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Validation Study of the Transfusion Risk and Clinical Knowledge (TRACK) Tool in Cardiac Surgery Patients: A
Jonathan Leff1, Christopher A Romano2, Stephanie Gilbert3
1Department of Anesthesiology, Montefiore Medical Center, Bronx, NY; Albert Einstein College of Medicine, Bronx, NY.
Insights
The Transfusion Risk and Clinical Knowledge (TRACK) score effectively predicts perioperative blood transfusions in US cardiac surgery patients. This validation study supports TRACK
Area of Science:
- Cardiovascular Surgery
- Transfusion Medicine
- Medical Informatics
Background:
- The Transfusion Risk and Clinical Knowledge (TRACK) scoring system aids in predicting perioperative blood transfusions.
- External validation of the TRACK score in the US population is necessary.
- This study aimed to validate the TRACK score at a US academic medical center.
Purpose of the Study:
- To externally validate the TRACK scoring system for predicting perioperative blood transfusions.
- To assess the discriminatory power of the TRACK score in adult cardiac surgery patients.
- To establish optimal cutoff scores for identifying high-risk patients.
Main Methods:
- Single-center retrospective analysis of 2,776 adult cardiac surgery patients (2010-2015).
- Utilized the Society of Thoracic Surgeons database to determine TRACK scores.
- Employed receiver operating characteristic (ROC) curves to evaluate predictive accuracy.
Main Results:
- 51.8% of patients received perioperative transfusions.
- The average TRACK score was significantly higher in transfused (12.4 ± 7.2) versus non-transfused (6.1 ± 5.4) patients (p < 0.001).
- Area under the ROC curve was 0.768 for predicting any perioperative transfusion; a cutoff score of ≥22 yielded 67% sensitivity and 73% specificity.
Conclusions:
- The TRACK score is a valid predictor of perioperative blood transfusions in US cardiac surgery patients.
- This study confirms the external validity and clinical utility of the TRACK score.
- Established cutoff scores enhance the identification of patients at high risk for transfusion.
Objective:
The Transfusion Risk and Clinical Knowledge (TRACK) scoring system has been developed for predicting perioperative blood transfusions. However, the TRACK score needs to be validated externally in the US population. The primary objective of this study is to validate TRACK at the authors' institution.
Design:
This study was a single-center retrospective analysis.
Setting:
Operating room and intensive care units of academic medical center.
Participants:
Adult cardiac surgery patients.
Interventions:
The authors retrospectively queried all cardiac surgeries at the authors' institution between 2010 and 2015 from the Society of Thoracic Surgeons database. The TRACK scores were determined for all patients. The authors used receiver operating characteristic (ROC) curves to assess the discriminatory power of TRACK in predicting any perioperative, intraoperative, and postoperative transfusions. The maximum Youden's index was used to determine optimal cutoff scores for predicting perioperative transfusions.
Measurements And Main Results:
The authors analyzed 2,776 cardiac surgery patients with 51.8% transfused perioperatively. The average TRACK score (mean ± standard deviation) in transfused versus non-transfused patients was 12.4 ± 7.2 versus 6.1 ± 5.4, respectively (p < 0.001). The area under the ROC curve was 0.768 (95% confidence interval 0.800-0.835, p < 0.001) for any perioperative transfusion. Optimal sensitivity (67%) and specificity (73%) for predicting any perioperative transfusions was achieved with a TRACK score cutoff of greater than or equal to 22 of 32.
Conclusion:
This study demonstrates the validity of the TRACK score in predicting blood perioperative transfusions in cardiac surgery patients at the authors' institution. This study supports the external validity of TRACK and adds to its clinical utility by establishing cutoff scores for identifying patients at high risk of transfusion.
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