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Research article
Jennifer Strande
Medical College of Wisconsin
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5918-230X
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Subclinical diastolic dysfunction is a precursor for developing heart failure with preserved ejection fraction (HFpEF); yet not all patients progress to HFpEF. Our objective was to evaluate clinical and echocardiographic variables to identify patients who develop HFpEF.Methods and Results Clinical, laboratory, and echocardiographic data were retrospectively collected for 81 patients without HF and 81 matched patients with HFpEF at the time of first documentation of subclinical diastolic dysfunction. Unsupervised clustering identified 3 subgroups which differed in gender composition, severity of cardiac hypertrophy and aortic stenosis, NT-proBNP, percentage of patients who progressed to HFpEF, and timing of disease progression from diastolic dysfunction to HFpEF to death. Clusters that had higher percentages of women had progressively milder cardiac hypertrophy, less severe aortic stenosis, lower NT-proBNP, were diagnosed at an older age with HFpEF, and survived to an older age. Independent predictors of HFpEF for the entire cohort included diabetes, chronic kidney disease, atrial fibrillation, and diuretic use, with additional predictive variables found for each cluster.Conclusions Cluster analysis can identify phenotypically distinct subgroups of patients with diastolic dysfunction. Clusters differ in HFpEF and mortality outcome. In addition, the variables that correlate with and predict HFpEF outcome differ among clusters.
Keywords
Diastolic dysfunction, Heart failure with preserved ejection fraction, Unsupervised Machine Learning, Hierarchical Clustering
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Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Cardiovascular Disorders.
No community comments so far
Editorial decision: Major revision
On 26 Apr, 2020
Review #1 received
Received 25 Apr, 2020
Reviewer #1 agreed
On 15 Apr, 2020
Reviewers invited
Invitations sent on 07 Apr, 2020
Editor assigned
On 03 Mar, 2020
Submission checks complete
On 02 Mar, 2020
Editor invited
On 02 Mar, 2020
Version 1
Posted 13 Nov, 2019
No comments provided
Editorial decision: Minor revision
On 08 Feb, 2020
Review #2 received
Received 28 Jan, 2020
Review #1 received
Received 02 Dec, 2019
Reviewer #2 agreed
On 21 Nov, 2019
Editor assigned
On 21 Nov, 2019
Reviewers invited
Invitations sent on 21 Nov, 2019
Reviewer #1 agreed
On 21 Nov, 2019
Submission checks complete
On 12 Nov, 2019
Editor invited
On 11 Nov, 2019
First submitted
On 04 Nov, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
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A new preprint design is coming!
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See the published version of this preprint at BMC Cardiovascular Disorders.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Jennifer Strande
Medical College of Wisconsin
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5918-230X
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Cardiovascular Disorders.
No community comments so far
Editorial decision: Major revision
On 26 Apr, 2020
Review #1 received
Received 25 Apr, 2020
Reviewer #1 agreed
On 15 Apr, 2020
Reviewers invited
Invitations sent on 07 Apr, 2020
Editor assigned
On 03 Mar, 2020
Submission checks complete
On 02 Mar, 2020
Editor invited
On 02 Mar, 2020
Version 1
Posted 13 Nov, 2019
No comments provided
Editorial decision: Minor revision
On 08 Feb, 2020
Review #2 received
Received 28 Jan, 2020
Review #1 received
Received 02 Dec, 2019
Reviewer #2 agreed
On 21 Nov, 2019
Editor assigned
On 21 Nov, 2019
Reviewers invited
Invitations sent on 21 Nov, 2019
Reviewer #1 agreed
On 21 Nov, 2019
Submission checks complete
On 12 Nov, 2019
Editor invited
On 11 Nov, 2019
First submitted
On 04 Nov, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Cardiovascular Disorders.
Subclinical diastolic dysfunction is a precursor for developing heart failure with preserved ejection fraction (HFpEF); yet not all patients progress to HFpEF. Our objective was to evaluate clinical and echocardiographic variables to identify patients who develop HFpEF.Methods and Results Clinical, laboratory, and echocardiographic data were retrospectively collected for 81 patients without HF and 81 matched patients with HFpEF at the time of first documentation of subclinical diastolic dysfunction. Unsupervised clustering identified 3 subgroups which differed in gender composition, severity of cardiac hypertrophy and aortic stenosis, NT-proBNP, percentage of patients who progressed to HFpEF, and timing of disease progression from diastolic dysfunction to HFpEF to death. Clusters that had higher percentages of women had progressively milder cardiac hypertrophy, less severe aortic stenosis, lower NT-proBNP, were diagnosed at an older age with HFpEF, and survived to an older age. Independent predictors of HFpEF for the entire cohort included diabetes, chronic kidney disease, atrial fibrillation, and diuretic use, with additional predictive variables found for each cluster.Conclusions Cluster analysis can identify phenotypically distinct subgroups of patients with diastolic dysfunction. Clusters differ in HFpEF and mortality outcome. In addition, the variables that correlate with and predict HFpEF outcome differ among clusters.
Figure 1
Figure 2
This is a list of supplementary files associated with this preprint. Click to download.
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