Allergic Cross-Sensitivity between Penicillin and Carbapenem Antibiotics
Bibliographic record
Abstract
Objective: To review the literature evaluating the cross-hypersensitivity between carbapenem and penicillin antibiotics. Data Sources: Primary literature was accessed through MEDLINE (1980–June 2004), EMBASE (1980–December 2004), International Pharmaceutical Abstracts, PubMed, and references of reviewed articles. Key search terms were carbapenem, imipenem, meropenem, ertapenem, drug hypersensitivity, and penicillin allergy. Study Selection and Data Extraction: All articles describing clinical studies involving the use of carbapenem antibiotics in patients allergic to penicillin were reviewed. Data Synthesis: Four studies assessed carbapenem hypersensitivity in penicillin-allergic patients. Original estimates deemed the cross-reactivity to be 50% based on skin testing in a small number of patients; however, 3 more recent retrospective analyses indicate the overall incidence to be approximately 10%. The retrospective nature and presence of confounding factors in the more recent studies make it difficult to apply the lower estimates of carbapenem cross-sensitivity to a general patient population. The majority of cross-reactivity reactions reported was the development of a rash or hives. Conclusions: With minimal data available, the incidence of allergic reaction to carbapenem antibiotics in patients with self-reported penicillin allergy is likely less than the original skin test–determined estimates of 50%. However, caution should be used in patients with previously reported anaphylactic reactions to penicillin. A detailed allergy history is important in determining the clinical consequences of the potential cross-reactivity of carbapenem antibiotics in penicillin-allergic patients.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".