Epidemiology and management of painful procedures in children in Canadian hospitals
Bibliographic record
Abstract
BACKGROUND: Children being cared for in hospital undergo multiple painful procedures daily. However, little is known about the frequency of these procedures and associated interventions to manage the pain. We undertook this study to determine, for children in Canadian hospitals, the frequency of painful procedures, the types of pain management interventions associated with painful procedures and the influence of the type of hospital unit on procedural pain management. METHODS: We reviewed medical charts for infants and children up to 18 years of age who had been admitted to 32 inpatient units at eight Canadian pediatric hospitals between October 2007 and April 2008. We recorded all of the painful procedures performed and the pain management interventions that had been implemented in the 24-hour period preceding data collection. We performed descriptive and comparative (analysis of variance, χ(2)) analyses. RESULTS: Of the 3822 children included in the study, 2987 (78.2%) had undergone at least one painful procedure in the 24-hour period preceding data collection, for a total of 18 929 painful procedures (mean 6.3 per child who had any painful procedure). For 2334 (78.1%) of the 2987 children who had a painful procedure, a pain management intervention in the previous 24 hours was documented in the chart: 1980 (84.8%) had a pharmacologic intervention, 609 (26.1%) a physical intervention, 584 (25.0%) a psychologic intervention and 753 (32.3%) a combination of interventions. However, for only 844 (28.3%) of the 2987 children was one or more pain management interventions administered and documented specifically for a painful procedure. Pediatric intensive care units reported the highest proportion of painful procedures and analgesics administered. INTERPRETATION: For less than one-third of painful procedures was there documentation of one or more specific pain management interventions. Strategies for implementing changes in pain management must be tailored to the type of hospital unit.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".