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Sökning: onr:"swepub:oai:gup.ub.gu.se/310427" > Clustering based on...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00004111naa a2200553 4500
001oai:gup.ub.gu.se/310427
003SwePub
008240528s2022 | |||||||||||000 ||eng|
0247 a https://gup.ub.gu.se/publication/3104272 URI
0247 a https://doi.org/10.1002/ehf2.137042 DOI
040 a (SwePub)gu
041 a eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Uszko-Lencer, Nhmk4 aut
2451 0a Clustering based on comorbidities in patients with chronic heart failure: an illustration of clinical diversity
264 c 2021-11-18
264 1b Wiley,c 2022
520 a Aims It is increasingly recognized that the presence of comorbidities substantially contributes to the disease burden in patients with heart failure (HF). Several reports have suggested that clustering of comorbidities can lead to improved characterization of the disease phenotypes, which may influence management of the individual patient. Therefore, we aimed to cluster patients with HF based on medical comorbidities and their treatment and, subsequently, compare the clinical characteristics between these clusters. Methods and results A total of 603 patients with HF entering an outpatient HF rehabilitation programme were included [median age 65 years (interquartile range 56-71), 57% ischaemic origin of cardiomyopathy, and left ventricular ejection fraction 35% (26-45)]. Exercise performance, daily life activities, disease-specific health status, coping styles, and personality traits were assessed. In addition, the presence of 12 clinically relevant comorbidities was recorded, based on targeted diagnostics combined with applicable pharmacotherapies. Self-organizing maps (SOMs; ) were used to visualize clusters, generated by using a hybrid algorithm that applies the classical hierarchical cluster method of Ward on top of the SOM topology. Five clusters were identified: (1) a least comorbidities cluster; (2) a cachectic/implosive cluster; (3) a metabolic diabetes cluster; (4) a metabolic renal cluster; and (5) a psychologic cluster. Exercise performance, daily life activities, disease-specific health status, coping styles, personality traits, and number of comorbidities were significantly different between these clusters. Conclusions Distinct combinations of comorbidities could be identified in patients with HF. Therapy may be tailored based on these clusters as next step towards precision medicine. The effect of such an approach needs to be prospectively tested.
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Kardiologi0 (SwePub)302062 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Cardiac and Cardiovascular Systems0 (SwePub)302062 hsv//eng
653 a Heart failure
653 a Clustering
653 a Comorbidities
653 a pulmonary rehabilitation
653 a coping styles
653 a reliability
653 a validity
653 a copd
653 a frailty
653 a life
653 a care
653 a Cardiovascular System & Cardiology
7001 a Janssen, D. J. A.4 aut
7001 a Gaffron, S.4 aut
7001 a Vanfleteren, Lowie E G Wu Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för invärtesmedicin och klinisk nutrition,Institute of Medicine, Department of Internal Medicine and Clinical Nutrition4 aut0 (Swepub:gu)xvanlo
7001 a Janssen, E.4 aut
7001 a Werter, C.4 aut
7001 a Franssen, F. M. E.4 aut
7001 a Wouters, E. F. M.4 aut
7001 a Rechberger, S.4 aut
7001 a La Rocca, H. P. B.4 aut
7001 a Spruit, M. A.4 aut
7102 a Göteborgs universitetb Institutionen för medicin, avdelningen för invärtesmedicin och klinisk nutrition4 org
7730 t ESC Heart Failured : Wileyg 9:1, s. 614-626q 9:1<614-626x 2055-5822
8564 u https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ehf2.13704
8564 8u https://gup.ub.gu.se/publication/310427
8564 8u https://doi.org/10.1002/ehf2.13704

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