Journal articles: 'Clinical Practice Research Datalink (CPRD)'

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Herrett, Emily, Arlene M. Gallagher, Krishnan Bhaskaran, Harriet Forbes, Rohini Mathur, Tjeerd van Staa, and Liam Smeeth. "Data Resource Profile: Clinical Practice Research Datalink (CPRD)." International Journal of Epidemiology 44, no. 3 (June 2015): 827–36. http://dx.doi.org/10.1093/ije/dyv098.

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Schmidt, James C. F., Paul C. Lambert, Clare L. Gillies, and Michael J. Sweeting. "Patterns of rates of mortality in the Clinical Practice Research Datalink." PLOS ONE 17, no. 8 (August 4, 2022): e0265709. http://dx.doi.org/10.1371/journal.pone.0265709.

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The Clinical Practice Research Datalink (CPRD) is a widely used data resource, representative in demographic profile, with accurate death recordings but it is unclear if mortality rates within CPRD GOLD are similar to rates in the general population. Rates may additionally be affected by selection bias caused by the requirement that a cohort have a minimum lookback window, i.e. observation time prior to start of at-risk follow-up. Standardised Mortality Ratios (SMRs) were calculated incorporating published population reference rates from the Office for National Statistics (ONS), using Poisson regression with rates in CPRD GOLD contrasted to ONS rates, stratified by age, calendar year and sex. An overall SMR was estimated along with SMRs presented for cohorts with different lookback windows (1, 2, 5, 10 years). SMRs were stratified by calendar year, length of follow-up and age group. Mortality rates in a random sample of 1 million CPRD GOLD patients were slightly lower than the national population [SMR = 0.980 95% confidence interval (CI) (0.973, 0.987)]. Cohorts with observational lookback had SMRs below one [1 year of lookback; SMR = 0.905 (0.898, 0.912), 2 years; SMR = 0.881 (0.874, 0.888), 5 years; SMR = 0.849 (0.841, 0.857), 10 years; SMR = 0.837 (0.827, 0.847)]. Mortality rates in the first two years after patient entry into CPRD were higher than the general population, while SMRs dropped below one thereafter. Mortality rates in CPRD, using simple entry requirements, are similar to rates seen in the English population. The requirement of at least a single year of lookback results in lower mortality rates compared to national estimates.

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Wolf, Achim, Daniel Dedman, Jennifer Campbell, Helen Booth, Darren Lunn, Jennifer Chapman, and Puja Myles. "Data resource profile: Clinical Practice Research Datalink (CPRD) Aurum." International Journal of Epidemiology 48, no. 6 (March 11, 2019): 1740–1740. http://dx.doi.org/10.1093/ije/dyz034.

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KOECHLIN, ALICE, PETER BOYLE, and PHILIPPE AUTIER. "Heterogeneity between Pharmacoepidemiological Studies Using the Clinical Practice Research Datalink (CPRD)." Diabetes 67, Supplement 1 (May 2018): 1507—P. http://dx.doi.org/10.2337/db18-1507-p.

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Nissen, Francis, Daniel R. Morales, Hana Mullerova, Liam Smeeth, Ian J. Douglas, and Jennifer K. Quint. "Validation of asthma recording in the Clinical Practice Research Datalink (CPRD)." BMJ Open 7, no. 8 (August 2017): e017474. http://dx.doi.org/10.1136/bmjopen-2017-017474.

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ObjectivesThe optimal method of identifying people with asthma from electronic health records in primary care is not known. The aim of this study is to determine the positive predictive value (PPV) of different algorithms using clinical codes and prescription data to identify people with asthma in the United Kingdom Clinical Practice Research Datalink (CPRD).Methods684 participants registered with a general practitioner (GP) practice contributing to CPRD between 1 December 2013 and 30 November 2015 were selected according to one of eight predefined potential asthma identification algorithms. A questionnaire was sent to the GPs to confirm asthma status and provide additional information to support an asthma diagnosis. Two study physicians independently reviewed and adjudicated the questionnaires and additional information to form a gold standard for asthma diagnosis. The PPV was calculated for each algorithm.Results684 questionnaires were sent, of which 494 (72%) were returned and 475 (69%) were complete and analysed. All five algorithms including a specific Read code indicating asthma or non-specific Read code accompanied by additional conditions performed well. The PPV for asthma diagnosis using only a specific asthma code was 86.4% (95% CI 77.4% to 95.4%). Extra information on asthma medication prescription (PPV 83.3%), evidence of reversibility testing (PPV 86.0%) or a combination of all three selection criteria (PPV 86.4%) did not result in a higher PPV. The algorithm using non-specific asthma codes, information on reversibility testing and respiratory medication use scored highest (PPV 90.7%, 95% CI (82.8% to 98.7%), but had a much lower identifiable population. Algorithms based on asthma symptom codes had low PPVs (43.1% to 57.8%)%).ConclusionsPeople with asthma can be accurately identified from UK primary care records using specific Read codes. The inclusion of spirometry or asthma medications in the algorithm did not clearly improve accuracy.Ethics and disseminationThe protocol for this research was approved by the Independent Scientific Advisory Committee (ISAC) for MHRA Database Research (protocol number15_257) and the approved protocol was made available to the journal and reviewers during peer review. Generic ethical approval for observational research using the CPRD with approval from ISAC has been granted by a Health Research Authority Research Ethics Committee (East Midlands—Derby, REC reference number 05/MRE04/87).The results will be submitted for publication and will be disseminated through research conferences and peer-reviewed journals.

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Sammon, Cormac J., Thomas P. Leahy, and Sreeram Ramagopalan. "Nonindependence of patient data in the clinical practice research datalink: a case study in atrial fibrillation patients." Journal of Comparative Effectiveness Research 9, no. 6 (April 2020): 395–403. http://dx.doi.org/10.2217/cer-2019-0191.

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Aim: The impact of different strategies to handle patients with data recorded under multiple Clinical Practice Research Datalink (CPRD) identifiers (IDs) is unknown. Patients and methods: Six approaches to handling patients appearing under multiple CPRD IDs were defined. The impact of the approaches was illustrated using a case study describing the clinical characteristics of a population of nonvalvular atrial fibrillation patients. Results: 5.6% of patients had more than one CPRD ID. Across all six approaches implemented, no material difference in the characteristics of nonvalvular atrial fibrillation patients were observed. Conclusion: While strategies which longitudinally append patient registration periods under different CPRD IDs maintain independence while using all available data, their implementation had little impact on the results of our case study.

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Rebordosa, Cristina, Estel Plana, Jaume Aguado, Steven Thomas, Esther García-Gil, Susana Perez‐Gutthann, and Jordi Castellsague. "GOLD assessment of COPD severity in the Clinical Practice Research Datalink (CPRD)." Pharmacoepidemiology and Drug Safety 28, no. 2 (May 8, 2018): 126–33. http://dx.doi.org/10.1002/pds.4448.

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Leite, Andreia, Sara L. Thomas, and Nick J. Andrews. "Implementing near real-time vaccine safety surveillance using the Clinical Practice Research Datalink (CPRD)." Vaccine 35, no. 49 (December 2017): 6885–92. http://dx.doi.org/10.1016/j.vaccine.2017.09.022.

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Gulliford, Martin C., Xiaohui Sun, Thamina Anjuman, Eleanor Yelland, and Tarita Murray-Thomas. "Comparison of antibiotic prescribing records in two UK primary care electronic health record systems: cohort study using CPRD GOLD and CPRD Aurum databases." BMJ Open 10, no. 6 (June 2020): e038767. http://dx.doi.org/10.1136/bmjopen-2020-038767.

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ObjectivesWe aimed to evaluate recording of antibiotic prescribing from two primary care electronic health record systems.DesignCohort study.SettingUK general practices contributing to the Clinical Practice Research Datalink (CPRD) databases: CPRD GOLD (Vision data) and CPRD Aurum (EMIS data). English CPRD GOLD general practices were analysed as a subgroup, as all CPRD Aurum practices were located in England.Participants158 305 patients were randomly sampled from CPRD Aurum and 160 394 from CPRD GOLD.Outcome measuresAntibiotic prescriptions in 2017 were identified. Age-standardised and sex-standardised antibiotic prescribing rates per 1000 person years were calculated. Prescribing of individual antibiotic products and associated medical diagnoses was evaluated.ResultsThere were 101 360 antibiotic prescriptions at 883 CPRD Aurum practices and 112 931 prescriptions at 290 CPRD GOLD practices, including 112 general practices in England. The age-standardised and sex-standardised antibiotic prescribing rate in 2017 was 512.6 (95% CI 510.4 to 514.9) per 1000 person years in CPRD Aurum and 584.3 (582.1 to 586.5) per 1000 person years in CPRD GOLD (505.2 (501.6 to 508.9) per 1000 person years if restricted to practices in England). The 25 most frequently prescribed antibiotic products were similar in both databases. One or more medical codes were recorded on the same date as an antibiotic prescription for 72 989 (74%) prescriptions in CPRD Aurum, 84 756 (78%) in CPRD GOLD and 28 471 (78%) for CPRD GOLD in England. Skin, respiratory and genitourinary tract infections were recorded for 39 035 (40%) prescriptions in CPRD Aurum, 41 326 (38%) in CPRD GOLD, with 15 481 (42%) in English CPRD GOLD practices only.ConclusionEstimates for antibiotic prescribing and infection recording were broadly similar in both databases suggesting similar recording across EMIS and Vision systems. Future research on antimicrobial stewardship can also be conducted using primary care data in CPRD Aurum.

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Booth, Helen, Eleanor Yelland, David Mullett, Arlene Gallagher, Shivani Padmanabhan, Stephen Welburn, Janet Valentine, and Puja Myles. "The Royal College of General Practitioners (RCGP) quality improvement initiative using Clinical Practice Research Datalink (CPRD) data: Lessons learned." British Journal of General Practice 69, suppl 1 (June 2019): bjgp19X703697. http://dx.doi.org/10.3399/bjgp19x703697.

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BackgroundQuality improvement (QI) is a priority for general practice, and GPs are expected to participate and provide evidence of QI activity. Pressures on the primary care workforce require approaches to QI to prioritise efficiency and effectiveness.AimThis project aimed generate and scale up bespoke QI reports for GP practices contributing data to CPRD.MethodCPRD is a UK government research service facilitating public health research using anonymised primary care data. A pilot report was designed with stakeholders and covered two indicators from the RCGP Patient Safety Toolkit. The reports enabled GPs to identify patients needing case review and to benchmark data on practice-level prescribing. Reports for 12 practices, containing real patient data, were sent to GPs and feedback was obtained via interviews. The report was scaled up to 457 practices and a survey sent out to request feedback.ResultsGPs used the reports to review the care of individual patients, and to implement QI actions such as adding flags to patients notes. One participant used the report as evidence for their annual appraisal. Survey response was limited (n = 31.7%) but overwhelmingly positive. Responders highlighted the importance of clinical input when developing indicators and ensuring the tone of the reports is supportive.ConclusionThe collaborative RCGP/CPRD QI reports are unique in their ability to provide benchmarking and case-finding on a national scale. The indicators selected must lead to actionable reports. Clinical input is required to ensure code lists are appropriate and that reports are clinically relevant. CPRD aims to send out two reports annually.

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McDonald, L., S. Ramagopalan, L. Burns, and R. Postema. "Identifying Patients With Lupus Nephritis in the United Kingdom (Uk) Clinical Practice Research Datalink (Cprd)." Value in Health 20, no. 9 (October 2017): A743. http://dx.doi.org/10.1016/j.jval.2017.08.2059.

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Quint, J. K., H. Mullerova, R. L. DiSantostefano, H. Forbes, S. Eaton, J. R. Hurst, K. Davis, and L. Smeeth. "Validation of chronic obstructive pulmonary disease recording in the Clinical Practice Research Datalink (CPRD-GOLD)." BMJ Open 4, no. 7 (July 23, 2014): e005540-e005540. http://dx.doi.org/10.1136/bmjopen-2014-005540.

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Nash, Anthony, and M. Zameel Cader. "Extraction of CPRD additional clinical data using R." F1000Research 9 (September 11, 2020): 1124. http://dx.doi.org/10.12688/f1000research.26228.1.

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The Clinical Practice Research Datalink is a nation-wide database of primary healthcare data records in England (UK) linked to several health services. A visit to a health practitioner can result in the digital storing of diagnostic and prescription therapeutic information. Access to patient primary care and linked service data depends on the research in mind; however, typically several flat files that describe patient interactions with a health practitioner are delivered. Some of these files will describe additional data such as the result of medical tests and patient lifestyles, denoted collectively into entity values. This data is used to supplement the medical notes recorded by a general practitioner. We have made available a set of R scripts that reads the clinical flat files, additional clinical flat files and entity values, and returns patient clinical data linked with the requested additional data. We have also included medcode descriptions associated with several entities along with instruction of how to extend the code for additional entities. The code is free to download under the MIT license: https://github.com/acnash/CPRD_Additional_Clinical

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Grimaldi-Bensouda, Lamiae, Olaf Klungel, Xavier Kurz, Mark C. H. de Groot, Ana S. Maciel Afonso, Marie L. de Bruin, Robert Reynolds, and Michel Rossignol. "Calcium channel blockers and cancer: a risk analysis using the UK Clinical Practice Research Datalink (CPRD)." BMJ Open 6, no. 1 (January 2016): e009147. http://dx.doi.org/10.1136/bmjopen-2015-009147.

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Aoki, Yasunori, Claudia S. Cabrera, Mario Ouwens, Krister Bamberg, Jenny Nyström, Itamar Raz, Benjamin M. Scirica, Bengt Hamrén, Peter J. Greasley, and Dinko Rekić. "Bilirubin levels and kidney function decline: An analysis of clinical trial and real world data." PLOS ONE 17, no. 6 (June 21, 2022): e0269970. http://dx.doi.org/10.1371/journal.pone.0269970.

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Objective To evaluate if previously found associations between low serum bilirubin concentration and kidney function decline is independent of hemoglobin and other key confounders. Research design and methods Clinical trial data from the SAVOR-TIMI 53 trial as well as the UK primary care electronic healthcare records, Clinical Practice Research Datalink (CPRD), were used to construct three cohorts of patients at risk of chronic kidney disease (CKD). The randomized clinical trial (RCT) cohort from the subset of SAVOR-TIMI 53 trial consisted of 10,555 type-2 diabetic patients with increased risk of cardiovascular disease. The two observational data cohorts from CPRD consisted of 71,104 newly diagnosed type-2 diabetes (CPRD-DM2) and 82,065 newly diagnosed hypertensive (CPRD-HT) patients without diabetes. Cohorts were stratified according to baseline circulating total bilirubin levels to determine association on the primary end point of a 30% reduction from baseline in estimated glomerular filtration rate (eGFR) and the secondary end point of albuminuria. Results The confounder adjusted hazard ratios of the subpopulation with lower than median bilirubin levels compared to above median bilirubin levels for the primary end point were 1.18 (1.02–1.37), 1.12 (1.05–1.19) and 1.09 (1.01–1.17), for the secondary end point were 1.26 (1.06–1.52), 1.11 (1.01–1.21) and 1.18 (1.01–1.39) for SAVOR-TIMI 53, CPRD-DM2, CPRD-HT, respectively. Conclusion Our findings are consistent across all cohorts and endpoints: lower serum bilirubin levels are associated with a greater kidney function decline independent of hemoglobin and other key confounders. This suggests that increased monitoring of kidney health in patients with lower bilirubin levels may be considered, especially for diabetic patients.

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Bhaskaran, Krishnan, Harriet J. Forbes, Ian Douglas, David A. Leon, and Liam Smeeth. "Representativeness and optimal use of body mass index (BMI) in the UK Clinical Practice Research Datalink (CPRD)." BMJ Open 3, no. 9 (September 2013): e003389. http://dx.doi.org/10.1136/bmjopen-2013-003389.

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Chaudhry, Zain, Fahmida Mannan, Angela Gibson-White, Usama Syed, Shirin Ahmed, Antonis Kousoulis, and Azeem Majeed. "Outputs and Growth of Primary Care Databases in the United Kingdom: Bibliometric Analysis." Journal of Innovation in Health Informatics 24, no. 3 (October 17, 2017): 284. http://dx.doi.org/10.14236/jhi.v24i3.942.

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Background: Electronic health database (EHD) data is increasingly used by researchers. The major United Kingdom EHDs are the ‘Clinical Practice Research Datalink’ (CPRD), ‘The Health Improvement Network’ (THIN) and ‘QResearch’. Over time, outputs from these databases have increased, but have not been evaluated.Objective: This study compares research outputs from CPRD, THIN and QResearch assessing growth and publication outputs over a 10-year period (2004-2013). CPRD was also reviewed separately over 20 years as a case study.Methods: Publications from CPRD and QResearch were extracted using the Science Citation Index (SCI) of the Thomson Scientific Institute for Scientific Information (Web of Science). THIN data was obtained from University College London and validated in Web of Science. All databases were analysed for growth in publications, the speciality areas and the journals in which their data have been published.Results: These databases collectively produced 1,296 publications over a ten-year period, with CPRD representing 63.6% (n=825 papers), THIN 30.4% (n=394) and QResearch 5.9% (n=77). Pharmacoepidemiology and General Medicine were the most common specialities featured. Over the 9-year period (2004-2013), publications for THIN and QResearch have slowly increased over time, whereas CPRD publications have increased substantially in last 4 years with almost 75% of CPRD publications published in the past 9 years.Conclusion: These databases are enhancing scientific research and are growing yearly, however display variability in their growth. They could become more powerful research tools if the National Health Service and general practitioners can provide accurate and comprehensive data for inclusion in these databases.

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Scheepers, Lieke E. J. M., Andrea M. Burden, Ilja C. W. Arts, Bart Spaetgens, Patrick Souverein, Frank de Vries, and Annelies Boonen. "Medication adherence among gout patients initiated allopurinol: a retrospective cohort study in the Clinical Practice Research Datalink (CPRD)." Rheumatology 57, no. 9 (June 8, 2018): 1641–50. http://dx.doi.org/10.1093/rheumatology/key155.

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Khan, Tanvir, Abtin Alvand, Daniel Prieto-Alhambra, David J. Culliford, Andrew Judge, William F. Jackson, Brigitte E. Scammell, Nigel K. Arden, and Andrew James Price. "ACL and meniscal injuries increase the risk of primary total knee replacement for osteoarthritis: a matched case–control study using the Clinical Practice Research Datalink (CPRD)." British Journal of Sports Medicine 53, no. 15 (January 13, 2018): 965–68. http://dx.doi.org/10.1136/bjsports-2017-097762.

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ObjectivesThe aim of this study was to investigate whether ACL injury (ACLi) or meniscal injury increases the risk of end-stage osteoarthritis (OA) resulting in total knee replacement (TKR).MethodsA matched case–control study of all TKRs performed in the UK between January 1990 and July 2011 and recorded in the Clinical Practice Research Datalink (CPRD) was undertaken. The CPRD contains longitudinal data on approximately 3.6 million patients. Two controls were selected for each case of TKR, matched on age, sex and general practitioner location as a proxy for socioeconomic status. Individuals with inflammatory arthritis were excluded. The odds of having TKR for individuals with a CPRD-recorded ACLi were compared with those without ACLi using conditional logistic regression, after adjustment for body mass index, previous knee fracture and meniscal injury. The adjusted odds of TKR in individuals with a recorded meniscal injury compared with those without were calculated.ResultsAfter exclusion of individuals with inflammatory arthritis, there were 49 723 in the case group and 104 353 controls. 153 (0.31%) cases had a history of ACLi compared with 41 (0.04%) controls. The adjusted OR of TKR after ACLi was 6.96 (95% CI 4.73 to 10.31). 4217 (8.48%) individuals in the TKR group had a recorded meniscal injury compared with 669 (0.64%) controls. The adjusted OR of TKR after meniscal injury was 15.24 (95% CI 13.88 to 16.69).ConclusionThis study demonstrates that ACLi is associated with a sevenfold increased odds of TKR resulting from OA. Meniscal injury is associated with a 15-fold increase odds of TKR for OA.

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Trafford, Alex M., Rosa Parisi, Martin K. Rutter, Evangelos Kontopantelis, Christopher E. M. Griffiths, and Darren M. Ashcroft. "Concordance and timing in recording cancer events in primary care, hospital and mortality records for patients with and without psoriasis: A population-based cohort study." PLOS ONE 16, no. 7 (July 19, 2021): e0254661. http://dx.doi.org/10.1371/journal.pone.0254661.

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Background The association between psoriasis and the risk of cancer has been investigated in numerous studies utilising electronic health records (EHRs), with conflicting results in the extent of the association. Objectives To assess concordance and timing of cancer recording between primary care, hospital and death registration data for people with and without psoriasis. Methods Cohort studies delineated using primary care EHRs from the Clinical Practice Research Datalink (CPRD) GOLD and Aurum databases, with linkage to hospital episode statistics (HES), Office for National Statistics (ONS) mortality data and indices of multiple deprivation (IMD). People with psoriasis were matched to those without psoriasis by age, sex and general practice. Cancer recording between databases was investigated by proportion concordant, that being the presence of cancer record in both source and comparator datasets. Delay in recording cancer diagnoses between CPRD and HES records and predictors of discordance were also assessed. Results 58,904 people with psoriasis and 350,592 comparison patients were included using CPRD GOLD; whereas 213,400 people with psoriasis and 1,268,998 comparison patients were included in CPRD Aurum. For all cancer records (excluding keratinocyte), concordance between CPRD and HES was greater than 80%. Concordance for same-site cancer records was markedly lower (<68% GOLD-linked data; <72% Aurum-linked data). Concordance of non-Hodgkin lymphoma and liver cancer recording between CPRD and HES was lower for people with psoriasis compared to those without. Conclusions Concordance between CPRD and HES is poor when restricted to cancers of the same site, with greater discordance in people with psoriasis for some cancers of specific sites. The use of linked patient-level data is an important step in reducing misclassification of cancer outcomes in epidemiological studies using routinely collected electronic health records.

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Pathak, Neha, Claire X. Zhang, Yamina Boukari, Rachel Burns, Rohini Mathur, Arturo Gonzalez-Izquierdo, Spiros Denaxas, Pam Sonnenberg, Andrew Hayward, and Robert W. Aldridge. "Development and Validation of a Primary Care Electronic Health Record Phenotype to Study Migration and Health in the UK." International Journal of Environmental Research and Public Health 18, no. 24 (December 17, 2021): 13304. http://dx.doi.org/10.3390/ijerph182413304.

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International migrants comprised 14% of the UK’s population in 2020; however, their health is rarely studied at a population level using primary care electronic health records due to difficulties in their identification. We developed a migration phenotype using country of birth, visa status, non-English main/first language and non-UK-origin codes and applied it to the Clinical Practice Research Datalink (CPRD) GOLD database of 16,071,111 primary care patients between 1997 and 2018. We compared the completeness and representativeness of the identified migrant population to Office for National Statistics (ONS) country-of-birth and 2011 census data by year, age, sex, geographic region of birth and ethnicity. Between 1997 to 2018, 403,768 migrants (2.51% of the CPRD GOLD population) were identified: 178,749 (1.11%) had foreign-country-of-birth or visa -status codes, 216,731 (1.35%) non-English-main/first-language codes, and 8288 (0.05%) non-UK-origin codes. The cohort was similarly distributed versus ONS data by sex and region of birth. Migration recording improved over time and younger migrants were better represented than those aged ≥50. The validated phenotype identified a large migrant cohort for use in migration health research in CPRD GOLD to inform healthcare policy and practice. The under-recording of migration status in earlier years and older ages necessitates cautious interpretation of future studies in these groups.

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Koshiaris, Constantinos, Ann Van den Bruel, Brian D. Nicholson, Sarah Lay-Flurrie, FD Richard Hobbs, and Jason L. Oke. "Clinical prediction tools to identify patients at highest risk of myeloma in primary care: a retrospective open cohort study." British Journal of General Practice 71, no. 706 (April 6, 2021): e347-e355. http://dx.doi.org/10.3399/bjgp.2020.0697.

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BackgroundPatients with myeloma experience substantial delays in their diagnosis, which can adversely affect their prognosis.AimTo generate a clinical prediction rule to identify primary care patients who are at highest risk of myeloma.Design and settingRetrospective open cohort study using electronic health records data from the UK’s Clinical Practice Research Datalink (CPRD) between 1 January 2000 and 1 January 2014.MethodPatients from the CPRD were included in the study if they were aged ≥40 years, had two full blood counts within a year, and had no previous diagnosis of myeloma. Cases of myeloma were identified in the following 2 years. Derivation and external validation datasets were created based on geographical region. Prediction equations were estimated using Cox proportional hazards models including patient characteristics, symptoms, and blood test results. Calibration, discrimination, and clinical utility were evaluated in the validation set.ResultsOf 1 281 926 eligible patients, 737 (0.06%) were diagnosed with myeloma within 2 years. Independent predictors of myeloma included: older age; male sex; back, chest and rib pain; nosebleeds; low haemoglobin, platelets, and white cell count; and raised mean corpuscular volume, calcium, and erythrocyte sedimentation rate. A model including symptoms and full blood count had an area under the curve of 0.84 (95% CI = 0.81 to 0.87) and sensitivity of 62% (95% CI = 55% to 68%) at the highest risk decile. The corresponding statistics for a second model, which also included calcium and inflammatory markers, were an area under the curve of 0.87 (95% CI = 0.84 to 0.90) and sensitivity of 72% (95% CI = 66% to 78%).ConclusionThe implementation of these prediction rules would highlight the possibility of myeloma in patients where GPs do not suspect myeloma. Future research should focus on the prospective evaluation of further external validity and the impact on clinical practice.

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Burkard, Theresa, Marlene Rauch, Susan S. Jick, and Christoph R. Meier. "Validity of bariatric surgery codes in the UK Clinical Practice Research Datalink ( CPRD ) GOLD compared with Hospital Episodes Statistics." Pharmacoepidemiology and Drug Safety 30, no. 7 (March 17, 2021): 858–67. http://dx.doi.org/10.1002/pds.5221.

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Swain, S., A. Sarmanova, C. Mallen, C. F. Kuo, C. Coupland, M. Doherty, and W. Zhang. "Trends in incidence and prevalence of osteoarthritis in the United Kingdom: findings from the Clinical Practice Research Datalink (CPRD)." Osteoarthritis and Cartilage 28, no. 6 (June 2020): 792–801. http://dx.doi.org/10.1016/j.joca.2020.03.004.

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Francis, Nick A., Kerenza Hood, Ronan Lyons, and Christopher C. Butler. "Understanding flucloxacillin prescribing trends and treatment non-response in UK primary care: a Clinical Practice Research Datalink (CPRD) study." Journal of Antimicrobial Chemotherapy 71, no. 7 (April 18, 2016): 2037–46. http://dx.doi.org/10.1093/jac/dkw084.

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Rodgers, Lauren R., Michael N. Weedon, William E. Henley, Andrew T. Hattersley, and Beverley M. Shields. "Cohort profile for the MASTERMIND study: using the Clinical Practice Research Datalink (CPRD) to investigate stratification of response to treatment in patients with type 2 diabetes." BMJ Open 7, no. 10 (October 2017): e017989. http://dx.doi.org/10.1136/bmjopen-2017-017989.

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PurposeThis is a retrospective cohort study using observational data from anonymised primary care records. We identify and extract all patients with type 2 diabetes and associated clinical data from the Clinical Practice Research Datalink (CPRD) to inform models of disease progression and stratification of treatment.ParticipantsData were extracted from CPRD on 8 August 2016. The initial data set contained all patients (n=313 485) in the database who had received a type 2 diabetes medication. Criteria were applied to identify and exclude those with type 1 diabetes, polycystic ovarian syndrome or other forms of diabetes (n=40 204), and for data quality control (n=12). We identified 251 338 patients for inclusion in future analyses of diabetes progression and treatment response.Findings to dateFor 6-month response to treatment, measured by change in glycated haemoglobin (HbA1c), we have 91 765 patients with 119 785 treatment response episodes. The greatest impact on reduction of HbA1c occurs with first-line and second-line treatments, metformin and sulfonylurea. Patients moving to third-line treatments tend to have greater weights and higher body mass index. We have investigated the impact of non-adherence to commonly used glucose-lowering medications on HbA1c. For baseline-adjusted HbA1c change over 1 year, non-adherent patients had lower HbA1c reductions than adherent patients, with mean and 95% CI of −4.4 (−4.7 to −4.0) mmol/mol (−0.40 (−0.43 to −0.37) %).Future plansFindings from studies using these data will help inform future treatment plans and guidelines. Additional data are added with updates from CPRD. This will increase the numbers of patients on newer medications and add more data on those already receiving treatment. There are several ongoing studies investigating different hypotheses regarding differential response to treatment and progression of diabetes. For side effects, links to Hospital Episode Statistics data, where severe events such as hypoglycaemia will be recorded, will also be explored.

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Persson, Monica S. M., Karen E. Harman, Yana Vinogradova, Sinead M. Langan, Julia Hippisley-Cox, Kim S. Thomas, and Sonia Gran. "Validation study of bullous pemphigoid and pemphigus vulgaris recording in routinely collected electronic primary healthcare records in England." BMJ Open 10, no. 7 (July 2020): e035934. http://dx.doi.org/10.1136/bmjopen-2019-035934.

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ObjectivesThe validity of bullous pemphigoid and pemphigus vulgaris recording in routinely collected healthcare data in the UK is unknown. We assessed the positive predictive value (PPV) for bullous pemphigoid and pemphigus vulgaris primary care Read codes in the Clinical Practice Research Datalink (CPRD) using linked inpatient data (Hospital Episode Statistics (HES)) as the diagnostic benchmark.SettingAdult participants with bullous pemphigoid or pemphigus vulgaris registered with HES-linked general practices in England between January 1998 and December 2017. Code-based algorithms were used to identify patients from the CPRD and extract their benchmark blistering disease diagnosis from HES.Primary outcome measureThe PPVs of Read codes for bullous pemphigoid and pemphigus vulgaris.ResultsOf 2468 incident cases of bullous pemphigoid and 431 of pemphigus vulgaris, 797 (32.3%) and 85 (19.7%) patients, respectively, had a hospitalisation record for a blistering disease. The PPV for bullous pemphigoid Read codes was 93.2% (95% CI 91.3% to 94.8%). Of the bullous pemphigoid cases, 3.0% had an HES diagnosis of pemphigus vulgaris and 3.8% of another blistering disease. The PPV for pemphigus vulgaris Read codes was 58.5% (95% CI 48.0% to 68.9%). Of the pemphigus vulgaris cases, 24.7% had an HES diagnosis of bullous pemphigoid and 16.5% of another blistering disease.ConclusionsThe CPRD can be used to study bullous pemphigoid, but recording of pemphigus vulgaris needs to improve in primary care.

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Downham, Christina, Elizabeth Visser, Mark Vickers, and Carl Counsell. "SEASON OF GLANDULAR FEVER AS A RISK FACTOR FOR MULTIPLE SCLEROSIS." Journal of Neurology, Neurosurgery & Psychiatry 86, no. 11 (October 14, 2015): e4.10-e4. http://dx.doi.org/10.1136/jnnp-2015-312379.107.

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BackgroundGlandular fever (GF) is a known risk factor for multiple sclerosis (MS) but it is unclear if the risk varies by season due to vitamin D-related variations in immune responses.MethodsPatients with MS diagnosed between 16–60 yrs were identified from the Clinical Practice Research Datalink (CPRD) along with up to six controls per case, matched by age, gender, general practice and duration of observation in CPRD prior to the date of diagnosis (index date). The numbers of patients and controls with a coded diagnosis of GF prior to the index date were identified and the date of GF diagnosis noted. Multivariable logistic regression analysed whether cases were more likely than controls to have GF in winter rather than summer, adjusted for age, gender and region.Results9247 cases (118 with GF) and 55033 controls (483 with GF) were included. GF was more common in MS cases than controls (odds ratio [OR] 1.77, 95% CI 1.53–2.05) but winter exposure was not associated with a higher risk of MS than summer (OR 1.09, 95% CI 0.72–1.66).ConclusionsGlandular fever in winter as opposed to summer does not appear to be associated with a greater risk of developing MS.

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Barry, Ciarrah-Jane, Christy Burden, Neil Davies, and Venexia Walker. "Pharmacoepidemiology in pregnancy: analysis protocol for an observational cohort study in the UK Clinical Practice Research Datalink." Wellcome Open Research 7 (January 12, 2022): 12. http://dx.doi.org/10.12688/wellcomeopenres.17523.1.

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Large numbers of women take prescription and over-the-counter medications during pregnancy. However, there is very little definitive evidence about the potential effects of these drugs on the mothers and offspring. We will investigate the risks and benefits of continuing prescriptive drug use for chronic pre-existing maternal conditions such as diabetes, hypertension and thyroid related conditions throughout pregnancy. If left untreated, these conditions are established risk factors for adverse neonatal and maternal outcomes. However, some treatments for these conditions are associated with adverse neonatal outcomes. Our primary aims are twofold. Firstly, we aim to estimate the beneficial effect on the mother of continuing treatment during pregnancy. Second, we aim to determine whether there is an associated detrimental impact on the neonate of continuation of maternal treatment during pregnancy. To establish this evidence, we will investigate the relationship between maternal drug prescriptions and adverse and beneficial offspring outcomes to provide evidence to guide clinical decisions. We will conduct a hypothesis testing observational intergenerational cohort study using data from the UK Clinical Practice Research Datalink (CPRD). We will apply four statistical methods: multivariable adjusted regression, propensity score regression, instrumental variables analysis and negative control analysis. These methods should account for potential confounding when estimating the association between the drug exposure and maternal or neonatal outcome. In this protocol we describe the aims, motivation, study design, cohort and statistical analyses of our study to aid reproducibility and transparency within research.

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Leite, Andreia, Nick J. Andrews, and Sara L. Thomas. "Assessing recording delays in general practice records to inform near real-time vaccine safety surveillance using the Clinical Practice Research Datalink (CPRD)." Pharmacoepidemiology and Drug Safety 26, no. 4 (February 3, 2017): 437–45. http://dx.doi.org/10.1002/pds.4173.

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Abrahami, Devin, Emily Gibson McDonald, Mireille Schnitzer, and Laurent Azoulay. "Trends in acid suppressant drug prescriptions in primary care in the UK: a population-based cross-sectional study." BMJ Open 10, no. 12 (December 2020): e041529. http://dx.doi.org/10.1136/bmjopen-2020-041529.

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ObjectiveTo examine proton pump inhibitor (PPI) and histamine-2 receptor antagonist (H2RA) prescribing patterns over a 29-year period by quantifying annual prevalence and prescribing intensity over time.DesignPopulation-based cross-sectional study.SettingMore than 700 general practices contributing data to the UK Clinical Practice Research Datalink (CPRD).ParticipantsWithin a cohort of 14 242 329 patients registered in the CPRD, 3 027 383 patients were prescribed at least one PPI or H2RA from 1 January 1990 to 31 December 2018.Primary and secondary outcome measuresAnnual prescription rates were estimated by dividing the number of patients prescribed a PPI or H2RA by the total CPRD population. Change in prescribing intensity (number of prescriptions per year divided by person-years of follow-up) was calculated using negative binomial regression.ResultsFrom 1990 to 2018, 21.3% of the CPRD population was exposed to at least one acid suppressant drug. During that period, PPI prevalence increased from 0.2% to 14.2%, while H2RA prevalence remained low (range: 1.2%–3.4%). Yearly prescribing intensity to PPIs increased during the first 15 years of the study period but remained relatively constant for the remainder of the study period. In contrast, yearly prescribing intensity of H2RAs decreased from 1990 to 2009 but has begun to slightly increase over the past 5 years.ConclusionsWhile PPI prevalence has been increasing over time, its prescribing intensity has recently plateaued. Notwithstanding their efficacy, PPIs are associated with a number of adverse effects not attributed to H2RAs, whose prescribing intensity has begun to increase. Thus, H2RAs remain a valuable treatment option for individuals with gastric conditions.

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Hashmi, Maimoona, Mark Wright, Kirin Sultana, Benjamin Barratt, Lia Chatzidiakou, Elizabeth Moore, Şefki Kolozali, et al. "Preliminary results from the COPE study using primary-care electronic health records and environmental modelling to examine COPD exacerbations." British Journal of General Practice 68, suppl 1 (June 2018): bjgp18X696749. http://dx.doi.org/10.3399/bjgp18x696749.

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BackgroundChronic Obstructive Airway Disease (COPD) is marked by often severely debilitating exacerbations. Efficient patient-centric research approaches are needed to better inform health management primary-care.AimThe ‘COPE study’ aims to develop a method of predicting COPD exacerbations utilising personal air quality sensors, environmental exposure modelling and electronic health records through the recruitment of patients from consenting GPs contributing to the Clinical Practice Research Datalink (CPRD).MethodThe study made use of Electronic Healthcare Records (EHR) from CPRD, an anonymised GP records database to screen and locate patients within GP practices in Central London. Personal air monitors were used to capture data on individual activities and environmental exposures. Output from the monitors were then linked with the EHR data to obtain information on COPD management, severity, comorbidities and exacerbations. Symptom changes not equating to full exacerbations were captured on diary cards. Linear regression was used to investigate the relationship between subject peak flow, symptoms, exacerbation events and exposure data.ResultsPreliminary results on the first 80 patients who have completed the study indicate variable susceptibility to environmental stressors in COPD patients. Some individuals appear highly susceptible to environmental stress and others appear to have unrelated triggers.ConclusionRecruiting patients through EHR for a study is feasible and allows easy collection of data for long term follow up. Portable environmental sensors could now be used to develop personalised models to predict risk of COPD exacerbations in susceptible individuals. Identification of direct links between participant health and activities would allow improved health management thus cost savings.

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Mitchell, Anneka, Tomas J. Welsh, Margaret C. Watson, Julia Snowball, and Anita McGrogan. "Use of oral anticoagulants in older people with atrial fibrillation in UK general practice: protocol for a cohort study using the Clinical Practice Research Datalink (CPRD) database." BMJ Open 9, no. 12 (December 2019): e032646. http://dx.doi.org/10.1136/bmjopen-2019-032646.

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IntroductionWarfarin has frequently been underused in older people for stroke prevention in atrial fibrillation (AF). Direct oral anticoagulants (DOACs) entered the UK market from 2008 and have been recommended as an alternative to warfarin. This study aimed to describe any changes in the prescribing of oral anticoagulants (OACs) to people aged ≥75 years in UK general practice before and after the introduction of DOACs, to examine differences in patient characteristics which may influence prescribers’ decisions regarding anticoagulation, to evaluate the time people stay on OACs and switching between OACs.Methods and analysisA retrospective cohort study design will be used. Patients with a diagnosis of AF will be identified from the Clinical Practice Research Datalink (CPRD). The study period will run from 1 January 2003 to 27 December 2017. Patients enter the cohort at the latest date of the start of the study period, first AF diagnosis, 75th birthday or a year from when they started to contribute research standard data. Follow-up continues until they leave the practice, death, the date the practice stops contributing research standard data or the end of the study period (27 December 2017). Exposure to OACs will be defined as ≥1 prescription issued for an OAC of interest during the study period. Patients issued an OAC in the year preceding study entry will be defined as ‘prevalent users’. Patients starting on an OAC during the study period will be defined as ‘incident users’. Incidence and prevalence of OAC prescribing, patient demographics and characteristics will be described during three time periods: 2003–2007, 2008–2012 and 2013–2017. Persistence (defined as the time from initiation to discontinuation of medication) with and switching between different OACs will be described.Ethics and disseminationThe protocol for this study was approved by the CPRD Independent Scientific Advisory Committee. The results will be disseminated in a peer-reviewed journal and at conferences.Trial registration numberEUPAS29923.

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de Arellano Serna, Antonio Ramirez, Matt Glover, Cormac Sammon, Tzu-Chun Kuo, Philip Spearpoint, and Peter Rutherford. "PP459 Healthcare Resource Utilisation Of Anti-Neutrophil Cytoplasmic Antibody Associated Vasculitis Patients: Real-World Data From English Clinical Practice Research Datalink." International Journal of Technology Assessment in Health Care 36, S1 (December 2020): 37. http://dx.doi.org/10.1017/s0266462320001804.

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IntroductionAnti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) is a rare, serious and often life-threatening disease. The use of available treatments options (immunosuppressants and glucocorticoids (GCs)) improves the prognosis of AAV greatly; however, GC use is associated with significant toxicity related morbidities and the management of AAV is costly. However, information of the costs associated with AAV in the United Kingdom is limited. This study aimed to quantify the burden of AAV using a large England and Wales source of real-world data, the Clinical Practice Research Datalink (CPRD) Hospital Episode Statistics (HES) linked database, to identify healthcare resource utilization and generate estimates of costs.MethodsIncident patients (n = 220) were included if ≥ eighteen years, with diagnosis read codes G754.00/G75A.00; ICD codes M31.3/M31.7 from January 1997 to December 2017. Costs were taken from Unit Costs of Social and Health Care, National Health Service reference costs and electronic drug tariff. Distinction was made between type of consultations, outpatient visits and inpatient admission based on Healthcare Resource Grouping. Costs were summarised as mean per member per year (PMPY) in 2016 prices and presented before and after diagnosis.ResultsIn the year preceding AAV diagnosis, mean costs PMPY were GBP12,012 [USD15,400], (GBP5,339 [USD6,845] inpatient, GBP766 [USD982] outpatient, GBP314 [USD403] GP, GBP5,594 [USD7,172] GP prescribing). In the year of AAV diagnosis (Y0) costs PMPY were GBP28,252 [USD36,220], GBP15,436 [USD19,790] inpatient, GBP1,863 [USD2,388] outpatient, GBP2,407 [USD3,086] GBP8,545 [USD10,956] GP prescribing). Costs in the years post-diagnosis remained higher than pre-diagnosis with a low of GBP22,839 [USD29,281] in Y4. The prescribing costs (GC, methotrexate and azathioprine) were the largest contributor in Y0-Y4 (GBP15,047 [USD19,291] Y1; GBP12,325 [USD15,801] Y4).ConclusionsDiagnosis of AAV is associated with increased healthcare costs, including higher inpatients costs in the year of diagnosis and subsequently higher prescribing costs in the community. Given the incidence (17.2 cases per million) and considering only costs in the year of diagnosis, an additional GBP15.6 million [USD24.6 million] of healthcare resource utilization occurs every year from new diagnoses of AAV. However, this will likely be underestimated due to the lack of secondary care prescribing data in CPRD-HES and prescribing of immunosuppressant treatments in this setting.

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Rockenschaub, Patrick, Vincent Nguyen, Robert W. Aldridge, Dionisio Acosta, Juan Miguel García-Gómez, and Carlos Sáez. "Data-driven discovery of changes in clinical code usage over time: a case-study on changes in cardiovascular disease recording in two English electronic health records databases (2001–2015)." BMJ Open 10, no. 2 (February 2020): e034396. http://dx.doi.org/10.1136/bmjopen-2019-034396.

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ObjectivesTo demonstrate how data-driven variability methods can be used to identify changes in disease recording in two English electronic health records databases between 2001 and 2015.DesignRepeated cross-sectional analysis that applied data-driven temporal variability methods to assess month-by-month changes in routinely collected medical data. A measure of difference between months was calculated based on joint distributions of age, gender, socioeconomic status and recorded cardiovascular diseases. Distances between months were used to identify temporal trends in data recording.Setting400 English primary care practices from the Clinical Practice Research Datalink (CPRD GOLD) and 451 hospital providers from the Hospital Episode Statistics (HES).Main outcomesThe proportion of patients (CPRD GOLD) and hospital admissions (HES) with a recorded cardiovascular disease (CPRD GOLD: coronary heart disease, heart failure, peripheral arterial disease, stroke; HES: International Classification of Disease codes I20-I69/G45).ResultsBoth databases showed gradual changes in cardiovascular disease recording between 2001 and 2008. The recorded prevalence of included cardiovascular diseases in CPRD GOLD increased by 47%–62%, which partially reversed after 2008. For hospital records in HES, there was a relative decrease in angina pectoris (−34.4%) and unspecified stroke (−42.3%) over the same time period, with a concomitant increase in chronic coronary heart disease (+14.3%). Multiple abrupt changes in the use of myocardial infarction codes in hospital were found in March/April 2010, 2012 and 2014, possibly linked to updates of clinical coding guidelines.ConclusionsIdentified temporal variability could be related to potentially non-medical causes such as updated coding guidelines. These artificial changes may introduce temporal correlation among diagnoses inferred from routine data, violating the assumptions of frequently used statistical methods. Temporal variability measures provide an objective and robust technique to identify, and subsequently account for, those changes in electronic health records studies without any prior knowledge of the data collection process.

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Hire, Adrian J., Darren M. Ashcroft, David A. Springate, and Douglas T. Steinke. "ADHD in the United Kingdom: Regional and Socioeconomic Variations in Incidence Rates Amongst Children and Adolescents (2004-2013)." Journal of Attention Disorders 22, no. 2 (November 23, 2015): 134–42. http://dx.doi.org/10.1177/1087054715613441.

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Objective: To describe the incidence and distribution of ADHD within the United Kingdom, and to examine whether there was any association between ADHD incidence and socioeconomic deprivation. Method: The study used data from the Clinical Practice Research Datalink (CPRD). Patients diagnosed with ADHD before the age of 19 between January 1, 2004 and December 31, 2013 were stratified according to the region in which their general practice was based. Practice Index of Multiple Deprivation (IMD) score was used as a surrogate measure of patients’ deprivation status. Results: ADHD incidence was relatively stable between 2004 and 2013, but peaked in the last 2 years studied. Statistically significant ( p ≤ .05) differences in incidence were observed between U.K. regions. In almost every year studied, incidence rates were highest among the most deprived patients and lowest among the least deprived patients. Conclusion: In the United Kingdom, ADHD may be associated with socioeconomic deprivation.

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Nadarajah, Ramesh, Jianhua Wu, Alejandro F. Frangi, David Hogg, Campbell Cowan, and Chris Gale. "Predicting patient-level new-onset atrial fibrillation from population-based nationwide electronic health records: protocol of FIND-AF for developing a precision medicine prediction model using artificial intelligence." BMJ Open 11, no. 11 (November 2021): e052887. http://dx.doi.org/10.1136/bmjopen-2021-052887.

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IntroductionAtrial fibrillation (AF) is a major cardiovascular health problem: it is common, chronic and incurs substantial healthcare expenditure because of stroke. Oral anticoagulation reduces the risk of thromboembolic stroke in those at higher risk; but for a number of patients, stroke is the first manifestation of undetected AF. There is a rationale for the early diagnosis of AF, before the first complication occurs, but population-based screening is not recommended. Previous prediction models have been limited by their data sources and methodologies. An accurate model that uses existing routinely collected data is needed to inform clinicians of patient-level risk of AF, inform national screening policy and highlight predictors that may be amenable to primary prevention.Methods and analysisWe will investigate the application of a range of deep learning techniques, including an adapted convolutional neural network, recurrent neural network and Transformer, on routinely collected primary care data to create a personalised model predicting the risk of new-onset AF over a range of time periods. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation, and the CPRD-AURUM dataset will be used for external geographical validation. Both comprise a sizeable representative population and are linked at patient-level to secondary care databases. The performance of the deep learning models will be compared against classic machine learning and traditional statistical predictive modelling methods. We will only use risk factors accessible in primary care and endow the model with the ability to update risk prediction as it is presented with new data, to make the model more useful in clinical practice.Ethics and disseminationPermissions for CPRD-GOLD and CPRD-AURUM datasets were obtained from CPRD (ref no: 19_076). The CPRD ethical approval committee approved the study. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences.Trial registration detailsA systematic review to incorporate within the overall project was registered on PROSPERO (registration number CRD42021245093). The study was registered on ClinicalTrials.gov (NCT04657900).

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van Bodegraven, Birgitta, Victoria Palin, Chirag Mistry, Matthew Sperrin, Andrew White, William Welfare, Darren M. Ashcroft, and Tjeerd Pieter van Staa. "Infection-related complications after common infection in association with new antibiotic prescribing in primary care: retrospective cohort study using linked electronic health records." BMJ Open 11, no. 1 (January 2021): e041218. http://dx.doi.org/10.1136/bmjopen-2020-041218.

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ObjectiveDetermine the association of incident antibiotic prescribing levels for common infections with infection-related complications and hospitalisations by comparing high with low prescribing general practitioner practices.Design retrospective cohort studyRetrospective cohort study.Data sourceUK primary care records from the Clinical Practice Research Datalink (CPRD GOLD) and SAIL Databank (SAIL) linked with Hospital Episode Statistics (HES) data, including 546 CPRD, 346 CPRD-HES and 338 SAIL-HES practices.ExposuresInitial general practice visit for one of six common infections and the proportion of antibiotic prescribing in each practice.Main outcome measuresIncidence of infection-related complications (as recorded in general practice) or infection-related hospital admission within 30 days after consultation for a common infection.ResultsA practice with 10.4% higher antibiotic prescribing (the IQR) was associated with a 5.7% lower rate of infection-related hospital admissions (adjusted analysis, 95% CI 3.3% to 8.0%). The association varied by infection with larger associations in hospital admissions with lower respiratory tract infection (16.1%; 95% CI 12.4% to 19.7%) and urinary tract infection (14.7%; 95% CI 7.6% to 21.1%) and smaller association in hospital admissions for upper respiratory tract infection (6.5%; 95% CI 3.5% to 9.5%) The association of antibiotic prescribing levels and hospital admission was largest in patients aged 18–39 years (8.6%; 95% CI 4.0% to 13.0%) and smallest in the elderly aged 75+ years (0.3%; 95% CI −3.4% to 3.9%).ConclusionsThere is an association between lower levels of practice level antibiotic prescribing and higher infection-related hospital admissions. Indiscriminately reducing antibiotic prescribing may lead to harm. Greater focus is needed to optimise antibiotic use by reducing inappropriate antibiotic prescribing and better targeting antibiotics to patients at high risk of infection-related complications.

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FLEMING, D. M., R. J. TAYLOR, F. HAGUINET, C. SCHUCK-PAIM, J. LOGIE, D. J. WEBB, R. L. LUSTIG, and G. MATIAS. "Influenza-attributable burden in United Kingdom primary care." Epidemiology and Infection 144, no. 3 (July 13, 2015): 537–47. http://dx.doi.org/10.1017/s0950268815001119.

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SUMMARYInfluenza is rarely laboratory-confirmed and the outpatient influenza burden is rarely studied due to a lack of suitable data. We used the Clinical Practice Research Datalink (CPRD) and surveillance data from Public Health England in a linear regression model to assess the number of persons consulting UK general practitioners (GP episodes) for respiratory illness, otitis media and antibiotic prescriptions attributable to influenza during 14 seasons, 1995–2009. In CPRD we ascertained influenza vaccination status in each season and risk status (conditions associated with severe influenza outcomes). Seasonal mean estimates of influenza-attributable GP episodes in the UK were 857 996 for respiratory disease including 68 777 for otitis media, with wide inter-seasonal variability. In an average season, 2·4%/0·5% of children aged <5 years and 1·3%/0·1% of seniors aged ⩾75 years had a GP episode for respiratory illness attributed to influenza A/B. Two-thirds of influenza-attributable GP episodes were estimated to result in prescription of antibiotics. These estimates are substantially greater than those derived from clinically reported influenza-like illness in surveillance programmes. Because health service costs of influenza are largely borne in general practice, these are important findings for cost-benefit assessment of influenza vaccination programmes.

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Kingswood, Christopher, Patrick Bolton, Pamela Crawford, Christopher Harland, Simon R. Johnson, Julian R. Sampson, Charles Shepherd, et al. "The clinical profile of tuberous sclerosis complex (TSC) in the United Kingdom: A retrospective cohort study in the Clinical Practice Research Datalink (CPRD)." European Journal of Paediatric Neurology 20, no. 2 (March 2016): 296–308. http://dx.doi.org/10.1016/j.ejpn.2015.11.011.

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Oshagbemi, Olorunfemi A., Frits M. E. Franssen, Suzanne van Kraaij, Dionne C. W. Braeken, Emiel F. M. Wouters, Anke H. Maitland-van der Zee, Johanna H. M. Driessen, and Frank de Vries. "Blood Eosinophil Counts, Withdrawal of Inhaled Corticosteroids and Risk of COPD Exacerbations and Mortality in the Clinical Practice Research Datalink (CPRD)." COPD: Journal of Chronic Obstructive Pulmonary Disease 16, no. 2 (March 4, 2019): 152–59. http://dx.doi.org/10.1080/15412555.2019.1608172.

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Hong, Jin-Liern, Ann Marie McNeill, Jinghua He, Yong Chen, and Kimberly G. Brodovicz. "Identification of impaired fasting glucose, healthcare utilization and progression to diabetes in the UK using the Clinical Practice Research Datalink (CPRD)." Pharmacoepidemiology and Drug Safety 25, no. 12 (May 19, 2016): 1375–86. http://dx.doi.org/10.1002/pds.4007.

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Weir, Sharada, Mihail Samnaliev, Tzu-Chun Kuo, Caitriona Ni Choitir, Travis S. Tierney, David Cumming, Julie Bruce, Andrea Manca, Rod S. Taylor, and Sam Eldabe. "The incidence and healthcare costs of persistent postoperative pain following lumbar spine surgery in the UK: a cohort study using the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics (HES)." BMJ Open 7, no. 9 (September 2017): e017585. http://dx.doi.org/10.1136/bmjopen-2017-017585.

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ObjectiveTo characterise incidence and healthcare costs associated with persistent postoperative pain (PPP) following lumbar surgery.DesignRetrospective, population-based cohort study.SettingClinical Practice Research Datalink (CPRD) and Hospital Episode Statistics (HES) databases.ParticipantsPopulation-based cohort of 10 216 adults who underwent lumbar surgery in England from 1997/1998 through 2011/2012 and had at least 1 year of presurgery data and 2 years of postoperative follow-up data in the linked CPRD–HES.Primary and secondary outcomes measuresIncidence and total healthcare costs over 2, 5 and 10 years attributable to persistent PPP following initial lumbar surgery.ResultsThe rate of individuals undergoing lumbar surgery in the CPRD–HES linked data doubled over the 15-year study period, fiscal years 1997/1998 to 2011/2012, from 2.5 to 4.9 per 10 000 adults. Over the most recent 5-year period (2007/2008 to 2011/2012), on average 20.8% (95% CI 19.7% to 21.9%) of lumbar surgery patients met criteria for PPP. Rates of healthcare usage were significantly higher for patients with PPP across all types of care. Over 2 years following initial spine surgery, the mean cost difference between patients with and without PPP was £5383 (95% CI £4872 to £5916). Over 5 and 10 years following initial spine surgery, the mean cost difference between patients with and without PPP increased to £10 195 (95% CI £8726 to £11 669) and £14 318 (95% CI £8386 to £19 771), respectively. Extrapolated to the UK population, we estimate that nearly 5000 adults experience PPP after spine surgery annually, with each new cohort costing the UK National Health Service in excess of £70 million over the first 10 years alone.ConclusionsPersistent pain affects more than one-in-five lumbar surgery patients and accounts for substantial long-term healthcare costs. There is a need for formal, evidence-based guidelines for a coherent, coordinated management strategy for patients with continuing pain after lumbar surgery.

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Wright, Alison K., Milton Fabian Suarez-Ortegon, Stephanie H. Read, Evangelos Kontopantelis, Iain Buchan, Richard Emsley, Naveed Sattar, Darren M. Ashcroft, Sarah H. Wild, and Martin K. Rutter. "Risk Factor Control and Cardiovascular Event Risk in People With Type 2 Diabetes in Primary and Secondary Prevention Settings." Circulation 142, no. 20 (November 17, 2020): 1925–36. http://dx.doi.org/10.1161/circulationaha.120.046783.

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Background: To examine the association between the degree of risk factor control and cardiovascular disease (CVD) risk in type 2 diabetes and to assess if the presence of cardio-renal disease modifies these relationships. Methods: A retrospective cohort study using data from English practices from CPRD GOLD (Clinical Practice Research Datalink) and the SCI-Diabetes dataset (Scottish Care Information-Diabetes), with linkage to hospital and mortality data. We identified 101 749 with type 2 diabetes (T2D) in CPRD matched with 378 938 controls without diabetes and 330 892 with type 2 diabetes in SCI-Diabetes between 2006 and 2015. The main exposure was number of optimized risk factors: nonsmoker, total cholesterol ≤4 mmol/L, triglycerides ≤1.7 mmol/L, glycated haemoglobin (HbA1c) ≤53 mmol/mol (≤7.0%), systolic blood pressure <140mm Hg, or <130 mm Hg if high risk. Cox models were used to assess cardiovascular risk associated with levels of risk factor control. Results: In CPRD, the mean baseline age in T2D was 63 years and 28% had cardio-renal disease (SCI-Diabetes: 62 years; 35% cardio-renal disease). Over 3 years follow-up (SCI-Diabetes: 6 years), CVD events occurred among 27 900 (27%) CPRD-T2D, 101 362 (31%) SCI-Diabetes-T2D, and 75 520 (19%) CPRD-controls. In CPRD, compared with controls, T2D participants with optimal risk factor control (all risk factors controlled) had a higher risk of CVD events (adjusted hazard ratio, 1.21; 95% confidence interval, 1.12–1.29). In T2D participants from CPRD and SCI-Diabetes, pooled hazard ratios for CVD associated with 5 risk factors being elevated versus optimal risk factor control were 1.09 (95% confidence interval, 1.01–1.17) in people with cardio-renal disease but 1.96 (95% confidence interval, 1.82–2.12) in people without cardio-renal disease. People without cardio-renal disease were younger and more likely to have suboptimal risk factor control but had fewer prescriptions for risk factor modifying medications than those with cardio-renal disease. Conclusions: Optimally managed people with T2D have a 21% higher CVD risk when compared with controls. People with T2D without cardio-renal disease would be predicted to benefit greatly from CVD risk factor intervention.

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Nissen, Francis, Daniel R. Morales, Hana Mullerova, Liam Smeeth, Ian J. Douglas, and Jennifer K. Quint. "Concomitant diagnosis of asthma and COPD: a quantitative study in UK primary care." British Journal of General Practice 68, no. 676 (September 24, 2018): e775-e782. http://dx.doi.org/10.3399/bjgp18x699389.

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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.

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Ferguson, Rachel, David Culliford, Daniel Prieto-Alhambra, Rafael Pinedo-Villanueva, Antonella Delmestri, Nigel Arden, and Catherine Bowen. "Encounters for foot and ankle pain in UK primary care: a population-based cohort study of CPRD data." British Journal of General Practice 69, no. 683 (May 20, 2019): e422-e429. http://dx.doi.org/10.3399/bjgp19x703817.

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BackgroundOlder patients who have foot pain report variation in access to services to manage their foot health. To plan services it is essential to understand the scale and burden of foot pain that exists for GPs.AimTo provide UK-wide population-level data of the frequency of foot and/or ankle pain encounters recorded in general practice.Design and settingPopulation-based cohort design study using data drawn from the UK Clinical Practice Research Datalink (CPRD) from January 2010 to December 2013.MethodAll CPRD data were collected prospectively by participating GPs. The primary outcome was prevalence of GP encounters for foot and/or ankle pain, stratified by age, sex, and different subgroups of causes.ResultsA foot and/or ankle pain encounter was recorded for 346 067 patients, and there was a total of 567 095 recorded encounters (mean per person 1.6, standard deviation [SD] 1.3). The prevalence of recorded encounters of foot and/or ankle pain was 2980 per 100 000 (3%). The number of patients with a recorded encounter of foot and/or ankle pain was 1820 per 100 000 (1.8%). Foot and/or ankle pain encounters were reported across all age groups (54.4% females), with those aged 71–80 years placing the greatest burden on GPs. The most common specified referrals were to orthopaedics (n = 36 881) and physiotherapy (n = 33 987), followed by podiatry (n = 25 980).ConclusionThe burden of foot and/or ankle pain encounters recorded by GPs is not insubstantial, and spans all ages, with a high proportion of referrals to orthopaedics. The authors recommend further exploration of ‘first-contact practitioners’ for foot and/or ankle pain in general practice to alleviate the burden on GPs.

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Evans, William, Ralph Kwame Akyea, Stephen Weng, Joe Kai, and Nadeem Qureshi. "Identifying Patients with Bicuspid Aortic Valve Disease in UK Primary Care: A Case–Control Study and Prediction Model." Journal of Personalized Medicine 12, no. 8 (August 5, 2022): 1290. http://dx.doi.org/10.3390/jpm12081290.

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Bicuspid aortic valve disease (BAV) is the most common congenital heart condition, and early detection can improve outcomes for patients. In this case–control study, patients with a diagnosis of BAV were identified from their electronic primary-care records in the UK’s Clinical Practice Research Datalink (CPRD). Each case was propensity-score matched to up to five controls. The clinical features recorded before diagnosis were compared. The proposed clinical features shown to be associated with BAV (p < 0.05) were incorporated into a multivariable regression model. We identified 2898 cases. The prevalence of BAV in the CPRD was 1 in 5181, significantly lower than expected, suggesting that diagnosis and/or recording could be improved. The following biologically plausible clinical features were associated with a subsequent diagnosis of BAV: palpitations (OR: 2.86 (95% CI: 1.60, 3.16)), atrial fibrillation (AF) (OR: 2.25 (95% CI: 1.60, 3.16)) and hypertension (OR: 1.72 (1.48, 2.00)). The best model had an AUC of 0.669 (95% CI: 0.658 to 0.680), a positive predictive value (PPV) of 5.9% (95% CI: 4.0% to 8.7%) and a negative predictive value (NPV) of 99% (95% CI: 99% to 99%) at a population prevalence of 1%. This study indicates that palpitations, hypertension and AF should trigger a clinical suspicion of BAV and assessment via echocardiography. It also demonstrates the potential to develop a prediction model for BAV to stratify patients for echocardiography screening.

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Ronaldson, Sarah J., Anan Raghunath, David J. Torgerson, and Tjeerd Van Staa. "Cost-effectiveness of antibiotics for COPD management: observational analysis using CPRD data." ERJ Open Research 3, no. 2 (April 2017): 00085–2016. http://dx.doi.org/10.1183/23120541.00085-2016.

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It is often difficult to determine the cause of chronic obstructive pulmonary disease (COPD) exacerbations, and antibiotics are frequently prescribed. This study conducted an observational cost-effectiveness analysis of prescribing antibiotics for exacerbations of COPD based on routinely collected data from patient electronic health records.A cohort of 45 375 patients aged 40 years or more who attended their general practice for a COPD exacerbation during 2000–2013 was identified from the Clinical Practice Research Datalink. Two groups were formed (“immediate antibiotics” or “no antibiotics”) based on whether antibiotics were prescribed during the index general practice (GP) consultation, with data analysed according to subsequent healthcare resource use. A cost-effectiveness analysis was undertaken from the perspective of the UK National Health Service, using a time horizon of 4 weeks in the base case.The use of antibiotics for COPD exacerbations resulted in cost savings and an improvement in all outcomes analysed; i.e. GP visits, hospitalisations, community respiratory team referrals, all referrals, infections and subsequent antibiotics prescriptions were lower for the antibiotics group. Hence, the use of antibiotics was dominant over no antibiotics.The economic analysis suggests that use of antibiotics for COPD exacerbations is a cost-effective alternative to not prescribing antibiotics for patients who present to their GP, and remains cost-effective when longer time horizons of 3 months and 12 months are considered. It would be useful for a definitive trial to be undertaken in this area to determine the cost-effectiveness of antibiotics for COPD exacerbations.

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Shepherd, Charles, Matthias Koepp, Melissa Myland, Keyur Patel, Cristiana Miglio, Vathani Siva, Elizabeth Gray, and Maureen Neary. "Understanding the health economic burden of patients with tuberous sclerosis complex (TSC) with epilepsy: a retrospective cohort study in the UK Clinical Practice Research Datalink (CPRD)." BMJ Open 7, no. 10 (October 2017): e015236. http://dx.doi.org/10.1136/bmjopen-2016-015236.

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IntroductionEpilepsy is highly prevalent in tuberous sclerosis complex (TSC), a multi-system genetic disorder. The clinical and economic burden of this condition is expected to be substantial due to treatment challenges, debilitating co-morbidities and the relationship between TSC-related manifestations. This study estimated healthcare resource utilisation (HCRU) and costs for patients with TSC with epilepsy (TSC+E) in the UK.MethodsPatients with TSC+E in the Clinical Practice Research Datalink (CPRD) linked to Hospital Episodes Statistics were identified from April 1997 to March 2012. Clinical data were extracted over the entire history, and costs were reported over the most recent 3-year period. HCRU was compared with a matched Comparator cohort, and the key cost drivers were identified by regression modelling.ResultsIn total, 209 patients with TSC+E were identified, of which 40% recorded ≥2 other primary organ system manifestations and 42% had learning disability. Treatment with ≥2 concomitant antiepileptic drugs (AEDs) was prevalent (60%), potentially suggesting refractory epilepsy. Notwithstanding, many patients with TSC+E (12%) had no record of AED use in their entire history, which may indicate undertreatment for these patients.Brain surgery was recorded in 12% of patients. Routine electroencephalography and MRI were infrequently performed (30% of patients), yet general practitioner visits, hospitalisations and outpatient visits were more frequent in patients with TSC+E than the Comparator. This translated to threefold higher clinical costs (£14 335 vs £4448), which significantly increased with each additional primary manifestation (p<0.0001).ConclusionsPatients with TSC+E have increased HCRU compared with the general CPRD population, likely related to manifestations in several organ systems, substantial cognitive impairment and severe epilepsy, which is challenging to treat and may be intractable. Disease surveillance and testing appears to be inadequate with few treatments trialled.Multidisciplinary care in TSC clinics with specialist neurologist input may alleviate some of the morbidity of patients, but more innovative treatment and management options should be sought.

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Nightingale, A. L., J. E. Davidson, C. T. Molta, H. J. Kan, and N. J. McHugh. "THU0414 The Incidence and Presentation of Systemic Lupus Erythematosus (SLE) in UK Primary Care Using the UK Clinical Practice Research Datalink (CPRD)." Annals of the Rheumatic Diseases 73, Suppl 2 (June 2014): 325.2–325. http://dx.doi.org/10.1136/annrheumdis-2014-eular.3573.

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Journal articles on the topic 'Clinical Practice Research Datalink (CPRD)'

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