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Record W3042406966 · doi:10.1186/s12891-020-03495-9

Physical fitness in older women with osteoporosis and vertebral fracture after a resistance and balance exercise programme: 3-month post-intervention follow-up of a randomised controlled trial

2020· article· en· W3042406966 on OpenAlexaff
Brita Stanghelle, Hege Bentzen, Lora Giangregorio, Are Hugo Pripp, Dawn A. Skelton, Astrid Bergland

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2020
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsResearch Institute for AgingUniversity of Waterloo
FundersHøgskolen i Oslo og Akershus
KeywordsMedicinePhysical therapySports medicineRandomized controlled trialOsteoporosisResistance trainingIntervention (counseling)Balance (ability)Orthopedic surgeryRehabilitationRheumatologyPhysical fitnessPhysical medicine and rehabilitationInternal medicineSurgeryNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Exercise is recommended for individuals with vertebral fractures, but few studies have investigated the effect of exercise on outcomes of importance for this population. Post-intervention effects of exercise are even less studied. The objective of this study was to evaluate habitual walking speed and other health-related outcomes after cessation of a 3-month exercise intervention. METHODS: This follow-up study was conducted 3 months post-intervention of a randomised controlled trial. A total of 149 community-dwelling Norwegian women aged 65 years or older, diagnosed with osteoporosis and vertebral fracture were randomised into either exercise or control group. Primary outcome was habitual walking speed at 3 months. Secondary outcomes were other measures of physical fitness - including the Four Square Step Test (FSST), functional reach, grip strength and Senior Fitness Test - measures of health-related quality of life and fear of falling. Herein we report secondary data analysis of all outcomes at 6 months (3 months post-intervention). Data were analysed according to the intention-to-treat principle, linear mixed regression models were employed. RESULTS: For the primary outcome, habitual walking speed, there was no statistically significant difference between groups (0.03 m/s, 95%CI - 0.02 to 0.08, p = 0.271) at the 3-month post-intervention follow-up. For secondary outcomes of physical fitness, statistically significant differences in favour of the intervention group were found for balance using the FSST (- 0.68 s, 95%CI - 1.24 to - 0.11, p = 0.019), arm curl (1.3, 95%CI 0.25 to 2.29, p = 0.015), leg strength using the 30-s sit to stand (1.56, 95%CI 0.68 to 2.44, p = 0.001) and mobility using the 2.45-m up and go (- 0.38 s, 95%CI - 0.74 to - 0.02, p = 0.039). There was a statistically significant difference between the groups regarding fear of falling in favour of the intervention group (- 1.7, 95%CI - 2.97 to - 0.38, p = 0.011). No differences between groups were observed for health-related quality of life. CONCLUSION: The results show the improved effects of a multicomponent exercise programme on outcomes like muscle strength, balance and mobility as well as fear of falling in a group of older women with osteoporosis and vertebral fracture 3 months post-intervention. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02781974 . Registered 25.05.16. Retrospectively registered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.272
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2020
Admission routes1
Has abstractyes

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