Cognitive therapy in addition to standard care was more cost effective than standard care alone in bipolar disorder
Bibliographic record
Abstract
Lam DH, McCrone P, Wright K, et al. Cost-effectiveness of relapse-prevention cognitive therapy for bipolar disorder: 30-month study. Br J Psychiatry 2005;186:500–6. [OpenUrl][1][Abstract/FREE Full Text][2] Q In patients with bipolar disorder, is the addition of cognitive therapy to standard care cost effective? Clinical impact ratings Psychiatry ★★★★★★☆ ### ![Graphic][3] Design: randomised (allocation concealed*), blinded (outcome assessors),* controlled trial with 30 months’ follow up. ### ![Graphic][4] Setting: Maudsley and Bethlem NHS Trust, London, UK. ### ![Graphic][5] Patients: 103 outpatients who were 18–70 years of age (mean age 44 y, 56% women), had DSM-IV bipolar I disorder, relapsed frequently despite the use of mood stabilisers (ie, ⩾2 episodes in previous 2 y or ⩾3 episodes in 5 y), and did not currently fulfil criteria for a bipolar episode. Exclusion criteria: actively suicidal (Beck Depression Inventory suicide item scored 3) or met criteria for substance use disorder. ### ![Graphic][6] Intervention: 51 patients received cognitive therapy plus standard care, and 52 patients received standard care alone. ### ![Graphic][7] Outcomes: number of bipolar free days. Costs related to cognitive therapy and contact with mental … [1]: {openurl}?query=rft.jtitle%253DThe%2BBritish%2BJournal%2Bof%2BPsychiatry%26rft.stitle%253DBr.%2BJ.%2BPsychiatry%26rft.issn%253D0007-1250%26rft.aulast%253DLAM%26rft.auinit1%253DD.%2BH.%26rft.volume%253D186%26rft.issue%253D6%26rft.spage%253D500%26rft.epage%253D506%26rft.atitle%253DCost-effectiveness%2Bof%2Brelapse-prevention%2Bcognitive%2Btherapy%2Bfor%2Bbipolar%2B%2Bdisorder%253A%2B30-month%2Bstudy%26rft_id%253Dinfo%253Adoi%252F10.1192%252Fbjp.186.6.500%26rft_id%253Dinfo%253Apmid%252F15928361%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bjprcpsych&resid=186/6/500&atom=%2Febmed%2F11%2F2%2F60.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif [6]: /embed/inline-graphic-4.gif [7]: /embed/inline-graphic-5.gif
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".