医学
背景(考古学)
回顾性队列研究
外科
队列
单变量分析
共病
腰椎
多元分析
内科学
生物
古生物学
作者
Zach Pennington,Jeff Ehresman,Camilo A. Molina,Andrew Schilling,James Feghali,Sakibul Huq,Ravi Medikonda,A. Karim Ahmed,Ethan Cottrill,Daniel Lubelski,Steven M. Frank,Daniel M. Sciubba
标识
DOI:10.1016/j.spinee.2020.06.019
摘要
Abstract
BACKGROUND CONTEXT
Intraoperative blood loss (IOBL) is unavoidable during surgery; however, high IOBL is associated with increased morbidity and increased risk for requiring allogenic blood transfusion, itself associated with poorer outcomes. PURPOSE
Here we sought to develop and validate a predictive calculator for IOBL that could be used by surgeons to estimate likely blood loss. STUDY DESIGN/SETTING
Retrospective cohort. PATIENT SAMPLE
Series of consecutive patients who underwent elective lumbar spine surgery for degenerative pathologies over a 27-month period at a single tertiary care center. OUTCOME MEASURES
Primary outcome was IOBL. Secondary outcome was the occurrence of "major intraoperative bleeding," defined as IOBL exceeding 1 L. METHODS
Charts of included patients were reviewed for medical comorbidities, preoperative laboratory data, surgical plan, and anesthesia records. Univariate linear regressions were performed to find significant predictors of IOBL, which were then subjected to a multivariate analysis to identify the final model. Model training was performed using 70% of the included cohort and external validation was performed using 30% of the cohort. Results of the model were deployed as a freely available online calculator. RESULTS
We identified 1,281 patients who met inclusion/exclusion criteria. Mean age was 60±15 years, mean Charlson Comorbidity score was 1.1±1.6, and 51.8% were male. There were no significant differences between the training and validation cohorts with regard to any of the demographic variables or intraoperative variables; tranexamic acid use and surgical invasiveness were also similar in both cohorts. Multivariate analysis identified body mass index (βₙ=7.14; 95% confidence interval [3.15, 11.13]; p<.001), surgical invasiveness (βₙ=29.18; [24.62, 33.74]; p<.001), tranexamic acid use (βₙ=−0.093; [−0.171, −0.014]; p=.02), and surgical duration (βₙ=2.13; [1.75, 2.51]; p<.001) as significant predictors of IOBL. The model had an overall fit of r=0.693 in the validation cohort. Construction of a receiver-operating curve for predicting major IOBL showed a C-statistic of 0.895 within the validation cohort. CONCLUSION
Here we identify and validate a model for predicting IOBL in patients undergoing lumbar spine surgery. The model was a moderately strong predictor of absolute IOBL and was demonstrated to predict the occurrence of major IOBL with a high degree of accuracy. We propose it may have future utility when counseling patients about surgical morbidity and the probability of requiring transfusion.
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