Evidence map›Paper›PMID 32300703›Full record

ReviewJournal of frailty, sarcopenia and falls2018

Diagnostic imaging of two related chronic diseases: Sarcopenia and Osteoporosis.

Luciana La Tegola, Maria Mattera, Samantha Cornacchia, Xiaoguang Cheng, Giuseppe Guglielmi

Open access · goldAbstract readReview
In one paragraph

Review in Journal of frailty, sarcopenia and falls, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. 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 2 institutions in 2 countries.

Luciana La TegolaUniversità degli Studi di Foggia, Department of Radiology, Viale Luigi Pinto, 1. Foggia, Italy.
Maria MatteraUniversità degli Studi di Foggia, Department of Radiology, Viale Luigi Pinto, 1. Foggia, Italy.
Samantha CornacchiaMedical Physics, "Dimiccoli" Hospital, Barletta, Italy.
Xiaoguang ChengDepartment of Radiology, Beijing Jishuitan Hospital, Beijing, China.
Giuseppe GuglielmiUniversità degli Studi di Foggia, Department of Radiology, Viale Luigi Pinto, 1. Foggia, Italy.
University of Foggia · ITPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sarcopenia and osteoporosis are two major health problems worldwide, responsible for a serious clinical and financial burden due to the increasing life expectancy. Both when presented as a single entity and, in particular, in the form of "osteosarcopenia", they lead to an important increased risk of falls, fractures, hospitalization and mortality. In dealing with these two pathological conditions, it is important to understand that between bone and muscle there is not only a functional correlation but also a close relationship in the development and in maintenance, which is well expressed by the concept of "bone-muscle unit". This close relationship agrees with the existence of a linear association between sarcopenia and osteoporosis, in particular in elderly population. It is mandatory, in the clinical assessment of both diseases, to do an early diagnosis or to delay as far as possible the appearance of an established form in order to prevent the onset of complications. The aim of this review is to present the different imaging modalities available for a non-invasive investigation of bone and muscle mass and quality in osteoporosis and sarcopenia, with their application and limitations.

Indexed as

DXAMRIOsteoporosisQCTSarcopenia

Identifiers

PMID32300703
PMCPMC7155344
OpenAlexW2888967470

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.