Ceftriaxone-Induced Immune Hemolytic Anemia
Bibliographic record
Abstract
OBJECTIVES: To describe a case of ceftriaxone-induced immune hemolytic anemia (CIIHA) in a 6 year-old boy with sickle cell disease (SCD) and perform a systematic literature review to delineate the clinical and laboratory features of this condition. DATA SOURCES: EMBASE (1947-January 2014), MEDLINE (1946-January 2014), and databases from the US Food and Drug Administration and Health Canada were searched, using anemia, hemolytic anemia, hemolysis, and ceftriaxone as search terms. Additional references were identified from a review of literature citations. STUDY SELECTION AND DATA EXTRACTION: All case reports and observational studies describing clinical and laboratory features of CIIHA were included. DATA SYNTHESIS: A total of 37 eligible reports of CIIHA were identified, including our index case, and 70% were children. Mortality was 30% in all age groups and 64% in children. The majority of patients had underlying conditions (70%), of which SCD was most commonly reported. Previous ceftriaxone exposure was reported in 65%. Common features included elevated lactate dehydrogenase (70%); early, new-onset hemoglobinuria (59%); acute renal failure (46%); positive direct antibody testing (70%); and anticeftriaxone antibodies (68%). Also, 32% had a preceding, unrecognized, hemolytic episode associated with ceftriaxone. SUMMARY: Given the common use of ceftriaxone worldwide, knowledge of CIIHA, which often goes undiagnosed until late in the course, is essential for clinicians. Based on the findings of this review, we suggest obtaining past history of ceftriaxone exposures and screening for new-onset hemoglobinuria during ceftriaxone therapy in selected patients as potential methods for early diagnosis of this rare but potentially fatal condition.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".