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Record W3010134125 · doi:10.1007/s40266-020-00755-0

Frailty and Co-Prescribing of Potentially Interacting Drugs in New Users of Warfarin

2020· article· en· W3010134125 on OpenAlexaboutno aff
Milka Hauta‐aho, Simo Teperi, Maarit Jaana Korhonen, J. Simon Bell, Nicholas Farinola, Sally Johns, Sepehr Shakib, Risto Huupponen

Bibliographic record

VenueDrugs & Aging · 2020
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
FundersTurun YliopistoRoyal Adelaide Hospital
KeywordsMedicineWarfarinPharmacotherapyIntensive care medicineDrugPharmacologyAtrial fibrillationInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Warfarin is underutilised in frail older people because of the fear of bleeding complications. Drug interactions are an independent bleeding risk factor. However, the extent to which potential drug interactions are taken into account at warfarin therapy initiation in frail patients is not known. OBJECTIVE: The objective of this study was to investigate the use of potentially interacting drugs increasing the bleeding risk before and after warfarin initiation in frail and non-frail patients. METHODS: We conducted an observational study including inpatients aged ≥ 60 years initiated on warfarin in a tertiary hospital in Adelaide, South Australia. Frailty status was assessed with the Reported Edmonton Frail Scale. Medication charts were reviewed before and after warfarin initiation. RESULTS: In total, 151 patients (102 non-frail and 49 frail) were included. Before warfarin initiation, the use of clopidogrel and acetaminophen was more common in frail patients compared with non-frail patients (25.5% vs 10.2%, p = 0.0135, 63.8% vs 35.7% p = 0.0014, respectively). The use of non-steroidal anti-inflammatory drugs, 9.2% in non-frail patients and 6.4% in frail patients before warfarin initiation, was completely stopped after warfarin initiation in both groups. The use of antiplatelet drugs decreased from 56.1% in non-frail patients and 66.0 % in frail patients to 12.2% and 14.9%, respectively. Instead, the use of drugs affecting the metabolism of warfarin or vitamin K increased in both groups. No statistically significant difference was seen in the exposure to interacting drugs between study groups after warfarin initiation. Acetaminophen, senna glycosides and cytochrome P450 2C9 inhibiting drugs were the most common interacting drugs at discharge used in 49.0%, 18.4% and 20.4% of non-frail patients and 53.2%, 29.8% and 19.1% of frail patients, respectively. CONCLUSIONS: The overall frequency of potential drug interactions was moderate and frail patients were not exposed to warfarin drug interactions more often than non-frail patients. Further studies in larger study populations are required to verify these results.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.133
GPT teacher head0.395
Teacher spread0.261 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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