Development and validation of a risk-based algorithm for preoperative type and screen testing in spine surgery

• Published in: The spine journal 2022-09, Vol.22 (9), p.1472-1480
• Main Authors: Turcotte, Justin J., Holbert, S. Elliott, Orlov, Maxim D., Patton, Chad M.
• Format: Article
• Language: English
• Subjects: ABO/Rh type and antibody screen; Algorithm; Laboratory testing; Predictors; Spine surgery; Transfusion; Type and screen
• ISSN: 1529-9430; 1878-1632
• DOI: 10.1016/j.spinee.2022.04.006

With improvements in surgical techniques and perioperative management, transfusion rates after spine surgery have decreased over time. Given this trend, routine preoperative ABO/Rh type and antibody screen (T&S) laboratory testing may not be warranted in all patients undergoing spine surgery. The aim of the current study is to evaluate risk factors for intra/postoperative transfusion in patients undergoing a variety of spine procedures and to develop an algorithm for selectively ordering preoperative T&S testing in appropriate patients. This is a single institution, retrospective observational study of patients undergoing emergent or elective spine surgery. External validation of the algorithm was performed on a national sample of patients undergoing spine surgery from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) national database. A total of 5,947 surgeries from January 1, 2016 to December 31, 2019 at a single institution, and 166,113 surgeries from the 2016 to 2018 ACS-NSQIP database. The primary outcome measure was performance of intraoperative or postoperative transfusion. Using the institutional sample, univariate statistics (chi-square tests, fisher's exact test, 2-sided independent sample tests) were performed to compare demographics, comorbidities, and surgical details (case type, number of levels treated, etc.) between patients who did and did not require intra- or postoperative transfusion. Transfusion rates were calculated and compared across procedure types. Multivariate logistic regression was performed to identify independent predictors of transfusion and the model's accuracy was evaluated using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve. A risk-based algorithm suggesting no preoperative T&S in low transfusion risk procedures, routine preoperative T&S in high-risk procedures, and further assessment in medium risk thoracolumbar fusion procedures was created. The algorithm's sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were evaluated when it was applied to both the institutional and national samples. Potential cost savings from reducing T&S orders were calculated. In the institutional sample, 120 patients (2.0%) required intraoperative or postoperative transfusion. The highest rates of transfusion were found in corpectomy (10.5%) and anterior/posterior cervical fusion (6.9%) procedures. In the multivariate lo