Short-term Dual Therapy or Mono Therapy With Acetaminophen and Ibuprofen for Fever: A Network Meta-Analysis
Bibliographic record
Abstract
CONTEXT: There is uncertainty whether acetaminophen and ibuprofen are similar in their effects and safety when used as single or dual (alternating or combined) therapies. OBJECTIVE: To assess the comparative efficacy of acetaminophen, ibuprofen alone, alternating, or combined through a systematic review and network meta-analysis. DATA SOURCES: Medline, Embase, and CENTRAL from inception to September 20, 2023. STUDY SELECTION: Randomized trials comparing acetaminophen, ibuprofen, both alternating, and both combined, for treating children with fever. DATA EXTRACTION: Two reviewers independently screened abstracts and full texts, extracted the data, and assessed the risk of bias. We performed pairwise and network meta-analysis using the random-effects model. RESULTS: We included 31 trials (5009 children). We found that combined (odds ratio [OR], 0.19; confidence interval [CI], 0.09-0.42) and alternating therapies (OR, 0.20; CI, 0.06-0.63) may be superior to acetaminophen, whereas ibuprofen at a high dose may be comparable (OR, 0.98; CI, 0.63-1.59) in terms of proportion of afebrile children at the fourth hour. These results were similar at the sixth hour. There were no differences between ibuprofen (low or high dose), or alternating, or combined with acetaminophen in terms of adverse events. LIMITATIONS: We only evaluated the efficacy and safety during the first 6 hours. CONCLUSIONS: Dual may be superior to single therapies for treating fever in children. Acetaminophen may be inferior to combined or alternating therapies to get children afebrile at 4 and 6 hours. Compared with ibuprofen, acetaminophen was also inferior to ibuprofen alone at 4 hours, but similar at 6 hours. PROSPERO registration: CRD42016035236.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".