Evidence map›Paper›PMID 34251162›Full record

ArticleEuropean journal of translational myology2021

Testing soft tissue radiodensity parameters interplay with age and self-reported physical activity.

Marco Recenti, Carlo Ricciardi, Kyle Edmunds, Deborah Jacob, Monica Gambacorta, Paolo Gargiulo

Open access · goldAbstract read
In one paragraph

Article in European journal of translational myology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Guideline
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  3. Evaluating the Asymmetry of Muscle Activation and Strength in Paralympic Powerlifting Athletes.European journal of investigation in health, psychology and education · 2023
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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

6 authors at 3 institutions in 3 countries.

Marco RecentiInstitute for Biomedical and Neural Engineering, Reykjavík University, Reykjavík. marco18@ru.is.
Carlo RicciardiInstitute for Biomedical and Neural Engineering, Reykjavík University, Reykjavík, Iceland; Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Naples. carloricciardi.93@gmail.com.
Kyle EdmundsInstitute for Biomedical and Neural Engineering, Reykjavík University, Reykjavík. kyle14@ru.is.
Deborah JacobInstitute for Biomedical and Neural Engineering, Reykjavík University, Reykjavík. deborah20@ru.is.
Monica GambacortaUmberto I Hospital, ASL Salerno, Nocera Inferiore. m.gambacorta@aslsalerno.it.
Paolo GargiuloInstitute for Biomedical and Neural Engineering, Reykjavík University, Reykjavík, Iceland; Department of Science, Landspítali, Reykjavík. paologar@landspitali.is.
Reykjavík University · ISNational University Hospital of Iceland · ISOspedali Riuniti Umberto I · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging well is directly associated to a healthy lifestyle. The focus of this paper is to relate individual wellness with medical image features. Non-linear trimodal regression analysis (NTRA) is a novel method that models the radiodensitometric distributions of x-ray computed tomography (CT) cross-sections. It generates 11 patient-specific parameters that describe the quality and quantity of muscle, fat, and connective tissues. In this research, the relationship of these 11 NTRA parameters with age, physical activity, and lifestyle is investigated in the 3,157 elderly volunteers AGES-I dataset. First, univariate statistical analyses were performed, and subjects were grouped by age and self-reported past (youth-midlife) and present (within 12 months of the survey) physical activity to ascertain which parameters were the most influential. Then, machine learning (ML) analyses were conducted to classify patients using NTRA parameters as input features for three ML algorithms. ML is also used to classify a Lifestyle index using the age groups. This classification analysis yielded robust results with the lifestyle index underlying the relevant differences of the soft tissues between age groups, especially in fat and connective tissue. Univariate statistical models suggested that NTRA parameters may be susceptible to age and differences between past and present physical activity levels. Moreover, for both age and physical activity, lean muscle parameters expressed more significant variation than fat and connective tissues.

Identifiers

PMID34251162
PMCPMC8495362
OpenAlexW3179080189

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.