BACKGROUND: The incidence of spinal column tumors is estimated to be 0.62 per 100,000 individuals in the USA. It is especially important to understand the incidence and predictive factors for adverse events of surgery in spinal oncology patients, as a single complication may be associated with morbidity, mortality, and costs. The aim of the study was to use a large national registry to evaluate the perioperative cumulative incidence and predictors of major complications, for metastatic spinal tumors. METHODS: This study is a retrospective analysis of data from the DWG registry on patients who have undergone decompression with and without instrumentation undergoing tumor debulking, release of the neural structures, spinal stabilization or tumor extirpation in metastatic disease of the spine in 124 departments from January 2017 to January 2020, as well as vertebroplasty and percutaneous instrumentation. The outcomes evaluated were major complications defined by Finkelstein et al. as: death; cerebral (new postoperative coma or stroke), cardiac, pulmonary or renal complication; symptomatic venous thromboembolism; surgical site infection. RESULTS: In total, 1617 decompressions with and without instrumentation undergoing tumor debulking, release of the neural structures, spinal stabilization or tumor extirpation in metastatic disease in the spine were identified in the registry; N.=266 developed a major complication (group 2), while N.=1351 had no complication (group 1). The mean age in group 1 was 65 years (58.5%), in group 2 69 years (63.5%). In group 2, most of the patients had preoperatively an ASA Score of 3 and 4 (patients with severe general disease): 202/266 (75.9%) being significant. The overall prevalence of a major postoperative complication was 16.5% and for an intraoperative complication remained 8%. The likelihood ratio for major complications by blood loss greater than 500 mL were as follows: cardiovascular event with a likelihood of 4.22 pulmonary insufficiency 4.18 and cerebral 5.47. CONCLUSIONS: This analysis provides predictive models for surgeons to identify patients who may benefit from transitional care programs. Preoperative status, invasiveness, blood loss >500 mL and blood transfusions are independent predictors associated with higher risk of complication.
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