Fluid Status Changes During the Transition in Infants of Diabetic Mothers.
Bibliographic record
Abstract
Abstract BackgroundIn animal and human neonates, expansion of the extracellular fluid volume is associated with “wet” lung and poor respiratory outcomes.MethodsTo define fluid status changes during the transition from fetal to neonatal life in infants of diabetic mothers (IDM), we conducted a single centre (Policlinico Abano Terme, Abano Terme, Italy) study of 66 IDM and a 1:2 matched control group from January 1 to September 30, 2020. Fluid status changes were assessed by computing Δ Hct from umbilical cord blood at birth and capillary heel Hct at 48h, accounting for body weight decrease.ResultsIDM presented with significantly lower cord blood Hct levels in comparison to controls (47.33±4.52 vs 50.03±3.51%, p<0.001), mainly if delivered by elective cesarean section (45.01±3.77 vs 48.43±3.50%, p=0.001). Hct levels at 48h were comparable (55.18±5.42 vs 54.62±7.41%, p=0.703), concurrently with similar body weight decrease (-217.21±113.34 vs-217.51±67.28 g, p=0.614). This supports significantly higher ∆ Hct in IDM (5.13±5.24 vs 7.29±6.48, p<0.01) and extra circulating fluid loss of 2-3%.ConclusionGestational diabetes is associated with an excess of circulating fluids during the transition from fetal to neonatal life, challenging the current assumption that is per se at risk of wet lung.
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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 | 0.001 |
| 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 | 0.000 |
| 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".