Marc Hébert1, Chantal Mérette2, Anne-Marie Gagné3, Thomas Paccalet4, Isabel Moreau3, Joëlle Lavoie5, Michel Maziade2. 1. Centre de Recherche CERVO, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Québec, Quebec, Canada; Département d'Ophtalmologie et d'Oto-Rhino-Laryngologie-Chirurgie Cervico-Faciale, Faculté de Médecine, Université Laval, Québec, Quebec, Canada. Electronic address: marc.hebert@fmed.ulaval.ca. 2. Centre de Recherche CERVO, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Québec, Quebec, Canada; Département de Psychiatrie et Neurosciences, Faculté de Médecine, Université Laval, Québec, Quebec, Canada. 3. Centre de Recherche CERVO, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Québec, Quebec, Canada. 4. Institut National de Santé Publique du Québec, Québec, Quebec, Canada. 5. Sinai Health System, Toronto, Ontario, Canada.
Abstract
BACKGROUND: The retina is recognized as an approachable part of the brain owing to their common embryonic origin. The electroretinogram (ERG) has proved to be a valuable tool to investigate psychiatric disorders. We therefore investigated its accuracy as a tool to differentiate schizophrenia (SZ) from bipolar disorder (BP) even after balancing patients for their main antipsychotic medication. METHODS: ERG cone and rod luminance response functions were recorded in 150 patients with SZ and 151 patients with BP and compared with 200 control subjects. We created a subgroup of subjects-45 with SZ and 45 with BP-balanced for their main antipsychotic medication. RESULTS: A reduced cone a-wave amplitude and a prolonged b-wave latency were observed in both disorders, whereas a reduced cone b-wave amplitude was present in SZ only. Reduced mixed rod-cone a- and b-wave amplitudes were observed in both disorders. Patients with SZ were distinguishable from control subjects with 0.91 accuracy, 77% sensitivity, and 91% specificity with similar numbers for patients with BP (0.89, 76%, and 88%, respectively). Patients with SZ and patients with BP could be differentiated with an accuracy of 0.86 (whole sample) and 0.83 (subsamples of 45 patients with 80% sensitivity and 82% specificity). Antipsychotic dosages were not correlated with ERG parameters. CONCLUSIONS: The ERG waveform parameters used in this study provided a very accurate distinction between the two disorders when using a logistic regression model. This supports the ERG as a tool that could aid the clinician in the differential diagnosis of SZ and BP in stabilized medicated patients.
BACKGROUND: The retina is recognized as an approachable part of the brain owing to their common embryonic origin. The electroretinogram (ERG) has proved to be a valuable tool to investigate psychiatric disorders. We therefore investigated its accuracy as a tool to differentiate schizophrenia (SZ) from bipolar disorder (BP) even after balancing patients for their main antipsychotic medication. METHODS: ERG cone and rod luminance response functions were recorded in 150 patients with SZ and 151 patients with BP and compared with 200 control subjects. We created a subgroup of subjects-45 with SZ and 45 with BP-balanced for their main antipsychotic medication. RESULTS: A reduced cone a-wave amplitude and a prolonged b-wave latency were observed in both disorders, whereas a reduced cone b-wave amplitude was present in SZ only. Reduced mixed rod-cone a- and b-wave amplitudes were observed in both disorders. Patients with SZ were distinguishable from control subjects with 0.91 accuracy, 77% sensitivity, and 91% specificity with similar numbers for patients with BP (0.89, 76%, and 88%, respectively). Patients with SZ and patients with BP could be differentiated with an accuracy of 0.86 (whole sample) and 0.83 (subsamples of 45 patients with 80% sensitivity and 82% specificity). Antipsychotic dosages were not correlated with ERG parameters. CONCLUSIONS: The ERG waveform parameters used in this study provided a very accurate distinction between the two disorders when using a logistic regression model. This supports the ERG as a tool that could aid the clinician in the differential diagnosis of SZ and BP in stabilized medicated patients.
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