Systematic Review and Meta-analysis on the Efficacy of Cefixime For Treating Gonococcal Infections
Bibliographic record
Abstract
BACKGROUND: is known to have developed a high level of resistance against different classes of antimicrobials. Patients with coagulation disorders where intramuscular injections are contraindicated, oral cefixime in combination therapy can be utilized as an alternative regimen. Cefixime in combination with another macrolide might be considered as an alternative treatment option. The aim of this systematic review is to assess the efficacy of 400 mg cefixime against a range of comparator drugs. METHODOLOGY: Extensive literature search for randomized controlled trials was performed using Medline, Cochrane Registry of Controlled Trials, Embase, and Clinical trials registers. The trials assessed the efficacy of cefixime against a range of comparator drugs. Primary outcome of the study was the clinical resolution of signs and symptoms and negative culture at the end of follow-up period. RESULTS: After screening for a total of 1184, only 8 studies were eligible for a meta-analysis. Risk ratio random effects model was used with a 95% confidence interval (CI). The pooled efficacy of Cefixime was at 97% at 95 CI 1.01 (0.98, 1.05). No statistically significant difference was found between oral cefixime and comparator drugs. CONCLUSION: A total of 11 studies were included following a review of 1184 publications. 8 randomized controlled trials for 400 mg oral cefixime were included in meta-analysis. Despite a high grade of evidence, a high risk of bias was found among studies. Hence, more high quality randomized controlled trials on cefixime needs to be performed in future to guide the treatment of gonococcal infections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.044 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".