Bibliographic record
Abstract
Although liver injury is a recognized consequence of acute iron poisoning, its description is limited to several case reports. It appears to be dose-related, however, there are published reports of severe iron poisoning without liver injury. The purpose of this study is to examine the hypothesis that this is a dose-related phenomenon and to identify the serum iron concentration of risk for this outcome. The design of this study is a retrospective review of our hospital's experience over 20 years. Extracted data included demographics, time of ingestion, highest serum iron concentration and highest hepatic transaminase activity. Iron poisoning was defined as a serum iron concentration >300 microg/dL (55 micromol/L) within 12 hours of ingestion. Hepatotoxicity was defined as a serum transaminase (either ALT or AST) >150 U/L. Severe hepatotoxicity was defined >1000U/L. Seventy-three patients (1-48 years old) participated in the study and of these patients 60 (47 female) did not have hepatotoxicity. Their serum iron concentrations were 300-704 microg/dL (55-128 micromol/L). Thirteen patients had hepatotoxicity and of these patients, nine had severe liver injury. Severe injury was associated with serum iron concentrations well in excess of 1000 microg/dL (182 micromol/L). Our data support hepatotoxicity due to iron poisoning as a dose-related phenomenon with clinically important cases unlikely with a serum iron concentration of < 700 microg/dL (128 micromol/L) within the first 12 hours. Clinically important hepatotoxicity occurs with values in excess of 1000 microg/dL (182 micromol/L).
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".