High-dose Hook Effect in a Case of Giant Prolactinoma Confounded by Acute Kidney Injury
Bibliographic record
Abstract
A 21-year-old man admitted to the hospital for acute kidney injury developed blindness 5 days after admission. Workup included magnetic resonance imaging, which was terminated prematurely due to a ball bearing/air gun pellet in his neck causing pain. His incomplete scan revealed a large sellar mass causing significant compression of the optic chiasm. Hormone testing showed low levels of IGF-1 and testosterone. A mildly elevated prolactin (PRL) level was attributed to stalk effect and decreased kidney function. For treatment, the patient underwent transsphenoidal tumor resection. Unexpectedly, pituitary immunohistochemistry revealed a prolactinoma. Further inquiry corroborated a history of headache, hypogonadal symptoms, and gynecomastia. He was started on a dopamine agonist with improvement in his vision and hormone levels; however, PRL was further increased. In retrospect, the mildly elevated PRL on initial testing was caused by the high-dose hook effect whereby excessively high PRL levels result in erroneously low measurements by immunoassays. Thus, in patients presenting with large sellar masses and normal/mildly elevated PRL, the sample should be diluted to exclude high-dose hook effect and ensure an accurate level. In addition, questioning of metallic fragments in plain language may help prevent magnetic resonance imaging injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".