Discharge and Readmissions After Ventricular Assist Device Placement in the US Pediatric Hospitals: A Collaboration in ACTION
Bibliographic record
Abstract
Discharging children on ventricular assist device (VAD) support offers advantages for quality of life. We sought to describe discharge and readmission frequency in children on VAD support. All VAD-implanted patients aged 10-21 years at Advanced Cardiac Therapies Improving Outcomes Network (ACTION) centers were identified from the Pediatric Health Information System database (2009-2018). Discharge frequency on VAD was calculated. Patients discharged on VAD were compared with those not discharged. Freedom from readmission was assessed using the Kaplan-Meier method. A total of 298 VAD-implanted patients from 25 centers were identified, of which 163 (54.7%) were discharged. Discharges increased over time (36.9% [2009-2012] vs. 59.7% [2013-2018], p = 0.001). Of 144 discharged patients with follow-up, 96 (66.7%) were readmitted for reasons other than transplantation. Heart failure was the most common reason for readmission (27.7%), followed by infection (25.8%) and hematologic concerns (16.8%). In-hospital mortality on readmission was uncommon (1.8%) and the median length of stay was 6 days (interquartile range 2-19 days). Discharge of children on VAD support has increased over time, although variability exists across centers. Readmissions are common with diverse indications; however, the risk of mortality is low. Further interventions, including collaboration in ACTION, are critical to increasing discharges and optimizing outpatient management.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".