Evidence map›Paper›PMID 41001510›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Non-Linear Size Effects and Episodic Progression in the Ascending Aorta.

Carlos Alberto Campello Jorge, Prabhvir S Marway, Gregory Spahlinger, Heather A Knauer, Marion Hofmann-Bowman, Venkatesh L Murthy, Nicholas S Burris

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Carlos Alberto Campello JorgeDepartment of Radiology, University of Michigan.ORCID 0000-0001-5290-7294
Prabhvir S MarwayDepartment of Radiology, University of Michigan.ORCID 0000-0002-5768-4859
Gregory SpahlingerDepartment of Radiology, University of Michigan.
Heather A KnauerDepartment of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan.ORCID 0000-0001-8617-8958
Marion Hofmann-BowmanDepartment of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan.ORCID 0000-0002-5529-6000
Venkatesh L MurthyDepartment of Radiology, University of Michigan.ORCID 0000-0002-7901-1321
Nicholas S BurrisDepartment of Radiology, University of Michigan.ORCID 0000-0002-5198-4383

Funding

Implications of metabolism on healthy aging in African and Caucasian Americans: the Health ABC studyR01AG059729 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MURTHY, VENKATESH LOCHARLA, NEWMAN, ANNE B. · 2018 to 2022
$3.1M
Metabolic architecture of insulin action in Southwest American IndiansU01DK123013 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MURTHY, VENKATESH LOCHARLA, SHAH, RAVI · 2020 to 2025
$2.4M
Non-invasive hemodynamic and biomechanic imaging methods for early risk prediction in aortic dissectionR01HL170059 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI Nicholas Scott Burris, David Alexander Nordsletten · 2023 to 2026
$2.4M
NHLBI NIH HHS R01 HL170059NIA NIH HHS R01 AG059729NIDDK NIH HHS U01 DK123013
6 · The paper itself

Abstract

Background—: Predicting ascending aortic (AsAo) growth is challenging. Conventional paradigms often assume a linear and monotonic relationship between baseline size and future growth that occurs continuously-assumptions that may oversimplify biology-driven disease progression. We first evaluated whether body size-indexed baseline AsAo diameter shows a non-linear association with subsequent growth at the population-level, and second whether patient-level growth trajectories are predominantly continuous or episodic. Methods—: We performed a single-center, retrospective study (2012-2024). The Primary Cohort (n=3,315; ≥2 CT/MR scans) was used to model the relationship between baseline indexed AsAo size (Z-score) and subsequent annualized growth using multivariable linear regression and generalized additive models (GAMs), adjusting for clinical covariates. A Sub-Cohort (n=1,055; ≥4 scans) was used to classify longitudinal phenotypes as: Stable (Total Growth <2.0 mm), Stable-with-Noise (Total Growth <2.0 mm with alternating small changes), Continuous Growth (Total Growth ≥2.0 mm without a qualifying event), or Discontinuous/Episodic Growth (Total Growth ≥2.0 mm with ≥1 "growth event"). A growth event was defined as a diameter increase ≥2.0 mm within a single imaging interval or across two adjacent intervals (combined 0.5-5 years). Results—: In the Primary Cohort, baseline Z-score demonstrated a significant non-linear (U-shaped) association with subsequent growth in the GAM (p<0.001), with higher growth at both small (Z<0) and severely dilated (Z>5) sizes. In the Sub-Cohort examining growth trajectory, the distribution was: Stable: 50.4% (532/1,055), Stable-with-Noise: 21.6% (228/1,055), Continuous: 5.4% (57/1,055), and Discontinuous/Episodic 22.6% (238/1,055). Among patients with measurable growth (Total Growth ≥2.0 mm, n=295), 81%(n=238) exhibited episodic growth and 58.3% (172/295) had a non-dilated baseline aorta (Z<2). Group differences (e.g., younger age and smaller baseline Z-scores in the Growth vs. Stable groups) were consistent across sensitivity analyses. Conclusions—: AsAo growth is not well described by linear, continuous assumptions. Baseline size relates to future growth in a non-linear (U-shaped) manner, and nearly one-quarter of patients exhibit discrete growth bursts separated by periods of quiescence, with episodic behavior dominating among those who enlarge. These findings support a punctuated growth paradigm and argue for re-examining surveillance intervals, risk communication, and threshold-based decision pathways in thoracic aortic disease.

Identifiers

PMID41001510
PMCPMC12458601

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.