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Record W2802447724 · doi:10.18433/jpps29854

Clinical Outcomes of Aspirin Interaction with Other Non-Steroidal Anti-Inflammatory Drugs: A Systematic Review

2018· review· en· W2802447724 on OpenAlexafffundvenue
Zuhair Alqahtani, Fakhreddin Jamali

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2018
Typereview
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsRofecoxibCelecoxibAspirinNaproxenMeloxicamMedicineIbuprofenDiclofenacPharmacologyAcetaminophenCyclooxygenaseInternal medicineChemistry

Abstract

fetched live from OpenAlex

PURPOSE: Concomitant use of some non-Aspirin nonsteroidal anti-inflammatory drugs (NANSAIDs) reduces the extent of platelet aggregation of Aspirin (acetylsalicylic acid). This is while many observational studies and clinical trials suggest that Aspirin reduces cardiovascular (CV) risk attributed to the use of NANSAIDs. Thus, the therapeutic outcome of the interaction needs to be assessed. METHODS: We searched various databases up to October 2017 for molecular interaction studies between the drugs and long-term clinical outcomes based on randomized clinical trials and epidemiological observations that reported the effect estimates of CV risks (OR, RR or HR; 95% CI) of the interacting drugs alone or in combinations. Comparisons were made between outcomes after Aspirin alone, NANSAIDs alone and Aspirin with naproxen, ibuprofen, celecoxib, meloxicam, diclofenac or rofecoxib. RESULTS: In total, 32 eligible studies (20 molecular interactions studies and 12 observational trials) were found. Conflicting in vitro/in vivo/ex vivo platelet aggregation data were found for ibuprofen, naproxen and celecoxib. Nevertheless, for naproxen, the interaction at the aggregation level did not amount to a loss of cardioprotective effects of Aspirin. Similarly, for ibuprofen, the results overwhelmingly suggest no negative clinical CV outcomes following the combination therapy. Meloxicam and rofecoxib neither interacted with Aspirin at the level of platelet aggregation nor altered clinical outcomes. The clinical outcomes data for celecoxib and diclofenac are in conflict. CONCLUSION: Aspirin appears to maintain its cardioprotective effect in the presence of naproxen, ibuprofen, meloxicam and rofecoxib. The limited available data suggest that the effect of interaction at the platelet aggregation level may dissipate shortly, or the reduced platelet aggregation yielded by the interaction may be sufficient for cardioprotection; i.e., no need for near complete aggregation. In addition, cardioprotective effect of Aspirin, despite reduced platelet aggregation caused by NANSAIDs, may be through its involvement in other mechanisms such as the renin-angiotensin system and/or metabolism of arachidonic acid to biologically active compounds mediated by cytochrome P450. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

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)0.004
metaresearch head score (Gemma)0.019
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 score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0080.011
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.116
GPT teacher head0.487
Teacher spread0.371 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations22
Published2018
Admission routes3
Has abstractyes

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