Dataset Information

Epidemiology of knee osteoarthritis in general practice: a registry-based study.

ABSTRACT: OBJECTIVES:The present study investigated (1) trends in the prevalence and incidence of knee osteoarthritis over a 20-year period (1996-2015); (2) trends in multimorbidity and (3) trends in drug prescriptions. DESIGN:Registry-based study. SETTING:Primary healthcare, Flanders, Belgium. PARTICIPANTS:Data were collected from Intego, a general practice-based morbidity registration network. In the study period between 1996 and 2015, data from 440?140 unique patients were available. OUTCOME MEASURES:Trends in prevalence and incidence rate of knee osteoarthritis were computed using joinpoint regression analysis. The mean disease count was calculated to assess trends in multimorbidity. In addition, the number of drug prescriptions was identified by the Anatomical Therapeutic Chemical Classification code and trends were equally recorded with joinpoint regression. RESULTS:The total age-standardised prevalence of knee osteoarthritis increased from 2.0% in 1996 to 3.6% in 2015. An upward trend was observed with an average annual percentage change (AAPC) of 2.5 (95% CI 2.2 to 2.9). In 2015, the prevalence rates in the 10?year age groups from the 45-54 years age group onwards were 3.1%, 5.6%, 9.0% and 13.9%, to reach 15.0% in people aged 85 years and older. The incidence remained stable with 3.75‰ in 2015 (AAPC=-0.5, 95%?CI -1.4 to 0.5). The mean disease count significantly increased from 1.63 to 2.34 (p<0.001) for incident cases with knee osteoarthritis. Finally, we observed a significantly positive trend in the overall prescription of acetaminophen (AAPC=6.7, 95%?CI 5.6 to 7.7), weak opioids (AAPC=4.0, 95%?CI 0.9 to 7.3) and glucosamine (AAPC=8.6, 95%?CI 2.4 to 15.1). Oral non-steroidal anti-inflammatory drugs were most prescribed, with a prevalence rate of 29.8% in 2015, but remained stable during the study period (AAPC=0.0, 95%?CI -1.1 to 1.1). CONCLUSIONS:Increased prevalence, multimorbidity, and number of drug prescriptions confirm an increased burden of knee osteoarthritis. In future, these trends can be used to prioritise initiatives for improvement in care.

SUBMITTER: Spitaels D

PROVIDER: S-EPMC7044813 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Epidemiology of knee osteoarthritis in general practice: a registry-based study.

Spitaels David D Mamouris Pavlos P Vaes Bert B Smeets Miek M Luyten Frank F Hermens Rosella R Vankrunkelsven Patrik P

BMJ open 20200120 1

<h4>Objectives</h4>The present study investigated (1) trends in the prevalence and incidence of knee osteoarthritis over a 20-year period (1996-2015); (2) trends in multimorbidity and (3) trends in drug prescriptions.<h4>Design</h4>Registry-based study.<h4>Setting</h4>Primary healthcare, Flanders, Belgium.<h4>Participants</h4>Data were collected from Intego, a general practice-based morbidity registration network. In the study period between 1996 and 2015, data from 440 140 unique patients were ...[more]

PMID: 31964664

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Project description:Synovitis has long been considered a common and modifiable inflammatory feature of osteoarthritis (OA), but current disease-modifying anti-inflammatory treatments appear ineffective in OA clinical trials. Elucidating the temporal relationship between synovitis and OA could provide insight into the role of synovitis in OA. We conducted a prospective cohort study based on the baseline and three-year follow-up data from the Xiangya Osteoarthritis (XO) Study. We assessed bidirectional associations between ultrasound-detected synovitis and radiographic and symptomatic OA at knee and hand sites using generalized estimating equations. Additionally, we performed bidirectional Mendelian randomization (MR) analyses to test these hypotheses utilising whole-genome sequencing data in the XO population. Age, sex, body mass index, smoking, alcohol consumption, educational level, physical activity, and joint injury history were adjusted for these analyses. A total of 2211, 2420, 2280, and 2600 participants were enrolled for analyses of radiographic knee OA (RKOA), symptomatic knee OA (SKOA), radiographic hand OA (RHOA) and symptomatic hand OA (SHOA), respectively. The baseline synovitis (i.e., with synovitis vs. without synovitis) was associated with the incident RKOA (76/277 vs. 557/3674 knees), SKOA (49/387 vs. 287/4213 knees), RHOA (171/358 vs. 686/3664 hands) and SHOA (35/689 vs. 76/4327 hands), with adjusted odds ratio (aORs) of 2.2 (95% CI 1.7-3.1), 2.0 (1.3-2.9), 3.4 (2.7-4.4), and 2.4 (1.5-3.8), respectively. The baseline RKOA (with OA vs. without OA: 409/1246 vs. 481/3758 knees), SKOA (200/576 vs. 675/4356 knees), RHOA (192/778 vs. 410/3723 hands), and SHOA (41/162 vs. 548/4285 hands) were also associated with the incident synovitis, with aORs of 3.4 (95% CI 2.9-4.1), 2.7 (2.1-3.4), 2.3 (1.8-2.9) and 1.9 (1.2-2.8), respectively. These bidirectional associations were stronger when more active synovitis was compared with the reference group (all P < 0.05). MR analyses further supported bidirectional associations that synovitis significantly increased the odds of incident OA at both sites and vice versa (all ORs ranged from 1.2-1.7). Our population-based cohort study found novel evidence of a bidirectional association between synovitis and OA, which was further validated through MR analysis and suggested that the bidirectional association is likely causal. Our findings indicated that synovitis is both a risk factor and a consequence of the OA rather than solely a risk factor. The National Key Research and Development Plan, the National Natural Science Foundation of China, the Key Research and Development Program of Hunan Province, the Natural Science Foundation of Hunan Province, the Central South University Innovation-Driven Research Programme, and the Fundamental Research Funds for the Central Universities of Central South University.

Project description:ObjectiveWhile education, exercise, and weight reduction when indicated, are recommended first-line treatments for knee osteoarthritis patients, they remain poorly implemented in favour of pain killer treatment, imaging and referral to surgery. A reason could be that patients are more satisfied with receiving these adjunctive treatment elements. This study aimed to investigate the associations between the received elements of care and the patient's satisfaction with the care for knee osteoarthritis in general practice.DesignCross-sectional study.SettingA Danish general practice.SubjectsAll consecutive patients ≥30 years of age who consulted the general practitioner (GP) with chronic knee complaints during 18 months and who replied to a mailed questionnaire (n = 136).Main outcome measuresThe questionnaire addressed patient's knee-related quality of life, and overall satisfaction with care, as well as reception of seven types of information, which are known quality indicators. Information on reception of adjunctive treatment elements was obtained from electronic medical records.ResultsPatient satisfaction (versus neutrality/dissatisfaction) was positively associated with reception of information on: physical activity and exercise (relative risks [RR] 1.38, 95% bootstrap percentile interval [BPI] 1.02-4.33), and the relationship between weight and osteoarthritis (1.38, 1.01-4.41). No significant associations were found for the five remaining types of information and all the adjunctive treatment elements.ConclusionProviding information as education to patients with knee osteoarthritis as part of the treatment is positively associated with satisfaction with care.KEY POINTSGeneral practitioners worry about the doctor-patient relationship when addressing recommended lifestyle changes. However, this study revealed:•Patients in general practice with knee osteoarthritis are satisfied with care after having received information on lifestyle changes, such as exercise and the relationship between weight and osteoarthritis.•Patient satisfaction was not associated with the reception of adjunctive treatment elements for osteoarthritis.

Project description:BackgroundEarly identification of knee osteoarthritis (OA) can improve treatment outcomes and reduce medical costs. However, there are major limitations among existing classification or prediction models, including abstract data processing and complicated dataset attributes, which hinder their applications in clinical practice.ObjectiveThe aim of this study was to propose a Bayesian network (BN)-based classification model to classify people with knee OA. The proposed model can be treated as a prescreening tool, which can provide decision support for health professionals.MethodsThe proposed model's structure was based on a 3-level BN structure and then retrained by the Bayesian Search (BS) learning algorithm. The model's parameters were determined by the expectation-maximization algorithm. The used dataset included backgrounds, the target disease, and predictors. The performance of the model was evaluated based on classification accuracy, area under the curve (AUC), specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV); it was also compared with other well-known classification models. A test was also performed to explore whether physical fitness tests could improve the performance of the proposed model.ResultsA total of 249 elderly people between the ages of 60 and 80 years, living in the Kongjiang community (Shanghai), were recruited from April to September 2007. A total of 157 instances were adopted as the dataset after data preprocessing. The experimental results showed that the results of the proposed model were higher than, or equal to, the mean scores of other classification models: .754 for accuracy, .78 for AUC, .78 for specificity, and .73 for sensitivity. The proposed model provided .45 for PPV and .92 for NPV at the prevalence of 20%. The proposed model also showed a significant improvement when compared with the traditional BN model: 6.3% increase in accuracy (from .709 to .754), 4.0% increase in AUC (from .75 to .78), 6.8% increase in specificity (from .73 to .78), 5.8% increase in sensitivity (from .69 to .73), 15.4% increase in PPV (from .39 to .45), and 2.2% increase in NPV (from .90 to .92). Furthermore, the test results showed that the performance of the proposed model could be largely enhanced through physical fitness tests in 3 evaluation indices: 10.6% increase in accuracy (from .682 to .754), 16.4% increase in AUC (from .67 to .78), and 30.0% increase in specificity (from .60 to .78).ConclusionsThe proposed model presents a promising method to classify people with knee OA when compared with other classification models and the traditional BN model. It could be implemented in clinical practice as a prescreening tool for knee OA, which would not only improve the quality of health care for elderly people but also reduce overall medical costs.

Dataset Information

Epidemiology of knee osteoarthritis in general practice: a registry-based study.

Publications

Epidemiology of knee osteoarthritis in general practice: a registry-based study.

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