Evidence map›Paper›PMID 36979712›Full record

ArticleBiomedicines2023

COVID-19 in Older Patients: Assessment of Post-COVID-19 Sarcopenia.

Almudena López-Sampalo, Lidia Cobos-Palacios, Alberto Vilches-Pérez, Jaime Sanz-Cánovas, Antonio Vargas-Candela, Juan José Mancebo-Sevilla, Halbert Hernández-Negrín, Ricardo Gómez-Huelgas, María Rosa Bernal-López

Open access · goldFull text read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
1.9field-weighted citation impact, top 14% 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, 2 syntheses or guidelines pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  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

9 authors at 2 institutions in 1 country.

Almudena López-SampaloInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), University of Málaga, Avda. Hospital Civil s/n, 29009 Málaga, Spain.
Lidia Cobos-PalaciosInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), University of Málaga, Avda. Hospital Civil s/n, 29009 Málaga, Spain.ORCID 0000-0003-4401-233X
Alberto Vilches-PérezEndocrinology and Nutrition Department, Virgen de la Victoria University Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), 29010 Málaga, Spain.
Jaime Sanz-CánovasInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), University of Málaga, Avda. Hospital Civil s/n, 29009 Málaga, Spain.ORCID 0000-0003-3722-5492
Antonio Vargas-CandelaInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), University of Málaga, Avda. Hospital Civil s/n, 29009 Málaga, Spain.
Juan José Mancebo-SevillaInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), University of Málaga, Avda. Hospital Civil s/n, 29009 Málaga, Spain.
Halbert Hernández-NegrínInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), University of Málaga, Avda. Hospital Civil s/n, 29009 Málaga, Spain.
Ricardo Gómez-HuelgasInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), University of Málaga, Avda. Hospital Civil s/n, 29009 Málaga, Spain.ORCID 0000-0002-9909-3555
María Rosa Bernal-LópezInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA-Plataforma Bionand), University of Málaga, Avda. Hospital Civil s/n, 29009 Málaga, Spain.ORCID 0000-0002-0238-0890
Andalusian Centre for Nanomedicine and Biotechnology · ESInstituto de Salud Carlos III · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(1) Background: Acute COVID-19 infections produce alterations in the skeletal muscle, leading to acute sarcopenia, but the medium- and long-term consequences are still unknown. The aim of this study was to evaluate: (1) body composition; (2) muscle strength and the prevalence of sarcopenia; and (3) the relationship between muscle strength with symptomatic and functional evolution in older patients affected by/recovered from COVID-19; (2) Methods: A prospective, longitudinal study of patients aged ≥65 years who had suffered from COVID-19 infection between 1 March and 31 May 2020, as confirmed by PCR or subsequent seroconversion. Persistent symptoms, as well as anthropometric, clinical, and analytical characteristics, were analyzed at 3 and 12 months after infection. The degree of sarcopenia was determined by dynamometry and with SARC-F; (3) Results: 106 participants, aged 76.8 ± 7 years, were included. At 3 months postinfection, a high percentage of sarcopenic patients was found, especially among women and in those with hospitalization. At 12 months postinfection, this percentage had decreased, coinciding with a functional and symptomatic recovery, and the normalization of inflammatory parameters, especially interleukin-6 (4.7 ± 11.6 pg/mL vs. 1.5 ± 2.4 pg/mL,

Indexed as

COVID-19muscle strengthsarcopenia

Identifiers

PMID36979712
PMCPMC10045496
OpenAlexW4322619542

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read31
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.