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Record W135713322

An evaluation of pharmacist and health food store retailer's knowledge regarding potential drug interactions associated with St. John's wort.

2010· article· en· W135713322 on OpenAlexaffabout
Mitchell Levine

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinePharmacistInterviewMedical prescriptionProduct (mathematics)ChemistDrugAlternative medicineHerbal supplementHerbFamily medicinePharmacyTraditional medicinePsychiatryPharmacologyMedicinal herbs
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Natural health products (NHP) are increasingly being used by patients concomitantly receiving prescription drugs, which can result in potentially serious drug-herb interactions. This is particularly true for St. John's wort. OBJECTIVE: This study was conducted to evaluate pharmacists and natural health product retailers' knowledge on this topic. METHODS: An interviewer approached 24 pharmacists and 6 natural health product retailers to obtain information regarding St. John's wort. If asked, the interviewer indicated that they were currently using cyclosporine to treat a problem of proteinuria. The response of the pharmacist or NHP retailer to a series of questions was recorded after the encounter. RESULTS: 90% of respondents indicated that St. John's wort was useful for treating depression. Two-thirds of the respondents required prompting by the interviewer before providing any comments pertaining to safety. 60% of the respondents inquired about concurrent medications and 40% made statements regarding potential drug-herb interactions. CONCLUSION: Despite the potential for a serious drug-herb interaction involving St. John's wort and cyclosporine, less than half of the pharmacists and natural health product retailers that were encountered in the study addressed this topic with the prospective patient/client. Individuals selling natural health products need to communicate more information to their patients/clients regarding potential drug-herb interactions.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.109
GPT teacher head0.378
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2010
Admission routes2
Has abstractyes

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