Randomised controlled trial on the impact of kinesthetic stimulation on early somatic growth of preterm infants in Kangaroo position
Bibliographic record
Abstract
AIM: Evaluation of early growth in preterm infants receiving kinesthetic stimulation with massage in Kangaroo position or in incubator. METHODS: A cohort of 66 infants between 30 and 33 weeks of gestational age (GA), born at a university hospital in 2013 in Bogota, were randomised when eligible to intervention. We measured weight gain (g/kg/day) at five days and 15 days postrandomisation and weight at 40 weeks, according to chronological age at randomisation. RESULTS: Daily weight gain was significantly higher (p = 0.02) with kinesthetic stimulation in Kangaroo position with a growth at five days of 11.0 g/kg/day (95% CI 5.7;16.3) and at 15 days of 12.1 g/kg/day (95% CI 10.4;13.7) versus 2.1 g/kg/day (95% CI -3.1;7.4) at five days and 9.4 g/kg/day (95% CI 7.7;11.1) at 15 days in incubator. Weight at 40 weeks was higher (p = 0.05) in Kangaroo position group (2.904 g) than in incubator group (2.722 g) (95% CI 2.784;3.007). Daily weight gain according to chronological age at randomisation was higher when kinesthetic stimulation initiates before five days of life in Kangaroo position with 1.53 g/kg/day (95% CI 5.9;9.0) versus -11.9 g/kg/day (95% CI -19.0;-4.8) in incubator. CONCLUSION: Early kinesthetic stimulation in Kangaroo position reduces the initial weight loss in infants between 30-33 weeks born without major health problems.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".