Evidence map›Paper›PMID 37443685›Full record

ArticleDiagnostics (Basel, Switzerland)2023

The Role of BIA Analysis in Osteoporosis Risk Development: Hierarchical Clustering Approach.

Giacinto Angelo Sgarro, Luca Grilli, Anna Antonia Valenzano, Fiorenzo Moscatelli, Domenico Monacis, Giusi Toto, Antonella De Maria, Giovanni Messina, Rita Polito

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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  3. Article
  4. Article
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  7. Exploring the Interplay between Bone Marrow Stem Cells and Obesity.International journal of molecular sciences · 2024
    Review
  8. 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

9 authors at 2 institutions in 1 country.

Giacinto Angelo SgarroDepartment of Economics, Management and Territory (DEMeT) and Grant Office, University of Foggia, 71121 Foggia, Italy.
Luca GrilliDepartment of Economics, Management and Territory (DEMeT) and Grant Office, University of Foggia, 71121 Foggia, Italy.ORCID 0000-0003-0931-2054
Anna Antonia ValenzanoDepartment of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy.
Fiorenzo MoscatelliDepartment of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy.ORCID 0000-0003-1274-0332
Domenico MonacisDepartment of Humanities, Letters, Cultural Heritage, Educational Sciences, University of Foggia, 71100 Foggia, Italy.ORCID 0000-0001-6000-7579
Giusi TotoDepartment of Humanities, Letters, Cultural Heritage, Educational Sciences, University of Foggia, 71100 Foggia, Italy.ORCID 0000-0001-5538-5858
Antonella De MariaSection of Human Physiology and Unit of Dietetics and Sports Medicine, Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", 80131 Naples, Italy.
Giovanni MessinaDepartment of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy.ORCID 0000-0002-0011-867X
Rita PolitoDepartment of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy.
University of Foggia · ITUniversity of Campania "Luigi Vanvitelli" · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoporosis is a common musculoskeletal disorder among the elderly and a chronic condition which, like many other chronic conditions, requires long-term clinical management. It is caused by many factors, including lifestyle and obesity. Bioelectrical impedance analysis (BIA) is a method to estimate body composition based on a weak electric current flow through the body. The measured voltage is used to calculate body bioelectrical impedance, divided into resistance and reactance, which can be used to estimate body parameters such as total body water (TBW), fat-free mass (FFM), fat mass (FM), and muscle mass (MM). This study aims to find the tendency of osteoporosis in obese subjects, presenting a method based on hierarchical clustering, which, using BIA parameters, can group patients who show homogeneous characteristics. Grouping similar patients into clusters can be helpful in the field of medicine to identify disorders, pathologies, or more generally, characteristics of significant importance. Another added value of the clustering process is the possibility to define cluster prototypes, i.e., imaginary patients who represent models of "states", which can be used together with clustering results to identify subjects with similar characteristics in a classification context. The results show that hierarchical clustering is a method that can be used to provide the detection of states and, consequently, supply a more personalized medicine approach. In addition, this method allowed us to elect BIA as a potential prognostic and diagnostic instrument in osteoporosis risk development.

Indexed as

bioelectrical impedance analysis (BIA)body composition (BC)classificationclusteringosteoporosis

Identifiers

PMID37443685
PMCPMC10340711
OpenAlexW4383535830

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.