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Record W4321100519 · doi:10.1177/17151635231152243

Patterns of natural health product use at an outpatient heart function clinic

2023· article· en· W4321100519 on OpenAlexaffvenue
Kaitlyn Tress, Ada W. Chiu, Leanne Kwan, Wendy Gordon

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2023
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsFraser HealthRoyal Columbian Hospital
Fundersnot available
KeywordsMedicineAtrial fibrillationOutpatient clinicHealth careFamily medicinePediatricsInternal medicine

Abstract

fetched live from OpenAlex

Background: Natural health product (NHP) use is common among Canadians, but the NHPs used by outpatients with cardiovascular conditions such as atrial fibrillation and heart failure have not been identified. Objectives: Describe NHP use among outpatient cardiac patients, assess drug interactions and their potential implications and determine NHP documentation by health care providers. Methods: Telephone interviews were conducted by the main researcher with patients who attended the Cardiac Clinics at the Royal Columbian Hospital. Medication reconciliation was performed to elicit information regarding NHP use and clinic charts were used to supplement demographic information. Results: There were 119 successful interviews. Most patients were approximately 65 years old and male, were diagnosed with atrial fibrillation, had 2 to 3 queried comorbidities and took 2 cardiovascular medications. It was found that 62% of patients use NHPs, and 239 individual NHPs were identified. The most common NHPs used were vitamins and minerals (63%), especially vitamin D (13%), multivitamins (8%) and omega-3s (8%). Interactions between cardiac medications and NHPs occurred in 86% of patients. NHP use was completely documented by health care providers in 24% of patients. Conclusion: NHP use is common among patients who attend outpatient cardiac clinics. Interactions between NHPs and cardiovascular medications are prevalent and may carry specific individual patient risks. NHP documentation by health care providers is often incomplete.

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 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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.551
Threshold uncertainty score0.904

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.119
GPT teacher head0.363
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes2
Has abstractyes

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