Coronal malalignment (CM) has recently gained focus as a key predictor of functional outcomes in patients with adult spinal deformity (ASD). The kickstand rod technique has been described as a novel technique for CM correction using an accessory rod on the convex side of the deformity. This review aimed to evaluate the surgical technique and outcomes of corrective surgery using this technique. The literature search was conducted on three databases (PubMed, EMBASE, and Scopus). After reviewing the search results, six studies were shortlisted for data extraction and pooled analysis. Weighted means for surgical duration, length of stay, amount of coronal correction, and sagittal parameters were calculated. The studies included in the review were published between 2018 and 2023, with a total sample size of 97 patients. The mean age of the study cohort was 61.1 years, with female preponderance. The mean operative time was 333.6 minutes. The mean correction of CM was 5.1 cm (95% confidence interval [CI], 3.6-6.6), the mean sagittal correction was 5.6 cm (95% CI, 4.1-7.1), and the mean change in lumbar lordosis was 17° (95% CI, 10.4-24.1). Preoperative coronal imbalance and mean correction achieved postoperatively were directly related with age. The reoperation rate was 13.2%. The kickstand rod technique compares favorably with conventional techniques such as asymmetric osteotomies in CM management. This technique provides an additional accessory rod that helps increase construct stiffness. Because of limited data, definitive conclusions cannot be drawn from this review; however, this technique is a valuable tool for a surgeon dealing with ASD.
Keyphrases
- minimally invasive
- autism spectrum disorder
- systematic review
- end stage renal disease
- electronic health record
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- spinal cord
- attention deficit hyperactivity disorder
- magnetic resonance
- ejection fraction
- radiation therapy
- patients undergoing
- newly diagnosed
- atrial fibrillation
- clinical trial
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- chronic kidney disease
- coronary artery disease
- skeletal muscle
- squamous cell carcinoma
- magnetic resonance imaging
- prognostic factors
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- machine learning
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- young adults
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- artificial intelligence
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- case control
- patient reported
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