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      Health conditions in adults with HIV compared with the general population: A population-based cross-sectional analysis

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          Summary

          Background

          Life expectancy in adults with human immunodeficiency virus (HIV) has increased and managing other health conditions is increasingly important for patients and healthcare planning. The aim of this study was to examine the prevalence and association between different health conditions and HIV status.

          Methods

          We performed a cross-sectional analysis of adult UK Clinical Practice Research Datalink primary care electronic medical records linked to hospital admissions as of Nov 30, 2015. We examined 47 health condition groups and 304 physical and mental health conditions by HIV status, after adjustment for age, sex, social deprivation status using logistic regression.

          Findings

          There were 964 patients with HIV (61.7% male; 92.8% aged <65 years) and 941,113 non-HIV patients (49.4% male; 75.2% aged <65 years). Condition groups with the greatest prevalence in HIV that were also highly prevalent in adults without HIV included: lipid disorder (41.4% vs 40.2%), and hypertension (19.1% vs 24.6%). Following adjustment, 18 (37.5%) condition groups were more likely in adults with HIV and ten (20.8%) were less likely. Individual conditions that were less likely in adults with HIV included: atrial fibrillation (odds ratio [OR] 0.37 [95% CI 0.20–0.64]) and hypertension (OR_0.78 [0.65–0.94]); rheumatoid arthritis (OR 0.27 [0.05–0.84]); asthma (OR_0.65 (0.53–0.80]); and certain eye diseases such as macular degeneration (OR_0.30 [0.09–0.70]). Meanwhile individual conditions that were more likely included: liver fibrosis, sclerosis, and cirrhosis (OR_3.23 [1.85–5.20]); pulmonary embolism (OR_2.06 [1.15–3.36]); male infertility (OR_2.23 [1.50–3.16]) and female infertility (OR_2.01 [1.34–2.88]); bipolar disorder (OR_2.93 [1.52–5.05]) and depression (OR_1.49 [1.28–1.71]); cervical malignancy (OR_4.64 [1.15–12.15]); and infections.

          Interpretation

          Comorbidity is common in adults with HIV, with physical and mental health conditions spanning a wide spectrum. HIV management should consider multidisciplinary care models to provide optimal patient care.

          Funding

          The project was funded by the Bart’s Charity; DRM was funded by a Wellcome Trust Clinical Research Career Development Fellowship; DRM and DMM received funding from the HDR-UK Precision therapeutics programme.

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          Most cited references25

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          Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.

          Long-term disorders are the main challenge facing health-care systems worldwide, but health systems are largely configured for individual diseases rather than multimorbidity. We examined the distribution of multimorbidity, and of comorbidity of physical and mental health disorders, in relation to age and socioeconomic deprivation. In a cross-sectional study we extracted data on 40 morbidities from a database of 1,751,841 people registered with 314 medical practices in Scotland as of March, 2007. We analysed the data according to the number of morbidities, disorder type (physical or mental), sex, age, and socioeconomic status. We defined multimorbidity as the presence of two or more disorders. 42·2% (95% CI 42·1-42·3) of all patients had one or more morbidities, and 23·2% (23·08-23·21) were multimorbid. Although the prevalence of multimorbidity increased substantially with age and was present in most people aged 65 years and older, the absolute number of people with multimorbidity was higher in those younger than 65 years (210,500 vs 194,996). Onset of multimorbidity occurred 10-15 years earlier in people living in the most deprived areas compared with the most affluent, with socioeconomic deprivation particularly associated with multimorbidity that included mental health disorders (prevalence of both physical and mental health disorder 11·0%, 95% CI 10·9-11·2% in most deprived area vs 5·9%, 5·8%-6·0% in least deprived). The presence of a mental health disorder increased as the number of physical morbidities increased (adjusted odds ratio 6·74, 95% CI 6·59-6·90 for five or more disorders vs 1·95, 1·93-1·98 for one disorder), and was much greater in more deprived than in less deprived people (2·28, 2·21-2·32 vs 1·08, 1·05-1·11). Our findings challenge the single-disease framework by which most health care, medical research, and medical education is configured. A complementary strategy is needed, supporting generalist clinicians to provide personalised, comprehensive continuity of care, especially in socioeconomically deprived areas. Scottish Government Chief Scientist Office. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            Data Resource Profile: Clinical Practice Research Datalink (CPRD)

            The Clinical Practice Research Datalink (CPRD) is an ongoing primary care database of anonymised medical records from general practitioners, with coverage of over 11.3 million patients from 674 practices in the UK. With 4.4 million active (alive, currently registered) patients meeting quality criteria, approximately 6.9% of the UK population are included and patients are broadly representative of the UK general population in terms of age, sex and ethnicity. General practitioners are the gatekeepers of primary care and specialist referrals in the UK. The CPRD primary care database is therefore a rich source of health data for research, including data on demographics, symptoms, tests, diagnoses, therapies, health-related behaviours and referrals to secondary care. For over half of patients, linkage with datasets from secondary care, disease-specific cohorts and mortality records enhance the range of data available for research. The CPRD is very widely used internationally for epidemiological research and has been used to produce over 1000 research studies, published in peer-reviewed journals across a broad range of health outcomes. However, researchers must be aware of the complexity of routinely collected electronic health records, including ways to manage variable completeness, misclassification and development of disease definitions for research.
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              Validation and validity of diagnoses in the General Practice Research Database: a systematic review

              AIMS To investigate the range of methods used to validate diagnoses in the General Practice Research Database (GPRD), to summarize findings and to assess the quality of these validations. METHODS A systematic literature review was performed by searching PubMed and Embase for publications using GPRD data published between 1987 and April 2008. Additional publications were identified from conference proceedings, back issues of relevant journals, bibliographies of retrieved publications and relevant websites. Publications that reported attempts to validate disease diagnoses recorded in the GPRD were included. RESULTS We identified 212 publications, often validating more than one diagnosis. In total, 357 validations investigating 183 different diagnoses met our inclusion criteria. Of these, 303 (85%) utilized data from outside the GPRD to validate diagnoses. The remainder utilized only data recorded in the database. The median proportion of cases with a confirmed diagnosis was 89% (range 24–100%). Details of validation methods and results were often incomplete. CONCLUSIONS A number of methods have been used to assess validity. Overall, estimates of validity were high. However, the quality of reporting of the validations was often inadequate to permit a clear interpretation. Not all methods provided a quantitative estimate of validity and most methods considered only the positive predictive value of a set of diagnostic codes in a highly selected group of cases. We make recommendations for methodology and reporting to strengthen further the use of the GPRD in research.
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                Author and article information

                Contributors
                Journal
                EClinicalMedicine
                EClinicalMedicine
                EClinicalMedicine
                Elsevier
                2589-5370
                21 April 2022
                May 2022
                21 April 2022
                : 47
                : 101392
                Affiliations
                [a ]Division of Population Health and Genomics, University of Dundee, Dundee, United Kingdom
                [b ]Department of Public Health, University of Southern Denmark, Denmark
                [c ]Division of Population Health and Genomics, University of Dundee, United Kingdom
                [d ]Barts Health NHS Trust, Grahame Hayton Unit, Royal London Hospital, London, United Kingdom
                [e ]William Harvey Research Institute, Queen Mary University of London, United Kingdom
                Author notes
                [* ]Corresponding author at: Division of Population Health and Genomics, University of Dundee, Dundee, United Kingdom. d.r.z.morales@ 123456dundee.ac.uk
                [** ]Corresponding author. p.mcgettigan@ 123456qmul.ac.uk
                Article
                S2589-5370(22)00122-5 101392
                10.1016/j.eclinm.2022.101392
                9046106
                35497059
                c5ce0e69-5a71-488b-9a5c-bf578f96e3f1
                © 2022 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 9 February 2022
                : 21 March 2022
                : 28 March 2022
                Categories
                Articles

                hiv,comorbidity,multimorbidity
                hiv, comorbidity, multimorbidity

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