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Updated: Mar 30, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
The early identification of psychosis: can lessons be learnt from cardiac stress testing?
Swapnil Gupta1,2,3, Mohini Ranganathan1,2,3, Deepak Cyril D'Souza4,5,6
1Psychiatry Service 116A, VA Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT, 06516, USA.
Abstract:
Psychotic disorders including schizophrenia are amongst the most debilitating psychiatric disorders. There is an urgent need to develop methods to identify individuals at risk with greater precision and as early as possible. At present, a prerequisite for a diagnosis of schizophrenia is the occurrence of a psychotic episode. Therefore, attempting to detect schizophrenia on the basis of psychosis is analogous to diagnosing coronary artery disease (CAD) after the occurrence of a myocardial infarction (MI). The introduction of cardiac stress testing (CST) has revolutionized the detection of CAD and the prevention and management of angina and MI. In this paper, we attempt to apply lessons learnt from CST to the early detection of psychosis by proposing the development of an analogous psychosis stress test. We discuss in detail the various parameters of a proposed psychosis stress test including the choice of a suitable psychological or psychopharmacological "stressor," target population, outcome measures, safety of the approach, and the necessary evolution of test to become clinically informative. The history of evolution of CST may guide the development of a similar approach for the detection and management of psychotic disorders. The initial development of a test to unmask latent risk for schizophrenia will require the selection of a suitable and safe stimulus and the development of outcome measures as a prelude to testing in populations with a range of risk to determine predictive value. The use of CST in CAD offers the intriguing possibility that a similar approach may be applied to the detection and management of schizophrenia.
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