Hospitalized Children Continue to Report Undertreated and Preventable Pain
Bibliographic record
Abstract
BACKGROUND: Published reports of substantial rates of moderate to severe pediatric inpatient pain tend to overlook lower-intensity pain that may be clinically significant. OBJECTIVE: To document the prevalence of clinically significant pain in pediatric inpatients by considering the pain threshold at which each child desires intervention, and to assess sources of pain, pain assessment and intervention, and relationships among demographic and medical variables to reported pain. METHODS: Inpatients or their parents on four hospital units during four nonconsecutive days were eligible for inclusion. Interviews (76 parents; 31 patients) captured experiences of 107 inpatients (three weeks to 18 years of age) including current, worst and usual pain, pain treatment thresholds, sources of pain and help received during the previous 24 h. A chart review provided data regarding demographic and medical variables, and pain assessment and management. RESULTS: In total, 94% of patients experienced pain. The prevalence of clinically significant pain was 8% (current), 62% (worst) and 24% (usual). Current and worst pain was primarily procedural, and usual pain was primarily disease related. On average, patients had 4.03 documented pain assessments over 24 h. Caregiver responses (eg, reassurance) and nonpharmacological interventions were frequently reported (>90%) but infrequently documented (<50%); 66% of patients received pharmacological interventions. Younger patients received fewer pain assessments and opioids. Patients with clinically significant usual pain were more likely to have undergone surgery, and receive more pain assessments and interventions. CONCLUSIONS: While recent studies suggest reduced pain in pediatric inpatients, the present findings reveal a continued high frequency of undertreated pain. High rates of procedural pain are preventable and should be targeted given the underutilization of pain management strategies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".