Incidence and Prevalence of Knee Osteoarthritis Using Codified and Narrative Data From Electronic Health Records: A Population‐Based Study

Arslan, I.; Damen, Jurgen; Wilde, Marcel de; Driest, Jacoline J van den; Bindels, Patrick J E; Lei, Johan van der; Schiphof, D.; Bierma-Zeinstra, Sita M A

doi:10.1002/acr.24861

Cited by 20 publications

(15 citation statements)

References 21 publications

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“…To limit the possible underestimation of the overall incidence because of limited medical notes or non-uniform ICPC coding, multiple ICPC codes and free-text terms to identify patients with hand and wrist disorders were used. 6 The strength of this study is that the diagnoses that were coded with a general hand or wrist complaint code by the GP, were also assessed for a specific diagnosis.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Incidence of hand and wrist disorders in primary care

Krastman,

de Schepper,

Bindels

et al. 2024

BJGP Open

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BackgroundThe incidence of different types of hand and wrist disorders in primary care is unknown since there are no specific encodings for it.AimsTo determine the overall incidence and the incidence of specific types of hand and wrist disorders in primary care.Design & settingA healthcare registration database from Dutch general practice, which contains medical records of over 200 000 patients and included approximately 25% of the population of the area of Rotterdam.MethodPatients aged ≥18 years with a new diagnosis of hand or wrist disorder from 1 January 2015 to 31 December 2019 were extracted using a search algorithm based on ICPC coding and search terms in free text.ResultsThe mean incidence over the study period of a hand disorder was 5.9 per 1,000 persons–years and of a wrist disorder 0.3 per 1,000 persons–years. The incidence of trigger finger/thumb, fracture hand/finger, tendon/ligament tendinopathy, mallet finger and ligament injury hand/finger were 3 (2.69–3.15), 1 (1.03–1.33), 1 (0.98–1.28), 0.6 (0.48–0.69) and 0.1 (0.06–0.14) per 1,000 persons–years, respectively. The incidence of a wrist fracture and ligament injury were 0.2 (0.13–0.25) and 0.1 (0.04–0.12) per 1,000 persons–years, respectively.ConclusionsThere is a large difference between the number of patients presenting to the GP with hand and wrist complaints and the number of hand and wrist diagnosis reported in the medical files. Introducing specific ICPC codes for different types of hand and wrist disorders could (potentially) lead to a more accurate registration of a diagnosis and determination of the incidence figures.

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Section: Strengths and Limitationsmentioning

confidence: 99%

Incidence of hand and wrist disorders in primary care

Krastman,

de Schepper,

Bindels

et al. 2024

BJGP Open

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“…employed for deducing regional OA prevalence and incidence rate, which would impact future public health planning [12][13][14]. Despite the widespread use, a paucity of studies exists on which clinical features drive clinicians to make the OA diagnosis.…”

Section: Furthermore Registered Clinicians' Diagnosis Was Sometimesmentioning

confidence: 99%

A machine learning approach reveals features related to clinicians’ diagnosis of clinically relevant knee osteoarthritis

et al. 2022

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Objectives To identify highly-ranked features related to clinicians’ diagnosis of clinically relevant knee osteoarthritis (OA). Methods General practitioners (GPs) and secondary care physicians (SPs) were recruited to evaluate 5–10 years follow-up clinical and radiographic data of knees from the CHECK cohort for the presence of clinically relevant OA. GPs and SPs were gathered in pairs; each pair consisted of 1 GP and 1 SP, and the paired clinicians independently evaluated the same subset of knees. A diagnosis was made for each knee by the GP and SP before and after viewing radiographic data. Nested 5-fold cross-validation enhanced random forest models were built to identify the top 10 features related to the diagnosis. Results 17 clinician pairs evaluated 1106 knees with 139 clinical and 36 radiographic features. GPs diagnosed clinically relevant OA in 42% and 43% knees, before and after viewing radiographic data, respectively. SPs diagnosed in 43% and 51% knees, respectively. Models containing top 10 features had good performance for explaining clinicians’ diagnosis with area under the curve ranging from 0.76–0.83. Before viewing radiographic data, quantitative symptomatic features (i.e. WOMAC scores) were the most important ones related to the diagnosis of both GPs and SPs; after viewing radiographic data, radiographic features appeared in the top lists for both, but seemed to be more important for SPs than GPs. Conclusions Random forest models presented good performance in explaining clinicians’ diagnosis, which helped to reveal typical features of patients recognized as clinically relevant knee OA by clinicians from two different care settings.

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“…Osteoarthritis (OA), a heterogeneous, multifactorial chronic disease affecting multiple joints throughout the body, progresses differently between individuals over time (1,2). The knee joint is the most common site of OA (3,4). The structural lesions of knee OA that cause pain and loss of function are mainly involved in cartilage degeneration, bone remodeling, osteophyte formation, and chronic inflammation throughout the joint (5).…”

Section: Introductionmentioning

confidence: 99%

“…Several studies have reported the prevalence of knee OA in a few nations, but its large-scale distribution and variability across countries and regions remain unclear (6). Using data from the Global Burden of Disease Study (GBD) 2010 and 2017, previous studies have reported the burden of musculoskeletal disease and arthritis in different regions and countries using different classification methods, but no study has yet specifically analyzed the global burden of knee OA (4)(5)(6)(7). According to a study using the Dutch national public health database, the number of knee OA cases in the Netherlands was predicted to rise 41% between 2015 and 2040 (4,7).…”

Section: Introductionmentioning

confidence: 99%

“…Using data from the Global Burden of Disease Study (GBD) 2010 and 2017, previous studies have reported the burden of musculoskeletal disease and arthritis in different regions and countries using different classification methods, but no study has yet specifically analyzed the global burden of knee OA (4)(5)(6)(7). According to a study using the Dutch national public health database, the number of knee OA cases in the Netherlands was predicted to rise 41% between 2015 and 2040 (4,7). Given the increasing burden of knee OA, continuous disease surveillance is vital for planning and managing the health care needs of the population.…”

Section: Introductionmentioning

confidence: 99%

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Burden of Knee Osteoarthritis in 204 Countries and Territories, 1990–2019: Results From the Global Burden of Disease Study 2019

Yang

Wang

et al. 2023

Arthritis Care & Research

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ObjectiveTo report the global, regional, and national estimates of knee osteoarthritis (OA) burden and associated risk factors (high body mass index [BMI]) by age, sex, and sociodemographic index (SDI) for 204 countries from 1990 to 2019.MethodsWe analyzed the prevalence, incidence, years lived with disability (YLDs), and age‐standardized rates of knee OA using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Estimates of the knee OA burden were derived from data modeled using a Bayesian meta‐regression analytical tool (DisMod‐MR 2.1).ResultsThe global prevalence of knee OA in 2019 was ~364.6 million (95% uncertainty interval [95% UI] 315.3 to 417.4). The age‐standardized prevalence in 2019 was 4,376.0 per 100,000 (95% UI 3,793.0 to 5,004.9), an increase of 7.5% between 1990 and 2019. There were ~29.5 million incident cases of knee OA in 2019 (95% UI 25.6 to 33.7), with an age‐standardized incidence of 350.3 per 100,000 (95% UI 303.4 to 398.9). The global age‐standardized YLD resulting from knee OA was 138.2 (95% UI 68.5 to 281.3) per 100,000 population in 2019, an increase of 7.8% (95% UI 7.1 to 8.4) from 1990. Globally in 2019, 22.4% (95% UI 12.1 to 34.2) of YLD resulting from knee OA was attributable to high BMI, an increase of 40.5% since 1990.ConclusionThe prevalence, incidence, YLDs, and age‐standardized rates of knee OA increased substantially in most countries and regions from 1990 to 2019. Continuous monitoring of this burden is important for establishing appropriate public prevention policies and raising public awareness, especially in high‐ and high–middle SDI regions.

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Incidence and Prevalence of Knee Osteoarthritis Using Codified and Narrative Data From Electronic Health Records: A Population‐Based Study

Cited by 20 publications

References 21 publications

Incidence of hand and wrist disorders in primary care

Incidence of hand and wrist disorders in primary care

A machine learning approach reveals features related to clinicians’ diagnosis of clinically relevant knee osteoarthritis

Burden of Knee Osteoarthritis in 204 Countries and Territories, 1990–2019: Results From the Global Burden of Disease Study 2019

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