Prevalence and Characteristics of New Mental Health Interventions in PICU Survivors
Bibliographic record
Abstract
Abstract Background and Objectives As survival after pediatric critical illness improves, attention has shifted to post-intensive care syndrome (PICS-p) and specifically the long-term mental health of PICU survivors, who face elevated risks including posttraumatic stress, anxiety, and depression. However, little is known about actual patterns of post-discharge mental health care. The objective of this study is to examine the rates of mental health follow-up and psychopharmacology use among publicly insured children following PICU hospitalization, compared with those hospitalized on acute care wards, using a multi-state administrative dataset. Methods We performed a retrospective cohort study using 2016–2021 Medicaid claims across 10–12 states. The cohort comprised children aged 3–18 years discharged home after an index hospitalization and excluded perinatal admissions and hospitalizations primarily for mental health or traumatic brain injury. The primary exposure was pediatric intensive care unit (PICU) admission. The primary outcome was new mental health visits within one-year post-discharge. Secondary outcomes included visit provider type, visit diagnoses category, and new psychiatric prescriptions. We report descriptive statistics and measure associations with covariates using logistic regression. Results Among 144,763 Medicaid-insured pediatric hospitalizations (20.7% with PICU stays), only 8.8% initiated new mental health care. When compared to hospitalizations without PICU exposure, those with PICU exposure were more likely to complete new mental health visits (n=1,697 [6.1%] of PICU hospitalizations vs 5,252 [4.9%] of non-PICU hospitalizations). However, PICU exposure was not independently associated with a new mental health visit after adjustment (OR 1.06, 95% CI 1 – 1.13; p=0.067). Older age, complex chronic conditions, and longer length of stay were associated with new mental health visits. Hospitalizations with a PICU stay were significantly associated with increased rate of visits to psychologists or supportive therapists compared to those without a PICU stay (p<0.001). Conclusions Mental health follow-up after pediatric hospitalization is rare. Future studies should investigate barriers to care and identify effective methods for systematic screening and proactive referral.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".