Evidence map›Paper›PMID 37624825›Full record

ArticlePloS one2023

Identifying high risk clinical phenogroups of pulmonary hypertension through a clustering analysis.

Paula Rambarat, Emily K Zern, Dongyu Wang, Athar Roshandelpoor, Shahrooz Zarbafian, Elizabeth E Liu, Jessica K Wang, Jenna N McNeill, Carl T Andrews, Eugene V Pomerantsev and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 3 institutions in 1 country.

Paula RambaratDepartment of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID 0000-0003-2218-6742
Emily K ZernDivision of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Dongyu WangCardiovascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
Athar RoshandelpoorCardiovascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
Shahrooz ZarbafianDivision of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Elizabeth E LiuCardiovascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
Jessica K WangCardiovascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
Jenna N McNeillDivision of Pulmonary and Critical Care, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Carl T AndrewsDivision of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Eugene V PomerantsevDivision of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Nathaniel DiamantBroad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, United States of America.
Puneet BatraBroad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, United States of America.ORCID 0000-0001-6822-0593
Steven A LubitzCardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Michael H PicardDivision of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Jennifer E HoCardiovascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.ORCID 0000-0002-7987-4768
Massachusetts General Hospital · USBeth Israel Deaconess Medical Center · USBroad Institute · US

Funding

Eicosanoid Profiles as Determinants of HFpEFR01HL140224 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI HO, JENNIFER E · 2018 to 2021
$3.1M
The Association of Metabolic Disease and Pulmonary HypertensionR01HL134893 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI HO, JENNIFER E · 2017 to 2021
$2.9M
Mentoring in Patient-Oriented and Translational HFpEF ResearchK24HL153669 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Jennifer E Ho · 2020 to 2026
$744k
NHLBI NIH HHS K24 HL153669NHLBI NIH HHS R01 HL134893NHLBI NIH HHS R01 HL140224
6 · The paper itself

Abstract

introductionThe classification and management of pulmonary hypertension (PH) is challenging due to clinical heterogeneity of patients. We sought to identify distinct multimorbid phenogroups of patients with PH that are at particularly high-risk for adverse events.

methodsA hospital-based cohort of patients referred for right heart catheterization between 2005-2016 with PH were included. Key exclusion criteria were shock, cardiac arrest, cardiac transplant, or valvular surgery. K-prototypes was used to cluster patients into phenogroups based on 12 clinical covariates.

resultsAmong 5208 patients with mean age 64±12 years, 39% women, we identified 5 distinct multimorbid PH phenogroups with similar hemodynamic measures yet differing clinical outcomes: (1) "young men with obesity", (2) "women with hypertension", (3) "men with overweight", (4) "men with cardiometabolic and cardiovascular disease", and (5) "men with structural heart disease and atrial fibrillation." Over a median follow-up of 6.3 years, we observed 2182 deaths and 2002 major cardiovascular events (MACE). In age- and sex-adjusted analyses, phenogroups 4 and 5 had higher risk of MACE (HR 1.68, 95% CI 1.41-2.00 and HR 1.52, 95% CI 1.24-1.87, respectively, compared to the lowest risk phenogroup 1). Phenogroup 4 had the highest risk of mortality (HR 1.26, 95% CI 1.04-1.52, relative to phenogroup 1).

conclusionsCluster-based analyses identify patients with PH and specific comorbid cardiometabolic and cardiovascular disease burden that are at highest risk for adverse clinical outcomes. Interestingly, cardiopulmonary hemodynamics were similar across phenogroups, highlighting the importance of multimorbidity on clinical trajectory. Further studies are needed to better understand comorbid heterogeneity among patients with PH.

Indexed as

Atrial FibrillationHeart DiseasesHypertensionHypertension, PulmonaryAgedCluster AnalysisFemaleHumansMaleMiddle Aged

Identifiers

PMID37624825
PMCPMC10456132
OpenAlexW4386158434

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.