotypes” and to conclude differences in their overall characteristics. Subjects and Methods: A cross-sectional study was conducted on 75 patients with HFpEF. An agglomerative hierarchical clustering was performed using the concentrations of cardiac remodeling biomarkers, BNP, and cystatin C. Results: According to the obtained heat map of this analysis, we concluded two distinctive biomarker phenotypes within the HFpEF. The “remodeled phenotype” presented with significantly higher concentrations of cardiac remodeling biomarkers and cystatin C (p < 0.001), higher prevalence of myocardial infarction (p = 0.047), STEMI (p = 0.045), atrial fibrillation (p = 0.047), and anemia: lower erythrocytes count (p = 0.037), hemoglobin concentration (p = 0.034), and hematocrit (p = 0.046), compared to “non-remodeled phenotype.” Echocardiography showed that patients within “remodeled phenotype” had significantly increased parameters of left ventricular remodeling: left ventricular mass index (p < 0.001), left ventricular mass (p = 0.001), diameters of the interventricular septum (p = 0.027), posterior wall (p = 0.003), and function alterations, intermediate pauses duration >2.0 s (p < 0.006). Conclusion: Unsupervised hierarchical clustering applied to plasma concentration of various biomarkers in patients with HFpEF enables the identification of two biomarker phenotypes, significantly different in clinical characteristics and cardiac structure and function, whereas one phenotype particularly relates to patients with reduced ejection fraction. These findings imply distinct underlying pathophysiology within a unique cohort of HFpEF.
Author Ignjatovic, Aleksandra
Stojanovic, Dijana
Mitic, Valentina
Milenkovic, Jelena
Deljanin Ilic, Marina
Petrovic, Dejan
Author_xml – sequence: 1
  givenname: Valentina
  surname: Mitic
  fullname: Mitic, Valentina
– sequence: 2
  givenname: Dijana
  surname: Stojanovic
  fullname: Stojanovic, Dijana
  email: *Dijana Stojanovic, dijana.stojanovic@medfak.ni.ac.rs
– sequence: 3
  givenname: Marina
  surname: Deljanin Ilic
  fullname: Deljanin Ilic, Marina
– sequence: 4
  givenname: Dejan
  surname: Petrovic
  fullname: Petrovic, Dejan
– sequence: 5
  givenname: Aleksandra
  surname: Ignjatovic
  fullname: Ignjatovic, Aleksandra
– sequence: 6
  givenname: Jelena
  surname: Milenkovic
  fullname: Milenkovic, Jelena
BookMark eNptkctrGzEQxkVIycPNofceBL00h20lzb7UW2riuJDShabnRasdx3I2K3ekbfB_HwWHBEJP8zH8-ObxnbLD0Y_I2AcpvkhZ6K9CiAJyWRQH7ETmCjIhC3mYtJAyq4pKHrPTEDYJqwHEETuGqoIcAE5Y-O78vaE7JN6scfRxt8XA3ciXaCjyhXHDRMgfXFzzhjAg_cOeX27QRudHviCzF3-CG2_50iEZsmtnzcDnwxQiUup_4xe8cYOP_Hec-t179m5lhoBnz3XGbhaXN_Nldv3r6sf84jqzAHnMSq3VCmsN0HWyQ6N6bXtTm17ZTuqqkmVXKqVysJ3qZJ3urnVpLFpb6Np0MGOf97Zb8n8nDLG9d8HiMJgR_RRaVZe1VKDThBn79Abd-InGtFyrtBCgRJ6LRJ3vKUs-BMJVuyWXnrdrpWifgmhfgnh1vDN0i_RC_myaPdFu-1WiPv6XejZ5BJMIj5Y
Cites_doi 10.1002/ejhf.137
10.1515/CCLM.2002.060
10.1016/j.jacc.2015.03.043
10.1515/cclm-2020-0310
10.1016/j.ejim.2022.01.012
10.1620/tjem.250.233
10.1515/CCLM.2006.063
10.1016/j.jacc.2014.03.034
10.3390/ijms24010844
10.1161/JAHA.118.009034
10.1002/ejhf.327
10.1002/ejhf.430
10.1093/eurheartj/ehy712
10.1002/ejhf.592
10.1093/eurheartj/ehu204
10.1136/heartjnl-2019-315481
10.1152/ajpheart.00684.2005
10.1093/eurheartj/ehz641
10.1038/nrg2897
10.1002/ejhf.1621
10.1097/HCO.0b013e32833f0438
10.1093/eurheartj/ehaa083
10.1016/j.jacc.2014.07.979
10.1093/ehjci/jev014
10.1161/CIRCULATIONAHA.114.010637
10.1016/j.jchf.2019.09.009
10.1016/j.ijcard.2020.08.065
10.3390/jcdd9080256
10.1515/CCLM.2004.108
10.1016/S2213-8587(18)30051-2
10.1002/ejhf.483
10.1161/JAHA.115.002477
10.1016/j.jchf.2013.10.006
10.1016/B978-0-12-375003-7.00006-6
ContentType Journal Article
Copyright 2023 The Author(s). Published by S. Karger AG, Basel
2023 The Author(s). Published by S. Karger AG, Basel. This work is licensed under the Creative Commons Attribution – Non-Commercial License http://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
The Author(s). Published by S. Karger AG, Basel.
Copyright_xml – notice: 2023 The Author(s). Published by S. Karger AG, Basel
– notice: 2023 The Author(s). Published by S. Karger AG, Basel. This work is licensed under the Creative Commons Attribution – Non-Commercial License http://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: The Author(s). Published by S. Karger AG, Basel.
DBID M--
AAYXX
CITATION
3V.
7X7
7XB
88E
8FI
8FJ
8FK
ABUWG
AFKRA
BENPR
CCPQU
FYUFA
GHDGH
K9.
M0S
M1P
PHGZM
PHGZT
PJZUB
PKEHL
PPXIY
PQEST
PQQKQ
PQUKI
PRINS
7X8
DOI 10.1159/000534155
DatabaseTitle CrossRef
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
ProQuest One Community College
ProQuest One Health & Nursing
ProQuest Hospital Collection
Health Research Premium Collection (Alumni)
ProQuest Central China
ProQuest Hospital Collection (Alumni)
ProQuest Central
ProQuest Health & Medical Complete
Health Research Premium Collection
ProQuest Medical Library
ProQuest One Academic UKI Edition
Health and Medicine Complete (Alumni Edition)
Health & Medical Research Collection
ProQuest Central (New)
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Medical Library (Alumni)
ProQuest Central (Alumni)
MEDLINE - Academic
DatabaseTitleList MEDLINE - Academic
ProQuest One Academic Middle East (New)
CrossRef

Database_xml – sequence: 1
  dbid: M--
  name: Karger Open Access
  url: https://www.karger.com/OpenAccess
  sourceTypes:
    Enrichment Source
    Publisher
– sequence: 2
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 1423-0151
EndPage 307
ExternalDocumentID 10_1159_000534155
534155
GeographicLocations United Kingdom--UK
United States--US
GeographicLocations_xml – name: United Kingdom--UK
– name: United States--US
GroupedDBID ---
0R~
0~B
30W
326
36B
3O.
3V.
4.4
53G
5GY
7X7
88E
8FI
8FJ
8UI
AAWTL
AAYIC
ABPAZ
ABUWG
ACGFS
ADBBV
AENEX
AEYAO
AFKRA
AHMBA
ALDHI
ALIPV
ALMA_UNASSIGNED_HOLDINGS
AOIJS
AZPMC
BAWUL
BCNDV
BENPR
BPHCQ
BVXVI
CCPQU
CS3
CYUIP
DU5
E0A
E3Z
EBS
EMB
EMOBN
F5P
FB.
FYUFA
GROUPED_DOAJ
HMCUK
HYE
HZ~
IAO
IHR
KUZGX
M--
M1P
MK0
O1H
O9-
OK1
P2P
PQQKQ
PROAC
PSQYO
RKO
RNS
RPM
SV3
UJ6
UKHRP
AAYXX
ABBTS
ABWCG
ACQXL
ADAGL
AFJJK
AFSIO
AHFRZ
AIOBO
CAG
CITATION
COF
DIK
EJD
ITC
PHGZM
PHGZT
PJZUB
PPXIY
RIG
RXVBD
TR2
7XB
8FK
K9.
PKEHL
PQEST
PQUKI
PRINS
7X8
ID FETCH-LOGICAL-c334t-6992fe8933bb1bea2d9cda8ad2cb197716b622243cb2b18423896acecc598ab3
IEDL.DBID 7X7
ISSN 1011-7571
1423-0151
IngestDate Fri Jul 11 04:55:58 EDT 2025
Fri Jul 25 05:24:09 EDT 2025
Tue Aug 05 12:01:03 EDT 2025
Thu Sep 05 17:57:48 EDT 2024
Thu Aug 29 12:04:47 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 4-5
Keywords Heart failure with a preserved ejection fraction
Phenomapping
Hierarchical clustering
Cardiac remodeling biomarkers
Cystatin C
Language English
License This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC). Usage and distribution for commercial purposes requires written permission.
https://creativecommons.org/licenses/by-nc/4.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c334t-6992fe8933bb1bea2d9cda8ad2cb197716b622243cb2b18423896acecc598ab3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
OpenAccessLink https://karger.com/doi/10.1159/000534155
PMID 37734333
PQID 2900320440
PQPubID 2047984
PageCount 11
ParticipantIDs proquest_miscellaneous_2868123989
karger_primary_534155
crossref_primary_10_1159_000534155
proquest_journals_2900320440
PublicationCentury 2000
PublicationDate 2023-11-01
PublicationDateYYYYMMDD 2023-11-01
PublicationDate_xml – month: 11
  year: 2023
  text: 2023-11-01
  day: 01
PublicationDecade 2020
PublicationPlace Basel, Switzerland
PublicationPlace_xml – name: Basel, Switzerland
– name: Basel
PublicationTitle Medical principles and practice
PublicationTitleAlternate Med Princ Pract
PublicationYear 2023
Publisher S. Karger AG
Publisher_xml – name: S. Karger AG
References D’Elia E, Vaduganathan M, Gori M, Gavazzi A, Butler J, Senni M. Role of biomarkers in cardiac structure phenotyping in heart failure with preserved ejection fraction: critical appraisal and practical use. Eur J Heart Fail. 2015;17(12):1231–9.
Tromp J, Ouwerkerk W, Demissei BG, Anker SD, Cleland JG, Dickstein K. Novel endotypes in heart failure: effects on guideline-directed medical therapy. Eur Heart J. 2018;39(48):4269–76.
Hwang SJ, Melenovsky V, Borlaug BA. Implications of coronary artery disease in heart failure with preserved ejection fraction. J Am Coll Cardiol. 20146325 Pt A281727.
Farmakis D, Mueller C, Apple FS. High-sensitivity cardiac troponin assays for cardiovascular risk stratification in the general population. Eur Heart J. 2020;41(41):4050–6.
Lanktree MB, Johansen CT, Joy TR, Hegele RA. A translational view of the genetics of lipodystrophy and ectopic fat deposition. Prog Mol Biol Transl Sci. 2010;94:159–96.
Ahlqvist E, Storm P, Käräjämäki A, Martinell M, Dorkhan M, Carlsson A. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018;6(5):361–9.
Kao DP, Lewsey JD, Anand IS, Massie BM, Zile MR, Carson PE. Characterization of subgroups of heart failure patients with preserved ejection fraction with possible implications for prognosis and treatment response. Eur J Heart Fail. 2015;17(9):925–35.
Clerico A, Zaninotto M, Passino C, Aspromonte N, Piepoli MF, Migliardi M. Evidence on clinical relevance of cardiovascular risk evaluation in the general population using cardio-specific biomarkers. Clin Chem Lab Med. 2020;59(1):79–90.
Pieske B, Tschöpe C, de Boer RA, Fraser AG, Anker SD, Donal E. How to diagnose heart failure with preserved ejection fraction: the HFA–PEFF diagnostic algorithm: a consensus recommendation from the Heart Failure Association (HFA) of the European Society of Cardiology (ESC). Eur Heart J. 2019;40(40):3297–317.
Clerico A, Carlo Zucchelli G, Pilo A, Passino C, Emdin M. Clinical relevance of biological variation: the lesson of brain natriuretic peptide (BNP) and NT-proBNP assay. Clin Chem Lab Med. 2006;44(4):366–78.
Perrone MA, Aimo A, Bernardini S, Clerico A. Inflammageing and cardiovascular system: focus on cardiokines and cardiac-specific biomarkers. Int J Mol Sci. 2023;24(1):844.
Clerico A, Recchia FA, Passino C, Emdin M. Cardiac endocrine function is an essential component of the homeostatic regulation network: physiological and clinical implications. Am J Physiol Heart Circ Physiol. 2006;290(1):17–29.
Butler J, Fonarow G, Zile MR, Lam CS, Roessig L, Schelbert EB. Developing therapies for heart failure with preserved ejection fraction: current state and future directions. JACC Heart Fail. 2014;2:97–112.
Cohen JB, Schrauben SJ, Zhao L, Basso MD, Cvijic ME, Li Z. Clinical phenogroups in heart failure with preserved ejection fraction: detailed phenotypes, prognosis, and response to Spironolactone. JACC Heart Fail. 2020;8(3):172–84.
Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European society of cardiology (ESC) Developed with the special contribution of the heart failure association (HFA) of the ESC. Eur J Heart Fail. 2016;18(8):891–975.
Houle D, Govindaraju D, Omholt S. Phenomics: the next challenge. Nat Rev Genet. 2010;11(12):855–66.
Lund LH, Donal E, Oger E, Hage C, Persson H, Haugen-Löfman I. Association between cardiovascular vs. non-cardiovascular co-morbidities and outcomes in heart failure with preserved ejection fraction. Eur J Heart Fail. 2014;16(9):992–1001.
Senni M, Paulus WJ, Gavazzi A, Fraser AG, Díez J, Solomon SD. New strategies for heart failure with preserved ejection fraction: the importance of targeted therapies for heart failure phenotypes. Eur Heart J. 2014;35(40):2797–815.
Emdin M, Passino C, Prontera C, Iervasi A, Ripoli A, Masini S. Cardiac natriuretic hormones, neuro-hormones, thyroid hormones and cytokines in normal subjects and patients with heart failure. Clin Chem Lab Med. 2004;42(6):627–36.
Kelly JP, Mentz RJ, Mebazaa A, Voors AA, Butler J, Roessig L. Patient selection in heart failure with preserved ejection fraction clinical trials. Am Coll Cardiol. 2015;65(16):1668–82.
Ahmad T, Pencina MJ, Schulte PJ, O'Brien E, Whellan DJ, Piña IL. Clinical implications of chronic heart failure phenotypes defined by cluster analysis. J Am Coll Cardiol. 2014;64(17):1765–74.
Samson R, Jaiswal A, Ennezat PV, Cassidy M, Le Jemtel TH. Clinical phenotypes in heart failure with preserved ejection fraction. J Am Heart Assoc. 2016;5(1):e002477.
Aimo A, Georgiopoulos G, Panichella G, Vergaro G, Passino C, Emdin M. High-sensitivity troponins for outcome prediction in the general population: a systematic review and meta-analysis. Eur J Intern Med. 2022;98:61–8.
Lang RM, Badano LP, Mor-Avi VV, Afilalo J, Armstrong A, Ernande L. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015;16(3):233–70.
van Riet EES, Hoes AW, Wagenaar KP, Limburg A, Landman MAJ, Rutten FH. Epidemiology of heart failure: the prevalence of heart failure and ventricular dysfunction in older adults over time. A systematic review. Eur J Heart Fail. 2016;18(3):242–52.
Morfino P, Aimo A, Castiglione V, Vergaro G, Emdin M, Clerico A. Biomarkers of HFpEF: natriuretic peptides, high-sensitivity troponins and beyond. J Cardiovasc Dev Dis. 2022;9(8):256.
R Core TeamR: a language and environment for statistical computingVienna, AustriaR Foundation for Statistical Computing. 2014. http://www.R-project.org/.
Shah SJ, Katz DH, Selvaraj S, Burke MA, Yancy CW, Gheorghiade M. Phenomapping for novel classification of heart failure with preserved ejection fraction. Circulation. 2015;131(3):269–79.
Hedman AK, Hage C, Sharma A, Brosnan MJ, Buckbinder L, Gan LM. Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning. Heart. 2020;106(5):342–9.
Hastie T, Tibshirani R, Friedman J. Unsupervised learning: hierarchical clustering2nd ed. In: Hastie T, Tibshirani R, Friedman J, editors. The elements of statistical learningNew York, NYSpringer. 2009. p. 5208.
Segar MW, Patel KV, Ayers C, Basit M, Tang WH, Willett D. Phenomapping of patients with heart failure with preserved ejection fraction using machine learning-based unsupervised cluster analysis. Eur J Heart Fail. 2020;22(1):148–58.
Ohara T, Little WC. Evolving focus on diastolic dysfunction in patients with coronary artery disease. Curr Opin Cardiol. 2010;25(6):613–21.
Mitic V, Stojanovic D, Deljanin Ilic M, Stojanovic M, Petrovic D, Ignjatovic A. Cardiac remodeling biomarkers as potential circulating markers of left ventricular hypertrophy in heart failure with preserved ejection fraction. Tohoku J Exp Med. 2020;250(4):233–42.
Gu J, Pan J, Lin H, Zhang J, Wang C. Characteristics, prognosis and treatment response in distinct phenogroups of heart failure with preserved ejection fraction. Int J Cardiol. 2021;323:148–54.
Clerico A, Del Ry S, Maffei S, Prontera C, Emdin M, Giannessi D. The circulating levels of cardiac natriuretic hormones in healthy adults: effects of age and sex. Clin Chem Lab Med. 2002;40(4):371–7.
Liu CM, Lin CY, Chang SL, Lin YJ, Lo LW, Hu YF. Intermediate pause at daytime is associated with increased cardiovascular risk and mortality: an 8-year cohort study. J Am Heart Assoc. 2018;7(12):e009034.
ref13
ref12
ref34
ref15
ref14
ref31
ref30
ref11
ref33
ref10
ref32
ref2
ref1
ref17
ref16
ref19
ref18
ref24
ref23
ref26
ref25
ref20
ref22
ref21
ref28
ref27
ref29
ref8
ref7
ref9
ref4
ref3
ref6
ref5
References_xml – reference: Pieske B, Tschöpe C, de Boer RA, Fraser AG, Anker SD, Donal E. How to diagnose heart failure with preserved ejection fraction: the HFA–PEFF diagnostic algorithm: a consensus recommendation from the Heart Failure Association (HFA) of the European Society of Cardiology (ESC). Eur Heart J. 2019;40(40):3297–317.
– reference: Shah SJ, Katz DH, Selvaraj S, Burke MA, Yancy CW, Gheorghiade M. Phenomapping for novel classification of heart failure with preserved ejection fraction. Circulation. 2015;131(3):269–79.
– reference: Segar MW, Patel KV, Ayers C, Basit M, Tang WH, Willett D. Phenomapping of patients with heart failure with preserved ejection fraction using machine learning-based unsupervised cluster analysis. Eur J Heart Fail. 2020;22(1):148–58.
– reference: Cohen JB, Schrauben SJ, Zhao L, Basso MD, Cvijic ME, Li Z. Clinical phenogroups in heart failure with preserved ejection fraction: detailed phenotypes, prognosis, and response to Spironolactone. JACC Heart Fail. 2020;8(3):172–84.
– reference: D’Elia E, Vaduganathan M, Gori M, Gavazzi A, Butler J, Senni M. Role of biomarkers in cardiac structure phenotyping in heart failure with preserved ejection fraction: critical appraisal and practical use. Eur J Heart Fail. 2015;17(12):1231–9.
– reference: Kao DP, Lewsey JD, Anand IS, Massie BM, Zile MR, Carson PE. Characterization of subgroups of heart failure patients with preserved ejection fraction with possible implications for prognosis and treatment response. Eur J Heart Fail. 2015;17(9):925–35.
– reference: Lang RM, Badano LP, Mor-Avi VV, Afilalo J, Armstrong A, Ernande L. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015;16(3):233–70.
– reference: Gu J, Pan J, Lin H, Zhang J, Wang C. Characteristics, prognosis and treatment response in distinct phenogroups of heart failure with preserved ejection fraction. Int J Cardiol. 2021;323:148–54.
– reference: Farmakis D, Mueller C, Apple FS. High-sensitivity cardiac troponin assays for cardiovascular risk stratification in the general population. Eur Heart J. 2020;41(41):4050–6.
– reference: Houle D, Govindaraju D, Omholt S. Phenomics: the next challenge. Nat Rev Genet. 2010;11(12):855–66.
– reference: Hedman AK, Hage C, Sharma A, Brosnan MJ, Buckbinder L, Gan LM. Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning. Heart. 2020;106(5):342–9.
– reference: Mitic V, Stojanovic D, Deljanin Ilic M, Stojanovic M, Petrovic D, Ignjatovic A. Cardiac remodeling biomarkers as potential circulating markers of left ventricular hypertrophy in heart failure with preserved ejection fraction. Tohoku J Exp Med. 2020;250(4):233–42.
– reference: Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European society of cardiology (ESC) Developed with the special contribution of the heart failure association (HFA) of the ESC. Eur J Heart Fail. 2016;18(8):891–975.
– reference: Ahmad T, Pencina MJ, Schulte PJ, O'Brien E, Whellan DJ, Piña IL. Clinical implications of chronic heart failure phenotypes defined by cluster analysis. J Am Coll Cardiol. 2014;64(17):1765–74.
– reference: Clerico A, Del Ry S, Maffei S, Prontera C, Emdin M, Giannessi D. The circulating levels of cardiac natriuretic hormones in healthy adults: effects of age and sex. Clin Chem Lab Med. 2002;40(4):371–7.
– reference: Liu CM, Lin CY, Chang SL, Lin YJ, Lo LW, Hu YF. Intermediate pause at daytime is associated with increased cardiovascular risk and mortality: an 8-year cohort study. J Am Heart Assoc. 2018;7(12):e009034.
– reference: Lanktree MB, Johansen CT, Joy TR, Hegele RA. A translational view of the genetics of lipodystrophy and ectopic fat deposition. Prog Mol Biol Transl Sci. 2010;94:159–96.
– reference: Lund LH, Donal E, Oger E, Hage C, Persson H, Haugen-Löfman I. Association between cardiovascular vs. non-cardiovascular co-morbidities and outcomes in heart failure with preserved ejection fraction. Eur J Heart Fail. 2014;16(9):992–1001.
– reference: Emdin M, Passino C, Prontera C, Iervasi A, Ripoli A, Masini S. Cardiac natriuretic hormones, neuro-hormones, thyroid hormones and cytokines in normal subjects and patients with heart failure. Clin Chem Lab Med. 2004;42(6):627–36.
– reference: Ahlqvist E, Storm P, Käräjämäki A, Martinell M, Dorkhan M, Carlsson A. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018;6(5):361–9.
– reference: Hwang SJ, Melenovsky V, Borlaug BA. Implications of coronary artery disease in heart failure with preserved ejection fraction. J Am Coll Cardiol. 20146325 Pt A281727.
– reference: van Riet EES, Hoes AW, Wagenaar KP, Limburg A, Landman MAJ, Rutten FH. Epidemiology of heart failure: the prevalence of heart failure and ventricular dysfunction in older adults over time. A systematic review. Eur J Heart Fail. 2016;18(3):242–52.
– reference: Ohara T, Little WC. Evolving focus on diastolic dysfunction in patients with coronary artery disease. Curr Opin Cardiol. 2010;25(6):613–21.
– reference: Samson R, Jaiswal A, Ennezat PV, Cassidy M, Le Jemtel TH. Clinical phenotypes in heart failure with preserved ejection fraction. J Am Heart Assoc. 2016;5(1):e002477.
– reference: Clerico A, Recchia FA, Passino C, Emdin M. Cardiac endocrine function is an essential component of the homeostatic regulation network: physiological and clinical implications. Am J Physiol Heart Circ Physiol. 2006;290(1):17–29.
– reference: Hastie T, Tibshirani R, Friedman J. Unsupervised learning: hierarchical clustering2nd ed. In: Hastie T, Tibshirani R, Friedman J, editors. The elements of statistical learningNew York, NYSpringer. 2009. p. 5208.
– reference: Tromp J, Ouwerkerk W, Demissei BG, Anker SD, Cleland JG, Dickstein K. Novel endotypes in heart failure: effects on guideline-directed medical therapy. Eur Heart J. 2018;39(48):4269–76.
– reference: Aimo A, Georgiopoulos G, Panichella G, Vergaro G, Passino C, Emdin M. High-sensitivity troponins for outcome prediction in the general population: a systematic review and meta-analysis. Eur J Intern Med. 2022;98:61–8.
– reference: Butler J, Fonarow G, Zile MR, Lam CS, Roessig L, Schelbert EB. Developing therapies for heart failure with preserved ejection fraction: current state and future directions. JACC Heart Fail. 2014;2:97–112.
– reference: Clerico A, Carlo Zucchelli G, Pilo A, Passino C, Emdin M. Clinical relevance of biological variation: the lesson of brain natriuretic peptide (BNP) and NT-proBNP assay. Clin Chem Lab Med. 2006;44(4):366–78.
– reference: Senni M, Paulus WJ, Gavazzi A, Fraser AG, Díez J, Solomon SD. New strategies for heart failure with preserved ejection fraction: the importance of targeted therapies for heart failure phenotypes. Eur Heart J. 2014;35(40):2797–815.
– reference: R Core TeamR: a language and environment for statistical computingVienna, AustriaR Foundation for Statistical Computing. 2014. http://www.R-project.org/.
– reference: Perrone MA, Aimo A, Bernardini S, Clerico A. Inflammageing and cardiovascular system: focus on cardiokines and cardiac-specific biomarkers. Int J Mol Sci. 2023;24(1):844.
– reference: Morfino P, Aimo A, Castiglione V, Vergaro G, Emdin M, Clerico A. Biomarkers of HFpEF: natriuretic peptides, high-sensitivity troponins and beyond. J Cardiovasc Dev Dis. 2022;9(8):256.
– reference: Clerico A, Zaninotto M, Passino C, Aspromonte N, Piepoli MF, Migliardi M. Evidence on clinical relevance of cardiovascular risk evaluation in the general population using cardio-specific biomarkers. Clin Chem Lab Med. 2020;59(1):79–90.
– reference: Kelly JP, Mentz RJ, Mebazaa A, Voors AA, Butler J, Roessig L. Patient selection in heart failure with preserved ejection fraction clinical trials. Am Coll Cardiol. 2015;65(16):1668–82.
– ident: ref21
  doi: 10.1002/ejhf.137
– ident: ref29
  doi: 10.1515/CCLM.2002.060
– ident: ref6
  doi: 10.1016/j.jacc.2015.03.043
– ident: ref33
  doi: 10.1515/cclm-2020-0310
– ident: ref34
  doi: 10.1016/j.ejim.2022.01.012
– ident: ref22
  doi: 10.1620/tjem.250.233
– ident: ref26
  doi: 10.1515/CCLM.2006.063
– ident: ref23
  doi: 10.1016/j.jacc.2014.03.034
– ident: ref28
  doi: 10.3390/ijms24010844
– ident: ref31
  doi: 10.1161/JAHA.118.009034
– ident: ref13
  doi: 10.1002/ejhf.327
– ident: ref20
  doi: 10.1002/ejhf.430
– ident: ref18
  doi: 10.1093/eurheartj/ehy712
– ident: ref1
  doi: 10.1002/ejhf.592
– ident: ref4
  doi: 10.1093/eurheartj/ehu204
– ident: ref11
  doi: 10.1136/heartjnl-2019-315481
– ident: ref25
  doi: 10.1152/ajpheart.00684.2005
– ident: ref2
  doi: 10.1093/eurheartj/ehz641
– ident: ref9
  doi: 10.1038/nrg2897
– ident: ref15
  doi: 10.1002/ejhf.1621
– ident: ref24
  doi: 10.1097/HCO.0b013e32833f0438
– ident: ref32
  doi: 10.1093/eurheartj/ehaa083
– ident: ref17
  doi: 10.1016/j.jacc.2014.07.979
– ident: ref19
  doi: 10.1093/ehjci/jev014
– ident: ref5
  doi: 10.1161/CIRCULATIONAHA.114.010637
– ident: ref16
  doi: 10.1016/j.jchf.2019.09.009
– ident: ref14
  doi: 10.1016/j.ijcard.2020.08.065
– ident: ref8
  doi: 10.3390/jcdd9080256
– ident: ref27
  doi: 10.1515/CCLM.2004.108
– ident: ref12
  doi: 10.1016/S2213-8587(18)30051-2
– ident: ref3
  doi: 10.1002/ejhf.483
– ident: ref30
  doi: 10.1161/JAHA.115.002477
– ident: ref7
  doi: 10.1016/j.jchf.2013.10.006
– ident: ref10
  doi: 10.1016/B978-0-12-375003-7.00006-6
SSID ssj0008330
Score 2.3242455
Snippet Objectives: We hypothesized the existence of distinct phenotype-based groups within the very heterogeneous population of patients of heart failure with...
We hypothesized the existence of distinct phenotype-based groups within the very heterogeneous population of patients of heart failure with preserved ejection...
SourceID proquest
crossref
karger
SourceType Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 297
SubjectTerms Biomarkers
Clustering
Cysts
Ejection fraction
Electrocardiography
Flow velocity
Genotype & phenotype
Heart failure
Heart rate
Machine learning
Original Paper
Patients
Plasma
Population
Pulmonary arteries
Rehabilitation
Title Biomarker Phenotypes in Heart Failure with Preserved Ejection Fraction Using Hierarchical Clustering: A Pilot Study
URI https://karger.com/doi/10.1159/000534155
https://www.proquest.com/docview/2900320440
https://www.proquest.com/docview/2868123989
Volume 32
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3NS8MwFA86RbyInzidI4rX4Nq0aeNFNtkYwqTIhN1KkqZYne3cuoP_vXlpN1HBSw5JyCFf7-v33g-ha6Zp4IHTXUoIM6auQ4QvBVGK-7yjQUWA5OTRIxs-ew8Tf1I73BY1rHL1J9qPOikU-MhvXHC5uUCQfDf7IMAaBdHVmkJjE21B6TKAdAWTtcFltAtaVSNwHBL4gVNXFjIS3HLZURCmP-TR9hvAr-d__mUrbAb7aK_WEnG3OtYDtKHzQ7QzquPgR2jRy4p3ANbMcfSi8wIcqQuc5XhoLm6JByIDtDkGJysGkAXAGhPcf7W4qxwP5lU6A7aAATzMIAvZkqJM8f10CbUTTP8t7uIomxYlBrDh5zEaD_rj-yGp6ROIotQrCePcTbXRR6iUjtTCTbhKRCgSV0nHqH0Ok8xoBx5V0pXG0DPCmzOhzJn6PBSSnqBGXuT6FGEmOqmgzOvQQELJMJGoNNSJ54P0Z17aRFerPYxnVZGM2BoXPo_XG91Ex9Xurqes-lu_-kdRVA3Fs8Ss3VqdRVw_r0X8fRma6HI9bB4GRDtEroulmRNCaTXKQ372_xLnaBc45KsEwxZqlPOlvjCaRinb9jq10Vav_xg9ta29btoRIV_cydRg
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwED-NDrG9TAOG1lGGQfAY0diJG0-apm20ythaRahIe4tsxxHZSlLaVGh_1P7H-fJRBEi87dWOLOV89n34d_cD-MANG3iYdFcKnxlT6jrSV9LRWviib9BFwOLk8YSH37wv1_71Bty3tTAIq2zvxOqiTgqNOfJPFFNuFAmST-Y_HWSNwtfVlkKjVotLc_fLhmzL44vPdn8_UjoaTs9Dp2EVcDRjXulwIWhqkGVeKVcZSROhExnIhGrlWm_I5Ypbo-kxraiy8Y-1aYJLbX_VF4FUzC77BDY9ZiOZDmyeDSfR1_XVHzBWtz9wXWfgD9ymlZF1GSryPIbW-w8D-PQW8d6LfwxBZd1Gu7DTuKXktNaj57Bh8hfwbNw8vL-E5VlW_EAkz4JE301eYOZ2SbKchFYkJRnJDOHtBLO6BFEdiKNMyPCmAnrlZLSo6ydIhVAgYYZlzxULy4ycz1bYrMGOH5FTEmWzoiSIbrzbg-ljSPYVdPIiN_tAuOynknGvzwYKe5TJRKeBSTwf3Q3upV1438owntddOeIqmvFFvBZ0F_Zq6a4_acd7f42Po6ieiueJXbvX7kXcnOdl_Fv7uvBuPW1PIj6vyNwUK_tNgL3cmAjEwf-XeAtb4XR8FV9dTC5fwzYS2NfVjT3olIuVeWPdnFIdNspFIH5kdX4AKIkPcQ
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwEB6VgqpeEI8iFhYwCI5RN3bixEgIlbbRlrJVDkXaW2Q7jghsk2U3K9Sfxr9jJo9FgMStVzuylPHY8_A38wG8lk5EASXdjaFnxoL7ng6N9qxVoZo4chGoOHl2Iaefg4_zcL4DP4daGIJVDndie1HntaUc-SGnlBsnguTDoodFpCfJ--V3jxik6KV1oNPoVOTcXf_A8G397uwE9_oN58np5fHU6xkGPCtE0HhSKV44Ypw3xjdO81zZXMc659b46Bn50kg0oIGwhhuMhdC-Kakt_naoYm0ELnsLbkci9OmIRfNtrIeOjegaIfi-F4WR3zc1QuehpdETZMf_MIV3vhHye_WPSWjtXHIP7vYOKjvqNOo-7LjqAezN-if4h7D-UNZXhOlZsfSLq2rK4a5ZWbEpCqRhiS4J6M4ov8sI30GIypydfm0hXxVLVl0lBWuxCmxaUgF0y8eyYMeLDbVtwPG37Iil5aJuGOEcrw_g8ibk-gh2q7pyj4FJPSm0kMFERIa6lencFrHLg5AcDxkUI3g1yDBbdv05sjauCVW2FfQIDjrpbj8Zxsd_jc_StJvKljmuPR72IutP9jr7rYcjeLmdxjNJDy26cvUGv4mpq5tQsXry_yVewB4qcfbp7OL8KewTk31X5jiG3Wa1cc_Q32nM81azGGQ3rMm_AOIUEkE
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Biomarker+Phenotypes+in+Heart+Failure+with+Preserved+Ejection+Fraction+Using+Hierarchical+Clustering-A+Pilot+Study&rft.jtitle=Medical+principles+and+practice&rft.au=Mitic%2C+Valentina&rft.au=Stojanovic%2C+Dijana&rft.au=Deljanin-Ilic%2C+Marina&rft.au=Petrovic%2C+Dejan&rft.date=2023-11-01&rft.issn=1423-0151&rft.eissn=1423-0151&rft_id=info:doi/10.1159%2F000534155&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1011-7571&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1011-7571&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1011-7571&client=summon