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Spine J. 2017 Oct;17(10):1383-1392. doi: 10.1016/j.spinee.2017.05.031. Epub 2017 Jul 14.

A simplified clinical prediction rule for prognosticating independent walking after spinal cord injury: a prospective study from a Canadian multicenter spinal cord injury registry.

Author information

1
Ottawa Combined Adult Spinal Surgery Program, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada.
2
Rick Hansen Institute, Blusson Spinal Cord Centre, 6400-818 W. 10th Ave, Vancouver, BC V5Z 1M9, Canada; The University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.
3
Rick Hansen Institute, Blusson Spinal Cord Centre, 6400-818 W. 10th Ave, Vancouver, BC V5Z 1M9, Canada.
4
Division of Orthopaedic Surgery, Department of Surgery, Faculty of Medicine, University of Ottawa, The Ottawa Hospital, 1053 Carling Ave, Ottawa, ON K1Y 4E9, Canada; Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON K1Y 4E9, Canada.
5
Ottawa Combined Adult Spinal Surgery Program, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada; Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON K1Y 4E9, Canada.
6
Ottawa Combined Adult Spinal Surgery Program, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada; Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON K1Y 4E9, Canada; Division of Neurosurgery, Department of Surgery, Faculty of Medicine, University of Ottawa, The Ottawa Hospital, 1053 Carling Ave, Ottawa, ON K1Y 4E9, Canada.
7
Département Sciences Neurologiques, Pavillon Enfant-Jésus, CHU de Québec, 1401 18e rue, QC G1J 1Z4, Canada.
8
Dalhousie University, Saint John Regional Hospital, PO Box 2100, Saint John, NB E2L 4L2, Canada.
9
Division of Orthopaedics, Department of Surgery, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada.
10
University of Toronto Spine Program, St. Michael's Hospital, 55 Queen St E., Suite 1008, Toronto, ON M5C 1R6, Canada.
11
Ottawa Combined Adult Spinal Surgery Program, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada; Division of Orthopaedic Surgery, Department of Surgery, Faculty of Medicine, University of Ottawa, The Ottawa Hospital, 1053 Carling Ave, Ottawa, ON K1Y 4E9, Canada; Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON K1Y 4E9, Canada. Electronic address: pphan@toh.ca.

Abstract

BACKGROUND CONTEXT:

Traumatic spinal cord injury (SCI) is a debilitating condition with limited treatment options for neurologic or functional recovery. The ability to predict the prognosis of walking post injury with emerging prediction models could aid in rehabilitation strategies and reintegration into the community.

PURPOSE:

To revalidate an existing clinical prediction model for independent ambulation (van Middendorp et al., 2011) using acute and long-term post-injury follow-up data, and to investigatethe accuracy of a simplified model using prospectively collected data from a Canadian multicenter SCI database, the Rick Hansen Spinal Cord Injury Registry (RHSCIR).

STUDY DESIGN:

Prospective cohort study.

PARTICIPANT SAMPLE:

The analysis cohort consisted of 278 adult individuals with traumatic SCI enrolled in the RHSCIR for whom complete neurologic examination data and Functional Independence Measure (FIM) outcome data were available.

OUTCOME MEASURES:

The FIM locomotor score was used to assess independent walking ability (defined as modified or complete independence in walk or combined walk and wheelchair modality) at 1-year follow-up for each participant.

METHODS:

A logistic regression (LR) model based on age and four neurologic variables was applied to our cohort of 278 RHSCIR participants. Additionally, a simplified LR model was created. The Hosmer-Lemeshow goodness of fit test was used to check if the predictive model is applicable to our data set. The performance of the model was verified by calculating the area under the receiver operating characteristic curve (AUC). The accuracy of the model was tested using a cross-validation technique. This study was supported by a grant from The Ottawa Hospital Academic Medical Organization ($50,000 over 2 years). The RHSCIR is sponsored by the Rick Hansen Institute and is supported by funding from Health Canada, Western Economic Diversification Canada, and the provincial governments of Alberta, British Columbia, Manitoba, and Ontario. ET and JP report receiving grants from the Rick Hansen Institute (approximately $60,000 and $30,000 per year, respectively). DMR reports receiving remuneration for consulting services provided to Palladian Health, LLC and Pacira Pharmaceuticals, Inc ($20,000-$30,000 annually), although neither relationship presents a potential conflict of interest with the submitted work. KEH received a grant for involvement in the present study from the Government of Canada as part of the Canada Summer Jobs Program ($3,000). JP reports receiving an educational grant from Medtronic Canada outside of the submitted work ($75,000 annually). TM reports receiving educational fellowship support from AO Spine, AO Trauma, and Medtronic; however, none of these relationships are financial in nature. All remaining authors have no conflicts of interest to disclose.

RESULTS:

The fitted prediction model generated 85% overall classification accuracy, 79% sensitivity, and 90% specificity. The prediction model was able to accurately classify independent walking ability (AUC 0.889, 95% confidence interval [CI] 0.846-0.933, p<.001) compared with the existing prediction model, despite the use of a different outcome measure (FIM vs. Spinal Cord Independence Measure) to qualify walking ability. A simplified, three-variable LR model based on age and two neurologic variables had an overall classification accuracy of 84%, with 76% sensitivity and 90% specificity, demonstrating comparable accuracy with its five-variable prediction model counterpart. The AUC was 0.866 (95% CI 0.816-0.916, p<.01), only marginally less than that of the existing prediction model.

CONCLUSIONS:

A simplified predictive model with similar accuracy to a more complex model for predicting independent walking was created, which improves utility in a clinical setting. Such models will allow clinicians to better predict the prognosis of ambulation in individuals who have sustained a traumatic SCI.

KEYWORDS:

Functional outcome; Logistic regression; Prediction; Prognosis; Traumatic spinal cord injury; Walking

PMID:
28716636
DOI:
10.1016/j.spinee.2017.05.031
[Indexed for MEDLINE]
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