Abstract
Introduction: One of the most common issues following pedicle screw fixation is pedicle screw loosening. There are, however, few trustworthy methods for predicting screw loosening. The goal of the current study was to identify an efficient technique for using preoperative CT scanning to predict screw loosening in older patients and to offer recommendations for preoperative surgical planning.
Methods: The current analysis included retrospectively all patients who underwent lumbar pedicle screw fixation for degenerative lumbar diseases in our department between January 2015 and January 2022. Hounsfield units were used to assess each vertebra's attenuation in a CT scan (HU). Postoperative X-ray testing identified screw loosening. Using IBMSPSS 24.00 software, one-way analysis of variance (ANOVA) and receiver operating characteristic (ROC) curve analysis were performed.
Results: Over a mean follow-up period of 28.4±11.5 (range 12-44 months) months, screw loosening was noted in 53 of 242 patients (136 male and 106 female, average age 58.7±7.3 years). Gender, BMI, smoking habits, and whether or not a patient had diabetes or spondylolisthesis were not shown to be significantly different among the patients (P>0.05). The difference between the average lumbar vertebral HU values in the screw-loosening group and the control group was significant (P<0.01) at 120.3±31.5HU and 138.6±37.6HU, respectively. The average HU value of L1-L4 exhibited an area under the curve (AUC) of 0.691 (95% CI: 0.614-0.784), according to ROC curve analysis. A HU cut-off value of 122 HU is a likely cut-off point to predict screw loosening with a sensitivity of 70% and a specificity of 58%.
Conclusion: The use of screw augmentation techniques can be decided using a prospective CT scan HU value-based prediction. An independent risk factor for screw loosening in an instrumented lumbar vertebra is a cutoff L1-L5 average HU value of 122 HU.
Keywords: Osteoporosis, Spine surgery, Hounsfield unit, Computed tomography, Pedicle screw loosening, Treatment.
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