Investigating the Effectiveness and Tolerability of Intranasal Esketamine Among Older Adults With Treatment-Resistant Depression (TRD): A Post-hoc Analysis from the REAL-ESK Study Group
Bibliographic record
Abstract
INTRODUCTION: Treatment-resistant depression (TRD) is a serious and debilitating psychiatric disorder that frequently affects older patients. Esketamine nasal spray (ESK-NS) has recently been approved as a treatment for TRD, with multiple studies establishing its efficacy and tolerability. However, the real-world effectiveness, tolerability, and safety of this treatment in older adults is still unclear. OBJECTIVES: To evaluate the efficacy and tolerability of ESK-NS in older subjects with TRD. METHODS: This is a post-hoc analysis of the REAL-ESK study, a multicenter, retrospective, observational study. Participants here selected were 65 years or older at baseline. The Montgomery-Åsberg Depression Rating Scale (MADRS) and the Hamilton Anxiety Rating Scale (HAM-A) were used to assess depressive and anxiety symptoms, respectively. Data were collected at three-time points: baseline, 1 month after the start of treatment (T1), and 3 months after treatment (T2). RESULTS: <0.001, Cohen's d = 1.419). At T2, 53.3% of subjects were responders (MADRS score reduced ≥50%), while 33.33% were in remission (MADRS<10). ESK-NS-related adverse effects were in order of frequency dizziness (50%), followed by dissociation (33.3%), sedation (30%), and hypertension (13.33%). Six out of 30 participants (20%) discontinued treatment. CONCLUSIONS: Our findings provide preliminary evidence of ESK-NS effectiveness in older adults with TRD, a highly debilitating depressive presentation. Furthermore, we observe high levels of treatment-emergent adverse events, which, in the majority of instances, did not require treatment suspension.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".