High‐dose calcium reduces early‐onset hyperkalemia in extremely preterm neonates
Bibliographic record
Abstract
BACKGROUND: Early-onset hyperkalemia often occurs in extremely preterm infants during a few days after birth. While there are several treatments for hyperkalemia, calcium infusion to reduce plasma potassium concentrations remains controversial. The purpose of this study is to investigate whether a high dosage of calcium reduces early-onset hyperkalemia. METHODS: Extremely low-birthweight neonates born at 22-25 weeks' gestation were enrolled. We analyzed data using multivariate regression analysis and performed a retrospective cohort study with patients divided into two groups according to the dosage of calcium in their initial infusion. RESULTS: A total of 103 patients were eligible. Early-onset hyperkalemia was observed in 27 patients. The dosage of calcium gluconate during 24 h after birth was the only independent factor affecting early-onset hyperkalemia. The maximum plasma potassium concentration during 72 h after birth was negatively correlated with the dosage of calcium. High-dose calcium reduced occurrences of hyperkalemia and hypoglycemia caused by insulin infusion given for treatment of hyperkalemia, without increasing the risk of any other complications. CONCLUSIONS: Infusion of calcium gluconate may reduce early-onset hyperkalemia in a dose-dependent manner.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".