Dataset Information

Variable Response to Antifibrinolytics Correlates with Blood-loss and Transfusion in Posterior Spinal Fusion.

ABSTRACT:

Purpose

Posterior spinal fusion (PSF) activates the fibrinolytic protease plasmin, which is implicated in blood loss and transfusion. While antifibrinolytic drugs have improved blood loss and reduced transfusion, variable blood loss has been observed in similar PSF procedures treated with the same dose of antifibrinolytics. However, both the cause of this and the appropriate measures to determine antifibrinolytic efficacy during high-blood-loss spine surgery are unknown, making clinical trials to optimize antifibrinolytic dosing in PSF difficult. We hypothesized that patients undergoing PSF respond differently to antifibrinolytic dosing, resulting in variable blood loss, and that specific diagnostic markers of plasmin activity will accurately measure the efficacy of antifibrinolytics in PSF.

Methods

A prospective study of 17 patients undergoing elective PSF with the same dosing regimen of TXA was conducted. Surgery-induced plasmin activity was exhaustively analyzed in perioperative blood samples and correlated to measures of inflammation, bleeding, and transfusion.

Results

While markers of in vivo plasmin activation (PAP and D-dimer) suggested significant breakthrough plasmin activation and fibrinolysis (P < 0.01), in vitro plasmin assays, including TEG, did not detect plasmin activation. In vivo measures of breakthrough plasmin activation correlated with blood loss (R² = 0.400, 0.264; P < 0.01), transfusions (R² = 0.388; P < 0.01), and complement activation (R² = 0.346, P < 0.05).

Conclusions

Despite all patients receiving a high dose of TXA, its efficacy among patients was variable, indicated by notable intra-operative plasmin activity. Markers of in vivo plasmin activation best correlated with clinical outcomes. These findings suggest that the efficacy of antifibrinolytic therapy to inhibit plasmin in PSF surgery should be determined by markers of in vivo plasmin activation in future studies.

Level of evidence

Level II-diagnostic.

SUBMITTER: Gibson BHY

PROVIDER: S-EPMC9891390 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

Variable Response to Antifibrinolytics Correlates with Blood-loss and Transfusion in Posterior Spinal Fusion.

Gibson Breanne H Y BHY Duvernay Matthew T MT McKeithan Lydia J LJ Benvenuti Teresa A TA Warhoover Tracy A TA Martus Jeffrey E JE Mencio Gregory A GA Emerson Brian R BR Moore-Lotridge Stephanie N SN Borst Alexandra J AJ Schoenecker Jonathan G JG

Spine deformity 20220305 4

<h4>Purpose</h4>Posterior spinal fusion (PSF) activates the fibrinolytic protease plasmin, which is implicated in blood loss and transfusion. While antifibrinolytic drugs have improved blood loss and reduced transfusion, variable blood loss has been observed in similar PSF procedures treated with the same dose of antifibrinolytics. However, both the cause of this and the appropriate measures to determine antifibrinolytic efficacy during high-blood-loss spine surgery are unknown, making clinical ...[more]

PMID: 35247191

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Project description:Background: Accurate estimation of perioperative blood transfusion risk in lumbar posterior interbody fusion is essential to reduce the number, cost, and complications associated with blood transfusions. Machine learning algorithms have the potential to outperform traditional prediction methods in predicting perioperative blood transfusion. This study aimed to construct a machine learning-based perioperative transfusion risk prediction model for lumbar posterior interbody fusion in order to improve the efficacy of surgical decision-making. Methods: We retrospectively collected clinical data on 1905 patients who underwent lumbar posterior interbody fusion surgery at the Second Hospital of Shanxi Medical University between January 2021 and March 2023. All the data was randomly divided into a training set and a validation set, and the "feature_importances" method provided by eXtreme Gradient Boosting (XGBoost) algorithm was applied to select statistically significant features on the training set to establish five machine learning prediction models. The optimal model was identified by utilizing the area under the curve (AUC) and the probability calibration curve on the validation set. Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME) were employed for interpretable analysis of the optimal model. Results: In the postoperative outcomes of patients, the number of hospital days in the transfusion group was longer than that in the non-transfusion group. Additionally, the transfusion group experienced higher total hospital costs, 90-day readmission rates, and complication rates within 90 days after surgery than the non-transfusion group. A total of 9 features were selected for the models. The XGBoost model performed best with an AUC value of 0.958. The SHAP values showed that intraoperative blood loss, intraoperative fluid infusion, and number of fused segments were the top 3 most important features affecting perioperative blood transfusion in lumbar posterior interbody fusion. The LIME algorithm was used to interpret the individualized prediction. Conclusion: Surgery, ASA class, levels fused, total intraoperative blood loss, operative time, and preoperative Hb are viable predictors of perioperative blood transfusion in lumbar posterior interbody fusion. The XGBoost model has demonstrated superior predictive efficacy compared to the traditional logistic regression model, making it a more effective decision-making tool for perioperative blood transfusion.

Dataset Information

Variable Response to Antifibrinolytics Correlates with Blood-loss and Transfusion in Posterior Spinal Fusion.

Purpose

Methods

Results

Conclusions

Level of evidence

Publications

Variable Response to Antifibrinolytics Correlates with Blood-loss and Transfusion in Posterior Spinal Fusion.

Similar Datasets

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