Acute interstitial nephritis with acetaminophen and alcohol intoxication
Bibliographic record
Abstract
Drug-induced acute interstitial nephritis (AIN) represents a growing cause of renal failure in current medical practice. While antimicrobials and non-steroidal anti-inflammatory drugs are typically associated with drug-induced AIN, few reports have been made on the involvement of other analgesics. We report our experience in managing a 17-year-old female with AIN and subsequent renal injury following an acetaminophen overdose in conjunction with acute alcohol intoxication. It is well established that acetaminophen metabolism, particularly at high doses, produces reactive metabolites that may induce renal and hepatic toxicity. It is also plausible however, that such reactive species could instead alter renal peptide immunogenicity, thereby inducing AIN. In the following report, we review a possible mechanism for the acetaminophen-induced AIN observed in our patient and also discuss the potential involvement of acute alcohol ingestion in disease onset. The objective of our report is to increase awareness of healthcare professionals to the potential involvement of these commonly used agents in AIN pathogenesis.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".