Growth hormone deficiency testing and treatment following mild traumatic brain injury
Bibliographic record
Abstract
Pituitary dysfunction, specifically growth hormone (GH) deficiency, can occur following traumatic brain injury. Our objective was to characterize the prevalence of GH deficiency (GHD) testing and response to recombinant human GH (rhGH) treatment in adults with persistent symptoms following mild traumatic brain injury (mTBI) referred for assessment of pituitary dysfunction. A retrospective chart review was conducted of patients seen at an outpatient brain injury clinic with a diagnosis of mTBI and persistent post-concussive symptoms who were referred to endocrinology. Clinical assessments of symptoms were collected. Investigations and results of GHD were collected, including initiation of rhGH treatment and treatment response. Of the 253 patients seen in both brain injury and endocrinology clinics, 97 with mTBI were referred for investigation of pituitary dysfunction and 73 (75%) had dynamic testing for assessment of GHD. Of the 26 individuals diagnosed with GHD, 23 (88%) started rhGH. GH therapy was inconsistently offered based on interpretation of GH dynamic testing results. Of those who started rhGH, 18 (78%) had a useful treatment response. This study suggests that clinical management of these patients is varied, highlighting a need for clear guidelines for the diagnosis and management of GHD following mTBI.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".