Clinical Efficacy and Safety of Ceftriaxone in Surgical Prophylaxis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction Adequate antimicrobial monitoring helps identify the changing pattern of infection prevention postoperatively. The review aims at assessing the efficacy and safety of prophylactic ceftriaxone in surgical site infection. Materials and Methods The review followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A systematic search was conducted in PubMed, EMBASE, and CINAHL databases. Randomized control trials, published till December 2022 in English, studying only preoperative ceftriaxone, and focusing on general surgical procedures were included. Meta-analysis was done using review manager software. Results Of the 2961 articles, nine were included in the review. Elevated gram-positive (33%) and gram-negative (67%) isolates were observed from the surgical site post-prophylaxis. Surgical site infection was developed in 53 (3.41%) patients in the ceftriaxone group and 108 (6.9%) patients in the comparator groups [OR 0.47 (95% CI: 0.33-0.65), p <0.0001]. Adverse events were assessed in six studies, from which 111 (21.4%) and 163 (31.2%) patients in the intervention and comparator groups developed the same [RR: 0.56 (95% CI: 0.31-1.01), p=0.06]. An overall estimate of [MD: -1.12 (95%CI: -1.36 to -0.89), p<0.00001)] was obtained on assessing hospital stays in the included articles. Conclusion The evidence generated identified various microbial isolates from the infected sites. The drug assured its efficacy profile in surgical prophylaxis. More studies in general surgery can give a better conclusion about ceftriaxone prophylaxis.
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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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.039 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".