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Record W2510448714 · doi:10.18433/j3b897

Onset of Action and Efficacy of Ibuprofen Liquigel as Compared to Solid Tablets: A Systematic Review and Meta-Analysis

2016· review· en· W2510448714 on OpenAlexaffvenue
Hanan Al Lawati, Fakhreddin Jamali

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2016
Typereview
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIbuprofenMeta-analysisMedicinePain reliefSignificant differenceOnset of actionAnalgesicSystematic reviewClinical trialClinical efficacyAnesthesiaMEDLINEInternal medicinePharmacologyChemistry

Abstract

fetched live from OpenAlex

PURPOSE: Ibuprofen liquigel has been believed to provide faster analgesic effect. However, comparative studies evaluating the efficacy of liquigel versus regular tablets are not available. Hence, we carried out a systematic review and a meta-analysis to compare the onset of action and efficacy of over-the-counter doses of ibuprofen liquigel (IBULG) vs ibuprofen tablets (IBUT). Methods. Published clinical trials of IBULG and IBUT were identified through a systematic search of various data bases up to October, 2015. RESULTS: In total 18 eligible studies on IBUT and 4 on IBULG were found. There was no significant difference in the median time to the first perceptible pain relief or the proportion of patients with more than 50% pain relief between the two products. However, IBULG yielded significantly greater odd ratios in meaningful pain relief at 60, 90 and 120 min, but not at 30 min, as compared with IBUT. Conclusion. The available evidence, although not overwhelming, suggest a faster onset of analgesia for liquigel as compared with tablets. 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 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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.852
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.238
GPT teacher head0.525
Teacher spread0.287 · 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 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

Citations13
Published2016
Admission routes2
Has abstractyes

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