Clinical and Hematological Factors Affecting Perioperative Blood Loss Following Total Knee Arthroplasty: A New Clinical Prediction Model
Authors: Hengyan Zhang1, Xuemeng Mu1, Zheping Zhang2, Jin Lin1, Jin Jin1, Wenwei Qian1, Bin Feng1, Xisheng Weng1
Affiliations:
1Department of Orthopaedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing 100730, China
2Department of Orthopaedics, Beijing Puren Hospital, Beijing 100062, China
Introduction
Total knee arthroplasty (TKA) is a widely performed surgical procedure for treating end-stage knee osteoarthritis. Despite its effectiveness, TKA is associated with various complications, including infection, thromboembolism, and significant blood loss. Excessive perioperative blood loss can lead to increased transfusion rates, prolonged hospitalization, and higher healthcare costs. Although advancements in surgical techniques and adjuvant medications have reduced postoperative blood loss, there remains a need for a systematic approach to predict and manage this risk.
This study aimed to:
- Identify clinical and hematological factors influencing blood loss following TKA.
- Develop a predictive model for individualized estimation of perioperative blood loss.
- Propose strategies for managing adverse outcomes associated with blood loss.
Methods
The study was approved by the Institutional Review Board of Peking Union Medical College Hospital (No. S-K2005). As a retrospective study, patient informed consent was waived. Data from 1,587 patients who underwent primary TKA were analyzed. Variables included demographics (age, gender, body mass index [BMI]), lifestyle factors (tobacco and alcohol use), and perioperative laboratory parameters.
Total blood loss was calculated using a formula that accounted for both uncompensated and compensated red blood cell (RBC) loss. Uncompensated RBC loss was derived from the difference between initial and final RBC volumes, while compensated RBC loss included transfusions received. Initial and final RBC volumes were calculated using estimated blood volume and hematocrit (HCT) levels. Blood volume was estimated separately for men and women based on body surface area.
Statistical analyses were performed using SPSS and RStudio. Multivariable stepwise linear regression identified independent factors influencing blood loss. A LASSO Cox regression model was used to assess associations between predictors and outcomes. The model was internally validated using 1,000 bootstrap samples and externally validated using a cohort of 500 patients from another center. Model performance was evaluated using receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA).
Results
The average total blood loss on the third postoperative day was 961.29 ± 489.40 mL. Male patients experienced significantly higher blood loss (1,218.33 ± 549.67 mL) compared to female patients (898.89 ± 452.53 mL).
Multivariate analysis identified several independent risk factors for blood loss, including preoperative HCT, albumin (ALB) levels, and tobacco use. A nomogram was developed to predict the risk of postoperative hemorrhage, with a cutoff score of 200 indicating high risk. The nomogram demonstrated good accuracy, with an unadjusted C index of 0.78 and a bootstrap-corrected C index of 0.77. ROC analysis showed an area under the curve (AUC) of 0.784, with sensitivity and specificity of 79% and 64%, respectively.
External validation confirmed the model’s stability, with an AUC of 0.774. Calibration plots and DCA indicated high consistency between predicted and observed outcomes, as well as clinical utility.
Discussion
This study provides a comprehensive analysis of factors influencing perioperative blood loss following TKA and introduces a novel predictive model. The findings highlight the importance of preoperative hematological parameters and lifestyle factors in assessing blood loss risk.
Tobacco Use
Tobacco use was positively correlated with increased blood loss. Smoking can damage endothelial cells, impair platelet function, and increase hemolysis, all of which contribute to higher bleeding risk.
Preoperative Hematocrit
Higher preoperative HCT levels were associated with greater blood loss. Elevated HCT may lead to increased blood accumulation in interstitial spaces and exacerbate postoperative hyperfibrinolysis, resulting in higher total blood loss.
Preoperative Albumin
Elevated albumin levels were also linked to increased blood loss. Albumin can compromise coagulation, inhibit platelet aggregation, and cause volume expansion, all of which contribute to bleeding.
Clinical Implications
The nomogram developed in this study offers a practical tool for clinicians to identify patients at high risk of postoperative hemorrhage. By integrating demographic and hematological factors, the model enables personalized blood management strategies, potentially reducing transfusion rates and improving patient outcomes.
Limitations
This study has several limitations. First, the data were sourced from a single center, limiting geographical generalizability. Second, the retrospective design relied on medical records, which may be incomplete or inaccurate. Future prospective studies are needed to validate the findings and refine the predictive model.
Conclusion
This study identifies key clinical and hematological factors influencing perioperative blood loss following TKA and presents a novel predictive model. The nomogram provides a valuable tool for assessing blood loss risk and guiding clinical decision-making. By enabling personalized blood management strategies, this model has the potential to improve patient outcomes and reduce healthcare costs.
DOI: doi.org/10.1097/CM9.0000000000003519
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