Evidence map›Paper›PMID 41025271›Full record

GuidelineAnnals of geriatric medicine and research2025

Position statement: Evidence-Based Exercise Guidelines for Sarcopenia in Older Adults: Insights from the Korean Working Group on Sarcopenia.

Seongryu Bae, Sunga Kong, Chul-Hyun Kim, Ji-Seok Kim, Jin-Ho Koh, Sang Ki Lee, Seok-Ki Min, Seungyong Lee, Jun-Il Yoo, Deog-Yoon Kim and 2 more

Abstract readSystematic ReviewPractice Guideline
In one paragraph

Guideline in Annals of geriatric medicine and research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Optimizing prescription of resistance training for body composition, muscle strength, and physical performance in older adults with sarcopenia: a systematic review and meta-analysis.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2026
    Review
  5. 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

12 authors.

Seongryu BaeDepartment of Health Sciences, Graduate School of Dong-A University, Busan, Korea.
Sunga KongDepartment of Clinical Research Design and Evaluation, Samsung Advanced Institute of Health Sciences and Technology, Sungkyunkwan University, Seoul, Korea.
Chul-Hyun KimDepartment of Sports Medicine, Soonchunhyang University, Asan, Korea.
Ji-Seok KimDepartment of Physical Education, Gyeongsang National University, Jinju, Korea.
Jin-Ho KohDepartment of Convergence Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea.
Sang Ki LeeDepartment of Sport Science, College of Natural Science, Chungnam National University, Daejeon, Korea.
Seok-Ki MinDepartment of Sports and Leisure, Yongin University, Yongin, Korea.
Seungyong LeeDepartment of Physical Education, Incheon National University, Incheon, Korea.
Jun-Il YooDepartment of Orthopaedic Surgery, Inha University Hospital, Inha University School of Medicine, Incheon, Korea.
Deog-Yoon KimDepartement of Nuclear Medicine, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Korea.
Hyuntae ParkDepartment of Health Sciences, Graduate School of Dong-A University, Busan, Korea.
Changsun KimDepartment of Physical Education, Dongduk Women's University, Seoul, Korea.

Funding

Ministry of Food and Drug Safety 1711138174Ministry of Food and Drug Safety KMDF_PR_20200901_ 0101Ministry of Food and Drug Safety RS-2020- KD000101Ministry of Health and WelfareMinistry of Science and ICTMinistry of Trade, Industry and Energy
6 · The paper itself

Abstract

backgroundSarcopenia is a geriatric muscle disease characterized by the loss of muscle mass, strength, and physical function. To better reflect the unique characteristics of sarcopenia in Korean older adults, the Korean Working Group on Sarcopenia (KWGS) developed a diagnostic algorithm, including a new category of "functional sarcopenia." This study aimed to establish evidence-based exercise guidelines tailored to the KWGS framework.

methodsA multidisciplinary expert committee conducted a systematic review of randomized controlled trials (RCTs) published between 2000 and 2024 to assess exercise interventions according exercise interventions by FITT (frequency, intensity, time, type) principles. Five key questions were developed, focusing on optimizing exercise modalities to improve muscle mass, strength, and physical performance in older adults with or without sarcopenia.

resultsA total of 42 RCTs met the inclusion criteria. Resistance training was most effective for improving muscle mass and strength, while combined resistance and aerobic exercise is most effective for enhancing physical function. The guideline recommends individualized exercise prescriptions based on sarcopenia subtypes and specific functional deficits, supported by evidence grades and levels.

conclusionThis is the first Korean evidence-based exercise guideline developed within the KWGS algorithm, offering clinical and community practitioners specific, actionable strategies for preventing and managing sarcopenia. It supports tailored interventions using FITT principles aligned with individual goals and sarcopenia classification.

Indexed as

ExerciseExercise TherapySarcopeniaAgedEvidence-Based MedicineHumansMaleMuscle StrengthRandomized Controlled Trials as TopicRepublic of KoreaResistance TrainingGuidelinesLean body massMuscle strengthPhysical fitnessSarcopenia

Identifiers

PMID41025271
PMCPMC12489597

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.