Extensive pulmonary involvement with raltegravir-induced DRESS syndrome in a postpartum woman with HIV
Bibliographic record
Abstract
An 18-year-old postpartum woman with HIV, on lamivudine-zidovudine, lopinavir-ritonavir and raltegravir, presented with a 1-week history of rash and fevers. Initially admitted to obstetrics and gynaecology service for treatment of possible endometritis, she was transferred to the HIV medicine service for high fever, respiratory distress, hypotension and tachycardia. On admission, she was febrile (102°F) with findings of cervical and submandibular lymphadenopathy, diffuse morbilliform rash, generalised pruritus, facial oedema, and oedematous hands and feet. Consultations to various specialty services were initiated to rule out infectious, dermatological, rheumatological and drug-induced aetiologies. On the fourth day of hospitalisation, laboratory findings of significant eosinophilia and hepatitis (alanine aminotransferase 147 IU/L and aspartate aminotransferase 124 IU/L), in conjunction with the identification of the timing of medication use, led to a diagnosis of DRESS (drug reaction with eosinophilia and systemic symptoms) syndrome secondary to raltegravir. After discontinuing raltegravir and starting prednisone, her DRESS symptoms completely resolved.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".