Fluid Management Practices After Surgery for Congenital Heart Disease: A Worldwide Survey*
Bibliographic record
Abstract
OBJECTIVES: To determine common practice for fluid management after cardiac surgery for congenital heart disease among pediatric cardiac intensivists. DESIGN: A survey consisting of 17 questions about fluid management practices after pediatric cardiac surgery. Distribution was done by email, social media, World Federation of Pediatric Intensive and Critical Care Societies website, and World Federation of Pediatric Intensive and Critical Care Societies newsletter using the electronic survey distribution and collection system Research Electronic Data Capture. SETTING: PICUs around the world. SUBJECTS: Pediatric intensivists managing children after surgery for congenital heart disease. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: One-hundred eight responses from 18 countries and six continents were received. The most common prescribed fluids for IV maintenance are isotonic solutions, mainly NaCl 0.9% (42%); followed by hypotonic fluids (33%) and balanced crystalloids solutions (14%). The majority of the respondents limit total fluid intake to 50% during the first 24 hours after cardiac surgery. The most frequently used fluid as first choice for resuscitation is NaCl 0.9% (44%), the second most frequent choice are colloids (27%). Furthermore, 64% of respondents switch to a second fluid for ongoing resuscitation, 76% of these choose a colloid. Albumin 5% is the most commonly used colloid (61%). Almost all respondents (96%) agree there is a need for research on this topic. CONCLUSIONS: Our survey demonstrates great variation in fluid management practices, not only for maintenance fluids but also for volume resuscitation. Despite the lack of evidence, colloids are frequently administered. The results highlight the need for further research and evidence-based guidelines on this topic.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".