Insulin Infusion Dosing in Pediatric Diabetic Ketoacidosis: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
In children with diabetic ketoacidosis (DKA), insulin infusions are the mainstay of treatment; however, optimal dosing remains unclear. Our objective was to compare the efficacy and safety of different insulin infusion doses for the treatment of pediatric DKA. DATA SOURCES: We searched MEDLINE, EMBASE, PubMed, and Cochrane from inception to April 1, 2022. STUDY SELECTION: We included randomized controlled trials (RCTs) of children with DKA comparing intravenous insulin infusion administered at 0.05 units/kg/hr (low dose) versus 0.1 units/kg/hr (standard dose). DATA EXTRACTION: We extracted data independently and in duplicate and pooled using a random effects model. We assessed the overall certainty of evidence for each outcome using the Grading Recommendations Assessment, Development and Evaluation approach. DATA SYNTHESIS: = 190 participants). In children with DKA, low-dose compared with standard-dose insulin infusion probably has no effect on time to resolution of hyperglycemia (mean difference [MD], 0.22 hr fewer; 95% CI, 1.19 hr fewer to 0.75 hr more; moderate certainty), or time to resolution of acidosis (MD, 0.61 hr more; 95% CI, 1.81 hr fewer to 3.02 hr more; moderate certainty). Low-dose insulin infusion probably decreases the incidence of hypokalemia (relative risk [RR], 0.65; 95% CI, 0.47-0.89; moderate certainty) and hypoglycemia (RR, 0.37; 95% CI, 0.15-0.80; moderate certainty), but may have no effect on rate of change of blood glucose (MD, 0.42 mmol/L/hr slower; 95% CI, 1 mmol/L/hr slower to 0.18 mmol/L/hr faster; low certainty). CONCLUSIONS: In children with DKA, the use of low-dose insulin infusion is probably as efficacious as standard-dose insulin, and probably reduces treatment-related adverse events. Imprecision limited the certainty in the outcomes of interest, and the generalizability of the results is limited by all studies being performed in a single country.
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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 | 0.005 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.026 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".