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The Relationship Between Patient Perceived Pain and the Numerical Rating System: A Prospective Validation Using

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This study introduces a novel method to reconstruct Numeric Rating System (NRS) pain scores using Clinically Aligned Pain Assessment (CAPA) measures. The developed model accurately predicts NRS scores, offering a valuable tool for pain assessment in clinical settings.

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Area of Science:

  • Pain Medicine
  • Health Informatics
  • Clinical Assessment

Background:

  • The Numeric Rating System (NRS) is a common pain assessment tool.
  • Limitations exist in capturing comprehensive pain data with NRS alone.
  • The Clinically Aligned Pain Assessment (CAPA) offers detailed pain-related information.

Purpose of the Study:

  • To develop and validate a method for reconstructing NRS pain scores using CAPA measures.
  • To assess the accuracy of a predictive model linking CAPA components to NRS scores.
  • To enhance pain assessment by leveraging readily available clinical data.

Main Methods:

  • Observational retrospective cohort study with prospective validation.
  • Utilized de-identified adult patient data from a major health system (2011-2020).
  • An ordinal regression model was employed, using CAPA components to predict NRS scores.

Main Results:

  • A significant relationship was found between all CAPA components and NRS scores.
  • The model demonstrated good predictive accuracy with RMSE of 1.938 and Somers' D of 0.803 in the development set.
  • Prospective validation yielded RMSE of 2.1 and Somers' D of 0.74, confirming model efficacy.

Conclusions:

  • The developed method accurately reconstructs NRS pain scores from CAPA measures.
  • This approach offers a reliable way to estimate NRS scores when direct measurement is unavailable.
  • The model showed particular exactness for NRS scores between 0 and 7.