Low-Dose Heparin Use and the Patency of Peripheral IV Catheters in Children: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To assess evidence from randomized controlled trials (RCTs) on the efficacy of low-dose heparin for prolonging patency of peripheral intravenous (PIV) catheters in the pediatric population. METHODS: We searched Medline, Embase, CINAHL, and Cochrane Central Register of Controlled Trials to identify studies up to June 6, 2012. Additional citations were retrieved from the bibliography of selected articles. The eligible studies were RCTs of low-dose heparin used in PIV catheters as compared with control and measured any one of the following outcomes: duration of catheter patency, infusion failure rates, or phlebitis. Data were extracted by 1 reviewer by using a standardized form and checked for accuracy by a second reviewer. Discrepancies were resolved by consensus. RESULTS: Thirteen RCTs were identified (3 RCTs of continuous infusion and 10 RCTs of intermittent flush). Catheters using heparin had longer patency (mean difference [95% confidence interval]: 26.51 hours [2.37 to 50.65], P < .001, for the infusion studies and 2.82 hours [-0.04 to 5.67], P = .05, for intermittent flush studies). Heparin usage also resulted in a lower rate of infusion failure (rate ratio [95% confidence interval]: 0.78 [0.62 to 0.99], P = .04, for the infusion studies and 0.88 [0.72 to 1.09], P = .25, for intermittent flush studies). Lower phlebitis rates were also observed with heparin usage; however, the results did not reach significance. There was no increase in heparin-related side effects noted. CONCLUSIONS: Low-dose heparin as continuous infusion in PIV catheters resulted in clinically significant benefits in terms of catheter patency and fewer episodes of infusion failures. Heparin's use in intermittent flush solutions showed minimal benefits.
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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 | 0.013 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".