Establishment and assessment of a nomogram for predicting blood transfusion risk in posterior lumbar spinal fusion

H Wang, K Wang, B Lv, H Xu, W Jiang, J Zhao… - Journal of Orthopaedic …, 2021 - Springer
H Wang, K Wang, B Lv, H Xu, W Jiang, J Zhao, M Kang, R Dong, Y Qu
Journal of Orthopaedic Surgery and Research, 2021Springer
Background The aim of this study was to determine the risk factors and develop a nomogram
for blood transfusions after posterior lumbar spinal fusion (PSL). Methods We conducted a
retrospective, single-center study based on 885 patients receiving PSL, and data was
obtained from May 2015 to September 2019. Univariable and multivariable logistics
regression analysis were conducted to identify risk factors for blood transfusion, and a
nomogram was constructed to individually evaluate the risk of blood transfusion …
Background
The aim of this study was to determine the risk factors and develop a nomogram for blood transfusions after posterior lumbar spinal fusion (PSL).
Methods
We conducted a retrospective, single-center study based on 885 patients receiving PSL, and data was obtained from May 2015 to September 2019. Univariable and multivariable logistics regression analysis were conducted to identify risk factors for blood transfusion, and a nomogram was constructed to individually evaluate the risk of blood transfusion. Discrimination, calibration, and clinical usefulness were validated by the receiver operating characteristics (ROC), C-index, calibration plot, and decision curve analysis, respectively. Bootstrapping validation was performed to assess the performance of the model.
Results
Of 885 patients, 885 were enrolled in the final study population, and 289 received blood transfusion. Statistical analyses showed that low preoperative hemoglobin (Hb), longer time to surgery, operative time, levels of fusion > 1, longer surgery duration, and higher total intraoperative blood loss (IBL) were the risk factors for transfusion. The C-index was 0.898 (95% CI 0.847–0.949) in this dataset and 0.895 in bootstrapping validation, respectively. Calibration curve showed satisfied discrimination and calibration of the nomogram. Decision curve analysis (DCA) shown that the nomogram was clinical utility.
Conclusions
In summary, we investigated the relationship between the blood transfusion requirement and predictors: levels of fusion, operative time, time to surgery, total intraoperative EBL, and preoperative Hb level. Our nomogram with a robust performance in the assessment of risk of transfusion can contribute to clinicians in making clinical decision. However, external validation is still needed in the further.
Springer
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