Bibliographic record
Abstract
Studies on head injury-induced pituitary dysfunction are limited in number and conflicting results have been reported.To further clarify this issue, 29 consecutive patients (24 males), with severe (n = 21) or moderate (n = 8) head trauma, having a mean age of 37 ± 17 years were investigated in the immediate post-trauma period.All patients required mechanical ventilatory support for 8-55 days and were enrolled in the study within a few days before ICU discharge.Basal hormonal assessment included measurement of cortisol, corticotropin, free thyroxine (fT4), thyrotropin (TSH), testosterone (T) in men, estradiol (E2) in women, prolactin (PRL), and growth hormone (GH).Cortisol and GH levels were measured also after stimulation with 100 µg human corticotropin releasing hormone (hCRH) and 100 µg growth hormone releasing hormone (GHRH), respectively.Cortisol hyporesponsiveness was considered when peak cortisol concentration was less than 20 µg/dl following hCRH.TSH deficiency was diagnosed when a subnormal serum fT4 level was associated with a normal or low TSH.Hypogonadism was considered when T (males) or E2 (women) were below the local reference ranges, in the presence of normal PRL levels.Severe or partial GH deficiencies were defined as a peak GH below 3 µg/l or between 3 and 5 µg/l, respectively, after stimulation with GHRH.Twenty-one subnormal responses were found in 15 of the 29 patients (52%) tested; seven (24%) had hypogonadism, seven (24%) had cortisol hyporesponsiveness, five (17%) had hypothyroidism, and two patients (7%) had partial GH deficiency.These preliminary results suggest that a certain degree of hypopituitarism occurs in more than 50% of patients with moderate or severe head injury in the immediate post-trauma period, with cortisol hyporesponsiveness and hypogonadism being most common.Further studies are required to elucidate the pathogenesis of these abnormalities and to investigate whether they affect long-term morbidity.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".