@article{Gough2026,

title = {Within-individual variation of depression symptom measurement instruments in primary care: a retrospective cohort study},

author = {Alex Gough and Alice Sitch and Tom Marshall},

doi = {10.1016/j.jad.2026.121246},

issn = {01650327},

year  = {2026},

date = {2026-01-01},

journal = {Journal of Affective Disorders},

volume = {401},

pages = {121246},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{deDumast2026,

title = {Implications of incorporating morbidity into primary care workload models for NHS funding allocations: a retrospective observational study in England},

author = {Lyvia Dumast and Patrick Moore and Kym I E Snell and Tom Marshall},

doi = {10.1136/bmjopen-2025-114094},

issn = {2044-6055},

year  = {2026},

date = {2026-01-01},

journal = {BMJ Open},

volume = {16},

issue = {6},

pages = {e114094},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Yang2026,

title = {Characteristics, all-cause healthcare resource utilisation, and costs among high-risk adults with long COVID during Omicron predominance, 2022–2023: a retrospective cohort study using UK primary care data},

author = {Jingyan Yang and Kiran K. Rai and Hannah Gowman and Cale Harrison and David Gruben and Rebecca Butfield and Charlie Reynard and Rosie Hulme and Isabel Jimenez and Hannah R. Volkman and Jennifer L. Nguyen},

doi = {10.1186/s12913-026-14852-0},

issn = {1472-6963},

year  = {2026},

date = {2026-01-01},

journal = {BMC Health Services Research},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Singh2026,

title = {Autoimmune diseases and risk of adverse pregnancy outcomes: a population-based cohort study of five million pregnancies in the UK},

author = {Megha Singh and Anuradhaa Subramanian and Steven Wambua and Neil Cockburn and Stephanie J Hanley and Siang Ing Lee and Arturo Gonzalez-Izquierdo and Mairead Black and John A Reynolds and Francesca L Crowe and Krishnarajah Nirantharakumar},

doi = {10.1186/s12916-026-04921-w},

issn = {1741-7015},

year  = {2026},

date = {2026-01-01},

journal = {BMC Medicine},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hong2026,

title = {Imputation Free Deep Survival Prediction with Conditional Variational Autoencoders},

author = {Natalia Hong and Aditya Acharya and Krishna Gokhale and Jenny Cooper and Charles Gadd and Francesca Crowe and Krishnarajah Nirantharakumar and Christopher Yau},

doi = {10.1007/s41666-026-00234-y},

issn = {2509-4971},

year  = {2026},

date = {2026-01-01},

journal = {Journal of Healthcare Informatics Research},

volume = {10},

issue = {2},

pages = {275-298},

abstract = {<p>Electronic Health Records (EHRs) provide rich opportunities for developing risk prediction tools to support clinical decision-making, yet they are inherently incomplete because data are recorded selectively during routine care. Such missingness may be informative, reflecting clinical judgment and patient status, and missing data patterns can shift between model development and real-world deployment. These challenges limit the reliability and transportability of predictive models in healthcare settings. We propose an imputation-free framework that jointly trains Conditional Variational Autoencoders with deep survival models to enable risk prediction directly from incomplete EHR data. We demonstrate the approach using the deep survival model DeSurv and evaluate its performance through simulation studies and two retrospective cohorts from the Clinical Practice Research Datalink primary care database. The proposed framework consistently outperforms conventional missing data methods, achieving superior performance on ground-truth metrics in simulations and improved calibration-based survival metrics in real-world cohorts. It also demonstrates increased robustness to unseen missingness patterns and distributional shifts. By providing a unified strategy for handling missing data across development, validation, and deployment, this work advances methodological robustness in healthcare informatics and supports more reliable clinical risk prediction in practice.</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gadd2026,

title = {SurvivEHR: a competing risks, time-to-event foundation model for multiple long-term conditions from primary care electronic health records},

author = {Charles Gadd and Krishna Gokhale and Aditya Acharya and Jennifer Cooper and Francesca Crowe and Leah Fitzsimmons and Thomas Jackson and Krishnarajah Nirantharakumar and Christopher Yau and Rebecca Birch and Marco Canducci and Dominic Danks and Alexander d’Elia and Alastair Denniston and Sarah Flanagan and Suzy Gallier and Naijie Guan and Xin Guan and Imane Guellil and Georgios Gkoutos and Shamil Haroon and Eleanor Hathaway and Louise Jackson and Janet Lord and Zeinab Majid and Tom Marshall and George Morris and Charlotte Owen and Elizabeth Sapey and Chris Sainsbury and Charlotte Spurway and Peter Tino and Steven Wambua and Amaya Azcoaga-Lorenzo and Colin McCowan and Luciana Rocha Pedro and Muhammad Usman and Natalia Hong and Sara Matijevic and Kaspar Martens and Tim Williams and Puja Myles},

doi = {10.1038/s41746-026-02709-z},

issn = {2398-6352},

year  = {2026},

date = {2026-01-01},

journal = {npj Digital Medicine},

abstract = {<p>Multiple long-term conditions (MLTCs), or multimorbidity—the co-occurrence of multiple chronic conditions—present a growing challenge for primary care. Existing predictive models typically focus on single outcomes and often fail to capture the temporal and competing-risk structure inherent in longitudinal electronic health records (EHRs). Here, we present SurvivEHR, a generative transformer-based foundation model trained on over 7.6 billion coded events from 23 million patients in UK primary care. SurvivEHR is pre-trained using a competing-risk, time-to-next-event objective, enabling calibrated risk stratification across a broad range of diagnoses, investigations, medications, and mortality events. We show that this pre-training objective yields strong next-event discrimination and learns clinically meaningful patient trajectories. When adapted through fine-tuning, SurvivEHR achieves improved performance on downstream prognostic tasks, including longer-horizon risk prediction, with particular benefits in low-resource settings. By learning longitudinal patient representations directly from routine primary care records, SurvivEHR provides a scalable foundation for developing generalisable clinical risk models that reflect the complexity of MLTCs in primary care.</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Guan2026,

title = {Sickness absence in the working age population: a retrospective cohort study using primary care health record data},

author = {Naijie Guan and James Rockey and Tom Marshall and Eleanor Hathaway and Tracy Roberts and Francesca Crowe and Louise J. Jackson and Shamil Haroon},

doi = {10.1186/s12889-026-26296-6},

issn = {1471-2458},

year  = {2026},

date = {2026-01-01},

journal = {BMC Public Health},

volume = {26},

issue = {1},

pages = {829},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jordan2026,

title = {Prognostic score for predicting respiratory admissions among patients with chronic obstructive pulmonary disease in primary care: development and validation in population cohorts (Birmingham Lung Improvement Studies (BLISS))},

author = {Rachel E Jordan and Spencer J Keene and Frits M E Franssen and David Fitzmaurice and Nicola J Adderley and Andrew P Dickens and James T Martin and Alice J Sitch and Alexandra Enocson and Sue Jowett and Richard D Riley and Martin R Miller and Brendan G Cooper and Alice Turner and Kate Jolly and Jon G Ayres and Robert Stockley and Sheila Greenfield and Stanley Siebert and Amanda Daley and K K Cheng and Frank Vries and Emiel F M Wouters and Peymane Adab},

doi = {10.1136/bmj-2025-084521},

issn = {1756-1833},

year  = {2026},

date = {2026-01-01},

journal = {BMJ},

volume = {392},

pages = {e084521},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Finnikin2026,

title = {Cardiovascular Risk Estimation and Statin Adherence: A Historical Cohort Study},

author = {Samuel Finnikin and Brian Willis and Tim Evans and Brian Finney and Kwan Nok Chris Hui and Rani Khatib and Tom Marshall},

doi = {10.1177/0272989X261455267},

issn = {0272-989X},

year  = {2026},

date = {2026-01-01},

journal = {Medical Decision Making},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Finnikin2026c,

title = {Gout flares, serum urate and seasonality: a descriptive cohort study},

author = {Samuel Finnikin and Christian D. Mallen and Edward Roddy},

doi = {10.1007/s10067-025-07898-8},

issn = {0770-3198},

year  = {2026},

date = {2026-01-01},

journal = {Clinical Rheumatology},

volume = {45},

issue = {2},

pages = {1439-1448},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Phillips2026,

title = {Migraine, associated treatments and risk of miscarriage: A matched cohort study and nested case-control study using the CPRD pregnancy register},

author = {Katherine Phillips and Krishna Gokhale and Christine Damase-Michel and Helen Dolk and Catherine Nelson-Piercy and Benjamin R Wakerley and Francesca Crowe and Krishnarajah Nirantharakumar},

doi = {10.1177/03331024251414634},

issn = {0333-1024},

year  = {2026},

date = {2026-01-01},

journal = {Cephalalgia},

volume = {46},

issue = {1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gooden2026,

title = {The Risk of Suicide Attempts After Head Injury},

author = {Tiffany E. Gooden and Anuradhaa Subramanian and Jennifer Cooper and Krishnarajah Nirantharakumar and Nicola J Adderley and G. Neil Thomas},

doi = {10.1212/WNL.0000000000214474},

issn = {0028-3878},

year  = {2026},

date = {2026-01-01},

journal = {Neurology},

volume = {106},

issue = {2},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Dragoi2025,

title = {CAR T access and outcomes in large B‐cell lymphoma according to ethnicity and socioeconomic deprivation in the UK},

author = {Diana Dragoi and Samuel Cusworth and Laura Oldham and Robin Sanderson and Jane Norman and Joht Chandan and Amrith Mathew and Emil Kumar and Shankara Paneesha and Eleni Tholouli and Andres Moya Davila and Styliani Bouziana and Piers Patten and Prudence Hardefeldt and Deborah Yallop and Sridhar Chaganti and David Burns and Andrea Kuhnl},

doi = {10.1111/bjh.19997},

issn = {0007-1048},

year  = {2025},

date = {2025-01-01},

journal = {British Journal of Haematology},

abstract = {<p> Data on the impact of ethnic and socioeconomic factors on Chimeric antigen receptor (CAR) T‐cell therapy (access and outcomes are limited, but key to understand whether results from the registration trials are generalizable to real‐world patient populations. Here, we analysed ethnicity, socioeconomic deprivation and referral patterns in a cohort of 314 large B‐cell lymphoma patients approved for third‐line CD19 CAR‐T across three large UK CAR‐T centres. Patients from deprived areas had a lower infusion rate compared to low deprivation areas (73% vs. 86%, <italic>p</italic> = 0.04). CAR‐T response rates, toxicities, progression‐free survival or non‐relapse mortality were similar with respect to ethnicity or deprivation. We did not find evidence of referral barriers according to ethnicity, but potential regional barriers for socioeconomically deprived patients in two of three centres. Intention‐to‐treat overall survival was significantly inferior in patients from deprived areas (1‐year OS 44.5% vs. 58% for high vs. low deprivation; <italic>p</italic> = 0.02), likely reflecting general health disparities and higher drop‐out rates in this group. Our data suggest similar outcomes of CD19 CAR‐T‐treated patients across a socioeconomically and ethnically heterogeneous real‐world population. Results demonstrate broad access to CAR‐T within the UK national delivery system, but the high drop‐out rate and potential regional referral barriers for deprived communities should be further investigated. </p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Umar2025,

title = {Development and validation of a risk prediction tool for the diagnosis of inflammatory bowel disease in patients presenting in primary care with abdominal symptoms},

author = {Nosheen Umar and Steven Wambua and Phil Harvey and Samuel Cusworth and Krish Nirantharakumar and Shamil Haroon and Nigel Trudgill and Nicola J Adderley},

doi = {10.1093/ecco-jcc/jjaf044},

issn = {1873-9946},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Crohn's and Colitis},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Heppell2025,

title = {Comprehensive Update on Multiple Sclerosis-Associated Uveitis and New Epidemiological Insights from the United Kingdom},

author = {Cara Heppell and Anuradhaa Subramanian and Nicola J. Adderley and Krishnarajah Nirantharakumar and Alastair K. Denniston and Carlos Pavesio and Tasanee Braithwaite},

doi = {10.1080/09273948.2025.2491567},

issn = {0927-3948},

year  = {2025},

date = {2025-01-01},

journal = {Ocular Immunology and Inflammation},

pages = {1-13},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cooper2025,

title = {Defining phenotypes of disease severity for long-term cardiovascular, renal, metabolic, and mental health conditions in primary care electronic health records: A mixed-methods study using the nominal group technique},

author = {Jennifer Cooper and Thomas Jackson and Shamil Haroon and Francesca L. Crowe and Eleanor Hathaway and Leah Fitzsimmons and Krishnarajah Nirantharakumar},

doi = {10.1016/j.jbi.2025.104831},

issn = {15320464},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Biomedical Informatics},

volume = {166},

pages = {104831},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Minhas2025,

title = {Association between atopic disorders and mental ill health: a UK-based retrospective cohort study},

author = {Sonica Minhas and Joht Singh Chandan and Rebecca Knibb and Lavanya Diwakar and Nicola Adderley},

doi = {10.1136/bmjopen-2024-089181},

issn = {2044-6055},

year  = {2025},

date = {2025-01-01},

journal = {BMJ Open},

volume = {15},

issue = {5},

pages = {e089181},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Freer2025,

title = {Trends in prevalence of anaemia among people living with <scp>HIV</scp> in the <scp>UK</scp> : 20 cross‐sectional analyses using population‐based electronic primary healthcare records},

author = {George B. Freer and Jennifer Cooper and Krishnarajah Nirantharakumar and G. Neil Thomas and Tiffany E. Gooden},

doi = {10.1111/hiv.70044},

issn = {1464-2662},

year  = {2025},

date = {2025-01-01},

journal = {HIV Medicine},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Singh2025,

title = {Trends in the prevalence of autoimmune diseases during pregnancy in the UK, 2000–21: a retrospective cohort study},

author = {Megha Singh and Katherine Phillips and Jingya Wang and Anuradhaa Subramanian and Kelly-Ann Eastwood and Krishnarajah Nirantharakumar and Francesca L Crowe},

doi = {10.1016/S2665-9913(25)00039-6},

issn = {26659913},

year  = {2025},

date = {2025-01-01},

journal = {The Lancet Rheumatology},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jeyakumar2025,

title = {The epidemiology of hereditary spastic paraplegia and associated common mental health outcomes in England and Northern Ireland},

author = {Harini Jeyakumar and Joht Singh Chandan and Krishnarajah Nirantharakumar and Siang Ing Lee},

doi = {10.1186/s13023-025-03849-3},

issn = {1750-1172},

year  = {2025},

date = {2025-01-01},

journal = {Orphanet Journal of Rare Diseases},

volume = {20},

issue = {1},

pages = {326},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Diwakar2025,

title = {Prevalence trends and risk factors for allergic rhinoconjunctivitis, asthma and eczema in the UK.},

author = {Lavanya Diwakar and Anuradhaa Subramanian and Divya K Shah and Sumithra Subramaniam and Victoria S Pelly and Sheila Greenfield and David Moore and Krishnarajah Nirantharakumar},

doi = {10.1186/s13223-025-00975-2},

issn = {1710-1484},

year  = {2025},

date = {2025-01-01},

journal = {Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology},

volume = {21},

issue = {1},

pages = {31},

abstract = {BACKGROUND Allergic rhinoconjunctivitis (ARC), asthma and eczema carry a substantial morbidity. These conditions often co-exist within the same individual and their prevalence can differ based on age, ethnicity and gender. OBJECTIVES Using a UK primary care database, we estimated the trends in prevalence over the last decade for ARC, asthma and eczema and associated risk factors. METHODS Longitudinal cohort analysis of the health improvement (THIN) database between 1st Jan 2010 and 1st Jan 2019. Logistic regression analysis was used to explore risk factors for diagnosis of these conditions. RESULTS An average of 4.17 million records per year were analysed, 19.4% were children and 49.75% were male. There was an increase in prevalence of ARC, asthma and eczema amongst adults during the study period, whereas ARC and asthma prevalence amongst children has fallen. By 2018, 1:8 adults and 1:14 children had ARC; asthma was diagnosed in 1:7 adults and 1:10 children whereas eczema was diagnosed in 1:6 adults and 1:4 children respectively. There were regional discrepancies in allergy prevalence across the UK. Caucasians generally had the highest rates of asthma and lower rates of ARC compared with other ethnic groups. Having other allergies substantially increases the odds of having asthma, eczema and ARC. CONCLUSION The population burden of ARC, asthma and eczema in the UK is substantial. These conditions are often associated with other allergies and can, therefore, be complex to manage. These data support calls for improvement of pathways of care for allergy patients in the UK.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Erridge2025,

title = {Cannabis Use and Analgesic Prescribing in UK Primary Care: A Retrospective Cohort Study of Patients with Osteoarthritis},

author = {Simon Erridge and Joht Singh Chandan and Krishna M. Gokhale and Christian Billinghurst and Mikael H. Sodergren},

doi = {10.3390/medicines12040027},

issn = {2305-6320},

year  = {2025},

date = {2025-01-01},

journal = {Medicines},

volume = {12},

issue = {4},

pages = {27},

abstract = {<p>Objectives: This study aims to assess differences in analgesia prescribing in UK primary care between individuals with osteoarthritis who have a recorded exposure to cannabis use and those who do not. Methods: This population-based retrospective cohort study included opioid-naïve patients with osteoarthritis (aged 25–85 years) who were active in Clinical Practice Research Datalink Aurum between 1 January 1995 and 15 December 2023. Patients with osteoarthritis who had current or historic cannabis use recorded were matched to two unexposed individuals by age, sex, smoking status, and health authority. Patients were followed up to assess prescriptions of analgesia. Cox regression was performed adjusted for age, sex, and ethnicity. Results: 662 exposed patients were matched to 1319 unexposed patients. Cannabis-exposed individuals were more likely to be prescribed opioids (adjusted hazard ratio (HR): 2.06; 95% confidence interval (CI): 1.74–2.43; p < 0.001), gabapentinoids (HR: 3.31; 95% CI: 2.34–4.67; p < 0.001), non-steroidal anti-inflammatory drugs (HR: 1.99; 95% CI: 1.72–2.31; p < 0.001), tricyclic antidepressants (HR: 2.64; 95% CI: 2.03–3.44; p < 0.001), other antidepressants (HR: 7.22; 95% CI: 5.24–9.94; p < 0.001), and paracetamol (HR: 3.30; 95% CI: 2.43–4.48; p < 0.001). Conclusions: This study suggests there is an association between coded exposure to cannabis in UK primary care records and increased prescribing of analgesia. Given the relative scarcity of recorded cannabis use relative to its prevalence in the general population, these findings must be interpreted cautiously. The increased hazard of using analgesia and mortality within the cannabis-exposed cohort may be confounded by socioeconomic status and a higher likelihood of coding cannabis use in those experiencing adverse effects after consumption or cannabis misuse disorder.</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Makhdom2025,

title = {Obstructive Sleep Apnoea and Risk of Fragility Fracture in Patients With Type 2 Diabetes: A Population‐Based Retrospective Cohort Study},

author = {Esraa A. Makhdom and Anuradhaa Subramanian and Krishnarajah Nirantharakumar and Nicola J. Adderley and Abd A. Tahrani},

doi = {10.1002/edm2.70100},

issn = {2398-9238},

year  = {2025},

date = {2025-01-01},

journal = {Endocrinology, Diabetes & Metabolism},

volume = {8},

issue = {6},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pickard-Michels2025,

title = {Association between mental health disorders and asthma exacerbations in adults: a retrospective cohort study in UK primary care},

author = {Tris Pickard-Michels and Nicola J Adderley and Prasad Nagakumar and Nikita Simms-Williams and Alice Sitch and Rasiah Thayakaran and Dhanusha Punyadasa and Krishnarajah Nirantharakumar and Shamil Haroon},

doi = {10.1136/bmjresp-2025-003244},

issn = {2052-4439},

year  = {2025},

date = {2025-01-01},

journal = {BMJ Open Respiratory Research},

volume = {12},

issue = {1},

pages = {e003244},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gough2025,

title = {Within-individual variation of HbA1c measurements in primary care: A retrospective cohort study},

author = {Alex Gough and Tom Marshall and Alice Sitch},

doi = {10.1371/journal.pone.0333438},

issn = {1932-6203},

year  = {2025},

date = {2025-01-01},

journal = {PLOS One},

volume = {20},

issue = {10},

pages = {e0333438},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wang2025,

title = {Estimating inequality in alcohol-related liver disease burden in the UK, 2009 to 2020: a population-based study using routinely collected data},

author = {Zhaonan Wang and Krishnarajah Nirantharakumar and Arlene Copland and Darren Quelch and Rasiah Thayakaran and Joht Singh Chandan and James Ferguson and Matthew Brookes and Matthew Lewis and Neil Rajoriya and Nigel Trudgill and Ramesh Arasaradnam and Sally Bradberry and Shamil Haroon and Neeraj Bhala and Nicola J Adderley},

doi = {10.1016/j.lanprc.2025.100002},

issn = {30505143},

year  = {2025},

date = {2025-01-01},

journal = {The Lancet Primary Care},

pages = {100002},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Umar2024,

title = {The Time to Inflammatory Bowel Disease Diagnosis for Patients Presenting with Abdominal Symptoms in Primary Care and its Association with Emergency Hospital Admissions and Surgery: A Retrospective Cohort Study},

author = {Nosheen Umar and Phil Harvey and Nicola J Adderley and Shamil Haroon and Nigel Trudgill},

doi = {10.1093/ibd/izae057},

issn = {1078-0998},

year  = {2024},

date = {2024-01-01},

journal = {Inflammatory Bowel Diseases},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gokhale2024,

title = {Using Repeated Measurements to Predict Cardiovascular Risk in Patients With Type 2 Diabetes Mellitus},

author = {Krishna M Gokhale and Joht Singh Chandan and Chris Sainsbury and Peter Tino and Abd Tahrani and Konstantinos Toulis and Krishnarajah Nirantharakumar},

doi = {10.1016/j.amjcard.2023.10.008},

issn = {00029149},

year  = {2024},

date = {2024-01-01},

journal = {The American Journal of Cardiology},

volume = {210},

pages = {133-142},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tan2024,

title = {Socioeconomic Deprivation and the Risk of Sight-Threatening Diabetic Retinopathy (STDR): A Population-Based Cohort Study in the U.K.},

author = {Luyuan Tan and Jingya Wang and Jieun Han and Christopher Sainsbury and Alastair K. Denniston and Francesca L. Crowe and Konstantinos A. Toulis and Muhammad Ali Karamat and Mi Yao and Krishnarajah Nirantharakumar},

doi = {10.2337/dc23-1626},

issn = {0149-5992},

year  = {2024},

date = {2024-01-01},

journal = {Diabetes Care},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Han2024,

title = {Association of sildenafil use with age-related macular degeneration: a retrospective cohort study},

author = {Ji Eun Diana Han and Anuradhaa Subramanian and Wen Hwa Lee and Jesse Coker and Alastair K Denniston and Krishnarajah Nirantharakumar and Nicola Jaime Adderley},

doi = {10.1136/bmjophth-2023-001525},

issn = {2397-3269},

year  = {2024},

date = {2024-01-01},

journal = {BMJ Open Ophthalmology},

volume = {9},

issue = {1},

pages = {e001525},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dElia2024,

title = {Prodromal symptoms of rheumatoid arthritis in a primary care database: variation by ethnicity and socioeconomic status},

author = {Alexander d’Elia and Aliaksandra Baranskaya and Shamil Haroon and Ben Hammond and Nicola J Adderley and Krishnarajah Nirantharakumar and Joht Singh Chandan and Marie Falahee and Karim Raza},

url = {https://academic.oup.com/rheumatology/advance-article/doi/10.1093/rheumatology/keae157/7625566},

doi = {10.1093/rheumatology/keae157},

issn = {1462-0324},

year  = {2024},

date = {2024-01-01},

journal = {Rheumatology},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Phillips2024,

title = {Trends in the prevalence and pharmacological management of migraine during pregnancy in the UK, 2000–2018},

author = {Katherine Phillips and Krishnarajah Nirantharakumar and Benjamin R Wakerley and Francesca L Crowe},

doi = {10.1136/jnnp-2024-333530},

issn = {0022-3050},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Neurology, Neurosurgery & Psychiatry},

pages = {jnnp-2024-333530},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{deDumast2024,

title = {Trends in clinical workload in UK primary care 2005-2019},

author = {Lyvia Dumast and Patrick Moore and Kym Snell and Tom Marshall},

doi = {10.3399/BJGP.2023.0527},

issn = {0960-1643},

year  = {2024},

date = {2024-01-01},

journal = {British Journal of General Practice},

pages = {BJGP.2023.0527},

abstract = {<p>Background: Substantial increases in UK consulting rates, mean consultation duration and clinical workload were observed between 2007 and 2014. No analysis of more recent trends in clinical workload has been published to date. This study updates and builds on previous research, identifying underlying changes in population morbidity levels affecting demand for primary health care. Aim: To describe the changes in clinical workload in UK primary care since 2005. Design and setting: Retrospective cohort study. Method: Over 500 million anonymised electronic health records were obtained from IQVIA Medical Research Data to examine consulting rates with GPs and practice nurses together with the duration of these consultations to determine total patient-level workload per person-year. Results: Age-standardised mean GP direct (face-to-face and telephone) consulting rates fell steadily by 2.0% a year from 2014 to 2019. Between 2005 and 2019 mean GP direct consulting rates fell by 5.8% overall whereas mean workload per person-year increased by 25.8%, due in part to a 36.9% increase in mean consultation duration. Indirect GP workload almost tripled over the fifteen years, contributing to a 48.3% increase in overall clinical workload per person-year. The proportion of the study population with two or more serious chronic conditions increased from 22.5% to 31.6%, accounting for almost 55.0% of total clinical workload in 2019. Conclusion: Findings show sustained increases in consulting rates, consultation duration and clinical workload until 2014. From 2015, however, rising demand for healthcare and a larger administrative workload have led to capacity constraints as the system nears saturation.</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mobley2024,

title = {Thromboembolic events and vascular dementia in patients with atrial fibrillation and low apparent stroke risk},

author = {Alastair R. Mobley and Anuradhaa Subramanian and Asgher Champsi and Xiaoxia Wang and Puja Myles and Paul McGreavy and Karina V. Bunting and David Shukla and Krishnarajah Nirantharakumar and Dipak Kotecha},

doi = {10.1038/s41591-024-03049-9},

issn = {1078-8956},

year  = {2024},

date = {2024-01-01},

journal = {Nature Medicine},

abstract = {<p> The prevention of thromboembolism in atrial fibrillation (AF) is typically restricted to patients with specific risk factors and ignores outcomes such as vascular dementia. This population-based cohort study used electronic healthcare records from 5,199,994 primary care patients (UK; 2005–2020). A total of 290,525 (5.6%) had a diagnosis of AF and were aged 40–75 years, of which 36,340 had no history of stroke, a low perceived risk of stroke based on clinical risk factors and no oral anticoagulant prescription. Matching was performed for age, sex and region to 117,298 controls without AF. During 5 years median follow-up (831,005 person-years), incident stroke occurred in 3.8% with AF versus 1.5% control (adjusted hazard ratio (HR) 2.06, 95% confidence interval (CI) 1.91–2.21; <italic>P</italic> < 0.001), arterial thromboembolism 0.3% versus 0.1% (HR 2.39, 95% CI 1.83–3.11; <italic>P</italic> < 0.001), and all-cause mortality 8.9% versus 5.0% (HR 1.44, 95% CI 1.38–1.50; <italic>P</italic> < 0.001). AF was associated with all-cause dementia (HR 1.17, 95% CI 1.04–1.32; <italic>P</italic> = 0.010), driven by vascular dementia (HR 1.68, 95% CI 1.33–2.12; <italic>P</italic> < 0.001) rather than Alzheimer’s disease (HR 0.85, 95% CI 0.70–1.03; <italic>P</italic> = 0.09). Death and thromboembolic outcomes, including vascular dementia, are substantially increased in patients with AF despite a lack of conventional stroke risk factors. </p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cockburn2024b,

title = {Automating incidence and prevalence analysis in open cohorts},

author = {Neil Cockburn and Ben Hammond and Illin Gani and Samuel Cusworth and Aditya Acharya and Krishna Gokhale and Rasiah Thayakaran and Francesca Crowe and Sonica Minhas and William Parry Smith and Beck Taylor and Krishnarajah Nirantharakumar and Joht Singh Chandan},

doi = {10.1186/s12874-024-02266-7},

issn = {1471-2288},

year  = {2024},

date = {2024-01-01},

journal = {BMC Medical Research Methodology},

volume = {24},

issue = {1},

pages = {144},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Champsi2024,

title = {Gender and contemporary risk of adverse events in atrial fibrillation},

author = {Asgher Champsi and Alastair R Mobley and Anuradhaa Subramanian and Krishnarajah Nirantharakumar and Xiaoxia Wang and David Shukla and Karina V Bunting and Inge Molgaard and Jeremy Dwight and Ruben Casado Arroyo and Harry J G M Crijns and Luigina Guasti and Maddalena Lettino and R Thomas Lumbers and Bart Maesen and Michiel Rienstra and Emma Svennberg and Otilia Țica and Vassil Traykov and Stylianos Tzeis and Isabelle Gelder and Dipak Kotecha},

doi = {10.1093/eurheartj/ehae539},

issn = {0195-668X},

year  = {2024},

date = {2024-01-01},

journal = {European Heart Journal},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wang2024b,

title = {Pharmacologic Treatments for Dementia and the Risk of Developing Age-Related Macular Degeneration},

author = {Jingya Wang and Christina Antza and Wen Hwa Lee and Jesse Coker and Pearse A. Keane and Alastair K. Denniston and Krishnarajah Nirantharakumar and Nicola J. Adderley},

doi = {10.1001/jamanetworkopen.2024.41166},

issn = {2574-3805},

year  = {2024},

date = {2024-01-01},

journal = {JAMA Network Open},

volume = {7},

issue = {10},

pages = {e2441166},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Snook2024,

title = {The risk of immune-mediated inflammatory diseases following exposure to childhood maltreatment: A retrospective cohort study using UK primary care data},

author = {Liam Snook and Sonica Minhas and Vrinda Nadda and Ben Hammond and Krishna M. Gokhale and Julie Taylor and Caroline Bradbury-Jones and Siddhartha Bandyopadhyay and Krishnarajah Nirantharakumar and Nicola J. Adderley and Joht Singh Chandan},

doi = {10.1016/j.heliyon.2024.e40493},

issn = {24058440},

year  = {2024},

date = {2024-01-01},

journal = {Heliyon},

volume = {10},

issue = {22},

pages = {e40493},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cockburn2024,

title = {Inequalities in the diagnosis of 275 chronic conditions in UK primary care between 2006 and 2021: a cohort study},

author = {Neil Cockburn and Samuel Cusworth and Aditya Acharya and Ben Hammond and Illin Gani and Rasiah Thayakaran and Krishna Gokhale and Bhiramah Rammanohar and Joht Singh Chandan},

doi = {10.1016/S0140-6736(24)02020-8},

issn = {01406736},

year  = {2024},

date = {2024-01-01},

journal = {The Lancet},

volume = {404},

pages = {S40},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wang2024,

title = {Obstructive sleep apnoea syndrome and future risk of dementia among individuals managed in UK general practice},

author = {Jingya Wang and Anuradhaa Subramanian and Neil Cockburn and Jingyi Xiao and Krishnarajah Nirantharakumar and Shamil Haroon},

doi = {10.1136/thorax-2024-221810},

issn = {0040-6376},

year  = {2024},

date = {2024-01-01},

journal = {Thorax},

pages = {thorax-2024-221810},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Simms-Williams2024,

title = {Risk factors for asthma-related hospital and intensive care admissions in children, adolescents and adults: a cohort study using primary and secondary care data},

author = {Nikita Simms-Williams and Prasad Nagakumar and Rasiah Thayakaran and Nicola J Adderley and Richard Hotham and Adel H Mansur and Krishnarajah Nirantharakumar and Shamil Haroon},

doi = {10.1136/bmjresp-2023-001746},

issn = {2052-4439},

year  = {2024},

date = {2024-01-01},

journal = {BMJ Open Respiratory Research},

volume = {11},

issue = {1},

pages = {e001746},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Shah2023,

title = {Long Covid symptoms and diagnosis in primary care: A cohort study using structured and unstructured data in The Health Improvement Network primary care database.},

author = {Anoop D Shah and Anuradhaa Subramanian and Jadene Lewis and Samir Dhalla and Elizabeth Ford and Shamil Haroon and Valerie Kuan and Krishnarajah Nirantharakumar},

doi = {10.1371/journal.pone.0290583},

issn = {1932-6203 (Electronic)},

year  = {2023},

date = {2023-01-01},

journal = {PloS one},

volume = {18},

issue = {9},

pages = {e0290583},

abstract = {BACKGROUND: Long Covid is a widely recognised consequence of COVID-19 infection, but little is known about the burden of symptoms that patients present with in primary care, as these are typically recorded only in free text clinical notes. AIMS: To compare symptoms in patients with and without a history of COVID-19, and investigate symptoms associated with a Long Covid diagnosis. METHODS: We used primary care electronic health record data until the end of December 2020 from The Health Improvement Network (THIN), a Cegedim database. We included adults registered with participating practices in England, Scotland or Wales. We extracted information about 89 symptoms and 'Long Covid' diagnoses from free text using natural language processing. We calculated hazard ratios (adjusted for age, sex, baseline medical conditions and prior symptoms) for each symptom from 12 weeks after the COVID-19 diagnosis. RESULTS: We compared 11,015 patients with confirmed COVID-19 and 18,098 unexposed controls. Only 20% of symptom records were coded, with 80% in free text. A wide range of symptoms were associated with COVID-19 at least 12 weeks post-infection, with strongest associations for fatigue (adjusted hazard ratio (aHR) 3.46, 95% confidence interval (CI) 2.87, 4.17), shortness of breath (aHR 2.89, 95% CI 2.48, 3.36), palpitations (aHR 2.59, 95% CI 1.86, 3.60), and phlegm (aHR 2.43, 95% CI 1.65, 3.59). However, a limited subset of symptoms were recorded within 7 days prior to a Long Covid diagnosis in more than 20% of cases: shortness of breath, chest pain, pain, fatigue, cough, and anxiety / depression. CONCLUSIONS: Numerous symptoms are reported to primary care at least 12 weeks after COVID-19 infection, but only a subset are commonly associated with a GP diagnosis of Long Covid.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Azcoaga-Lorenzo2023,

title = {Maternal multimorbidity and preterm birth in Scotland: an observational record-linkage study.},

author = {Amaya Azcoaga-Lorenzo and Adeniyi Francis Fagbamigbe and Utkarsh Agrawal and Mairead Black and Muhammad Usman and Siang Ing Lee and Kelly-Ann Eastwood and Ngawai Moss and Rachel Plachcinski and Catherine Nelson-Piercy and Sinead Brophy and Dermot O'Reilly and Krishnarajah Nirantharakumar and Colin McCowan},

doi = {10.1186/s12916-023-03058-4},

issn = {1741-7015 (Electronic)},

year  = {2023},

date = {2023-01-01},

journal = {BMC medicine},

volume = {21},

issue = {1},

pages = {352},

institution = {MuM-PreDiCT Group},

abstract = {BACKGROUND: Multimorbidity is common in women across the life course. Preterm birth is the single biggest cause of neonatal mortality and morbidity. We aim to estimate the prevalence of multimorbidity in pregnant women and to examine the association between maternal multimorbidity and PTB. METHODS: This is a retrospective cohort study using electronic health records from the Scottish Morbidity Records. All pregnancies among women aged 15 to 49 with a conception date between 1 January 2014 and 31 December 2018 were included. Multimorbidity was defined as the presence of two or more pre-existing long-term physical or mental health conditions, and complex multimorbidity as the presence of four or more. It was calculated at the time of conception using a predefined list of 79 conditions published by the MuM-PreDiCT consortium. PTB was defined as babies born alive between 24 and less than 37 completed weeks of gestation. We used Generalised Estimating Equations adjusted for maternal age, socioeconomic status, number of previous pregnancies, BMI, and smoking history to estimate the effect of maternal pre-existing multimorbidity. Absolut rates are reported in the results and tables, whilst Odds Ratios (ORs) are adjusted (aOR). RESULTS: Thirty thousand five hundred fifty-seven singleton births from 27,711 pregnant women were included in the analysis. The prevalence of pre-existing multimorbidity and complex multimorbidity was 16.8% (95% CI: 16.4-17.2) and 3.6% (95% CI: 3.3-3.8), respectively. The prevalence of multimorbidity in the youngest age group was 10.2%(95% CI: 8.8-11.6), while in those 40 to 44, it was 21.4% (95% CI: 18.4-24.4), and in the 45 to 49 age group, it was 20% (95% CI: 8.9-31.1). In women without multimorbidity, the prevalence of PTB was 6.7%; it was 11.6% in women with multimorbidity and 15.6% in women with complex multimorbidity. After adjusting for maternal age, socioeconomic status, number of previous pregnancies, Body Mass Index (BMI), and smoking, multimorbidity was associated with higher odds of PTB (aOR = 1.64, 95% CI: 1.48-1.82). CONCLUSIONS: Multimorbidity at the time of conception was present in one in six women and was associated with an increased risk of preterm birth. Multimorbidity presents a significant health burden to women and their offspring. Routine and comprehensive evaluation of women with multimorbidity before and during pregnancy is urgently needed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Syed2023,

title = {Incidence of immune-mediated inflammatory diseases following COVID-19: a matched cohort study in UK primary care.},

author = {Umer Syed and Anuradhaa Subramanian and David C Wraith and Janet M Lord and Kirsty McGee and Krishna Ghokale and Krishnarajah Nirantharakumar and Shamil Haroon},

doi = {10.1186/s12916-023-03049-5},

issn = {1741-7015 (Electronic)},

year  = {2023},

date = {2023-01-01},

journal = {BMC medicine},

volume = {21},

issue = {1},

pages = {363},

abstract = {BACKGROUND: Some patients infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) go on to experience post-COVID-19 condition or long COVID. Preliminary findings have given rise to the theory that long COVID may be due in part to a deranged immune response. In this study, we assess whether there is an association between SARS-CoV-2 infection and the incidence of immune-mediated inflammatory diseases (IMIDs). METHODS: Matched cohort study using primary care electronic health record data from the Clinical Practice Research Datalink Aurum database. The exposed cohort included 458,147 adults aged 18 years and older with a confirmed SARS-CoV-2 infection and no prior diagnosis of IMIDs. They were matched on age, sex, and general practice to 1,818,929 adults with no diagnosis of confirmed or suspected SARS-CoV-2 infection. The primary outcome was a composite of any of the following IMIDs: autoimmune thyroiditis, coeliac disease, inflammatory bowel disease (IBD), myasthenia gravis, pernicious anaemia, psoriasis, rheumatoid arthritis (RA), Sjogren's syndrome, systemic lupus erythematosus (SLE), type 1 diabetes mellitus (T1DM), and vitiligo. The secondary outcomes were each of these conditions separately. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for the primary and secondary outcomes, adjusting for age, sex, ethnic group, smoking status, body mass index, relevant infections, and medications. RESULTS: Six hundred and nighty six (0.15%) and 2230 (0.12%) patients in the exposed and unexposed cohort developed an IMID during the follow-up period over 0.29 person-years, giving a crude incidence rate of 4.59 and 3.65 per 1000 person-years, respectively. Patients in the exposed cohort had a 22% increased risk of developing an IMID, compared to the unexposed cohort (aHR 1.22, 95% CI 1.12 to 1.33). The incidence of three IMIDs was significantly associated with SARS-CoV-2 infection. These were T1DM (aHR 1.56, 1.09 to 2.23), IBD (aHR 1.36, 1.18 to 1.56), and psoriasis (1.23, 1.05 to 1.42). CONCLUSIONS: SARS-CoV-2 was associated with an increased incidence of IMIDs including T1DM, IBD and psoriasis. However, these findings could be potentially due to ascertainment bias. Further research is needed to replicate these findings in other populations and to measure autoantibody profiles in cohorts of individuals with COVID-19.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Haider2023,

title = {Diabetic retinopathy progression in patients under monitoring for treatment or vision loss: external validation and update of a multivariable prediction model.},

author = {Sajjad Haider and Nicola Adderley and Mohammad O Tallouzi and Salman Naveed Sadiq and David H Steel and Randhir Chavan and Ijaz Sheikh and Krishnarajah Nirantharakumar and Kym I E Snell},

doi = {10.1136/bmjopen-2023-073015},

issn = {2044-6055 (Electronic)},

year  = {2023},

date = {2023-01-01},

journal = {BMJ open},

volume = {13},

issue = {4},

pages = {e073015},

abstract = {INTRODUCTION: The number of people with diabetes mellitus is increasing globally and consequently so too is diabetic retinopathy (DR). Most patients with diabetes are monitored through the diabetic eye screening programme (DESP) until they have signs of retinopathy and these changes progress, requiring referral into hospital eye services (HES). Here, they continue to be monitored until they require treatment. Due to current pressures on HES, delays can occur, leading to harm. There is a need to triage patients based on their individual risk. At present, patients are stratified according to retinopathy stage alone, yet other risk factors like glycated haemoglobin (HbA1c) may be useful. Therefore, a prediction model that combines multiple prognostic factors to predict progression will be useful for triage in this setting to improve care.We previously developed a Diabetic Retinopathy Progression model to Treatment or Vision Loss (DRPTVL-UK) using a large primary care database. The aim of the present study is to externally validate the DRPTVL-UK model in a secondary care setting, specifically in a population under care by HES. This study will also provide an opportunity to update the model by considering additional predictors not previously available. METHODS AND ANALYSIS: We will use a retrospective cohort of 2400 patients with diabetes aged 12 years and over, referred from DESP to the NHS hospital trusts with referable DR between 2013 and 2016, with follow-up information recorded until December 2021.We will evaluate the external validity of the DRPTVL-UK model using measures of discrimination, calibration and net benefit. In addition, consensus meetings will be held to agree on acceptable risk thresholds for triage within the HES system. ETHICS AND DISSEMINATION: This study was approved by REC (ref 22/SC/0425, 05/12/2022, Hampshire A Research Ethics Committee). The results of the study will be published in a peer-reviewed journal, presented at clinical conferences. TRIAL REGISTRATION NUMBER: ISRCTN 10956293.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Phillips2023,

title = {Inequalities in the management of diabetic kidney disease in UK primary care: A cross-sectional analysis of a large primary care database.},

author = {Katherine Phillips and Jonathan M Hazlehurst and Christelle Sheppard and Srikanth Bellary and Wasim Hanif and Muhammad Ali Karamat and Francesca L Crowe and Anna Stone and G Neil Thomas and Javeria Peracha and Anthony Fenton and Christopher Sainsbury and Krishnarajah Nirantharakumar and Indranil Dasgupta},

doi = {10.1111/dme.15153},

issn = {1464-5491 (Electronic)},

year  = {2023},

date = {2023-01-01},

journal = {Diabetic medicine : a journal of the British Diabetic Association},

pages = {e15153},

abstract = {AIMS: To determine differences in the management of diabetic kidney disease (DKD) relevant to patient sex, ethnicity and socio-economic group in UK primary care. METHODS: A cross-sectional analysis as of January 1, 2019 was undertaken using the IQVIA Medical Research Data dataset, to determine the proportion of people with DKD managed in accordance with national guidelines, stratified by demographics. Robust Poisson regression models were used to calculate adjusted risk ratios (aRR) adjusting for age, sex, ethnicity and social deprivation. RESULTS: Of the 2.3 million participants, 161,278 had type 1 or 2 diabetes, of which 32,905 had DKD. Of people with DKD, 60% had albumin creatinine ratio (ACR) measured, 64% achieved blood pressure (BP, <140/90 mmHg) target, 58% achieved glycosylated haemoglobin (HbA1c, <58 mmol/mol) target, 68% prescribed renin-angiotensin-aldosterone system (RAAS) inhibitor in the previous year. Compared to men, women were less likely to have creatinine: aRR 0.99 (95% CI 0.98-0.99), ACR: aRR 0.94 (0.92-0.96), BP: aRR 0.98 (0.97-0.99), HbA(1c) : aRR 0.99 (0.98-0.99) and serum cholesterol: aRR 0.97 (0.96-0.98) measured; achieve BP: aRR 0.95 (0.94-0.98) or total cholesterol (<5 mmol/L) targets: aRR 0.86 (0.84-0.87); or be prescribed RAAS inhibitors: aRR 0.92 (0.90-0.94) or statins: aRR 0.94 (0.92-0.95). Compared to the least deprived areas, people from the most deprived areas were less likely to have BP measurements: aRR 0.98 (0.96-0.99); achieve BP: aRR 0.91 (0.8-0.95) or HbA(1c) : aRR 0.88 (0.85-0.92) targets, or be prescribed RAAS inhibitors: aRR 0.91 (0.87-0.95). Compared to people of white ethnicity; those of black ethnicity were less likely to be prescribed statins aRR 0.91 (0.85-0.97). CONCLUSIONS: There are unmet needs and inequalities in the management of DKD in the UK. Addressing these could reduce the increasing human and societal cost of managing DKD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gardner2023,

title = {Risk of progression from pre-diabetes to type 2 diabetes in a large UK adult cohort},

author = {Michael P. Gardner and Jingya Wang and Jonathan M. Hazlehurst and Chris Sainsbury and Jacqueline Blissett and Krishnarajah Nirantharakumar and Neil Thomas and Srikanth Bellary},

doi = {10.1111/DME.14996},

issn = {14645491},

year  = {2023},

date = {2023-01-01},

journal = {Diabetic Medicine},

volume = {40},

issue = {3},

publisher = {John Wiley and Sons Inc},

abstract = {Aims: People with pre-diabetes are at high risk of progressing to type 2 diabetes. This progression is not well characterised by ethnicity, deprivation and age, which we describe in a large cohort of individuals with pre-diabetes. Methods: A retrospective cohort study with The Health Improvement Network (THIN) database was conducted. Patients aged 18 years and over and diagnosed with pre-diabetes [HbA1c 42 mmol/mol (6.0%) to 48 mmol/mol (6.5%) were included]. Cox proportional hazards regression was used to calculate adjusted hazard rate ratios (aHR) for the risk of progression from pre-diabetes to type 2 diabetes for each of the exposure categories [ethnicity, deprivation (Townsend), age and body mass index (BMI)] separately. Results: Of the baseline population with pre-diabetes (n = 397,853), South Asian (aHR 1.31; 95% CI 1.26–1.37) or Mixed-Race individuals (aHR 1.22; 95% CI 1.11–1.33) had an increased risk of progression to type 2 diabetes compared with those of white European ethnicity. Likewise, deprivation (aHR 1.17; 95% CI 1.14–1.20; most vs. least deprived) was associated with an increased risk of progression. Both younger (aHR 0.63; 95% CI 0.58–0.69; 18 to <30 years) and older individuals (aHR 0.85; 95% CI 0.84–0.87; ≥65 years) had a slower risk of progression from pre-diabetes to type 2 diabetes, than middle-aged (40 to <65 years) individuals. Conclusions: South Asian or Mixed-Race individuals and people with social deprivation had an increased risk of progression from pre-diabetes to type 2 diabetes. Clinicians need to recognise the differing risk across their patient populations to implement appropriate prevention strategies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gooden2023,

title = {A matched cohort study investigating premature, accentuated, and accelerated aging in people living with HIV},

author = {Tiffany E. Gooden and Jingya Wang and Dawit T. Zemedikun and Stephen Taylor and Sheila Greenfield and Semira Manaseki-Holland and Krishnarajah Nirantharakumar and G. Neil Thomas},

doi = {10.1111/HIV.13375},

issn = {14681293},

year  = {2023},

date = {2023-01-01},

journal = {HIV Medicine},

volume = {24},

issue = {5},

pages = {640-647},

publisher = {John Wiley and Sons Inc},

abstract = {Introduction: The impact of HIV infection on the aging process is disputed and largely unknown. We aimed to identify whether people living with HIV experience premature, accelerated, and/or accentuated aging by investigating the development of four age-related non-communicable diseases in people living with versus without HIV. Methods: This population-based matched cohort study design used UK-based primary care electronic health records from the IQVIA Medical Research Database. Between January 2000 and January 2020, all people living with and without HIV aged ≥18 years were eligible. Outcomes included cardiovascular disease (CVD), hypertension, type 2 diabetes mellitus (T2DM), and chronic kidney disease (CKD), which were identified by Read codes. We used age at diagnosis to investigate premature aging and age at exit date to investigate accentuation and acceleration. For each outcome, people with and without HIV were excluded if they had the outcome of interest at baseline. Participants were matched based on propensity scores (1:1 ratio). Linear regression was used to report any difference in age at diagnosis between the two groups and to report the prevalence trends for age at exit date. Results: In total, 8880 people living with HIV were matched with 8880 people without HIV and were found to have an earlier onset of CVD (54.5 vs. 56.8; p = 0.002). Similarly, people living with HIV had an earlier onset of hypertension (49.7 vs. 51.4; p = 0.002). No difference was found for T2DM or CKD (53.4 vs. 52.6; p = 0.368 and 57.6 vs. 58.1; p = 0.483, respectively). The burden of CKD increased over time, whereas no difference in the burden was found for the other conditions. Conclusion: The earlier development of CVD and hypertension in people living with HIV than in those without HIV indicates premature aging, whereas the increased burden of CKD indicates accelerated aging.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Keerthy2023,

title = {Associations between primary care recorded cannabis use and mental ill health in the UK: A population-based retrospective cohort study using UK primary care data},

author = {Deepiksana Keerthy and Joht Singh Chandan and Juste Abramovaite and Krishna Margadhamane Gokhale and Siddhartha Bandyopadhyay and Ed Day and Steven Marwaha and Matthew R. Broome and Krishnarajah Nirantharakumar and Clara Humpston},

doi = {10.1017/S003329172100386X},

issn = {14698978},

year  = {2023},

date = {2023-01-01},

journal = {Psychological Medicine},

volume = {53},

issue = {5},

pages = {2106-2115},

publisher = {Cambridge University Press},

abstract = {Background Cannabis use is a global public health issue associated with increased risks of developing mental health disorders, especially in young people. We aimed to investigate the relationships between cannabis exposure and risks of receiving mental illness diagnoses or treatment as outcomes. Methods A population based, retrospective, open cohort study using patients recorded in 'IQVIA medical research data', a UK primary care database. Read codes were used to confirm patients with recorded exposure to cannabis use who were matched up to two unexposed patients. We examined the risk of developing three categories of mental ill health: depression, anxiety or serious mental illness (SMI). Results At study entry, the exposed cohort had an increased likelihood of having experienced mental ill health [odds ratio (OR) 4.13; 95% confidence interval (CI) 3.99-4.27] and mental ill health-related prescription (OR 2.95; 95% CI 2.86-3.05) compared to the unexposed group. During the study period we found that exposure to cannabis was associated with an increased risk of developing any mental disorder [adjusted hazard ratio (aHR) 2.73; 95% CI 2.59-2.88], also noted when examining by subtype of disorder: anxiety (aHR 2.46; 95% CI 2.29-2.64), depression (aHR 2.34; 95% CI 2.20-2.49) and SMI (aHR 6.41; 95% CI 5.42-7.57). These results remained robust in sensitivity analyses. Conclusion These findings point to the potential need for a public health approach to the management of people misusing cannabis. However, there is a gross under-recording of cannabis use in GP records, as seen by the prevalence of recorded cannabis exposure substantially lower than self-reported survey records.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}