A systematic review and meta-analysis comparing outcomes between using subcutaneous insulin and continuous insulin infusion in managing adult patients with diabetic ketoacidosis
Bibliographic record
Abstract
The purpose of this systematic review and meta-analysis was to synthesize the current literature to determine the safety and efficacy of using subcutaneous insulin compared to an intravenous (IV) insulin infusion in managing diabetic ketoacidosis (DKA). We searched Ovid-Medline, EMBASE, SCOPUS, BIOSIS and CENTRAL from inception to April 26, 2024. Randomized controlled trials (RCTs) and observational studies that assessed the use of subcutaneous compared to intravenous insulin for the treatment of mild to moderate DKA were included. Data extraction and quality assessment were performed by two independent reviewers and disagreements were resolved through further discussion or by a third reviewer. The Cochrane Risk of Bias tool version 2.0 was used to evaluate the RCTs and the Risk of Bias in Non-randomized Studies of Interventions (ROBINS)-I tool was used to evaluate the observational studies. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. Meta-analyses were conducted using random-effects models. We followed the PRISMA guidelines for reporting our findings. Six RCTs (245 participants) and four observational studies (8444 patients) met our inclusion criteria. Some studies showed a decreased length of stay (Mean Difference [MD] in days: -0.39; 95% CI: -2.83 to 2.08; I 2 : 0%) among individuals treated with subcutaneous insulin compared to intravenous insulin. There was no difference in the risk of all-cause mortality, time to resolution of DKA (MD in hours: 0.17; 95% confidence interval [CI]: -3.45 to 3.79; I 2 : 0%) and hypoglycemia (Risk Ratio [RR]: 1.02; 95% CI: 0.88 to 1.19; I 2 : 0%) between the two groups. Treatment of DKA with subcutaneous insulin may be a safe and effective alternative to IV insulin in selected patients. The limited available evidence underscores the need for further studies to explore optimal dosing, patient selection criteria and long-term outcomes.
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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 | 0.023 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.045 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".