Perioperative mortality after lumbar spinal fusion surgery: an analysis of epidemiology and risk factors

腰椎融合术后围手术期死亡率:流行病学和危险因素分析

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Abstract

STUDY DESIGN: Analysis of the Nationwide Inpatient Sample (NIS) from 1998 to 2008. OBJECTIVE: To analyze the most recent available and nationally representative data for risk factors contributing to in-hospital mortality after primary lumbar spine fusion. SUMMARY OF BACKGROUND DATA: The total number of lumbar spine fusion surgeries has increased dramatically over the past decades. While the field of spine fusion surgery remains highly dynamic with changes in perioperative care constantly affecting patient care, recent data affecting rates and risk for perioperative mortality remain very limited. METHODS: We obtained the NIS from the Hospital cost and utilization project. The impact of patient and health care system related demographics, including various comorbidities as well as postoperative complications on the outcome of in-hospital mortality after spine fusion were studied. Furthermore, we analyzed the timing of in-hospital mortality. RESULTS: An estimated total of 1,288,496 primary posterior lumbar spine fusion procedures were performed in the US between 1998 and 2008. The average mortality rate for lumbar spine fusion surgery was 0.2%. Independent risk factors for in-hospital mortality included advanced age, male gender, large hospital size, and emergency admission. Comorbidities associated with the highest in-hospital mortality after lumbar spine fusion surgery were coagulopathy, metastatic cancer, congestive heart failure and renal disease. Most lethal complications were cerebrovascular events, sepsis and pulmonary embolism. Furthermore, we demonstrated that the timing of death occurred relatively early in the in-hospital period with over half of fatalities occurring by postoperative day 9. CONCLUSION: This study provides nationally representative information on risk factors for and timing of perioperative mortality after primary lumbar spine fusion surgery. These data can be used to assess risk for this event and to develop targeted intervention to decrease such risk.

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