# A Novel Scoring System Predicting Red Blood Cell Transfusion Requirements in Patients Undergoing Invasive Spine Surgery

**Authors:** Alina Schenk, Jonas Ende, Jochen Hoch, Erdem Güresir, Josefin Grabert, Mark Coburn, Matthias Schmid, Markus Velten

PMC · DOI: 10.3390/jcm13040948 · 2024-02-07

## TL;DR

This study creates a scoring system to predict the need for blood transfusions in spine surgery patients, aiming to reduce blood shortages.

## Contribution

A novel logistic regression-based scoring system was developed to predict RBC transfusion requirements in spine surgery patients.

## Key findings

- The model achieved an average AUC of 0.87 for predicting transfusion needs.
- Surgical type and procedure extent were more influential than patient pre-existing conditions.
- Internal validation showed consistent performance with an AUC of 0.84.

## Abstract

Background: Access to blood products is crucial for patient safety during the perioperative course. However, reduced donations and seasonally occurring blood shortages pose a significant challenge to the healthcare system, with surgeries being postponed. The German Blood Transfusion act requires that RBC packages become assigned to an individual patient, resulting in a significant reduction in the available blood products, further aggravating shortages. We aimed to develop a scoring system predicting transfusion probability in patients undergoing spine surgery to reduce assignment and, thus, increase the availability of blood products. Methods: The medical records of 252 patients who underwent spine surgery were evaluated and 18 potential predictors for RBC transfusion were tested to construct a logistic-regression-based predictive scoring system for blood transfusion in patients undergoing spine surgery. Results: The variables found to be the most important included the type of surgery, vertebral body replacement, number of stages, and pre-operative Hb concentration, indicating that surgical specification and the extent of the surgical procedure were more influential than the pre-existing patient condition and medication. Conclusions: Our model showed a good discrimination ability with an average AUC [min, max] of 0.87 [0.6, 0.97] and internal validation with a similar AUC of 0.84 [0.66, 0.97]. In summary, we developed a scoring system to forecast patients’ perioperative transfusion needs when undergoing spine surgery using pre-operative predictors, potentially reducing the need for RBC allocation and, thus, resulting in an increased availability of this valuable resource.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC10888619/full.md

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Source: https://tomesphere.com/paper/PMC10888619