Using a logarithmic model to predict functional independence after spinal cord injury: a retrospective study

Yohei Tomioka, Osamu Uemura, Ryota Ishii, Meigen Liu

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Study design: A retrospective cohort study Objective: To establish a logarithmic model to predict functional independence after spinal cord injury. Setting: The National Hospital Organization, Murayama Medical Center, Japan. Methods: Thirty-one adults with a traumatic spinal cord injury (SCI) were enrolled. The Spinal Cord Independence Measure (SCIM) III scores obtained at month 1 and 3 after admission were used to construct a simple logarithmic model to predict SCIM III scores. The validity of the predicted scores was evaluated using a linear mixed model, and agreement between the predicted and measured scores were assessed using the Bland-Altman analysis. Results: In the linear mixed model, the fixed effect slope [95% CI] and the intercept [95% CI] were 1.18 [0.78, 1.58] and −1.75 [−10.3, 6.83], respectively. The scatter plot showed non-linear correlation between the predicted and actual SCIM III scores. This non-linearity became inconspicuous when Sphincter Management scores were omitted. The fixed effect slope and the intercept were 1.12 [0.89, 1.36] and −1.64 [−4.95, 1.68], respectively. A significant fixed or proportional bias was not identified on the Bland-Altman analysis of the total SCIM III score, with most scores lying between an upper limit of +15.3 and a lower limit of −19.3. Conclusion: The logarithmic model provided an accurate prediction of the functional independence score of individuals with SCI in our cohort which included various neurological levels and severity of the injury. Along with its simplicity, our prediction model could be useful in daily practice.

Original languageEnglish
Pages (from-to)1048-1056
Number of pages9
JournalSpinal Cord
Volume57
Issue number12
DOIs
Publication statusPublished - 2019 Dec 1

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology

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