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Clinical Features - Original Research

Predicting factors associated with frailty in aged patients with bone-arthrosis pain in the clinic

, , , &
Pages 391-396 | Received 10 Jul 2016, Accepted 10 Oct 2016, Published online: 02 Nov 2016
 

ABSTRACT

Objectives: To identify frail and pre-frail patients in a group of patients older than 60 years.

Methods: The phenotype model of Fried’s method was used to identify frailty and pre-frailty in total of 78 participants. Cognitive ability and psychosocial function tests were also given to 59 of the 78 patients.

Results: Prevalence of frailty and pre-frailty was 14.1% (11/78) and 46.2% (36/78), respectively. Of the 5 phenotype variables, weak grip strength was the most commonly seen variable with 53.8% of all participants and 100% in the frail group. Low energy expenditure, however, was not self-reported by any participant in the current study (0%). Prevalence of frailty in the present study is associated with chronological age. The current study indicates that 4 phenotypic variables (unintentional weight loss, self-reported exhaustion, gait speed and grip strength) contribute to the development to frailty, and that cognitive impairment and psychosocial frailty also predict frailty or pre-frailty in the patients older than 60 years old irrespective of chronic pain or osteoarthritis. The findings of the current study suggest frailty and pre-frailty are common in senior Chinese patients with chronic diseases.

Conclusion: Recognition and identification of frailty in a rehabilitation clinic or hospital might help physicians to provide appropriate counseling to patients and families about adverse outcomes of certain treatments such as surgery, and could optimize management of coexisting chronic diseases that might contribute to or be affected by frailty.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Additional information

Funding

This work is supported in part by funding from Heilongjiang Provincial Health Bureau funding (2012-690,2009-176), Heilongjiang province science and technology plan and technological project (GC10C303-4), Harbin technological innovative personnel and special fund project (2012RFXXS066) and The First Hospital of Harbin City talent introduction project (2013SYYRCYJ01-1).

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