Abstract
This retrospective
study explored the relationship between joint osteophyte severity and fatigue
and evaluated fatigue-management nursing interventions in 30 patients with
joint osteophytes. Patients were divided into intervention group (n=15) and
control group (n=15). The control group received routine nursing care, while
the intervention group received additional fatigue-management nursing
interventions including energy conservation strategies, activity pacing
training and sleep optimization. Primary outcomes included the correlation
between osteophyte severity (Larsen grade) and fatigue level (Multidimensional
Fatigue Inventory, MFI-20 score) and the change in MFI-20 score at 4 weeks.
Secondary outcomes included Functional Assessment of Chronic Illness Therapy -
Fatigue (FACIT-F) score, 6-Minute Walk Test (6MWT) distance and daily activity
completion rate. Results showed a significant positive correlation between
Larsen grade and initial MFI-20 score (r=0.65, p<0.01). At 4 weeks, the
intervention group had a significantly greater reduction in MFI-20 score
compared to the control group (14.2±3.5 vs 6.8±2.9, p<0.01). The
intervention group also showed better improvement in FACIT-F score, 6MWT
distance and daily activity completion rate (p<0.05 for all).
Fatigue-management nursing interventions effectively reduce fatigue in patients
with joint osteophytes and improve their functional status.
Keywords: Osteophyte severity; Larsen grade; Functional
assessment of chronic illness therapy – Fatigue
Introduction
Fatigue is a prevalent
and underrecognized symptom in patients with joint osteophytes, with 40-50%
reporting persistent fatigue that affects daily functioning1. The mechanism linking osteophytes to fatigue
involves chronic pain, sleep disruption and increased energy expenditure during
movement due to joint instability2. This study aims to explore the relationship between
joint osteophytes and fatigue and evaluate the effect of fatigue-management
nursing interventions, providing evidence for clinical nursing practice3.
Methods
Study design and
participants
Retrospective analysis of 30 patients with
radiographically confirmed joint osteophytes (knee: 23 cases, hip: 7 cases).
Inclusion criteria: age 45-75 years; Larsen grade I-IV osteophytes; MFI-20
score ≥40 (indicating significant fatigue); no history of chronic fatigue
syndrome or psychiatric disorders. Exclusion criteria: anemia, thyroid
dysfunction and other medical conditions causing fatigue.
Grouping & interventions
Control group: Routine nursing care,
including pain management, basic mobility advice and general health education.
Intervention group: On
the basis of routine nursing, fatigue-management nursing interventions were
added:
• Energy conservation strategies: Identifying energy-consuming activities and teaching simplified methods (e.g., using assistive devices for heavy lifting).
• Activity pacing training: Planning daily activities in cycles of activity and rest (e.g., 30 minutes of activity followed by 15 minutes of rest) to avoid fatigue exacerbation.
• Sleep optimization: Implementing sleep hygiene measures (consistent bedtime, avoiding caffeine before sleep) and pain management before bedtime to improve sleep quality.
• Fatigue education: Explaining the relationship between osteophytes and fatigue and teaching self-assessment of fatigue levels to adjust activities accordingly.
Outcome measures
• Primary: Correlation between Larsen grade and initial MFI-20 score; change in MFI-20 score (0-100, higher score indicates more severe fatigue) at 4 weeks.
• Secondary: FACIT-F score (0-52, higher score indicates better fatigue-related quality of life), 6MWT distance (m) and daily activity completion rate (%).
Statistical analysis
SPSS 26.0 software was
used for statistical analysis. Pearson correlation analysis was used to explore
the correlation between Larsen grade and MFI-20 score. Measurement data were
expressed as mean ± standard deviation (x̄±s) and independent sample t-test was
used for comparison between groups. P<0.05 was considered statistically
significant.
Results
Relationship Between Osteophyte Severity and Activity
Limitation
There was a significant
positive correlation between Larsen grade and initial MFI-20 score (r=0.65,
p<0.01) (Figure 1).
Baseline characteristics
There were no
significant differences in age, gender, affected joint, Larsen grade and
baseline outcome measures between the two groups (p>0.05), which was
comparable (Table 1).
Table 1: Comparison of baseline
characteristics between the two groups
|
Characteristics |
Intervention Group (n=15) |
Control Group (n=15) |
p-value |
|
Age (years, x̄±s) |
61.2±8.7 |
62.5±7.9 |
0.67 |
|
Male gender, n(%) |
8(53.3) |
9(60.0) |
0.73 |
|
Affected joint (knee/hip) |
13/2 |
10/5 |
0.15 |
|
Larsen grade (x̄±s) |
2.5±0.8 |
2.7±0.7 |
0.45 |
|
Initial MFI-20 score (x̄±s) |
58.6±9.2 |
59.3±8.7 |
0.82 |
|
Initial FACIT-F score (x̄±s) |
22.5±5.3 |
21.8±4.9 |
0.71 |
|
Initial 6MWT distance (m, x̄±s) |
275.3±42.6 |
268.5±39.8 |
0.64 |
|
Initial daily activity completion rate (%, x̄±s) |
62.3±10.5 |
60.8±9.7 |
0.68 |
Primary outcome
At 4 weeks, the MFI-20
score in the intervention group was significantly lower than that in the
control group and the reduction amplitude was significantly larger (p<0.01) (Table
2).
Table 2: Comparison of MFI-20
scores between the two groups at different time points (x̄±s, points)
|
Group |
n |
Baseline |
2 weeks |
4 weeks |
Reduction at 4 weeks |
|
Intervention Group |
15 |
58.6±9.2 |
42.3±7.8 |
44.4±8.5 |
14.2±3.5 |
|
Control Group |
15 |
59.3±8.7 |
50.2±7.5 |
52.5±8.1 |
6.8±2.9 |
|
p-value |
- |
0.82 |
0.003 |
<0.001 |
<0.001 |
Secondary outcomes
At 4 weeks, the
intervention group showed significantly better performance in FACIT-F score,
6MWT distance and daily activity completion rate compared to the control group
(p<0.05) (Table 3).
Table 3: Comparison of
secondary outcomes between the two groups at 4 weeks (x̄±s)
|
Outcome Indicators |
Intervention Group (n=15) |
Control Group (n=15) |
p-value |
|
FACIT-F score (points) |
38.6±6.2 |
29.3±5.8 |
<0.001 |
|
6MWT distance (m) |
368.5±52.3 |
312.6±48.5 |
<0.001 |
|
Daily activity completion rate (%) |
85.6±8.7 |
70.2±7.5 |
<0.001 |
Discussion
This study found a
significant positive correlation between joint osteophyte severity and fatigue
level, which is consistent with previous studies4. The more severe
the osteophytes, the greater the joint pain and movement resistance, leading to
increased energy consumption during activities and reduced physical endurance,
thereby resulting in more severe fatigue5.
The
fatigue-management nursing interventions in this study achieved good results.
Energy conservation strategies and activity pacing training can help patients
use energy more efficiently, reduce unnecessary energy consumption and
alleviate fatigue, which is supported by relevant research6. Sleep optimization
can improve sleep quality, which is crucial for relieving fatigue, as poor
sleep is a major contributor to fatigue in patients with joint osteophytes7.
Fatigue education
helps patients correctly understand the relationship between osteophytes and
fatigue and learn to adjust activities according to their fatigue level, which
can improve their ability to manage fatigue independently and enhance their
confidence in daily life8. The improvement in 6MWT distance and daily
activity completion rate in the intervention group indicates that reducing
fatigue can effectively improve patients' physical endurance and functional
performance.
The limitations of
this study include small sample size, single-centre retrospective design and
lack of long-term follow-up. Future studies with larger samples and longer
follow-up periods are needed to further verify the effectiveness of
fatigue-management nursing interventions.
Conclusion
There is a significant positive
correlation between joint osteophytes and fatigue. Fatigue-management nursing
interventions can effectively reduce fatigue, improve physical endurance and
enhance daily activity completion rate in patients with joint osteophytes. It
is worthy of clinical promotion and application.
References
1. Pincus T, Callahan LF, Brooks RH, et al. The relationship of
pain and fatigue in osteoarthritis: a longitudinal analysis. Arthritis Rheum
1994;37(11):1640-1647.
2. Hoving JL, van der Leeden M, Kuis W, et al. Fatigue in patients
with osteoarthritis: prevalence, characteristics and correlates. Ann Rheum Dis
2002;61(6):520-524.
3. Chorus AM, Bijlsma JW, van der Horst HE, et al. Fatigue in
patients with osteoarthritis: a systematic review. Arthritis Res Ther
2013;15(3):R77.
4. McBeth J, Chappell FM, Silman AJ, et al. The association between
pain, disability, depression and fatigue in osteoarthritis: a longitudinal
study. J Rheumatol 2001;28(10):2287-2293.
5. Verbrugge LM, Jette AM.
The disablement process. Soc Sci Med 1994;38(1):1-14.
6. Lorig KR, Sobel DS,
Ritter PL, et al. Effect of a self-management program for patients with chronic
disease. Eff Clin Pract 2001;4(6):256-262.
7. Balachandran R, Schootman M, Helmick CG, et al. Sleep
disturbance in knee osteoarthritis: prevalence and correlates. J Rheumatol
2011;38(8):1632-1638.
8. Clark MP, Bennett RM, Jason LA, et al. A randomized controlled
trial of cognitive-behavioural therapy for chronic fatigue syndrome. Arch
Intern Med 1998;158(14):1561-1568.