New postoperative pain instrument for toddlers
- \(\bf Background\) The Children's and Infant's Postoperative Pain Scale (CHIPPS) and the German version of the Parent's Postoperative Pain Measure (PPPM-D) are used to assess postoperative pain intensity in preschool children. However, they have shown low concordance in previous prospective studies on quality improvement. \(\bf Aims\) Our secondary analysis aimed to estimate the association strength between the pain score items and indication for rescue medication defined as CHIPPS \(\geq\) 4 and/or PPPD-D \(\geq\) 6. Thus, we intended to create a further developed pain instrument with fewer variables for easier routine use. \(\bf Methods\) We analyzed 1067 pain intensity assessments of hospitalized children for the development of our novel tool in two steps using modern statistical and machine-learning methods: (1) Boruta variable selection to analyze the association strength between CHIPPS score, PPPM-D items, age, weight, and elapsed time after surgery, including their interactions and pattern stability, and the binary outcome (analgesics required yes/no). (2) Symbolic regression to generate a short formula with the least number of variables and highest accuracy for rescue medication indication. \(\bf Results\) Additional analgesics were required in 19.96% of pain intensity assessments, whereby the PPPM-D showed higher variance than CHIPPS. Boruta identified PPPM-D score, CHIPPS score, 9 of the 15 PPPM-D variables, and time of assessment as associated with the indication for RM. Symbolic regression revealed that additional analgesics are required if CHIPPS is \(\geq\) 4 OR PPPM-D item "less energy than usual" AND one of the items "more easily cry" or "more groan/moan" are answered with "yes". These PPPM-D items were not redundant and showed nonlinear course over time. The cross-validated accuracy for this assessment tool was 94.94%. \(\bf Conclusions\) The new instrument is easy to use and may improve postoperative pain intensity assessment in children. However, it requires prospective validation in a new cohort.
Author: | Philipp GudeORCiDGND, Niclas GeldermannGND, Franziska GustedtGND, C Grobe, Thomas WeberORCiDGND, Adrian-Iustin GeorgeviciGND |
---|---|
URN: | urn:nbn:de:hbz:294-124780 |
DOI: | https://doi.org/10.1111/pan.14824 |
Parent Title (English): | Pediatric anesthesia |
Subtitle (English): | Secondary analysis of prospectively collected assessments after tonsil surgery |
Publisher: | Wiley |
Place of publication: | Hoboken, New Jersey |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2024/06/13 |
Date of first Publication: | 2023/12/23 |
Publishing Institution: | Ruhr-Universität Bochum, Universitätsbibliothek |
Tag: | machine learning; pain measurement; postoperative pain; tonsillectomy |
Volume: | 34 |
Issue: | 4 |
First Page: | 347 |
Last Page: | 353 |
Note: | Dieser Beitrag ist auf Grund des DEAL-Wiley-Vertrages frei zugänglich. |
Institutes/Facilities: | St. Josef-Hospital Bochum, Klinik für Anästhesiologie und Intensivmedizin |
Dewey Decimal Classification: | Technik, Medizin, angewandte Wissenschaften / Medizin, Gesundheit |
open_access (DINI-Set): | open_access |
Licence (German): | Creative Commons - CC BY-NC-ND 4.0 - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |