A Systematic Review: Can One Prescribe Carbapenems to Patients With IgE-Mediated Allergy to Penicillins or Cephalosporins?
Bibliographic record
Abstract
BACKGROUND: Cross-reactivity between penicillins or cephalosporins and carbapenems is anticipated as all have a beta lactam ring. However, the true incidence of immunoglobulin (Ig)E-mediated cross-reactivity is not known. METHODS: A systematic review was conducted to collect and combine all published data on children and adults reported to have a clinical history of IgE-mediated hypersensitivity to a penicillin and/or cephalosporin who were subsequently given a carbapenem. Reactions were classified as proven, suspected, or possible IgE-mediated and non-IgE-mediated. RESULTS: Ten studies and 12 case reports describing 854 participants fit the study criteria. For patients with previous proven, suspected, or possible IgE-mediated penicillin reactions (N = 838), the incidence of any type of suspected hypersensitivity reaction to a carbapenem was 36/838 (4.3%; 95% confidence interval [CI], 3.1%-5.9%) and the incidence of proven (1/838), suspected (0/838), or possible (19/838) IgE-mediated reactions was 20/838 (2.4%; 95% CI, 1.6%-3.7%). Of the subset of patients with positive penicillin skin tests (n = 295), only 1 had a hypersensitivity reaction (0.3%; 95% CI, .06%-1.9%), and this was a possible IgE-mediated reaction. For patients with previous proven, suspected, or possible IgE-mediated cephalosporin reactions (N = 12), the incidence of any type of hypersensitivity reaction to a carbapenem was 3/12 (25%); this included 2 non-IgE-mediated reactions and 1 possible IgE-mediated reaction. CONCLUSIONS: The cross-reactivity between penicillins and carbapenems for IgE-mediated reactions is very low, but caution is still advised. Cross-reactivity rates may be higher between cephalosporins and carbapenems; however, minimal data are available.
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 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 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".