Continuing paroxetine treatment reduces recurrence of major depression in the elderly
Bibliographic record
Abstract
Reynolds CF, Dew MA, Pollock BG, et al . Maintenance treatment of major depression in old age. N Engl J Med 2006;354:1130–8.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q Do paroxetine and psychotherapy reduce recurrent episodes of depression in the elderly? ### ![Graphic][5] Design: Two by two randomised controlled trial (randomisation stratified by number of episodes, use of additional pharmacotherapy, and degree of cognitive impairment). ### ![Graphic][6] Allocation: Unclear. ### ![Graphic][7] Blinding: Double blinded (for drug treatment). ### ![Graphic][8] Follow up period: Two years. ### ![Graphic][9] Setting: A university based clinic, Pittsburgh, USA; 1999 to 2005. ### ![Graphic][10] Patients: 116 people (⩾70 years old) who achieved a recovery from major depression (DSM-IV and a score of ⩾15 on the Hamilton Rating Scale for Depression and ⩾17 on the Folstein Mini-Mental State Examination) with open label paroxetine (10 mg daily initially, titrated up to 40 mg daily if necessary) and psychotherapy. A recovery was defined as a Hamilton score of 0 to 10 for three consecutive weeks, … [1]: {openurl}?query=rft.jtitle%253DNew%2BEngland%2BJournal%2Bof%2BMedicine%26rft.stitle%253DNEJM%26rft.aulast%253DReynolds%26rft.auinit1%253DC.%2BF.%26rft.volume%253D354%26rft.issue%253D11%26rft.spage%253D1130%26rft.epage%253D1138%26rft.atitle%253DMaintenance%2Btreatment%2Bof%2Bmajor%2Bdepression%2Bin%2Bold%2Bage.%26rft_id%253Dinfo%253Adoi%252F10.1056%252FNEJMoa052619%26rft_id%253Dinfo%253Apmid%252F16540613%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/external-ref?access_num=10.1056/NEJMoa052619&link_type=DOI [3]: /lookup/external-ref?access_num=16540613&link_type=MED&atom=%2Febmental%2F9%2F4%2F101.atom [4]: /lookup/external-ref?access_num=000235981700006&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif [9]: /embed/inline-graphic-5.gif [10]: /embed/inline-graphic-6.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
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".