Evidence map›Paper›PMID 37110223›Full record

ArticleMetabolites2023

A Machine-Learning Approach to Target Clinical and Biological Features Associated with Sarcopenia: Findings from Northern and Southern Italian Aging Populations.

Roberta Zupo, Alessia Moroni, Fabio Castellana, Clara Gasparri, Feliciana Catino, Luisa Lampignano, Simone Perna, Maria Lisa Clodoveo, Rodolfo Sardone, Mariangela Rondanelli

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

16 citing papers in PubMed, 21 citations in OpenAlex.

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  11. Multidisciplinary approach to sarcopenia: a narrative review.Journal of Yeungnam medical science · 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

10 authors at 4 institutions in 1 country.

Roberta ZupoDepartment of Interdisciplinary Medicine, University "Aldo Moro", Piazza Giulio Cesare 11, 70100 Bari, Italy.ORCID 0000-0001-9885-1185
Alessia MoroniEndocrinology and Nutrition Unit, Azienda di Servizi alla Persona "Istituto Santa Margherita", University of Pavia, 27100 Pavia, Italy.ORCID 0000-0003-3780-2931
Fabio CastellanaUnit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology IRCCS "Saverio de Bellis", Research Hospital, Castellana Grotte, 70013 Bari, Italy.ORCID 0000-0002-6439-8228
Clara GasparriEndocrinology and Nutrition Unit, Azienda di Servizi alla Persona "Istituto Santa Margherita", University of Pavia, 27100 Pavia, Italy.ORCID 0000-0002-1088-6648
Feliciana CatinoDepartment of Innovation and Smart City, Municipality of Taranto, 74121 Taranto, Italy.
Luisa LampignanoUnit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology IRCCS "Saverio de Bellis", Research Hospital, Castellana Grotte, 70013 Bari, Italy.ORCID 0000-0001-9299-3211
Simone PernaDepartment of Food, Environmental and Nutritional Sciences, Division of Human Nutrition, University of Milan, 20133 Milan, Italy.ORCID 0000-0002-2720-1473
Maria Lisa ClodoveoDepartment of Interdisciplinary Medicine, University "Aldo Moro", Piazza Giulio Cesare 11, 70100 Bari, Italy.ORCID 0000-0002-1717-2197
Rodolfo SardoneLocal Healthcare Authority of Taranto, 74121 Taranto, Italy.ORCID 0000-0003-1383-1850
Mariangela RondanelliDepartment of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy.ORCID 0000-0001-8336-4851
University of Pavia · ITGastroenterology Hospital "Saverio de Bellis" · ITUniversity of Bari Aldo Moro · ITUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epidemiological and public health resonance of sarcopenia in late life requires further research to identify better clinical markers useful for seeking proper care strategies in preventive medicine settings. Using a machine-learning approach, a search for clinical and fluid markers most associated with sarcopenia was carried out across older populations from northern and southern Italy. A dataset of adults >65 years of age (

Indexed as

agingartificial intelligencebody compositionelderlyItalymachine learningnutritionolder adultsSalus in Apuliasarcopenia

Identifiers

PMID37110223
PMCPMC10142879
OpenAlexW4366090731

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.