Longitudinal Measurements of Oxygen Consumption in Growing Infants during the First Weeks after Birth: Old Data Revisited
Bibliographic record
Abstract
BACKGROUND: In a study conducted in 1966-1969, longitudinal measurements were made of the metabolic rate in growing infants. Statistical methods for analyzing longitudinal data weren't readily accessible at that time. OBJECTIVES: To measure minimal rates of oxygen consumption (V·O2, ml/min) in growing infants during the first postnatal weeks and to determine the relationships between postnatal increases in V·O2, body size and postnatal age. METHODS: We studied 61 infants of any birth weight or gestational age, including 19 of very low birth weight. The infants, nursed in incubators, were clinically well and without need of oxygen supplementation or respiratory assistance. Serial measures of V·O2 using a closed-circuit method were obtained at approximately weekly intervals. V·O2 was measured under thermoneutral conditions with the infant asleep or resting quietly. Data were analyzed using mixed-effects models. RESULTS: During early postnatal growth, V·O2 rises as surface area (m(2))(1.94) (standard error, SE 0.054) or body weight (kg)(1.24) (SE 0.033). Multivariate analyses show statistically significant effects of both size and age. Reference intervals (RIs) for V·O2 for fixed values of body weight and postnatal age are presented. As V·O2 rises with increasing size and age, there is an increase in the skin-operative environmental temperature gradient (T skin-op) required for heat loss. Required T skin-op can be predicted from surface area and heat loss (heat production minus heat storage). CONCLUSIONS: Generation of RIs for minimal rates of V·O2 in growing infants from the 1960s was enabled by application of mixed-effects statistical models for analyses of longitudinal data. Results apply to the precaffeine era of neonatal care.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".