Effect of Different Interventions on Lumbar Spinal Stenosis: A Systematic Evaluation and Network Meta-Analysis
Year: 2024
Type: article
Study designs: Systematic Review, Meta-Analysis
Abstract: BACKGROUND: Surgery is the preferred option for lumbar spinal stenosis (LSS) when conservative methods cannot meet the needs. Recent advancements in surgical techniques have brought various new methods for treating LSS. METHODS: Four databases, PubMed, Embase, the Cochrane Library, and Web of Science, were searched, covering the period from the establishment of the databases until May 2024. Randomized controlled trials were carried out to treat LSS using different surgical approaches. The outcome measures included the visual analog scale (VAS) score, Oswestry disability index score, surgical duration, intraoperative blood loss, and length of hospital stay of patients. Bayesian random-effects network meta-analysis was performed using R software (V4.4) and STATA17.0 software to analyze each surgical approach. RESULTS: A total of 29 studies involving 4200 patients were included. Nine intervention methods, including laminotomy, decompression, decompression plus fusion, endoscopic decompression, interspinous process spacer device (IPSD), laminectomy, minimally invasive decompression, spinous process osteotomy, and lumbar interbody fusion, were analyzed. Network meta-analysis results indicated that endoscopic decompression (surface under the cumulative ranking curve [SUCRA = 88.70%) was the most effective in reducing short-term back VAS scores. IPSD (SUCRA = 98.00%) was the most effective in reducing long-term back VAS scores, surgical duration (SUCRA = 95.20%), and intraoperative blood loss (SUCRA = 100.00%). Endoscopic decompression (SUCRA = 83.60%) also showed the most significant effect in reducing hospital stays. CONCLUSIONS: Endoscopic decompression can effectively improve short-term back VAS scores and reduce hospital stays, while IPSD is effective in reducing long-term back VAS scores with minimal surgical duration and blood loss.
Source: World Neurosurgery
Authors: Yansong Ge, Yaoxing Lu, Cheng Ma, Benteng Lu, Erteng Ma, Yafei Zhang, Fei Zhao
Institution: Anhui University of Traditional Chinese Medicine
Language: English
Subfield: Pathology and Forensic Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,920
Award: G6805082435
OpenAlex ID: W4404656126
