Routine Laboratory Tests Predict 72-h Fatality in Patients With D-Dimer Levels ≥ 2 μg/mL: A Retrospective Cohort
Shuma Hayashi1, Ryoko Hayashi1, Kayoko Nakamura2
1Division of General Medicine, Department of Comprehensive Medicine 1, Jichi Medical University, Saitama Medical Center, Saitama, Japan.
Background:
Despite the high prognostic value of D-dimer in various clinical conditions, limited research has addressed short-term fatality prediction across disease categories. This study aimed to develop and compare models predicting 72-h fatality in patients with D-dimer levels ≥ 2 μg/mL, using laboratory variables. This timeframe was chosen based on its clinical relevance for early triage and intervention across multiple acute conditions.
Methods:
We retrospectively analyzed data from 5158 patients (241 deaths within 72 h). The primary outcome was 72-h fatality; predictors included age, sex, and 40 routine hematologic, biochemical, and coagulation tests. Traditional multivariate logistic regression analysis (MLRA) was compared with four machine learning (ML) models: Prediction One, LightGBM, XGBoost, and CatBoost. External validation was performed using a separate dataset of 5550 patients (309 deaths). D-dimer levels were recorded in any clinical setting despite limited patient medical information.
Results:
The 72-h fatality rate increased with increasing D-dimer levels (overall 4.67%). Major causes of death were intracranial disease (24.9%), malignancy (17.0%), and sepsis (8.3%). MLRA identified five key predictors: advanced age, low total protein and cholesterol levels, and elevated aspartate aminotransferase and D-dimer levels. Its performance (AUC 0.829, 95% CI 0.768-0.888; sensitivity 0.762; specificity 0.809) was exceeded by LightGBM (AUC 0.987; sensitivity 0.987; specificity 0.911), which outperformed Prediction One (0.814), XGBoost (0.981), and CatBoost (0.937).
Conclusion:
ML models, particularly LightGBM, effectively identify high-risk patients using routine laboratory tests. The model enables timely decision-making and early risk stratification in patients with high D-dimer values, even when clinical information is limited.
