Evidence map›Paper›PMID 33424643›Full record

ArticleFrontiers in physiology2020

Anthropometric Prediction of DXA-Measured Percentage of Fat Mass in Athletes With Unilateral Lower Limb Amputation.

Valentina Cavedon, Marco Sandri, Massimo Venturelli, Carlo Zancanaro, Chiara Milanese

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 38% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. 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 1 institution in 1 country.

Valentina CavedonDepartment of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
Marco SandriDepartment of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
Massimo VenturelliDepartment of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
Carlo ZancanaroDepartment of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
Chiara MilaneseDepartment of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
University of Verona · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To date there is no anthropometric equation specific to athletes with unilateral lower limb amputation to estimate the percentage of fat mass (%FM). This study investigated the accuracy of a set of anthropometric equations validated on able-bodied populations to predict the %FM assessed by-means of dual-energy x-ray absorptiometry (DXA) in athletes with unilateral lower limb amputation. Furthermore, a predictive anthropometric equation specific to athletes with unilateral lower limb amputation was developed from skinfold thickness measurements using DXA as the reference method for the estimation of the %FM. Twenty-nine white male athletes with unilateral lower limb amputation underwent a DXA scan and an anthropometric assessment on the same day. The %FM, calculated through several existing anthropometric equations validated upon able-bodied populations, was compared with the DXA-measured %FM (%FM_DXA). Accuracy and agreement between the two methods was computed with two-tailed paired-sample

Indexed as

athletes with physical impairmentsbland-altman analysisbody compositionpredictive equationskinfold thickness

Identifiers

PMID33424643
PMCPMC7786292
OpenAlexW3117137403

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.