Limited adherence to growth hormone replacement in patients with traumatic brain injury
Bibliographic record
Abstract
Background: Growth hormone deficiency is a recognized consequence of traumatic brain injury. The aim of this study was to determine adherence to human growth hormone therapy among patients with traumatic brain injury compared with patients with hypothalamic or pituitary disease. Methods: A retrospective chart review of patients with traumatic brain injury referred for growth hormone stimulation testing since December 2013. Within the same electronic medical record, patients who were started on human growth hormone for aetiologies other than traumatic brain injury were reviewed. Adherence to therapy at 1-year follow-up was compared. Results: Of the patients with traumatic brain injury, 12/23 (52%) returned for follow-up at 1 year to continue human growth hormone treatment, whereas 11/23 (48%) did not return at 1 year. Amongst the patients with non-traumatic brain injury: 25/29 (86%) continued human growth hormone treatment, vs 4/29 (14%) who did not return. A higher proportion of patients with non-traumatic brain injury continued human growth hormone treat-ment; ?2 (1, n?=?52)p?=?7.238, p?=?0.007. Conclusion: There may be differences in the patient-perceived benefits of human growth hormone between these patient populations. However, it is important to consider the potential influences of cognitive and psychosocial dysfunction that can occur in patients with brain injuries.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".