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ObjectiveWe investigated the burden of chronic kidney disease (CKD) among patients with severe mental illness (SMI).MethodsWe identified patients with SMI among all those aged 25–74 registered in the UK Clinical Practice Research Datalink as on March 31, 2014. We compared the prevalence of CKD (two measurements of estimated glomerular filtration rate <60 mL/min/1.73 m2 for ≥3 months) and renal replacement therapy between patients with and without SMI. For patients with and without a history of lithium prescription separately, we used logistic regression to examine the association between SMI and CKD, adjusting for demographics, lifestyle characteristics, and known CKD risk factors.ResultsThe CKD prevalence was 14.6% among patients with SMI and a history of lithium prescription (n = 4,295), 3.3% among patients with SMI and no history of lithium prescription (n = 24,101), and 2.1% among patients without SMI (n = 2,387,988; P < 0.001). The prevalence of renal replacement therapy was 0.23%, 0.15%, and 0.11%, respectively (P = 0.012). Compared to patients without SMI, the fully adjusted odds ratio for CKD was 6.49 (95% CI 5.84–7.21) for patients with SMI and a history of lithium prescription and 1.45 (95% CI 1.34–1.58) for patients with SMI and no history of lithium prescription. The higher prevalence of CKD in patients with SMI may, in part, be explained by more frequent blood testing as compared to the general population.ConclusionCKD is identified more commonly among patients with SMI than in the general population.

Purpose: Bipolar disorder (BPD) is often an under-addressed mental disorder. Limited studies have investigated its epidemiology and drug utilisation in Hong Kong (HK) and the United Kingdom (UK) and thus local prescribing practices remain unclear. This study aimed to determine the prevalence of BPD and the prescribing of psychotropic medications as maintenance treatment from 2001-2018 in HK and the UK. Method: A retrospective study using the data from Clinical Data Analysis and Reporting System in HK and IQVIA Medical Research Data in the UK.Results: The prevalence of BPD diagnosis in HK and the UK more than doubled during the study period. Some distinct changes in prescribing patterns over time were observed. Lithium use declined by 2.46% and 14.58% in HK and the UK, respectively. By 2018, patients were 4.6 times more likely to receive antidepressant monotherapy in the UK versus HK (15.62% vs. 3.42%). In HK, 38.41% of women of childbearing age were prescribed valproate in 2018 compared with 8.46% in the UK. Conclusion:The prevalence of BPD diagnosis has been increasing in HK and the UK. The disparity in prescribing patterns of BPD maintenance treatment in two regions reflected three major issues in clinical practice: (1) under-prescribing of lithium in both regions, (2) antidepressant monotherapy in the UK and (3) overprescribing of valproate to women of childbearing age in HK. A review of current clinical treatment guidelines and regulations of prescribing practice by local clinicians should be immediately implemented to ensure the safe use of medications in patients with BPD.

Background People with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI. Methods and findings We performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions. Conclusions In this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.