Evidence map›Paper›PMID 34276397›Full record

ArticleFrontiers in physiology2021

Predictive Modeling of Secondary Pulmonary Hypertension in Left Ventricular Diastolic Dysfunction.

Karlyn K Harrod, Jeffrey L Rogers, Jeffrey A Feinstein, Alison L Marsden, Daniele E Schiavazzi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

13 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. InVAErt networks for amortized inference and identifiability analysis of lumped-parameter haemodynamic models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Article
  4. Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Article
  5. Article
  6. Article
  7. Guidelines for mechanistic modeling and analysis in cardiovascular research.American journal of physiology. Heart and circulatory physiology · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. 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

5 authors at 3 institutions in 1 country.

Karlyn K HarrodDepartment of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, United States.
Jeffrey L RogersDepartment of Digital Health, T.J. Watson Research Center, International Business Machines Corporation, Yorktown Heights, NY, United States.
Jeffrey A FeinsteinDepartment of Pediatrics and Bioengineering, Stanford University, Stanford, CA, United States.
Alison L MarsdenDepartment of Pediatrics, Bioengineering and Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, United States.
Daniele E SchiavazziDepartment of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, United States.
Stanford University · USUniversity of Notre Dame · USIBM (United States) · US

Funding

Enabling reliable cardiovascular simulations via uncertainty quantificationR01EB018302 · NIBIB · STANFORD UNIVERSITY · PI MARSDEN, ALISON L · 2016 to 2019
$1.7M
NIBIB NIH HHS R01 EB018302
6 · The paper itself

Abstract

Diastolic dysfunction is a common pathology occurring in about one third of patients affected by heart failure. This condition may not be associated with a marked decrease in cardiac output or systemic pressure and therefore is more difficult to diagnose than its systolic counterpart. Compromised relaxation or increased stiffness of the left ventricle induces an increase in the upstream pulmonary pressures, and is classified as secondary or group II pulmonary hypertension (2018 Nice classification). This may result in an increase in the right ventricular afterload leading to right ventricular failure. Elevated pulmonary pressures are therefore an important clinical indicator of diastolic heart failure (sometimes referred to as

Indexed as

adaptive Markov chain Monte Carlocomputational physiologydata assimilationlumped parameter hemodynamic modelingmodel-based disease detectionpredictive models for pulmonary pressures

Identifiers

PMID34276397
PMCPMC8281259
OpenAlexW3184968944

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.