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Record W2104290001 · doi:10.1136/ebm.5.3.88

Review: lithium augmentation increases treatment response in refractory depression

2000· article· en· W2104290001 on OpenAlexaff
Raymond W. Lam

Bibliographic record

VenueEvidence-Based Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWeb of scienceLithium (medication)MedicinePlaceboInternal medicineRefractory (planetary science)Depression (economics)Cochrane LibraryRandomized controlled trialDouble blindMeta-analysisGastroenterologyPathologyBiologyAlternative medicine

Abstract

fetched live from OpenAlex

(1999) J Clin Psychopharmacol 19, 427. Bauer M, Döpfmer S. . Lithium augmentation in treatment-resistant depression: meta-analysis of placebo-controlled studies. . Oct; . : . –34 . [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: In patients with refractory depression, is lithium augmentation clinically effective? Studies were identified by searching Medline (1980 to June 1997) and the Cochrane Library and by scanning the references of published reviews and standard textbooks. Studies were selected if they were double blind, placebo controlled trials that involved patients who had not responded to conventional antidepressants; accepted, operationalised diagnostic criteria for depression were used; and outcome measures included acceptable criteria for assessing response. 2 reviewers independently assessed the quality of each study (Quality Assessment Scale by Detsky) and resolved differences by consensus. Data were extracted on study population, antidepressant treatment, lithium dose, treatment duration, response criteria, and treatment response. 9 randomised controlled trials (RCTs) involving 234 patients met the inclusion … [1]: {openurl}?query=rft.jtitle%253DJournal%2Bof%2Bclinical%2Bpsychopharmacology%26rft.stitle%253DJ%2BClin%2BPsychopharmacol%26rft.aulast%253DBauer%26rft.auinit1%253DM.%26rft.volume%253D19%26rft.issue%253D5%26rft.spage%253D427%26rft.epage%253D434%26rft.atitle%253DLithium%2Baugmentation%2Bin%2Btreatment-resistant%2Bdepression%253A%2Bmeta-analysis%2Bof%2Bplacebo-controlled%2Bstudies.%26rft_id%253Dinfo%253Adoi%252F10.1097%252F00004714-199910000-00006%26rft_id%253Dinfo%253Apmid%252F10505584%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=10.1097/00004714-199910000-00006&link_type=DOI [3]: /lookup/external-ref?access_num=10505584&link_type=MED&atom=%2Febmed%2F5%2F3%2F88.atom [4]: /lookup/external-ref?access_num=000082698200006&link_type=ISI

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 armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.001

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.

Opus teacher head0.057
GPT teacher head0.362
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview · Commentary

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".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

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