Is there a relationship between the Intermittent and Constant Osteoarthritis Pain score (ICOAP) and pain flares in knee osteoarthritis?

Is there a relationship between the Intermittent and Constant Osteoarthritis Pain score (ICOAP) and pain flares in knee osteoarthritis?

Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534 Results: Of 143 patients MRI data were available of baseline and twoyear follow-up. At on...

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Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534

Results: Of 143 patients MRI data were available of baseline and twoyear follow-up. At one-year follow-up 8 of the 143 patients had no MRI examination because of foreign stay, pregnancy and not available. The study population had the following baseline characteristics: median age 25.2 (IQR 21.4e32.6) years; 34.3% female; median Tegner activity score pre-trauma 9 (IQR 7e9); 85% scored 2þ on Lachman test and 58% positive ( 1þ) pivot shift. Patients with presence of BMLs in the medial tibiofemoral compartment one year after ACL rupture had lower subjective scores at two year follow-up compared to patients without BMLs: IKDC subjective (median score 77.0 versus 90.8; p ¼ 0.021), KOOS symptoms (median score 85.7 versus 92.9; p ¼ 0.007) and KOOS Sport and Recreation (median score 80.0 versus 90.0; p ¼ 0.001). Patients with progression of cartilage defects in the tibiofemoral compartment two years after ACL rupture showed significant lower subjective scores than patients without progression on KOOS symptoms (median score 85.7 versus 92.9; p ¼ 0.001) and KOOS QoL (median score 68.8 versus 75.0; p ¼ 0.007). Conclusions: Patients with an ACL rupture and presence of BMLs in the medial compartment one year after trauma and patients with progression of cartilage defects in the tibiofemoral compartment have lower subjective outcome scores two years after ACL rupture. 720 CROSS-CULTURAL VALIDATION OF THE COMPUTERIZED ANIMATED ACTIVITY QUESTIONNAIRE TO ASSESS ACTIVITY LIMITATIONS IN PATIENTS WITH HIP AND KNEE OSTEOARTHRITIS W.F. Peter y, R.H. de Vet y, M. Boers y, J. Harlaar y, L.D. Roorda z, R.W. Poolman x, V.A. Scholtes x, M. Steultjens k, E.M. Roos ¶, F. Guillemin #, M.G. Benedetti yy, H. Dagfinrud zz, A. Escobar xx, F. Galindo Garre y, C.B. Terwee y. y VU Univ. Med. Ctr., Amsterdam, Netherlands; z Reade, Amsterdam Rehabilitation Res. Ctr., Amsterdam, Netherlands; x OLVG Hosp., Amsterdam, Netherlands; k Glasgow Caledonian Univ., Glasgow, United Kingdom; ¶ Univ. of Southern Denmark, Odens, Denmark; # Univ. of Lorraine, Nancy, France; yy Istituto Ortpedico Rizzoli, Bologna, Italy; zz Diakonhjemmet Hosp., Oslo, Norway; xx Basurto Univ. Hosp., Bilbao, Spain Purpose: The computerized Animated Activity Questionnaire (AAQ) for assessing activity limitations in hip and knee osteoarthritis (HKOA) consists of video animations from which patients can choose the animation that best matches their own performance. The AAQ has demonstrated good validity and reliability. Application of the AAQ in international studies, requires good cross-cultural validity, i.e., minimal Differential Item Functioning (DIF) across countries. The aim of this study was to evaluate cross-cultural validity. Methods: Patients in 7 European countries patients completed the AAQ on a computer. Ordinal logistic regression analysis was used to evaluate DIF across languages (Dutch versus 6 other languages). DIF is defined as follows: If a patient in a country has the same level of activity limitation as a patient in the Netherlands (the reference country in which the AAQ is developed), they should score the same on each item of the AAQ. If there is a statistical significant difference between countries, there is DIF. We used frequently described criteria in literature to assess DIF between countries. Criteria for non-uniform DIF were set as a statistical significance (p < 0.001) pseudo R-square change according to Nagelkerke with a magnitude larger than 0.035 between the AAQ total score and the country variable (with Dutch as the reference group). Criteria for uniform DIF were set as a statistical significant (p < 0.001) odds ratio (OR) of the country variable with a magnitude outside the interval 0.53e1.89. Analyses were adjusted for sex, age, weight, height, and affected joint. The influence of each individual item with DIF on the total score was calculated by means of comparing the correlation between AAQ score with and without the DIF item. A Spearman’s correlation of 0.95 or less was interpreted as important influence of the DIF of that item on the total AAQ score. Results: Data of 1239 patients were available. Compared to Dutch (n ¼ 279), none of the 17 items showed DIF in English (n ¼ 202) and French (n ¼ 193). Uniform DIF occurred in the activity ‘walking outside’ for Spanish versus Dutch (OR 0.28) and Norwegian versus Dutch (OR 0.16), with for both countries scores representing slightly worse functioning compared to Dutch. For Danish versus Dutch, DIF occurred in two items (walking outside on uneven terrain; OR 0.45, walking inside; OR 0.43), also representing slightly worse functioning compared to Dutch. In all these languages, the occurrence of DIF did not influence the

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total score with correlations of 0.98e0.99 in comparing AAQ scores with and without DIF item (s). For Italian (n ¼ 203) versus Dutch, 6 items showed uniform DIF and 1 item showed non-uniform DIF, which makes it difficult to compare scores obtained in those two countries. Conclusions: Different language versions of the AAQ remain comparable with the original Dutch version except for the Italian version. The AAQ seems to have great potential for international use in research and daily clinical practice, especially in patients with low literacy and non-native speakers, because the use of video animations instead of written text. Future research will focus on responsiveness, interpretation of AAQ scores, and should explore explanations for DIF in Italy by means of qualitative research. 721 IS THERE A RELATIONSHIP BETWEEN THE INTERMITTENT AND CONSTANT OSTEOARTHRITIS PAIN SCORE (ICOAP) AND PAIN FLARES IN KNEE OSTEOARTHRITIS? I. Atukorala y, A. Pathmeswaran z, J. Makovey x, B. Metcalf k, L. March x, K.L. Bennell k, T. Chang y, Y. Zhang ¶, D.J. Hunter x. y Dept. of Clinical Med., Faculty of Med., University of Colombo, Sri Lanka; z Dept. of Publ. Hlth., Faculty of Med., University of Kelaniya, Ragama, Sri Lanka; x Inst. of Bone and Joint Hlth., Kolling Inst., University of Sydney, Australia; k Ctr. for Hlth., Exercise & Sports Med., Dept. of Physiotherapy, Sch. of Hlth.Sci., University of Melbourne, Australia; ¶ Clinical Epidemiology Res. and Training Unit, Boston University School of Medicine, MA, USA Purpose: The Intermittent and Constant Osteoarthritis Pain Score (ICOAP) is a recently validated multidimensional osteoarthritis pain measure. This 11-item tool takes into account both the constant (6 items) and intermittent (5 items) pain of knee osteoarthritis (KOA) within 7 days summated to a single score. These items are scored from 0 (no pain) to 4 (extremely severe pain). The intent of this project was to assess the association and utility of ICOAP and its subscales in predicting pain flares in KOA identified by a 0e10 point numerical rating scale (NRS). Methods: Study participants were selected from a 3-month web-based longitudinal follow up study developed to identify risk factors for KOA pain flares. Participants were requested to complete the ICOAP questionnaire at days 0, 30, 60 and 90 (control period assessment points) and at time points whenever they experienced knee pain flare (case period assessment points) during the follow up period. A KOA pain flare was defined as current pain with a greater than 2 point increase (on a 0e10point NRS) from the mildest KOA pain intensity reported at day 0. The ICOAP score at point of a KOA pain flare was used to identify whether ICOAP was associated with occurrence of a pain flare. Conditional logistic regression was used to identify the odds of association with pain flare by the individual subscales and total ICOAP. Receiver Operating Characteristic Curves (ROC curves) were used to assess the utility of the ICOAP and its subscales (immediately preceding the flare) in predicting pain flares using the pain flares identified by the numeric rating scale as the gold standard. The ICOAP value for the first flare during the follow up period was used to predict pain. Results: 213 persons (61%females) with multiple KOA pain flares were selected. Their mean age was 62.1 years (SD 8.5). The mean body mass index was 29.8 kg/m2 (SD 6.5). There were 652 flares documented with 1232 control periods over a 3month period. 325 flares had a documented ICOAP within the preceding 30 days. The time gap between control period and flare period assessment points differed between subjects with the mean time gap being 18.5 days (SD 9.3). The mean number of flares per person per month was 1.97 (SD 2.65). None of the patients had a pain flare at baseline ICOAP total, constant and intermittent subscales had a significant association with pain flare (Table 1). However, the ICOAP scores (total, constant and intermittent) did not usefully predict pain flares and demonstrated an area under the ROC curves of 0.69 (95% confidence interval (CI)0.67e0.72), 0.69 (95% CI 0.67e0.72), 0.67 (95% CI 0.64e0.69) for total ICOAP score, constant pain and intermittent pain subscales respectively. Conclusions: The total ICOAP score (as well as the Constant and Intermittent subscales) recorded at point of flare was associated with KOA pain flares identified by the NRS. However, the ICOAP and its subscales did not usefully predict a pain flare. The lack of difference between the constant and intermittent ICOAP score can be attributed to correlation of items in the two subscales. The lack of complete correlation between the ICOAP values and pain flare assessed by the NRS is

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Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534

possibly due to the multidimensional nature of the ICOAP in contrast to the uni-dimensional nature of NRS.

Association between ICOAP and its subscales and knee OA pain flares assessed at point of flare. ICOAP

Odds ratio (95% Confidence interval)

P

Total score Constant subscale score Intermittent subscale score

1.04 (1.03e1.05) 1.05 (1.03e1.07) 1.04 (1.02e1.05)

<0.0001 <0.0001 <0.0001

* for a one unit increase in ICOAP value..

722 CHANGES IN LEG MUSCLE STRENGTH AND POWER AFTER TAI CHI EXERCISE IN PATIENTS WITH SYMPTOMATIC KNEE OSTEOARTHRITIS K.F. Reid y, L. Price z, W.F. Harvey x, J.B. Driban x, R.A. Fielding y, C. Wang x. y Tufts Univ., Boston, MA, USA; z Tufts Med. Ctr. and Tufts Univ., Boston, MA, USA; x Tufts Med. Ctr., Boston, MA, USA Purpose: Tai Chi, a form of mind-body exercise, is a promising nonpharmacologic intervention that improves symptoms and functional outcomes among individuals with knee osteoarthritis (OA). However, despite its clinical efficacy, limited understanding exists on the major underlying physiological adaptations that occur in response to Tai Chi exercise, particularly among persons with knee OA. The purpose of this study was to examine potential adaptations in leg muscle strength and power following an intervention of Tai Chi exercise in individuals with symptomatic knee OA. Methods: We conducted a secondary analysis of data from a singleblind, randomized comparative effectiveness trial of Tai Chi exercise versus standardized physical therapy (PT) conducted in a population of older adults with symptomatic knee OA (n ¼ 122; mean age: 61.1 ± 10.2 yrs, BMI: 32.1 ± 6.7 kg/m2, 66% female, 62% Caucasian) who met the American College of Rheumatology criteria for knee OA. Participants were randomized to 12 weeks of Tai Chi (2x/week) using classical Yang style or to a standardized PT regimen (2x/week for 6 weeks, followed by 6 weeks of rigorously monitored home PT). At baseline and 12 weeks, maximal muscle strength was measured using a bilateral leg press exercise and peak muscle power was measured during 5 repetitions performed as fast as possible with resistance set to 40% of the 1-repetitiion maximum (Keiser Pneumatic Leg Press A420, Keiser Corporation, Fresno, CA). Pain was measured using the Western Ontario and McMaster Osteoarthritis Index (WOMAC). Results: At week 12, participants in Tai Chi elicited significant gains in muscle strength (mean change from baseline: D 114.2 newtons (P ¼ 0.0005) and muscle power: D 26.0 watts (P ¼ 0.03). Changes in muscle strength were significantly correlated with reductions in WOMAC pain after Tai Chi exercise (r ¼ 0.32, P ¼ 0.01). Conclusions: Tai Chi exercise is associated with significant and clinically meaningful improvements in muscle strength and power among older adults with symptomatic knee OA. These data provide important new insights into potential neuromuscular adaptations associated with Tai Chi exercise within this patient population. This knowledge may be important for development of more effective strategies to enhance and maximize the clinical benefits of mind-body interventions for persons with knee OA. 723 NOVEL USE OF ACCELEROMETRY DATA TO DEVELOP PHENOTYPES OF FREE-LIVING PHYSICAL ACTIVITY (PERFORMANCE) AND DIFFERENTIATE BETWEEN KNEE OSTEOARTHRITIS, LUMBAR SPINAL STENOSIS, AND HEALTHY POPULATIONS C. Tomkins-Lane y, J. Norden z, A. Sinha z, R. Hu x, M. Smuck z. y Mount Royal Univ., Calgary, AB, Canada; z Stanford Univ., Stanford, CA, USA; x Univ. of Calgary, Calgary, AB, Canada Purpose: Musculoskeletal disorders are associated with significant mobility limitations. In particular, osteoarthritis (OA) and lumbar spinal stenosis (LSS) are two leading causes of disability. There is a clear need for new personalized therapies aimed at increasing function and mobility in these populations, but there is a lack of objective measures. The identification and implementation of new objective and

quantifiable measures of function would improve diagnosis and evaluation of treatment effects in OA and LSS, and it would help identify disease-specific interventions. The goal of this study is to apply novel techniques designed for analyzing accelerometry data in populations with musculoskeletal pain to 1) identify characteristics (phenotypes) of free-living physical activity (performance) that are unique to individuals with OA and LSS, and 2) determine the best methods for differentiating between the conditions. Methods: All analyses were conducted using existing datasets, including: the Osteoarthritis Initiative 48-month data (OAI), the National Health and Nutrition Examination Survey (NHANES) 2003e4 data, and the Lumbar Spinal Stenosis Accelerometry Database (LSSAD). In order to characterize the accelerometry signals of OA, LSS and NHANES, we examined the data using 1) standard intervals for counts/ minute from Freedson et al., and 2) the Physical Performance (PP) analysis designed by our group specifically to interrogate data from mobility-limited pain populations. We evaluated the significance of each accelerometry feature alone in discriminating between the three groups (OA, LSS, NHANES). Then, we determined which set of features together best classifies individuals between the groups. Results: All Freedson and Physical Performance (PP) intervals discriminated between groups (p < 0.05 after accounting for multiple hypothesis testing) except for the following intervals: Freedson moderate, Freedson heavy, and PP moderate-heavy for LSSAD vs. NHANES, and Freedson heavy for LSSAD vs. OA. Given age and gender, classification rates were 80% accurate (pairwise) between diseases and painfree populations (OA vs. NHANES and LSS vs. NHANES). The most important features to distinguish between groups corresponded to sedentary and light activity. On the other hand, the subtler classification between diseased populations (OA vs. LSS) was 72% accurate, with moderate activity as the prominent distinguishing feature. Conclusions: We show how it is possible to derive new clinical insights from accelerometry data. Namely, we have developed a novel set of features that characterize movement patterns in people with OA and LSS. Many of these features were found to be statistically significant in discriminating between disease populations, and between disease populations and matched healthy controls. Furthermore, our approach determines a key set of discriminatory features, resulting in a framework for classifying musculoskeletal diseases. These new quantitative phenotypes for OA and LSS provide a more comprehensive method for analysis of free-living physical activity (performance), and provide the groundwork for more personalized approaches to improving function. 724 SIGNAL INTENSITY ALTERATION IN INFRAPATELLAR FAT PAD PREDICTS INCIDENT RADIOGRAPHIC OSTEOARTHRITIS OVER 4 YEARS IN THE OSTEOARTHRITIS INITIATIVE C. Ding y, Z. Chen y, M. Hannon z, C. Kwoh x, D. Hunter k. y Univ. of Tasmania, Hobart, Australia; z Univ. of Pittsburgh Graduate Sch. of Publ. Hlth., Pittsburgh, PA, USA; x Univ. of Arizona Arthritis Ctr. & Div. of Rheumatology, Tucson, AZ, USA; k Univ. of Sydney, Sydney, Australia Purpose: Increased signal intensity within infrapatellar fat pad (IPFP) on T2/ intermediate -weighted magnetic resonance images (MRI) may represent pathological changes such as inflammation and edema. The aim of this nested case-control study was to determine if IPFP signal intensity measures over up to 4 years prior to incident radiographic osteoarthritis (ROA) was associated with increased risks of ROA in participants from the Osteoarthritis Initiative (OAI) cohort. Methods: Case knees (n ¼ 354) were defined by incident ROA [Kellgren Lawrence grading (KLG)  2] on the postero-anterior knee radiographs at any assessment after baseline (BL) prior to the 48 month visit. They were matched one-to-one by gender, age (± 5 years) and radiographic status (KL ¼ 0 or 1 in the index knee, KL ¼ 0 or 1 or 2þ in the contralateral knee) with a control knee. Control knees did not develop incident ROA from BL to 48 months. Radiographs were assessed at P0 (visit when ROA was found on radiograph), 1 year prior to P0 (P-1), and at OAI BL. Sagittal planes of fat-saturated intermediate-weighted images with turbo spin-echo obtained on 3-T MRI were utilized to assess IPFP signal intensity semi-automatically using MATLAB. Measures of IPFP signal intensity included mean value [Mean (IPFP)] and standard deviation [sDev(IPFP)] of IPFP signal intensity, mean value [Mean (H)] and standard deviation [sDev(H)] of IPFP high signal intensity, median value [Median (H)] and upper quartile value [UQ(H)] of high signal intensity, volume of high signal intensity regions of IPFP