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Oxfordshire Community Stroke Project Classification: A proposed automated algorithm.

Joao Brainer Clares de Andrade1,2, Jay P Mohr2, Felipe Brito Timbó3

  • 1Department of Neurology, Universidade Federal de Sao Paulo, Sao Paulo, Brazil.

European Stroke Journal
|August 20, 2021
PubMed
Summary

A new computer-based algorithm improves the accuracy of the Oxfordshire Community Stroke Project (OCSP) classification for stroke patients. This tool aids neurology residents in better predicting neurological complications.

Keywords:
Oxfordshire Community Stroke Project classificationStrokealgorithmscale

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Area of Science:

  • Neurology
  • Medical Informatics

Background:

  • The Oxfordshire Community Stroke Project (OCSP) classification aids in predicting stroke complications.
  • Current reliance on neurological assessment for OCSP classification presents challenges.
  • A digital tool is needed to streamline stroke patient classification.

Purpose of the Study:

  • To develop and validate a computer-based algorithm for OCSP classification.
  • To assess the algorithm's impact on the accuracy of stroke patient categorization.

Main Methods:

  • A flowchart was developed into a computer-based algorithm (COMPACT) by vascular neurologists.
  • Neurology residents participated in a randomized trial using COMPACT or a symptom list.
  • Performance was measured by a 20-item questionnaire assessing OCSP classification accuracy.

Main Results:

  • The COMPACT algorithm group achieved a higher median score (16.5/20) compared to the symptom list group (15/20), p=0.014.
  • Algorithm use was significantly associated with improved overall correct classification scores (p=0.03).

Conclusions:

  • The COMPACT algorithm is a valuable tool for neurology residents.
  • Computer-based classification enhances accuracy and efficiency in managing stroke patients.
  • This tool may improve prognostication and prediction of neurological complications.