Identifying children at high risk for psychological sequelae after pediatric intensive care unit hospitalization*
Bibliographic record
Abstract
OBJECTIVE: To identify those patients in a pediatric intensive care unit who may be at highest risk for developing persistent psychological sequelae after hospital discharge. DESIGN: A secondary data analysis was conducted to examine data gathered in an earlier study of children's psychological responses after critical illness. The current study focused exclusively on patients who required pediatric intensive care unit hospitalization. PATIENTS: Sixty children, aged 6 to 17 yrs, hospitalized in two Canadian pediatric intensive care units. PROCEDURES: Children were categorized as either high risk or low risk for developing persistent psychological sequelae after discharge based on their level of illness severity and the number of invasive procedures to which they were exposed. Outcome data were analyzed using descriptive statistics, followed by an assessment of group differences at baseline, 6 wks, and 6 mos postdischarge. Combined effects of invasive procedures and illness severity on the outcome variables were explored. OUTCOME MEASURES: Three questionnaires were completed by all children 6 wks and 6 mos postdischarge, including the Children's Impact of Events Scale, the Children's Medical Fears Scale, and the Children's Health Locus of Control Scale. RESULTS: Children in the high risk group demonstrated more psychological sequelae 6 wks and 6 mos postdischarge. Exposure to high numbers of invasive procedures was the most important predictor of group differences 6 wks postdischarge. CONCLUSIONS: Findings suggest there is a group of children in the pediatric intensive care unit who are at higher risk for developing persistent psychological sequelae postdischarge. Exposure to high numbers of invasive procedures may be the driving force behind group differences, particularly at 6 wks postdischarge. These children warrant closer observation and follow-up.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".