A pilot study of new approaches to exploring illness trajectories and patterns of comorbidity in major mental disorders
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Updated: Oct 12, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Jan Scott1,2, Florence Vorspan2,3,4, Josephine Loftus5
1Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK.
Aims:
We explored lifetime comorbidities in clinical subsamples with a diagnosis of Psychosis (N = 143), bipolar (BD = 511), and unipolar disorders (UP = 861).
Methods:
We analyzed trajectories and patterns of comorbidities using novel metrics, namely bubble plots and density of antecedent events per year of illness exposure per individual.
Results:
Age at onset (AAO) of most comorbidities was similar to epidemiological studies, but cumulative rates were higher in clinical cases. There were some between group differences in patterns or burden of comorbidities, for example, Psychosis showed the earliest AAO of any mental disorder; UP showed the latest AAO of the index diagnosis. The relative risk of multimorbidity was lower in UP compared with other diagnoses, however, the goodness of fit for the illness trajectory path was lowest for BD.
Conclusions:
Bubble plots offer a useful representation of timing, sequence, cumulative probability and of comorbidities, the added value of reporting density measures was less obvious.
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