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

Top Spinal Cord Inj Rehabil, 2024 · DOI: 10.46292/sci23-00010 · Published: January 1, 2024

Spinal Cord Injury Research Methodology & Design

Simple Explanation

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. This systematic review examines existing literature on CPMs for TSCI and critically examines the predictor selection methods used.

Study Duration

Not specified

Participants

21 full-text studies (2009-2020) consisting of 33 distinct CPMs

Evidence Level

Systematic Review

Key Findings

1
The data analysis domain was most commonly at a high risk of bias when assessed for methodological quality.
2
Model presentation formats were inconsistently included with published CPMs; only two studies followed established guidelines for transparent reporting of multivariable prediction models.
3
Authors frequently cited previous literature for their initial selection of predictors, and stepwise selection was the most frequent predictor selection method during modelling.

Research Summary

This systematic review provides a comprehensive overview of the CPMs that have been developed for prognosticating patient-centered outcomes in individuals with TSCI. Findings suggest that most currently published CPMs have been developed to predict functional outcomes, with opportunity for further work in the prognostication of neurological and survival outcomes. More consistent use of model presentation formats and transparent reporting of prediction modelling studies are needed to support the dissemination and advancement of TSCI prognosis research.

Practical Implications

Improved Clinical Counseling

Prediction modelling studies for TSCI serve clinicians who counsel patients, providing valuable insights for long-term strategies and optimal management.

Enhanced Clinical Trials

Researchers can use prediction models to risk-stratify participants for clinical trials, leading to more targeted and effective research.

Improved Patient Coping

Patients coping with TSCI can benefit from prediction models, gaining a better understanding of potential outcomes and improving their quality of life.

Study Limitations

1
Most of the included studies were retrospective in nature and based on data from SCI-specific registries.
2
All studies were deemed to be at high ROB with respect to the Analysis domain, which may be influenced by the primary method used to handle missing data.
3
Inclusion of studies with small sample sizes or those without external validation may limit the validity in our findings.

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