The Association Between Severity of Radiographic Knee OA and Recurrent Falls in Middle and Older Aged Adults: The Osteoarthritis Initiative

Pain Medication Frequency and Fall Risk Among Community-Dwelling Older Adults With Arthritis

Pain medication is commonly used among older adults with arthritis, elevating the risk of falling. We examined fall risks related to the frequency of taking pain medication among community-dwelling older adults with arthritis by analyzing a nationally representative sample of community-dwelling Medicare beneficiaries aged >65 with self-reported arthritis (n = 4,225) in the 2015 National Health and Aging Trends Study. The survey-weighted logistic regression revealed that after controlling for confounding factors, recent falls were associated with taking pain medication daily compared to never (OR = 1.45, 95% CI: 1.06, 1.96). The other categories of medication frequency, compared to never, were not associated with fall risk. Findings suggest that more prudent use of pain medication should be stressed by health care providers for older adults with arthritis to help reduce the risk of falls and fall injuries. Nonpharmacological pain management is encouraged to support active living among older adults with arthritis.

Study of knee pain, fear of falling, and quality of life among community-dwelling older adults, Northern Thailand

Fall is the leading cause of disability and mortality due to unintentional injury in older adults. The aim of this study was to determine the prevalence and risk factors associated with knee pain, fear of falling, and quality of life among community-dwelling older adults in Northern Thailand. A cross-sectional study was conducted among older adults aged 60 and over. A total of 369 participants were enrolled from April to May 2024. Oxford knee score, a short version of the Falls Efficacy Scale International (FES-I) and World Health Organization quality of life-BREF-Thai, was measured. The results showed that the mean age was 69.4 years and 47 (12.7%) had a history of falls in the previous year. The prevalence of fear of falling was 39.3% for low, 22.5% for moderate, and 38.2% for high concern. Age, marital status, alcohol, history of falls, hypertension, arthritis, and osteoporosis were associated with fear of falling. After adjusting to age, gender, body mass index, education, marital status, smoking, alcohol, history of falls, and chronic disease, osteoarthritis of the knee was positively associated with increasing fear of falling (β: 0.361; p<0.001), while quality of life was negatively associated with fear of falling (β: -0.064; p<0.011). In conclusion, the identified determinants of fear of falling among the elderly indicated the need for fear of falling prevention programs targeting not only individual lifestyles but also chronic diseases. This study provides useful information that might help to develop and adopt effective policies for fear of falling control in Thailand.

Development and validation of a frailty index for use in the osteoarthritis initiative

BACKGROUND

The Osteoarthritis Initiative (OAI) evaluates the development and progression of osteoarthritis. Frailty captures the heterogeneity in aging. Use of this resource-intensive dataset to answer aging-related research questions could be enhanced by a frailty measure.

OBJECTIVE

To: (i) develop a deficit accumulation frailty index (FI) for the OAI; (ii) examine its relationship with age and compare between sexes, (iii) validate the FI versus all-cause mortality and (iv) compare this association with mortality with a modified frailty phenotype.

DESIGN

OAI cohort study.

SETTING

North America.

SUBJECTS

An FI was determined for 4,755/4,796 and 4,149/4,796 who had a valid FI and frailty phenotype.

METHODS

Fifty-nine-variables were screened for inclusion. Multivariate Cox regression evaluated the impact of FI or phenotype on all-cause mortality at follow-up (up to 146 months), controlling for age and sex.

RESULTS

Thirty-one items were included. FI scores (0.16 ± 0.09) were higher in older adults and among females (both, P < 0.001). By follow-up, 264 people had died (6.4%). Older age, being male, and greater FI were associated with a higher risk of all-cause mortality (all, P < 0.001). The model including FI was a better fit than the model including the phenotype (AIC: 4,167 vs. 4,178) and was a better predictor of all-cause mortality than the phenotype with an area under receiver operating characteristic curve: 0.652 vs. 0.581.

CONCLUSION

We developed an FI using the OAI and validated it in relation to all-cause mortality. The FI may be used to study aging on clinical, functional and structural aspects of osteoarthritis included in the OAI.

Radiographic knee osteoarthritis severity has no impact on fall risk: the locomotive syndrome and health outcomes in the aizu cohort study (LOHAS): a cross-sectional study

BACKGROUND

To investigate factors that have an impact on the risk of falls and determine whether radiographic knee osteoarthritis (KOA) is a factor involved in falls independent of knee pain, psychological factors, and physical function.

METHODS

A cross-sectional analysis was conducted on 1083 subjects for the 2009 Locomotive Syndrome and Health Outcomes in the Aizu Cohort Study (LOHAS). A logistic regression analysis was performed to examine the relationship between radiographic KOA and fall history.

RESULTS

Fall history was significantly associated with the severity of knee pain. Compared to subjects with no knee pain, the odds ratio (OR) was 1.53 times higher in the subjects with mild knee pain (95% confidence interval [CI]: 1.04-2.25), 1.69 times higher in those with moderate knee pain (95%CI: 1.03-2.79), and 2.98 times higher in those with severe knee pain (95%CI: 1.67-5.30). In subjects with depression, the OR was 1.91 (95%CI: 1.25-2.92), and in those with decreased mobility, the OR was 1.70 (95%CI: 1.08-2.69). Age, gender, knee crepitus, BMI, OLST, and sleeping pill use were not significantly associated with fall risk. In a multivariate analysis, radiographic KOA severity was not significantly associated with fall risk (OR 0.81, 95%CI 0.44-1.50 in mild OA; OR 1.10, 95%CI 0.57-2.14 in severe OA).

CONCLUSION

Knee pain, decreased mobility, and depression, but not the radiographic KOA severity, were significantly associated with a fall risk. Regardless of the individual's radiographic KOA severity, the risk of falls may be reduced by treating his/her knee pain, mobility problems, and/or psychological factors.

Physical Therapists' Attitudes, Beliefs, and Barriers Regarding Fall Screening and Prevention among Patients with Knee Osteoarthritis: A Cross-Sectional Study

Falls are commonly associated with knee osteoarthritis and represent a significant financial burden on the healthcare system. Therefore, the discovery of physical therapists' attitudes and practices regarding fall screening and prevention among patients with osteoarthritis should be investigated. Moreover, this study aimed to identify barriers that might limit its implementation among this population. A cross-sectional study design was used to collect the data. The electronic survey targeted licensed physical therapy professionals who currently work in clinical or academic settings in Saudi Arabia. The data were analyzed descriptively and inferentially using chi-square. Two hundred and six licensed physical therapists completed the survey, 119 females (57.8%) and 87 males (42.2%). The results of the structural equation modelling analysis showed that intention to use fall screening and management strategies was positively associated with the history of falls, identifying risk factors of falls, and documentation of risk factors of falls (p ≤ 0.0001). The most reported barriers to implement fall screening and prevention were lack of knowledge (n = 92, 45%), lack of training/skills (n = 84, 41%), and time constraints (n = 57, 45%), followed by patient compliance with 38% of the responses. The findings highlighted the importance of identifying the key opportunities for knowledge translation in clinical practices to enhance the sufficient implementation of fall screening and management in osteoarthritis care.

Anterior knee pain as a potential risk factor for falls in older adults: insights from the osteoarthritis initiative data

BACKGROUND

Knee joint pain has been demonstrated to be a separate risk factor for falling. A common pain site in the knee, anterior knee pain(AKP), is believed to be associated with early knee osteoarthritis (KOA).This study investigated the relationship between falls and AKP in people with or at risk for KOA.

METHODS

Four years of follow-up data from the Osteoarthritis Initiative cohort trial, a large-scale, multicenter observational investigation, were analyzed in this study. A patellar quadriceps tenderness/tendinitis knee exam was performed to evaluate AKP. Falls were self-reported. The associations between falls (recurrent falls: ≥2 falls/year; any falls: ≥1 fall(s)/year) and AKP were analyzed using the generalized estimation equation of repeated logistic regression and adjusted for confounding variables.

RESULTS

The study analyzed data from 3,318 participants, split into two groups: those with AKP (720 participants) and those without AKP (2,598 participants). The primary outcome of the study, which focused on repeated falls, revealed that participants with AKP were 1.27 times more likely to experience repeated falls compared to those without AKP (95% CI: 1.07-1.52, P = 0.007). However, when considering any falls experienced by an individual as an additional outcome, it is important to note that our findings did not indicate a significant predictive effect of AKP on any falls investigated. Sensitivity analyses, which excluded knee arthroplasty cases, yielded consistent results with the aforementioned findings.

CONCLUSIONS

Older adults with AKP experience a higher frequency of falls compared to those without AKP in individuals diagnosed with KOA or at a high risk of developing KOA.

Examination of the Increased Risk for Falls Among Individuals With Knee Osteoarthritis: A Canadian Longitudinal Study on Aging Population-Based Study

OBJECTIVE

To characterize the profile of individuals with and without knee osteoarthritis (OA) who fell, and to identify factors contributing to an individual with knee OA experiencing 1 or multiple injurious falls.

METHODS

Data are from the baseline and 3-year follow-up questionnaires of the Canadian Longitudinal Study on Aging, a population-based study of people ages 45-85 years at baseline. Analyses were limited to individuals either reporting knee OA or no arthritis at baseline (n = 21,710). Differences between falling patterns among those with and without knee OA were tested using chi-square tests and multivariable-adjusted logistic regression models. An ordinal logistic regression model examined predictors of experiencing 1 or more injurious falls among individuals with knee OA.

RESULTS

Among individuals reporting knee OA, 10% reported 1 or more injurious falls; 6% reported 1 fall, and 4% reported 2+ falls. Having knee OA significantly contributed to the risk of falling (odds ratio [OR] 1.33 [95% confidence interval (95% CI) 1.14-1.56]), and individuals with knee OA were more likely to report having a fall indoors while standing or walking. Among individuals with knee OA, reporting a previous fall (OR 1.75 [95% CI 1.22-2.52]), previous fracture (OR 1.42 [95% CI 1.12-1.80]), and having urinary incontinence (OR 1.38 [95% CI 1.01-1.88]) were significant predictors of falling.

CONCLUSION

Our findings support the idea that knee OA is an independent risk factor for falls. The circumstances in which falls occur differ from those for individuals without knee OA. The risk factors and environments that are associated with falling may provide opportunities for clinical intervention and fall prevention strategies.

Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment

PURPOSE

Evaluating lower extremity alignment using full-leg plain radiographs is an essential step in diagnosis and treatment of patients with knee osteoarthritis. The study objective was to present a deep learning-based anatomical landmark recognition and angle measurement model, using full-leg radiographs, and validate its performance.

METHODS

A total of 11,212 full-leg plain radiographs were used to create the model. To train the data, 15 anatomical landmarks were marked by two orthopaedic surgeons. Mechanical lateral distal femoral angle (mLDFA), medial proximal tibial angle (MPTA), joint line convergence angle (JLCA), and hip-knee-ankle angle (HKAA) were then measured. For inter-observer reliability, the inter-observer intraclass correlation coefficient (ICC) was evaluated by comparing measurements from the model, surgeons, and students, to ground truth measurements annotated by an orthopaedic specialist with 14 years of experience. To evaluate test-retest reliability, all measurements were made twice by each measurer. Intra-observer ICCs were then derived. Performance evaluation metrics used in previous studies were also derived for direct comparison of the model's performance.

RESULTS

Inter-observer ICCs for all angles of the model were 0.98 or higher (p < 0.001). Intra-observer ICCs for all angles were 1.00, which was higher than that of the orthopaedic specialist (0.97-1.00). Measurements made by the model showed no significant systemic variation. Except for JLCA, angles were precisely measured with absolute error averages under 0.52 degrees and proportion of outliers under 4.26%.

CONCLUSIONS

The deep learning model is capable of evaluating lower extremity alignment with performance as accurate as an orthopaedic specialist with 14 years of experience.

LEVEL OF EVIDENCE

III, retrospective cohort study.