scholarly journals Temporal relationship between osteoarthritis and comorbidities: a combined case control and cohort study in the UK primary care setting

Rheumatology ◽  
2021 ◽  
Author(s):  
Subhashisa Swain ◽  
Carol Coupland ◽  
Christian Mallen ◽  
Chang Fu Kuo ◽  
Aliya Sarmanova ◽  
...  
Keyword(s):  
Primary Care ◽  
Index Date ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
Developing Heart ◽  
Temporal Relationships ◽  
Hazard Ratios ◽  
Before And After ◽  
Irritable Bowel ◽  
The Uk

Abstract Objective To determine the burden of comorbidities in osteoarthritis (OA) and their temporal relationships in the UK. Methods The Clinical Practice Research Datalink (CPRD) GOLD was used to identify people with incident OA and age, gender and practice matched non-OA controls from UK primary care. Controls were assigned the same index date as matched cases (date of OA diagnosis). Associations between OA and 49 individual comorbidities and multimorbidity (≥2 comorbidities excluding OA) both before and after OA diagnosis were estimated, adjusting for covariates, using odds ratios (aOR) and hazard ratios (aHR) respectively. Results During 1997–2017, we identified 221 807 incident OA cases and 221 807 matched controls. Of 49 comorbidities examined, 38 were associated with OA both prior to, and following, the diagnosis of OA, and 2 (dementia and SLE) were associated with OA only following the diagnosis of OA. People with OA had higher risk of developing heart failure (aHR 1.63; 95% CI 1.56–1.71), dementia (aHR 1.62; 95% CI 1.56–1.68), liver diseases (aHR 1.51; 95% CI 1.37–1.67), irritable bowel syndrome (aHR 1.51; 95% CI 1.45–1.58), gastrointestinal bleeding (aHR 1.49; 95% CI 1.39–1.59), 10 musculoskeletal conditions and 25 other conditions following OA diagnosis. The aOR for multimorbidity prior to the index date was 1.71 (95% CI 1.69–1.74), whereas the aHR for multimorbidity after the index date was 1.29 (95% CI 1.28–1.30). Conclusions People with OA are more likely to have other chronic conditions both before and after the OA diagnosis. Further study on shared aetiology and causality of these associations is needed.

scholarly journals O16 Incidence, prevalence and associated comorbidity of axSpA within the UK: a retrospective database analysis

Rheumatology ◽  
2020 ◽  
Vol 59 (Supplement_2) ◽  
Author(s):  
Christopher L. I Morgan ◽  
Abigail White ◽  
Mark Tomlinson ◽  
Amie Scott ◽  
Haijun Tian
Keyword(s):  
Primary Care ◽  
Index Date ◽  
Practice Research ◽  
Care Practice ◽  
Clinical Practice Research Datalink ◽  
Case Ascertainment ◽  
International Statistical Classification ◽  
The Uk ◽  
Primary Care Practices ◽  
Incident Cases

Abstract Background This study reports the incidence and prevalence of axial spondyloarthritis (axSpA) in the UK, and describes the baseline characteristics and comorbidities associated with the condition. Methods This study was conducted using the Clinical Practice Research Datalink, a large routine primary care database in the UK. Approximately 60% of contributing English primary care practices are linked to Hospital Episode Statistics (HES) secondary care data. AxSpA and relevant comorbidities were identified from Read or International Statistical Classification of Diseases and Related Health Problems-10 codes in primary care or HES datasets, respectively. The date of first axSpA diagnosis defined the index date. Patients with ≥90 days between practice registration and first axSpA diagnosis were classified as incident cases. The incidence and prevalence of axSpA were calculated annually from 2003-2017 for the UK as a whole, each constituent nation and English practices linked to HES data, to maximise case ascertainment. Comorbidities occurring prior to the index date (inclusive) were reported and compared with non-axSpA patients matched for age, sex, primary care practice and concurrent practice registration. Results Overall, 20,199 axSpA patients were identified, of whom 8,387 (41.5%) were classified as incident cases. Of the incident cases, 2,600 (31.0%) were female. Mean age at first diagnosis was 45.5 years (standard deviation [SD]: 17.2), mean body mass index was 27.2 kg/m2 (SD: 5.9) and 2,481 (29.6%) patients were current smokers. In 2017, the incidence of axSpA was 8.0 per 100,000 person-years and the prevalence was 15.8 per 10,000 population, an increase from 12.7 per 10,000 population in 2003. For patients from English practices linked to HES data, the incidence was 10.8 per 100,000 person-years and the prevalence was 17.5 per 10,000 population. 8,385 (∼100.0%) axSpA patients could be matched to non-axSpA controls. At baseline, all selected comorbidities were significantly increased in axSpA cases vs controls (Table). Conclusion This study reports an increasing prevalence of axSpA over the study period and higher rates of specific comorbidities in patients with axSpA vs matched controls. Caveats related to routine database studies, including secular changes in case ascertainment and observation bias, should be considered when interpreting these results. Disclosures C.L.I. Morgan: Other; Employee of: Pharmatelligence. A. White: Shareholder/stock ownership; Novartis. Other; Employee of: Novartis. M. Tomlinson: Consultancies; Novartis. A. Scott: Consultancies; Novartis. H. Tian: Other; Employee of: Novartis.

scholarly journals OP0074 MULTIMORBIDITY CLUSTERS, DETERMINANTS AND TRAJECTORIES IN OSTEOARTHRITIS IN THE UK: FINDINGS FROM THE CLINICAL PRACTICE RESEARCH DATALINK

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 49.1-50
Author(s):  
S. Swain ◽  
C. Coupland ◽  
V. Strauss ◽  
C. Mallen ◽  
C. F. Kuo ◽  
...  
Keyword(s):  
Chronic Conditions ◽  
Index Date ◽  
Latent Class ◽  
Rapid Onset ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
Research Support ◽  
Gradual Onset ◽  
The Uk ◽  
Slow Onset

Background:Multimorbidity (≥2 chronic conditions) escalates the risk of adverse health outcomes. However, its burden in people with osteoarthritis (OA) remains largely unknown.Objectives:To identify the clusters of patients with multimorbidity and associated factors in OA and non-OA populations and to estimate the risk of developing multimorbidity clusters after the index date (after diagnosis).Methods:The study used the Clinical Practice Research Datalink – a primary care database from the UK. Firstly, age, sex and practice matched OA and non-OA people aged 20+ were identified to explore patterns and associations of clusters of multimorbidity within each group. Non-OA controls were assigned with same index date as that of matched OA cases. Secondly, multimorbidity trajectories for 20 years after the index date were examined in people without any comorbidities at baseline in both OA and non-OA groups. Latent class analysis was used to identify clusters and latent class growth modelling was used for cluster trajectories. The associations between clusters and age, sex, body mass index (BMI), alcohol use, smoking habits at baseline were quantified through multinomial logistic regression.Results:In total, 47 long-term conditions were studied in 443,822 people (OA- 221922; non-OA- 221900), with a mean age of 62 years (standard deviation ± 13 years), and 58% being women. The prevalence of multimorbidity was 76.6% and 68.9% in the OA and non-OA groups, respectively. In the OA group five clusters were identified including relatively healthy (18%), ‘cardiovascular (CVD) and musculoskeletal (MSK)’ (12.3%), metabolic syndrome (28.2%), ‘pain and psychological (9.1%), and ‘musculoskeletal’ (32.4%). The non-OA group had similar patterns except that the ‘pain+ psychological’ cluster was replaced by ‘thyroid and psychological’. (Figure 1) Among people with OA, ‘CVD+MSK’ and metabolic syndrome clusters were strongly associated with obesity with a relative risk ratio (RRR) of 2.04 (95% CI 1.95-2.13) and 2.10 (95% CI 2.03-2.17), respectively. Women had four times higher risk of being in the ‘pain+ psychological’ cluster than men when compared to the gender ratio in the healthy cluster, (RRR 4.28; 95% CI 4.09-4.48). In the non-OA group, obesity was significantly associated with all the clusters.Figure 1: Posterior probability distribution of chronic conditions across the clusters in Osteoarthritis (OA, n=221922) and Non-Osteoarthritis (Non-OA, n=221900) group. COPD- Chronic Obstructive Pulmonary Disease; CVD- Cardiovascular; MSK- MusculoskeletalOA (n=24139) and non-OA (n=24144) groups had five and four multimorbidity trajectory clusters, respectively. Among the OA population, 2.7% had rapid onset of multimorbidity, 9.5% had gradual onset and 11.6% had slow onset, whereas among the non-OA population, there was no rapid onset cluster, 4.6% had gradual onset and 14.3% had slow onset of multimorbidity. (Figure 2)Figure 2: Clusters of multimorbidity trajectories after index date in OA (n=24139) and Non-OA (n=24144)Conclusion:Distinct identified groups in OA and non-OA suggests further research for possible biological linkage within each cluster. The rapid onset of multimorbidity in OA should be considered for chronic disease management.Supported by:Acknowledgments:We would like to thank the University of Nottingham, UK, Beijing Joint Care Foundation, China and Foundation for Research in Rheumatology (FOREUM) for supporting the study.Disclosure of Interests:Subhashisa Swain: None declared, Carol Coupland: None declared, Victoria Strauss: None declared, Christian Mallen Grant/research support from: My department has received financial grants from BMS for a cardiology trial., Chang-Fu Kuo: None declared, Aliya Sarmanova: None declared, Michael Doherty Grant/research support from: AstraZeneca funded the Nottingham Sons of Gout study, Consultant of: Advisory borads on gout for Grunenthal and Mallinckrodt, Weiya Zhang Consultant of: Grunenthal for advice on gout management, Speakers bureau: Bioiberica as an invited speaker for EULAR 2016 satellite symposium

Risk of ischemic stroke in asymptomatic atrial fibrillation incidentally-detected in primary care compared with other clinical presentations

2021 ◽  
Author(s):  
Christopher Wallenhorst ◽  
Carlos Martinez ◽  
Ben FREEDMAN
Keyword(s):  
Atrial Fibrillation ◽  
Primary Care ◽  
Ischemic Stroke ◽  
Stroke Risk ◽  
Practice Research ◽  
Mortality Data ◽  
Clinical Practice Research Datalink ◽  
Primary Hospital ◽  
Ischemic Stroke Risk ◽  
The Uk

Background: It is uncertain whether stroke risk of asymptomatic ambulatory atrial fibrillation (AA-AF) incidentally-detected in primary care is comparable with other clinical AF presentations in primary care or hospital. Methods: The stoke risk of 22,035 patients with incident non-valvular AF from the UK primary care Clinical Practice Research Datalink with linkage to hospitalization and mortality data, was compared to 23,605 controls without AF (age and sex-matched 5:1 to 5,409 AA-AF patients). Incident AF included 5,913 with symptomatic ambulatory AF (SA-AF); 4,989 with Primary and 5,724 with non-Primary Hospital AF discharge diagnosis (PH-AF and Non-PH-AF); and 5,409 with AA-AF. Ischemic stroke adjusted subhazard ratios (aSHR) within 3 years of AA-AF were compared with SA-AF, PH-AF, Non-PH-AF and controls, accounting for mortality as competing risk and adjusted for ischemic stroke risk factors. Results: There were 1026 ischemic strokes in 49,544 person-years in patients with incident AF (crude incidence rate 2.1 ischemic strokes/100 person-years). Ischemic stroke aSHR over 3 years showed no differences between AA-AF, and SA-AF, PH-AF and nonPH-AF groups (aSHR 0.87-1.01 vs AA-AF). All AF groups showed a significantly higher aSHR compared to controls. (subhazard rate ratio 0.40 [0.34 - 0.47]. Conclusion: Ischemic stroke risk in patients with AA-AF incidentally-detected in primary care is far from benign, and not less than incident AF presenting clinically in general practice or hospital. This provides justification for identification of previously undetected AF, e.g. by opportunistic screening, and subsequent stroke prevention with thromboprophylaxis, to reduce the approximately 10% of ischemic strokes related to unrecognized AF.

scholarly journals Concomitant diagnosis of asthma and COPD: a quantitative study in UK primary care

2018 ◽  
Vol 68 (676) ◽  
pp. e775-e782 ◽  
Author(s):  
Francis Nissen ◽  
Daniel R Morales ◽  
Hana Mullerova ◽  
Liam Smeeth ◽  
Ian J Douglas ◽  
...  
Keyword(s):  
Primary Care ◽  
Practice Research ◽  
Chronic Obstructive ◽  
Clinical Practice Research Datalink ◽  
Read Code ◽  
Care Environment ◽  
Missed Opportunities ◽  
Obstructive Pulmonary Disease ◽  
Additional Information ◽  
The Uk

BackgroundAsthma and chronic obstructive pulmonary disease (COPD) share many characteristics and symptoms, and the differential diagnosis between the two diseases can be difficult in primary care. This study explored potential overlap between both diseases in a primary care environment.AimTo quantify how commonly patients with COPD have a concomitant diagnosis of asthma, and how commonly patients with asthma have a concomitant diagnosis of COPD in UK primary care. Additionally, the study aimed to determine the extent of possible misdiagnosis and missed opportunities for diagnosis.Design and settingPatients with validated asthma and patients with validated COPD in primary care were identified from the UK Clinical Practice Research Datalink (CPRD) in separate validation studies, and the diseases were confirmed by review of GP questionnaires.MethodThe prevalence of concurrent asthma and COPD in validated cases of either disease was examined based on CPRD coding, GP questionnaires, and requested additional information.ResultsIn total, 400 patients with COPD and 351 patients with asthma in primary care were identified. Of the patients with validated asthma, 15% (n = 52) had previously received a diagnostic COPD Read code, although COPD was only likely in 14.8% (95% confidence interval [CI] = 11.3 to 19.0) of patients with validated asthma. More than half (52.5%, n = 210) of patients with validated COPD had previously received a diagnostic asthma Read code. However, when considering additional evidence to support a diagnosis of asthma, concurrent asthma was only likely in 14.5% (95% CI = 11.2 to 18.3) of patients with validated COPD.ConclusionA concurrent asthma and COPD diagnosis appears to affect a relative minority of patients with COPD (14.5%) or asthma (14.8%). Asthma diagnosis may be over-recorded in people with COPD.

scholarly journals Drug therapy for alcohol dependence in primary care in the UK: A Clinical Practice Research Datalink study

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0173272 ◽  
Author(s):  
Andrew Thompson ◽  
Darren M. Ashcroft ◽  
Lynn Owens ◽  
Tjeerd P. van Staa ◽  
Munir Pirmohamed
Keyword(s):  
Primary Care ◽  
Clinical Practice ◽  
Drug Therapy ◽  
Alcohol Dependence ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
The Uk

scholarly journals Retrospective, multicohort analysis of the Clinical Practice Research Datalink (CPRD) to determine differences in the cost of medication wastage, dispensing fees and prescriber time of issuing either short (<60 days) or long (≥60 days) prescription lengths in primary care for common, chronic conditions in the UK

BMJ Open ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. e019382 ◽  
Author(s):  
Brett Doble ◽  
Rupert Payne ◽  
Amelia Harshfield ◽  
Edward C F Wilson
Keyword(s):  
Primary Care ◽  
Clinical Practice ◽  
Secondary Outcome ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
Lipid Management ◽  
Medication Wastage ◽  
The Uk ◽  
The Cost ◽  
Repeat Prescriptions

ObjectivesTo investigate patterns of early repeat prescriptions and treatment switching over an 11-year period to estimate differences in the cost of medication wastage, dispensing fees and prescriber time for short (<60 days) and long (≥60 days) prescription lengths from the perspective of the National Health Service in the UK.SettingRetrospective, multiple cohort study of primary care prescriptions from the Clinical Practice Research Datalink.ParticipantsFive random samples of 50 000 patients each prescribed oral drugs for (1) glucose control in type 2 diabetes mellitus (T2DM); (2) hypertension in T2DM; (3) statins (lipid management) in T2DM; (4) secondary prevention of myocardial infarction; and (5) depression.Primary and secondary outcome measuresThe volume of medication wastage from early repeat prescriptions and three other types of treatment switches was quantified and costed. Dispensing fees and prescriber time were also determined. Total unnecessary costs (TUC; cost of medication wastage, dispensing fees and prescriber time) associated with <60 day and ≥60 day prescriptions, standardised to a 120-day period, were then compared.ResultsLonger prescription lengths were associated with more medication waste per prescription. However, when including dispensing fees and prescriber time, longer prescription lengths resulted in lower TUC. This finding was consistent across all five cohorts. Savings ranged from £8.38 to £12.06 per prescription per 120 days if a single long prescription was issued instead of multiple short prescriptions. Prescriber time costs accounted for the largest component of TUC.ConclusionsShorter prescription lengths could potentially reduce medication wastage, but they may also increase dispensing fees and/or the time burden of issuing prescriptions.

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