Postoperative pain assessment using four behavioral scales in Pakistani children undergoing elective surgery
Bibliographic record
Abstract
BACKGROUND: Several measurement tools have been used for assessment of postoperative pain in pediatric patients. Self-report methods have limitations in younger children and parent, nurse or physician assessment can be used as a surrogate measure. These tools should be tested in different cultures as pain can be influenced by sociocultural factors. The objective was to assess the inter-rater agreement on four different behavioral pain assessment scales in our local population. MATERIALS AND METHODS: This prospective, descriptive, observational study was conducted in Pakistan. American Society of Anesthesiologists I and II children, 3-7 years of age, undergoing elective surgery were enrolled. Four pain assessment scales were used, Children's Hospital of Eastern Ontario Pain Scale (CHEOPS), Toddler Preschool Postoperative Pain Scale (TPPPS), objective pain scale (OPS), and Face, Legs, Activity, Cry, Consolability (FLACC). After 15 and 60 min of arrival in the postanesthesia care unit (PACU), each child evaluated his/her postoperative pain by self-reporting and was also independently assessed by the PACU nurse, PACU anesthetist and the parent. The sensitivity and specificity of the responses of the four pain assessment scales were compared to the response of the child. RESULTS: At 15 min, sensitivity and specificity were >60% for doctors and nurses on FLACC, OPS, and CHEOPS scales and for FLACC and CHEOPS scale for the parents. Parents showed poor agreement on OPS and TPPS. At 60 min, sensitivity was poor on the OPS scale by all three observers. Nurses showed a lower specificity on FLACC tool. Parents had poor specificity on CHEOPS and rate of false negatives was high with TPPS. CONCLUSIONS: We recommend the use of FLACC scale for assessment by parents, nurses, and doctors in Pakistani children aged between 3 and 7.
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| 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".