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Record W4409634883 · doi:10.3390/jpm15040161

Patient Experience with Intranasal Esketamine in Treatment-Resistant Depression: Insights from a Multicentric Italian Study (REAL-ESKperience)

2025· article· en· W4409634883 on OpenAlexaff
Marco Di Nicola, Maria Pepe, Giacomo d’Andrea, Ilaria Marcelli, Mauro Pettorruso, Ileana Andriola, Sergio Barlati, Matteo Carminati, C Cattaneo, Massimo Clerici, Domenico De Berardis, Sergio De Filippis, Bernardo Dell’Osso, Giorgio Di Lorenzo, Giuseppe Maina, Mirko Manchia, Matteo Marcatili, Vassilis Martiadis, Cinzia Niolu, A. Petralia, Gianluca Rosso, Gianluca Serafini, Maria Salvina Signorelli, Tommaso Vannucchi, Matteo Vismara, Raffaella Zanardi, Antonio Vita, Gabriele Sani, Giovanni Martinotti

Bibliographic record

VenueJournal of Personalized Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsDalhousie University
FundersUniversità degli Studi di BresciaUniversità Cattolica del Sacro CuoreUniversità di Catania
KeywordsMoodTreatment-resistant depressionClinical psychologyDepression (economics)MedicinePsychologyQuality of life (healthcare)PsychiatryMajor depressive disorderPsychotherapist

Abstract

fetched live from OpenAlex

Background. Treatment-resistant depression (TRD) is a prevalent, high-burden disorder. Esketamine nasal spray (ESK-NS) has been approved for, T.R.D.; and efficacy has been observed in both clinical trials and real-world studies. However, observations integrating patients’ perspective on this treatment are limited. This multicentric Italian study explored experiences with ESK-NS in TRD patients, focusing on perceived therapeutic effects and overall satisfaction. Methods. A self-report survey was administered to 236 outpatients with TRD (55.1% females, 54.1 ± 14.1 years) treated with ESK-NS for at least three consecutive months within standard clinical care. Based on satisfaction levels, participants were classified as “unsatisfied” (10.2%), “partially satisfied” (19.1%), “satisfied” (44.4%), or “very satisfied” (26.3%), and compared for sociodemographic, clinical characteristics, and feedback on perceived benefits. Artificial intelligence (OpenAI) served to categorize responses to an open-ended question. Results. Enhanced quality of life was reported by 88.4% of participants. Significant differences emerged in earliest self-perceived benefits, most relevant effects, and impact on global functioning across groups. Specifically, “very satisfied” patients described the following: early improvements in depressed mood, suicidal thoughts, and restlessness; decreased suicidal thoughts among the most significant effects; and functional gains across all domains. OpenAI identified experiences of personal growth and rediscovery and a desire for tailored settings and approaches as recurring topics. Conclusions. Most patients reported a positive perception of ESK-NS treatment. The most satisfied participants highlighted significant benefits to depressed mood, suicidal thoughts, and overall functioning. Patient-reported experiences offer insights into different psychopathological dimensions, including functional outcomes and quality of life. Integrating these perspectives into clinical practice might assist treatment personalization, improving patients’ adherence and satisfaction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.308
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2025
Admission routes1
Has abstractyes

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