DataSheet_1_Risk of Schizophrenia and Bipolar Disorder in Patients With Multiple Sclerosis: Record-Linkage Studies.docx (31.6 kB)

DataSheet_1_Risk of Schizophrenia and Bipolar Disorder in Patients With Multiple Sclerosis: Record-Linkage Studies.docx

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posted on 16.07.2020 by Ute-Christiane Meier, Sreeram V. Ramagopalan, Michael J. Goldacre, Raph Goldacre
Background

The epidemiology of psychiatric comorbidity in multiple sclerosis (MS) remains poorly understood.

Objective

We aimed to determine the risk of schizophrenia and bipolar disorder in MS patients.

Material and Methods

Retrospective cohort analyses were performed using an all-England national linked Hospital Episode Statistics (HES) dataset (1999–2016) and to determine whether schizophrenia or bipolar disorder are more commonly diagnosed subsequently in people with MS (n=128,194), and whether MS is more commonly diagnosed subsequently in people with schizophrenia (n=384,188) or bipolar disorder (n=203,592), than would be expected when compared with a reference cohort (~15 million people) after adjusting for age and other factors. Adjusted hazard ratios (aHRs) were calculated using Cox proportional hazards models.

Results

Findings were dependent on whether the index and subsequent diagnoses were selected as the primary reason for hospital admission or were taken from anywhere on the hospital record. When searching for diagnoses anywhere on the hospital record, there was a significantly elevated risk of subsequent schizophrenia (aHR 1.51, 95% confidence interval (CI) 1.40 to 1.60) and of bipolar disorder (aHR 1.14, 95% CI 1.04 to 1.24) in people with prior-recorded MS and of subsequent MS in people with prior-recorded schizophrenia (aHR 1.26, 1.15–1.37) or bipolar disorder (aHR 1.73, 1.57–1.91), but most of these associations were reduced to null when analyses were confined to diagnoses recorded as the primary reason for admission.

Conclusion

Further research is needed to investigate the potential association between MS and schizophrenia and/or bipolar disorder as it may shed light on underlying pathophysiology and help identify potential shared risk factors.

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