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ZENODO
Preprint . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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Predictive value of neurocognitive markers for SSRI treatment failure in major depressive disorder — a systematic review using multicenter published evidence from Harvard Medical School (Massachusetts General Hospital), Michigan Medicine, UVA Health, and all the Teaching Hospitals in Ghana (KBTH, KATH, TTH, HTH, 37MH, CCTH).

Authors: Poku, Chris Osei;

Predictive value of neurocognitive markers for SSRI treatment failure in major depressive disorder — a systematic review using multicenter published evidence from Harvard Medical School (Massachusetts General Hospital), Michigan Medicine, UVA Health, and all the Teaching Hospitals in Ghana (KBTH, KATH, TTH, HTH, 37MH, CCTH).

Abstract

Background. Cognitive dysfunction commonly accompanies major depressive disorder (MDD) and may predict poor response to selective serotonin reuptake inhibitors (SSRIs). Identifying reliable neurocognitive markers of SSRI nonresponse could guide precision treatment.Objective. To systematically review published evidence on neurocognitive predictors of SSRI treatment failure in MDD, emphasizing clinician-authored evidence and institutional resources from Massachusetts General Hospital (MGH), Michigan Medicine, UVA Health, and all the Teaching Hospitals in Ghana (KBTH, KATH, TTH, HTH, 37MH, CCTH), and to define gaps for a multicenter research agenda.Methods. We searched PubMed/PMC, Google Scholar, institutional webpages, and ClinicalTrials.gov through 31 December 2025 for studies testing baseline neurocognitive measures (neuropsychological tests, task-based/ resting EEG, behavioral emotionalprocessing tasks) as predictors of clinical response to SSRI treatment in adults with MDD. We included RCTs, prospective cohorts, and observational predictor studies. Two reviewers screened records; heterogeneous methods precluded meta-analysis so findings are synthesized narratively.Results. Robust evidence indicates that deficits in executive function, psychomotor speed, and emotional-processing biases at baseline are associated with poorer SSRI outcomes in multiple cohorts (Groves et al., 2018; Bruder et al., 2014; Gorlyn et al., 2008). Task-based and resting EEG signatures also predict SSRI response in several studies (Wu et al., 2020). Early changes in emotional processing after SSRI initiation correlate with later clinical improvement and may serve as early markers (Ang et al., 2020). Clinician-authored tools and research infrastructure at MGH (e.g., CPFQ; Baer et al., 2014), Michigan Medicine (psychiatry research programs), and UVA (neuropsychiatry/behavioral neurology programs) support feasibility for multicenter predictor studies, but no published multicenter predictor study jointly authored across these exact institutions and the Ghanaian teaching hospitals was identified. Ghanaian mental-health literature documents cognitive assessment capacity and MDD burden but lacks SSRI-predictor studies (Read et al., 2012).Conclusions. Baseline neurocognitive dysfunction—especially in executive/psychomotor domains and emotional processing—has predictive value for SSRI nonresponse, but heterogeneity across studies limits clinical translation. A multicenter prospective study linking standardized cognitive batteries, EEG, and harmonized SSRI treatment protocols across MGH, Michigan Medicine, UVA, and the Teaching Hospitals in Ghana is strongly recommended.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average