Models to predict the probability for intraoperative RBC transfusion during lumbar spinal stenosis and femoral fracture surgeries in aged patients

Clinical prediction model for red cell blood transfusion in elective primary posterior lumbar spine fusion

Overestimated the cross-match of preoperative PRC preparation for elective primary lumbar spinal fusion needs revision for cost-effectiveness. We aimed to develop a novel preoperative predictive model for appropriate PRC preparation. This clinical prediction model in a retrospective cohort was studied between January 2015 and September 2022. Multivariate logistic regression models were used to assess predictive variables. The logistic coefficient of each predictor generated scores to establish a predictive model. The area under the receiver operating characteristic curve (AuROC) was used to evaluate the model. The predictive performance was validated using bootstrapping techniques and externally validated in 102 independent cases. Among 416 patients, 178 (43%) required transfusion. Four final predictors: preoperative hematocrit level, laminectomy level, transforaminal lumbar interbody fusion level, and sacral fusion. When categorized into two risk groups, the positive predictive values for the low-risk score (≤ 4) were 18.4 (95% Cl 13.9, 23.6) and 83.9 (95% CI 77.1, 89.3) for the high-risk score (> 4). AuROC was 0.90. Internal validation (bootstrap shrinkage = 0.993) and external validation (AuROC: 0.91). A new model demonstrated exemplary performance and discrimination in predicting the appropriate preparation for PRC. This study should be corroborated by rigorous external validation in other hospitals and by prospective assessments.

The Utility of the Validated Intraoperative Bleeding Scale in Thoracolumbar Spine Surgery: A Single-Center Prospective Study

STUDY DESIGN

Prospective, single-center study.

OBJECTIVE

To evaluate the clinical relevance of the validated intraoperative bleeding severity scale (VIBe) in thoracolumbar spine surgery.

METHODS

Adult patients aged 18 through 88 undergoing elective decompression, instrumentation, and fusion of the thoracolumbar spine were prospectively enrolled after informed consent was provided and written consent was obtained. Validated intraoperative bleeding severity scores were recorded intraoperatively. Univariate analysis consisted of Student T-tests, Pearson's χ2 Tests, Fisher's Exact Tests, linear regression, and binary logistic regression. Multivariable regression was conducted to adjust for baseline characteristics and potential confounding variables.

RESULTS

A total of N = 121 patients were enrolled and included in the analysis. After adjusting for confounders, VIBe scores were correlated with an increased likelihood of intraoperative blood transfusion (β = 2.46, P = .012), postoperative blood transfusion (β = 2.36, P = .015), any transfusion (β = 2.49, P < .001), total transfusion volume (β = 180.8, P = .020), and estimated blood loss (EBL) (β = 409, P < .001). Validated intraoperative bleeding severity scores had no significant association with length of hospital stay, 30-day readmission, 30-day reoperation, 30-day emergency department visit, change in pre- to post-op hemoglobin and hematocrit, total drain output, or length of surgery.

CONCLUSION

The VIBe scale is associated with perioperative transfusion rates and EBL in patients undergoing thoracolumbar spine surgery. Overall, the VIBe scale has clinically relevant meaning in spine surgery, and shows potential utility in clinical research.

LEVEL OF EVIDENCE

Level II.

Blood transfusion risk prediction in spinal tuberculosis surgery: development and assessment of a novel predictive nomogram

Objective

The present study attempted to predict blood transfusion risk in spinal tuberculosis surgery by using a novel predictive nomogram.

Methods

The study was conducted on the clinical data of 495 patients (167 patients in the transfusion group and 328 patients in the non-transfusion group) who underwent spinal tuberculosis surgery in our hospital from June 2012 to June 2021. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analyses were used to screen out statistically significant parameters, which were included to establish a novel predictive nomogram model. The receiver operating characteristic (ROC) curve, calibration curves, C-index, and decision curve analysis (DCA) were used to evaluate the model. Finally, the nomogram was further assessed through internal validation.

Results

The C-index of the nomogram was 0.787 (95% confidence interval: 74.6%–.82.8%). The C-value calculated by internal validation was 0.763. The area under the curve (AUC) of the predictive nomogram was 0.785, and the DCA was 0.01–0.79.

Conclusion

A nomogram with high accuracy, clinical validity, and reliability was established to predict blood transfusion risk in spinal tuberculosis surgery. Surgeons must prepare preoperative surgical strategies and ensure adequate availability of blood before surgery.