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This page is an AI-assisted Turkish summary of the study presented at the 26th World Congress of Psychiatry. The study belongs to the presenting authors; please refer to the original source when citing it.

EV0914

E-PosterNeuroscience and ImagingSingle-arm pilot study

Pretreatment resting-state fMRI connectivity patterns and ketamine outcomes in treatment-resistant depression: A pilot study from a public hospital in Argentina

PRE-TREATMENT RESTING-STATE FMRI CONNECTIVITY PATTERNS AND KETAMINE OUTCOMES IN TREATMENT-RESISTANT DEPRESSION: A PILOT STUDY FROM A PUBLIC HOSPITAL IN ARGENTINA

Presenter: María Victoria Majul Conte Grand

Country: Argentina

Institution: Hospital Dr. Juan A. Fernández, Department of Medicine, Mental Health Section

In a small pilot cohort with treatment-resistant depression, none of the three prespecified baseline connectivity measures showed a statistically significant association with ketamine response.

The aim was to test whether baseline functional connectivity measured before the first infusion was associated with the percentage reduction in MADRS scores. Eight consecutive adults with treatment-resistant depression were enrolled (5 men, 3 women; age 40.5 ± 10 years; 6 unipolar, 2 bipolar; MADRS ≥ 20; at least 2 adequate treatment trials with inadequate response or a Hidalgo Mazzei score; psychotic disorders excluded). Pre-infusion resting-state fMRI scans were acquired 15.6 ± 8.7 weeks beforehand on a GE 3T scanner (2D gradient-echo EPI, TR 2.0 to 2.3 s, 200 volumes, voxel size 3.75 x 3.75 x 4 mm, T1 BRAVO); data were processed using SPM12 and CONN, Fisher's z-transformation was applied, intravenous ketamine was administered at 0.5 to 1.0 mg/kg over a mean of 12 infusions, and the analysis used Spearman correlations for each hypothesis, 8! permutations, Benjamini–Hochberg (BH) correction, and a leave-one-out method. The three prespecified hypotheses concerned the global sgACC dissociation index (IDG sgACC), anteroposterior default mode network integrity (MPFC PCC), and connectivity between the right amygdala and right sgACC. MADRS reductions ranged from a 7.7% worsening to a 96.8% improvement (mean 39.7% ± 33.9%). None of the hypotheses reached significance: H1 yielded rho = -0.405 and exact p = 0.327, H2 yielded rho = 0.524 and exact p = 0.197, and H3 yielded rho = 0.310 and exact p = 0.462; for n = 8, the BH thresholds were rho ≥ 0.833 / 0.786 / 0.738, whereas the highest observed value was 0.524. H2 showed the largest effect, with a consistent sign across all leave-one-out analyses; H1 was in the opposite direction to that predicted, and H3 depended on a single case. The authors state that the study demonstrates the feasibility of implementing a predefined, reproducible workflow in the public sector, that the findings are hypothesis-generating, and that anteroposterior default mode network integrity (rho = 0.52) was identified as the primary hypothesis for a prospectively powered replication study; the main limitations are the small sample, single-arm design, absence of post-treatment scans, and acquisition heterogeneity.

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How to cite this study

APA 7: Grand, M. V. M. C., et al. (2026, September 23-26). Pre-treatment resting-state fmri connectivity patterns and ketamine outcomes in treatment-resistant depression: a pilot study from a public hospital in argentina [E-poster]. 26th WPA World Congress of Psychiatry (WCP 2026), Stockholm, Sweden. https://cslide.ctimeetingtech.com/wcp26/attendee/eposter/file/1073

Vancouver: Grand MVMC, et al. Pre-treatment resting-state fmri connectivity patterns and ketamine outcomes in treatment-resistant depression: a pilot study from a public hospital in argentina [e-poster]. 26th WPA World Congress of Psychiatry (WCP 2026); 2026 Sep 23-26; Stockholm, Sweden. Available from: https://cslide.ctimeetingtech.com/wcp26/attendee/eposter/file/1073

Author names and title formatting were generated automatically from the congress system; please check them against the original poster before use.

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Sitenin son güncellemesi: 8 Kasım 2026 · Site editörü: Doç. Dr. Alişan Burak Yaşar, info@alisanburak.com