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.

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Metadaten
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):License LogoCreative Commons - CC BY-NC-ND 4.0 - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International