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Record W2044043339 · doi:10.1159/000117844

Estimation of Lithium Dose Requirement by Lithium Clearance, Serum Lithium and Saliva Lithium following a Loading Dose of Lithium Carbonate

2008· article· en· W2044043339 on OpenAlexaff
Stephen Tyrer, Paul Grof, M. Kalvar, Baron Shopsin

Bibliographic record

VenueNeuropsychobiology · 2008
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsLithium (medication)Lithium carbonateSalivaInternal medicineChemistryEndocrinologyMedicineIon

Abstract

fetched live from OpenAlex

Renal lithium clearance and the serum lithium levels following a single oral loading dose of lithium were used as measures to predict lithium dose requirement during long-term maintenance at 3 different psychiatric centers in North America. Saliva lithium values were also investigated at one of the centers. The correlation between lithium clearance and the 17-hour serum lithium level, and subsequent dosage was high; the mean correlation co-efficient from the 3 centers being 0.84 for renal lithium clearance and 0.75 for both the 17-hour and 10-hour serum lithium levels. These tests can therefore be recommended as a guide to estimate lithium dose requirement in patients starting lithium maintenance treatment although absolute reliance should not be placed on the prediction formulae obtained. The correlation between saliva lithium and eventual dosage was poor and of little predictive value.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.279
Teacher spread0.260 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations14
Published2008
Admission routes1
Has abstractyes

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