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Retinal macular morphology and cognitive functions in unmedicated first-episode psychosis patients
Neethu Kanjingat Nandan1, Sai Krishna Tikka2, Vijaya Sahu3
1PGY-2, Department of Psychiatry, Albert Einstein Medical Center, Philadelphia, PA, United States.
Background:
This study investigates retinal macular abnormalities and neurocognitive function, including facial emotion recognition, in individuals with unmedicated First-Episode Psychosis (FEP). The primary aim is to compare retinal morphology in FEP patients and healthy controls and examine correlations with cognitive performance.
Method:
Thirty-two FEP patients (aged 18-45) and 30 healthy controls underwent psychiatric assessment and retinal examination using the Spectral Domain - Optical Coherence Tomography (SD-OCT), with a focus on macula. Facial emotion recognition was evaluated using the Mandal emotion recognition test for four emotions (Sad, Anger, Happy, Fear). Visual memory and executive function were assessed using the Rey-Osterrieth Complex Figure Test and the Trail Making Test, respectively. Statistical analyses included t-test, correlation analysis, and linear discriminant function analysis.
Results:
FEP patients showed significant macular abnormalities, with reduced thickness in multiple quadrants. Facial emotion recognition scores were notably lower among patients for all emotions tested. Patients also showed visual memory deficits. Across the three measures there were significant correlations. Discriminant function analysis indicated that a combination of emotion recognition scores and inner nasal quadrant macular thickness of left eye could effectively differentiate patients from healthy controls with high accuracy (85.5 %).
Conclusion:
Our study demonstrates significant macular abnormalities, impaired facial emotion recognition, and visual memory deficits in patients with unmedicated FEP. These findings suggest potential of retinal abnormalities as biomarkers for psychosis. Future research with larger sample sizes could further establish retinal changes and facial emotion recognition as potential biomarkers.
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