Kangaroo mother care had a protective effect on the volume of brain structures in young adults born preterm
Bibliographic record
Abstract
AIM: The protective effects of Kangaroo mother care (KMC) on the neurodevelopment of preterm infants are well established, but we do not know whether the benefits persist beyond infancy. Our aim was to determine whether providing KMC in infancy affected brain volumes in young adulthood. METHOD: Standardised cognitive, memory and motor skills tests were used to determine the brain volumes of 20-year-old adults who had formed part of a randomised controlled trial of KMC versus incubator care. Multivariate analysis of brain volumes was conducted according to KMC exposure. RESULTS: The study comprised 178 adults born preterm: 97 had received KMC and 81 were incubator care controls. Bivariate analysis showed larger volumes of total grey matter, basal nuclei and cerebellum in those who had received KMC, and the white matter was better organised. This means that the volumes of the main brain structures associated with intelligence, attention, memory and coordination were larger in the KMC group. Multivariate lineal regression analysis demonstrated the direct relationship between brain volumes and duration of KMC, after controlling for potential confounders. CONCLUSION: Our findings suggest that the neuroprotective effects of KMC for preterm infants persisted beyond childhood and improved their lifetime functionality and quality 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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".