The Effects of Ketamine and Esketamine on Measures of Quality of Life in Major Depressive Disorder and Treatment-Resistant Depression: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: The rapid and clinically meaningful antidepressant effects of ketamine and esketamine are well-established in major depressive disorder (MDD) and treatment-resistant depression (TRD) as evidenced by improvement in clinician- and patient-reported depression measures. However, there remains a need to determine how these agents affect patient-reported quality of life (QoL). Herein, we aimed to systematically review extant studies evaluating the effect of ketamine and esketamine on QoL measures. METHODS: A literature search was conducted on online databases (PubMed, Scopus, Web of Science, Medline, and clinicaltrials.gov) for articles from inception to September 30th, 2024, reporting on the association between ketamine/esketamine and measures of QoL in persons diagnosed with MDD or TRD. A risk of bias assessment was conducted using the ROBINS-1 tool and the Newcastle-Ottawa Scale. RESULTS: Five studies were identified that investigated the association between ketamine/esketamine and measures of QoL in persons with MDD or TRD. Scales used to measure QoL included the WHOQOL-BREF scale, Assessment of Quality of Life 8D test, and the EuroQol-5 Dimension-5 Layers. Statistically significant findings (p < 0.001) suggest that ketamine and esketamine improve measures of QoL in persons with MDD or TRD. However, an overall moderate risk of bias was observed in the papers included in this analysis. DISCUSSION: Extant studies suggest that ketamine and esketamine treatment are associated with improvement in QoL measures in adults with MDD or TRD. Limitations of this study include hetergeneity in the types of QoL scales as well as study study duration among the studies included. Near-term research priorities should endeavour to investigate the effect of ketamine and esketamine on specific domains of QoL, respectively.
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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 | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".