scholarly journals Data-driven identification of ageing-related diseases from electronic health records

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Valerie Kuan ◽  
Helen C. Fraser ◽  
Melanie Hingorani ◽  
Spiros Denaxas ◽  
Arturo Gonzalez-Izquierdo ◽  
...  

AbstractReducing the burden of late-life morbidity requires an understanding of the mechanisms of ageing-related diseases (ARDs), defined as diseases that accumulate with increasing age. This has been hampered by the lack of formal criteria to identify ARDs. Here, we present a framework to identify ARDs using two complementary methods consisting of unsupervised machine learning and actuarial techniques, which we applied to electronic health records (EHRs) from 3,009,048 individuals in England using primary care data from the Clinical Practice Research Datalink (CPRD) linked to the Hospital Episode Statistics admitted patient care dataset between 1 April 2010 and 31 March 2015 (mean age 49.7 years (s.d. 18.6), 51% female, 70% white ethnicity). We grouped 278 high-burden diseases into nine main clusters according to their patterns of disease onset, using a hierarchical agglomerative clustering algorithm. Four of these clusters, encompassing 207 diseases spanning diverse organ systems and clinical specialties, had rates of disease onset that clearly increased with chronological age. However, the ages of onset for these four clusters were strikingly different, with median age of onset 82 years (IQR 82–83) for Cluster 1, 77 years (IQR 75–77) for Cluster 2, 69 years (IQR 66–71) for Cluster 3 and 57 years (IQR 54–59) for Cluster 4. Fitting to ageing-related actuarial models confirmed that the vast majority of these 207 diseases had a high probability of being ageing-related. Cardiovascular diseases and cancers were highly represented, while benign neoplastic, skin and psychiatric conditions were largely absent from the four ageing-related clusters. Our framework identifies and clusters ARDs and can form the basis for fundamental and translational research into ageing pathways.

2018 ◽  
Vol 68 (suppl 1) ◽  
pp. bjgp18X696749 ◽  
Author(s):  
Maimoona Hashmi ◽  
Mark Wright ◽  
Kirin Sultana ◽  
Benjamin Barratt ◽  
Lia Chatzidiakou ◽  
...  

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.


2015 ◽  
Vol 100 (3) ◽  
pp. 214-219 ◽  
Author(s):  
Cornelia H M van Jaarsveld ◽  
Martin C Gulliford

ObjectiveThis study aimed to use primary care electronic health records to evaluate the prevalence of overweight and obesity in 2–15-year-old children in England and compare trends over the last two decades.DesignCohort study of primary care electronic health records.Setting375 general practices in England that contribute to the UK Clinical Practice Research Datalink.PatientsIndividual participants were sampled if they were aged between 2 and 15 years during the period 1994–2013 and had one or more records of body mass index (BMI).Main outcome measurePrevalence of overweight (including obesity) was defined as a BMI equal to or greater than the 85th centile of the 1990 UK reference population.ResultsData were analysed for 370 544 children with 507 483 BMI records. From 1994 to 2003, the odds of overweight and obesity increased by 8.1% per year (95% CI 7.2% to 8.9%) compared with 0.4% (−0.2% to 1.1%) from 2004 to 2013. Trends were similar for boys and girls, but differed by age groups, with prevalence stabilising in 2004 to 2013 in the younger (2–10 year) but not older (11–15 year) age group, where rates continued to increase.ConclusionsPrimary care electronic health records in England may provide a valuable resource for monitoring obesity trends. More than a third of UK children are overweight or obese, but the prevalence of overweight and obesity may have stabilised between 2004 and 2013.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
M. S. M. Persson ◽  
K. E. Harman ◽  
K. S. Thomas ◽  
J. R. Chalmers ◽  
Y. Vinogradova ◽  
...  

Abstract Background Trials of novel agents are required to improve the care of patients with rare diseases, but trial feasibility may be uncertain due to concerns over insufficient patient numbers. We aimed to determine the size of the pool of potential participants in England 2015–2017 for trials in the autoimmune blistering skin disease bullous pemphigoid. Methods The size of the pool of potential participants was estimated using routinely collected healthcare data from linked primary care (Clinical Practice Research Datalink; CPRD) and secondary care (Hospital Episode Statistics; HES) databases. Thirteen consultant dermatologists were surveyed to determine the likelihood that a patient would be eligible for a trial based on the presence of cautions or contra-indications to prednisolone use. These criteria were applied to determine how they influenced the potential pool of participants. Results Extrapolated to the population of England, we would expect approximately 10,800 (point estimate 10,747; 95% CI 7191 to 17,239) new cases of bullous pemphigoid to be identified in a three-year period. For a future trial involving oral prednisolone (standard care), the application of cautions to its use as exclusion criteria would result in approximately 365 potential participants unlikely to be recruited, a further 5332 could be recruited with caution, and 5104 in whom recruitment is still possible. 11–17% of potential participants may have pre-existing dementia and require an alternative consent process. Conclusions Routinely collected electronic health records can be used to inform the feasibility of clinical trials in rare diseases, such as whether recruitment is feasible nationally and how long recruitment might take to meet recruitment targets. Future trials of bullous pemphigoid in England may use the data presented to inform trial design, including eligibility criteria and consent processes for enrolling people with dementia.


BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e033013 ◽  
Author(s):  
Dana Šumilo ◽  
Krishnarajah Nirantharakumar ◽  
Brian H Willis ◽  
Gavin Rudge ◽  
James Martin ◽  
...  

IntroductionIn the UK, about a quarter of women give birth by caesarean section (CS) and are offered prophylactic broad-spectrum antibiotics to reduce the risk of maternal postpartum infection. In 2011, national guidance was changed from recommending antibiotics after the umbilical cord was cut to giving antibiotics prior to skin incision based on evidence that earlier administration reduces maternal infectious morbidity. Although antibiotics cross the placenta, there are no known short-term harms to the baby. This study aims to address the research gap on longer term impact of these antibiotics on child health.Methods and analysisA controlled interrupted time series study will use anonymised mother-baby linked routine electronic health records for children born during 2006–2018 recorded in UK primary care (The Health Improvement Network, THIN and Clinical Practice Research Datalink, CPRD) and secondary care (Hospital Episode Statistics, HES) databases. The primary outcomes of interest are asthma and eczema, two common allergy-related diseases in childhood. In-utero exposure to antibiotics immediately prior to CS will be compared with no exposure when given after cord clamping. The risk of outcomes in children delivered by CS will also be compared with a control cohort delivered vaginally to account for time effects. We will use all available data from THIN, CPRD and HES with estimated power of 80% and 90% to detect relative increase in risk of asthma of 16% and 18%, respectively at the 5% significance level.Ethics and disseminationEthical approval has been obtained from the University of Birmingham Ethical Review Committee with scientific approvals obtained from the independent scientific advisory committees from the Medicines and Healthcare products Regulatory Agency for CPRD and the data provider, IQVIA for THIN. The results will be published in peer-reviewed journals, presented at national and international conferences and disseminated to stakeholders.


2021 ◽  
Author(s):  
Halie M. Rando ◽  
Tellen D. Bennett ◽  
James Brian Byrd ◽  
Carolyn Bramante ◽  
Tiffany J. Callahan ◽  
...  

Since late 2019, the novel coronavirus SARS-CoV-2 has introduced a wide array of health challenges globally. In addition to a complex acute presentation that can affect multiple organ systems, increasing evidence points to long-term sequelae being common and impactful. As the worldwide scientific community forges ahead with efforts to characterize a wide range of outcomes associated with SARS-CoV-2 infection, the proliferation of available data has made it clear that formal definitions are needed in order to design robust and consistent studies of Long COVID that consistently capture variation in long-term outcomes. In the present study, we investigate the definitions used in the literature published to date and compare them against data available from electronic health records and patient-reported information collected via surveys. Long COVID holds the potential to produce a second public health crisis on the heels of the pandemic. Proactive efforts to identify the characteristics of this heterogeneous condition are imperative for a rigorous scientific effort to investigate and mitigate this threat.


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