Continuing Care For Critically Ill Children Beyond Hospital Discharge: Current State of Follow-up
Bibliographic record
Abstract
OBJECTIVES: Survivors of the PICU face long-term morbidities across health domains. In this study, we detail active PICU follow-up programs (PFUPs) and identify perceptions and barriers about development and maintenance of PFUPs. METHODS: A web link to an adaptive survey was distributed through organizational listservs. Descriptive statistics characterized the sample and details of existing PFUPs. Likert responses regarding benefits and barriers were summarized. RESULTS: One hundred eleven respondents represented 60 institutions located in the United States (n = 55), Canada (n = 3), Australia (n = 1), and the United Kingdom (n = 1). Details for 17 active programs were provided. Five programs included broad PICU populations, while the majority were neurocritical care (53%) focused. Despite strong agreement on the need to assess and treat morbidity across multiple health domains, 29% were physician only programs, and considerable variation existed in services provided by programs across settings. More than 80% of all respondents agreed PFUPs provide direct benefits and are essential to advancing knowledge on long-term PICU outcomes. Respondents identified "lack of support" as the most important barrier, particularly funding for providers and staff, and lack of clinical space, though successful programs overcome this challenge using a variety of funding resources. CONCLUSIONS: Few systematic multidisciplinary PFUPs exist despite strong agreement about importance of this care and direct benefit to patients and families. We recommend stakeholders use our description of successful programs as a framework to develop multidisciplinary models to elevate continuity across inpatient and outpatient settings, improve patient care, and foster collaboration to advance knowledge.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".