Treatment of resistant depression: Diagnostic profile and therapeutic role of atypical antipsychotics and mood stabilizers
Bibliographic record
Abstract
Background: Major Depressive Disorder (MDD) is a highly prevalent and disabling or fatal disease. According to the STAR*D project, about 50% of patients with unipolar depression suffer from treatment-resistant depression (TRD). In addition, animal studies have suggested potential antidepressant properties of Valproate (VPA) possibly due to its implication in epigenetic programming. Method: We evaluated socio-demographic, psychopathological profiles and treatment outcomes in 78 patients (46 females, 32 males) with TRD from the Register of the Mood Disorder Clinic at McGill University Health Center (MUHC) by chart reviewer analysis. Clinical response was investigated prior to treatment (T-0) and after 30-90 days (T-3) of stable therapy using Montgomery-Asberg Depression Rating Scale (MADRS), Hamilton Depression Rating Scale (HAM-D17), Quick Inventory of Depressive Symptomatology (QIDS-C16) and Clinical Global Impression-severity of illness (CGI-S). These patients underwent several antidepressant treatment strategies. Only the last trial, when the patient responded to treatment and remained stable for more than 6 weeks (mean 12.5±5.90 weeks, T-3), and the treating psychiatrist kept the treatment unchanged, was included in this study for statistical analysis.Results: In the first research study, patients responded to three pharmacological interventions: A)antidepressants combination(21); B)mood stabilizers and antidepressants (16); C)atypical antipsychotics and antidepressant (41). Compared to T-0, patients in all treatment groups showed significant decrease in depressive symptoms on all scales at T-3 (P<0.001). Importantly, at T-0, Group-C showed higher depressive symptoms on all scales compared to Group-A (HAM-D17, 25.7±1 vs. 21.3±1.5, mean±S.E.M, P=0.02). In addition, Group-C, compared to Group-A showed increased previous suicide attempts (29.3% vs. 14.3%) and number of failed treatments (4.2±2.9 vs. 2.7±2, mean±SD). Finally, change from T-0 to T-3 (Δ) on HAM-D17 was significantly superior in Group-C (Δ=10.6) compared to Group-A (Δ=7, P=0.05). In the second study, we were also able to identify 14 patients (7 males and 7 females; age 19-59) who received VPA (375-1000mg/d) in addition to their treatment and clinical response to VPA was investigated after 1 (T-1), 4 (T-4) and 7 (T-7) months of therapy using the MADRS and CGI-S. As for the VPA augmentation group, VPA significantly decreased MADRS score at T-1 (23.5±1.0, P<0.001), T-4 (18.6±1.3, P<0.001), and T-7 (13.6±1.6, P<0.001) (effect size: partial η2=0.86). MADRS at T-4 was also lower than at T-1 (P<0.001) and at T-7 lower than at T-4 (P=0.008). Importantly, MADRS score at T-7 was closer to the reported value of remission (MADRS<10), and none of the patients relapsed during the observational period. Compared to T-0 (5.1±0.3), VPA also decreased CGI-S at T-1 (4.0±0.1, P=0.03), T-4 (3.3±0.2, P<0.001), and T-7 (2.6±0.3, P<0.001) (partial η2=0.74).Conclusion: The results highlight the importance of antipsychotic and/or mood stabilizer augmentation as first-line treatment in patients with severe TRD. Moreover, in a subgroup of patients, VPA showed substantial clinical improvement and maintenance over a long period and thus deserves further exploration in large double-blinded trials. We have identified a sub-class of TRD patients presenting with specific psychopathological features (significantly higher HAMD-17 score at T-0, higher suicide attempts, higher number of failed treatments, and a significantly better response to atypical antipsychotics and/or mood stabilizers) that respond significantly better to atypical antipsychotics and/or mood stabilizers. Randomized-controlled trials evaluating the independent roles of augmentation with antipsychotics or mood stabilizers are warranted in order to assess the initial pharmacological options for patients with severe TRD and to better characterize this subgroup of patients from a psychopathological and therapeutic point of view.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".