ArticleQuantitative imaging in medicine and surgery2022
Real-world study for identifying the predictive factors of surgical intervention and the value of magnetic resonance imaging in patients with low back pain.
Article in Quantitative imaging in medicine and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 3 citations in OpenAlex.
- Predictive value of texture analysis on lumbar MRI in patients with chronic low back pain.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2023Observational
- Functional magnetic resonance imaging reveals dysfunction of the paraspinal muscles in patients with chronic low back pain: a cross-sectional study.Quantitative imaging in medicine and surgery · 2023Article
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Authors and funding
7 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Low back pain (LBP) is a prevalent disease and can be disabling. Currently, many patients with LBP with or without radiculopathy commonly undergo magnetic resonance imaging (MRI) for diagnosis and therapeutic assessment, yet the final intervention is mainly centered around nonoperative treatment. This study's aim was to identify the predictive factors of surgical treatment and the value of MRI in patients with LBP with or without radiculopathy. Methods: The study included a training cohort that consisted of 461 patients with MRI from January 2014 to December 2018. Demographic characteristics and MRI findings were collected from our medical records. We developed and validated 2 nomograms to predict the possibility of receiving surgical treatment in LBP patients, based on multivariable logistic regression analysis. The performance of the 2 nomograms was assessed in terms of their calibration, discrimination, and clinical usefulness. An independent validation cohort containing 163 patients was comparatively analyzed. Results: The baseline model incorporated 6 clinicopathological variables, while the MRI model consisted of 9 variables including several MRI findings. Internal validation revealed the good performance of the 2 nomograms in discrimination and calibration, with a concordance index (C-index) of 0.799 (95% CI: 0.743-0.855) for the baseline model and 0.834 (95% CI: 0.783-0.884) for the MRI model, which showed that the addition of MRI findings to the nomogram failed to achieve better prognostic value (Z statistic =-1.509; P=0.131). Application of the 2 models in the validation cohort also showed good discrimination (baseline model: C-index 0.75, 95% CI: 0.671-0.829; MRI model: C-index 0.777, 95% CI: 0.696-0.857) and calibration. No significant predictive benefit was found in the MRI model in the validation cohort (Z statistic =-0.588; P=0.557). Conclusions: This study showed that clinical demographic characteristics provide good prognostic value to determine whether LBP patients with or without radiculopathy require surgical treatment. The addition of MRI findings yielded no significantly incremental prognostic value.
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