ArticleProceedings of the National Academy of Sciences of the United States of America2017
White blood cell population dynamics for risk stratification of acute coronary syndrome.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Plasma lipid remodeling during the early recovery phase after myocardial infarction.Scientific reports · 2026Article
- Mean platelet volume is a predictor for abscess formation in patients with epididymitis.Translational andrology and urology · 2025Article
- Improved leukocyte classification in bone marrow cytology using convolutional neural network with contrast enhancement.Scientific reports · 2025Article
- Transformer-based artificial intelligence on single-cell clinical data for homeostatic mechanism inference and rational biomarker discovery.medRxiv : the preprint server for health sciences · 2025Article
- Systemic Immune Inflammation Index (SII), System Inflammation Response Index (SIRI) and Risk of All-Cause Mortality and Cardiovascular Mortality: A 20-Year Follow-Up Cohort Study of 42,875 US Adults.Journal of clinical medicine · 2023Article
- White Blood Cell and Platelet Dynamics Define Human Inflammatory Recovery.medRxiv : the preprint server for health sciences · 2021Article
- Synthesis ofVaccines · 2021Article
- Evaluation of left ventricular myocardial movement in rats by velocity vector imaging.PloS one · 2020Article
- Article
- Optimized protocols for isolation, fixation, and flow cytometric characterization of leukocytes in ischemic hearts.American journal of physiology. Heart and circulatory physiology · 2019Article
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Authors and funding
3 authors.
Funding
Abstract
The complete blood count (CBC) provides a high-level assessment of a patient's immunologic state and guides the diagnosis and treatment of almost all diseases. Hematology analyzers evaluate CBCs by making high-dimensional single-cell measurements of size and cytoplasmic and nuclear morphology in high throughput, but only the final cell counts are commonly used for clinical decisions. Here, we utilize the underlying single-cell measurements from conventional clinical instruments to develop a mathematical model guided by cellular mechanisms that quantifies the population dynamics of neutrophil, lymphocyte, and monocyte characteristics. The dynamic model tracks the evolution of the morphology of WBC subpopulations as a patient transitions from a healthy to a diseased state. We show how healthy individuals and hospitalized patients with similar WBC counts can be robustly classified based on their WBC population dynamics. We combine the model with supervised learning techniques to risk-stratify patients under evaluation for acute coronary syndrome. In particular, the model can identify more than 70% of patients in our study population with initially negative screening tests who will be diagnosed with acute coronary syndrome in the subsequent 48 hours. More generally, our study shows how mechanistic modeling of existing clinical data can help realize the vision of precision medicine.
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