Bibliographic record
Abstract
12 additional cases of this condition have occurred at the same institution. Both cases involved the fluoroquinolone ciprofloxacin. Each patient previously had normal renal function. On day 5 and 7, respectively, of treatment with ciprofloxacin, serum creatinine levels were found to be significantly elevated, at 584 and 228 mmol/L, respectively (normal ranges 62 to 120 mmol/L for women and 55 to 115 mmol/L for men). The ciprofloxacin was discontinued. In the first case, prednisone was initiated, and the patient’s serum creatinine returned to baseline in 3 weeks. In the second case, no steroid was used, and by day 16 this patient’s creatinine level had also returned to normal. The rapid and full recovery in the absence of corticosteroid use in the second case raises the question of the role of corticosteroids in drug-induced acute interstitial nephritis. There have been no prospective trials evaluating whether prednisone therapy is really beneficial or necessary in this condition. Most of the impetus to use corticosteroids comes from one small study, 2 in which the number of days from peak serum creatinine to baseline was recorded. Eight patients with methicillin-induced acute interstitial nephritis received corticosteroids and 6 patients did not receive any drug therapy. In the prednisone-treated group, serum creatinine returned to baseline more rapidly than in the control group. Anecdotal case reports of corticosteroids hastening renal recovery in drug-induced acute interstitial nephritis make up the bulk of the additional evidence. 3,4
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".