Experience with real time continuous glucose monitoring in stabilising fluctuating glycaemia during intensive care of the preterm infant of a diabetic mother
Bibliographic record
Abstract
OBJECTIVE: The newborns of diabetic mothers suffer from perinatal complications more frequently than the newborns of healthy women. METHODS: We used for 7 days a real time continuous glucose monitoring system (RT-CGMS) to monitor glucose homeostasis and manage glucose administration in a premature newborn of a diabetic mother. RESULTS: The boy was born at 35 + 5 gestational weeks with typical signs of diabetic fetopathy. RT-CGMS revealed 2 late hypoglycaemia episodes on the 2nd and 4th days. The sensor readings correlated well with glycaemia measured in the laboratory (r = 0.908, p = 0.005). To support conclusions of this case report, we attached the data of five other preterm newborns of diabetic mothers who were later successfully treated according to the RT-CGMS data as well. CONCLUSIONS: This approach allows timely response to glycaemia instability and is applicable even in preterm infants.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".