ArticleScientific reports2017
Estimating prognosis in patients with acute myocardial infarction using personalized computational heart models.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02072850 (Cardiac Magnetic Resonance Imaging), which is not on this map. Cited by 8 papers.
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.
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.
Cardiac Magnetic Resonance Imaging: New Pathological Insights and Their Functional and Clinical Significance in ST Elevation Acute Myocardial Infarction.
Who cites it
8 citing papers in PubMed, 28 citations in OpenAlex.
- The functional impact of myofiber macroscopic organization and disarray in computational models of the murine heart.PLoS computational biology · 2026Article
- Deep Learning-Based Estimation of Myocardial Material Parameters from Cardiac MRI.Bioengineering (Basel, Switzerland) · 2025Article
- A multiscale finite element model of left ventricular mechanics incorporating baroreflex regulation.Computers in biology and medicine · 2024Article
- Bridging the gap between mechanistic biological models and machine learning surrogates.PLoS computational biology · 2023Review
- Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle.International journal for numerical methods in biomedical engineering · 2022Article
- Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium.Royal Society open science · 2021Article
- Biomechanics of infarcted left ventricle: a review of modelling.Biomedical engineering letters · 2020Review
- Fast parameter inference in a biomechanical model of the left ventricle by using statistical emulation.Journal of the Royal Statistical Society. Series C, Applied statistics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Biomechanical computational models have potential prognostic utility in patients after an acute ST-segment-elevation myocardial infarction (STEMI). In a proof-of-concept study, we defined two groups (1) an acute STEMI group (n = 6, 83% male, age 54 ± 12 years) complicated by left ventricular (LV) systolic dysfunction; (2) an age- and sex- matched hyper-control group (n = 6, 83% male, age 46 ± 14 years), no prior history of cardiovascular disease and normal systolic blood pressure (SBP < 130 mmHg). Cardiac MRI was performed in the patients (2 days & 6 months post-STEMI) and the volunteers, and biomechanical heart models were synthesized for each subject. The candidate parameters included normalized active tension (AT
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.