Niveles de cortisol en la saliva y séricos en recién nacidos
Bibliographic record
Abstract
INTRODUCTION: Given that serum cortisol level interpretation in newborn infants (NBIs) is hard, the objective of this study was to correlate baseline salivary and serum cortisol levels and to describe salivary cortisol levels in the first month of life. POPULATION AND METHODS: Descriptive, prospective, longitudinal, and correlational study. Term NBIs were selected from the Division of Neonatology of Hospital Nacional Profesor Alejandro Posadas in 2014. Cortisol was measured in saliva specimens while cortisol, cortisol-binding globulin, and albumin were measured in blood specimens. A linear correlation was performed to relate serum and salivary cortisol levels; Friedman test was conducted to compare cortisol levels during the first month of life, and the difference was used to analyze the performance of values equal to or lower than the first quartile. RESULTS: Fifty-five NBIs were studied. Serum cortisol: 7.65 (1.0-18.1 gg/dL); salivary cortisol: 35.88 (5.52-107.64 mmol/L); cortisol-binding globulin: 22.07 (16.5-33.0 gg/mL), expressed as median and range. The correlation coefficient between serum and salivary cortisol was 0.54, P = 0.001. Cortisol performance during the first month of life showed no statistically significant differences, and the difference between the second and the first specimen of values equal to or lower than the first quartile increased in 10 out of 12 patients. CONCLUSION: The measurement of cortisol in saliva reflects serum cortisol levels in normal NBIs. Some patients had low levels of cortisol at 36 hours of life and showed a trend towards a spontaneous increase during the first month of life.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".