Long-Term Impact of Residual Symptoms in Treatment-Resistant Depression
Bibliographic record
Abstract
OBJECTIVE: Although commonly encountered, little work has defined the longitudinal course of treatment-resistant depression (TRD) and the influence of residual posttreatment symptoms on longer-term outcome. The aim of our study was to assess the impact of posttreatment clinical states on longer-term outcome. METHOD: Patients (n = 118) with TRD received specialist inpatient treatment and were followed-up for a median of 3 years. Longitudinal outcome dichotomized into good and poor outcome was used as the primary outcome and functional measures were used as secondary outcomes. RESULTS: Among 118 treated patients, 40 (34%) entered clinical remission, 36 (31%) entered partial remission, and 42 (37%) remained in episode at discharge. At follow-up, 35% had longitudinally defined poor outcome. Posttreatment clinical status was the main predictor of both poor and good outcome. Nearly 50% of patients achieved postdischarge recovery, and subsequently had longer-term outcome, comparable with patients discharged in remission. Patients who remained in episode posttreatment were more symptomatically and functionally impaired. CONCLUSION: Posttreatment clinical states are a useful guide to clinicians for projecting the longer-term outcome of patients with TRD. The persistence of residual or syndromal symptoms predicts a poorer longer-term outcome, whereas treatment to remission is associated with better outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".