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. 2024 Winter;30(1):1-44.
doi: 10.46292/sci23-00010. Epub 2024 Feb 29.

Multivariable Prediction Models for Traumatic Spinal Cord Injury: A Systematic Review

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Multivariable Prediction Models for Traumatic Spinal Cord Injury: A Systematic Review

Ramtin Hakimjavadi et al. Top Spinal Cord Inj Rehabil. 2024 Winter.

Abstract

Background: Traumatic spinal cord injuries (TSCI) greatly affect the lives of patients and their families. Prognostication may improve treatment strategies, health care resource allocation, and counseling. Multivariable clinical prediction models (CPMs) for prognosis are tools that can estimate an absolute risk or probability that an outcome will occur.

Objectives: We sought to systematically review the existing literature on CPMs for TSCI and critically examine the predictor selection methods used.

Methods: We searched MEDLINE, PubMed, Embase, Scopus, and IEEE for English peer-reviewed studies and relevant references that developed multivariable CPMs to prognosticate patient-centered outcomes in adults with TSCI. Using narrative synthesis, we summarized the characteristics of the included studies and their CPMs, focusing on the predictor selection process.

Results: We screened 663 titles and abstracts; of these, 21 full-text studies (2009-2020) consisting of 33 distinct CPMs were included. The data analysis domain was most commonly at a high risk of bias when assessed for methodological quality. Model presentation formats were inconsistently included with published CPMs; only two studies followed established guidelines for transparent reporting of multivariable prediction models. Authors frequently cited previous literature for their initial selection of predictors, and stepwise selection was the most frequent predictor selection method during modelling.

Conclusion: Prediction modelling studies for TSCI serve clinicians who counsel patients, researchers aiming to risk-stratify participants for clinical trials, and patients coping with their injury. Poor methodological rigor in data analysis, inconsistent transparent reporting, and a lack of model presentation formats are vital areas for improvement in TSCI CPM research.

Keywords: multivariable; prediction model; predictor selection; prognosis; systematic review; traumatic spinal cord injury.

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Figures

Figure 1.
Figure 1.
Classification scheme for evaluating the consistency for which a predictor was deemed to hold significant predictive value across the 21 included studies.
Figure 2.
Figure 2.
PRISMA flow diagram depicting the study selection protocol. CPM = clinical prediction model; ROB = risk of bias.
Figure 3.
Figure 3.
Frequency of candidate and final predictor types in included studies. AIS = American Spinal Injury Association Impairment Scale; ISNCSCI = International Standards for Neurological Classification of Spinal Cord Injury; NLI = neurological level of injury.

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