Optimising early detection of degenerative cervical myelopathy: a systematic review of quantitative screening tools for primary care

Abstract

Background: Early diagnosis of degenerative cervical myelopathy (DCM) is often challenging due to subtle, non-specific symptoms, limited disease awareness and a lack of definitive diagnostic criteria. As primary care physicians are typically the first to encounter patients with early DCM, equipping them with effective screening tools is crucial for reducing diagnostic delays and improving patient outcomes. This systematic review evaluates the efficacy of quantitative screening methods for DCM that can be implemented in primary care settings.

Methods: A systematic search following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted across PubMed, Embase and Cochrane Library up to July 2024 using keywords relevant to DCM screening. Studies were included if they evaluated the sensitivity and specificity of DCM screening tools applicable to primary care settings. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

Results: The search identified 14 studies evaluating 18 screening methods for DCM. Questionnaires consistently showed high diagnostic accuracy, with Youden indices exceeding 0.60, while only three out of nine conventional physical performance tests met the same threshold. Sensor-assisted tests, particularly those using advanced technology like finger-wearable gyro sensors, exhibited the highest diagnostic accuracy but present challenges related to accessibility and learning curves.

Conclusion: This review highlights the potential of quantitative screening methods for early DCM detection in primary care. While questionnaires and conventional tests are effective and accessible, sensor-assisted tests offer greater accuracy but face implementation challenges. A tailored, multifaceted approach is crucial for improving outcomes. Future research should focus on validating these tools in diverse populations and standardising diagnostic criteria.