Duration of untreated illness and bipolar disorder: time for a new definition? Results from a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: We primarily aimed to explore the associations between duration of untreated illness (DUI), treatment response, and functioning in a cohort of patients with bipolar disorder (BD). METHODS: 261 participants with BD were recruited. DUI was defined as months from the first affective episode to the start of a mood-stabilizer. The functioning assessment short test (FAST) scores and treatment response scores for lithium, valproate, or lamotrigine according to the Alda Scale Total Score (TS) were compared between patients with short (<24 months) or long DUI. Differences in FAST scores among good (GR; TS≥7), poor (PR; TS=2-6), or non-responders (NR; TS<2) to each mood-stabilizer were analyzed. Linear regression was computed using the FAST global score as the dependent variable. RESULTS: DUI and FAST scores showed no statistically significant correlation. Patients with a longer DUI showed poorer response to lithium (Z=-3.196; p<0.001), but not to valproate or lamotrigine. Response to lithium (β=-1.814; p<0.001), number of hospitalizations (β=0.237; p<0.001), and illness duration (β=0.160; p=0.028) were associated with FAST total scores. GR to lithium was associated with better global functioning compared to PR or NR [H=27.631; p<0.001]. LIMITATIONS: The retrospective design could expose our data to a recall bias. Also, only few patients were on valproate or lamotrigine treatment. CONCLUSIONS: Poor functioning in BD could be the result of multiple affective relapses, rather than a direct effect of DUI. A timely diagnosis with subsequent effective prophylactic treatment, such as lithium, may prevent poor functional outcomes in real-world patients with BD.
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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 | 0.001 |
| 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".