ArticleEvidence-based dentistry2014
Ibuprofen is superior to paracetamol for pain relief following third molar removal.
Article in Evidence-based dentistry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- The effect of pregabalin for pain after third molar surgery: a systematic review and meta-analysis.BMC anesthesiology · 2026Pooled it
- Comparison of paracetamol, ibuprofen, and diclofenac potassium for pain relief following dental extractions and deep cavity preparations.Saudi medical journal · 2017Trial
- Oral pregabalin for postoperative pain relief after third molar extraction: a randomized controlled clinical trial.Clinical oral investigations · 2016Trial
- 20 years - 20 highlights.Evidence-based dentistry · 2019Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
data sourcesThe Cochrane Oral Health Group's Trials Register, the Cochrane Central Register of Controlled Trials (CENTRAL), Medline, Embase and the metaRegister of Controlled Trials were searched with no language restrictions. STUDY SELECTION: Randomised controlled double-blinded clinical trials using the third molar model were included. DATA EXTRACTION AND SYNTHESIS: Two review authors independently and in duplicate extracted data. The proportion of patients with at least 50% pain relief (based on total pain relief (TOTPAR) and summed pain intensity difference (SPID) data) was calculated for all three drugs at both two and six hours post-dosing and meta-analysed for comparison.
resultsSeven studies involving 2241 patients were included. Two studies were considered to be at low risk of bias, three at high risk and two unclear risk of bias. Ibuprofen was found to be a superior analgesic to paracetamol at several doses, with high quality evidence suggesting that ibuprofen 400 mg is superior to 1000 mg paracetamol based on pain relief (estimated from TOTPAR data) and the use of rescue medication meta-analyses. Risk ratio (RR) for at least 50% pain relief (based on TOTPAR) at six hours was 1.47 (95% confidence interval (CI) 1.28 to 1.69; five trials) favouring 400 mg ibuprofen over 1000 mg paracetamol, RR for not using rescue medication (also favouring ibuprofen) was 1.50 (95% CI 1.25 to 1.79; four trials). For combined drug RR for at least 50% of the maximum pain relief over six hours of 1.77 (95% CI 1.32 to 2.39) (paracetamol 1000 mg and ibuprofen 400 mg) (one trial; moderate quality evidence). RR not using rescue medication 1.60 (95% CI 1.36 to 1.88) (two trials; moderate quality evidence). Adverse events were comparable between the treatment groups, but no formal analysis could be undertaken.
conclusionsThere is high quality evidence that ibuprofen is superior to paracetamol at doses of 200 mg to 512 mg and 600 mg to 1000 mg respectively based on pain relief and use of rescue medication data collected at six hours postoperatively. The majority of this evidence (five out of six trials) compared ibuprofen 400 mg with paracetamol 1000 mg, these are the most frequently prescribed doses in clinical practice. The novel combination drug is showing encouraging results based on the outcomes from two trials when compared to the single drugs.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.