Association and limited incremental discrimination of the systemic coagulation-inflammation index for Gensini-defined coronary anatomical burden
- 1Department of Comprehensive Internal Medicine Ⅲ, The First Affiliated Hospital of Xinjiang Medical University
- 2Laboratory Department, The First Affiliated Hospital of Xinjiang Medical University
Abstract
Background: The systemic coagulation-inflammation index (SCI), calculated as platelet count × fibrinogen/white blood cell count, integrates coagulation-related and inflammatory components, but its value for coronary anatomical burden remains uncertain. We evaluated the association of SCI with Gensini-defined coronary anatomical burden and its incremental discrimination beyond conventional clinical variables and comparative performance relative to established inflammatory indices.
Methods: Eligible angiography records from a single center were retrospectively analyzed. SCI was evaluated in relation to continuous Gensini burden and high Gensini burden defined by the 75th and 80th percentiles, and was compared with NLR, SII, SIRI, PLR, and MLR. Multivariable regression, nonlinear spline analysis, multiplicity-adjusted comparisons, incremental-performance analysis, sensitivity analyses, and exploratory machine-learning models were applied.
Results: Higher SCI was associated with lower Gensini-defined anatomical burden in the primary multivariable model, although the relationship was not uniformly monotonic across analyses. For high Gensini burden at the 75th percentile, the adjusted OR per 1-SD increase in log-transformed SCI was 0.843 (95% CI 0.727–0.978). Adding SCI to the clinical base model increased AUC only from 0.764 to 0.766 ( Δ AUC 0.0019, 95% CI −0.0010 to 0.0083). Conventional inflammatory markers, particularly NLR, SII, and SIRI, showed larger estimated incremental gains. Machine-learning findings were exploratory and limited by the selected complete-feature sample and lack of external validation. Important limitations included unavailable ACS classification, uncertain timing of blood sampling relative to angiography and treatment, non-random exclusion of records with invalid or missing SCI components, and inability to verify unique-individual linkage.
Conclusions: SCI was associated with Gensini-defined coronary anatomical burden, but its incremental discriminatory value was limited and does not support routine clinical use. Prospective multicenter studies with standardized clinical characterization and external validation are warranted.
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BibTeX
@article{chen2026association,
title = {{Association and limited incremental discrimination of the systemic coagulation-inflammation index for Gensini-defined coronary anatomical burden}},
author = {Zhuo Chen and Palida Abulaiti and Palizhati Abudureyimu and Ying Gao and Zhi Xing and Maolin Lv and Hui Li and Jing Shang and Shajidan Abudureyimu},
journal = {Frontiers in Cardiovascular Medicine},
year = {2026},
month = nov,
doi = {10.3389/fcvm.2026.1925478},
url = {https://www.frontiersin.org/articles/10.3389/fcvm.2026.1925478/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Association and limited incremental discrimination of the systemic coagulation-inflammation index for Gensini-defined coronary anatomical burden
AU - Zhuo Chen
AU - Palida Abulaiti
AU - Palizhati Abudureyimu
AU - Ying Gao
AU - Zhi Xing
AU - Maolin Lv
AU - Hui Li
AU - Jing Shang
AU - Shajidan Abudureyimu
PY - 2026
DA - 2026/11/02
JO - Frontiers in Cardiovascular Medicine
DO - 10.3389/fcvm.2026.1925478
UR - https://www.frontiersin.org/articles/10.3389/fcvm.2026.1925478/full
AB - Background: The systemic coagulation-inflammation index (SCI), calculated as platelet count × fibrinogen/white blood cell count, integrates coagulation-related and inflammatory components, but its value for coronary anatomical burden remains uncertain. We evaluated the association of SCI with Gensini-defined coronary anatomical burden and its incremental discrimination beyond conventional clinical variables and comparative performance relative to established inflammatory indices. Methods: Eligible angiography records from a single center were retrospectively analyzed. SCI was evaluated in relation to continuous Gensini burden and high Gensini burden defined by the 75th and 80th percentiles, and was compared with NLR, SII, SIRI, PLR, and MLR. Multivariable regression, nonlinear spline analysis, multiplicity-adjusted comparisons, incremental-performance analysis, sensitivity analyses, and exploratory machine-learning models were applied. Results: Higher SCI was associated with lower Gensini-defined anatomical burden in the primary multivariable model, although the relationship was not uniformly monotonic across analyses. For high Gensini burden at the 75th percentile, the adjusted OR per 1-SD increase in log-transformed SCI was 0.843 (95% CI 0.727–0.978). Adding SCI to the clinical base model increased AUC only from 0.764 to 0.766 ( Δ AUC 0.0019, 95% CI −0.0010 to 0.0083). Conventional inflammatory markers, particularly NLR, SII, and SIRI, showed larger estimated incremental gains. Machine-learning findings were exploratory and limited by the selected complete-feature sample and lack of external validation. Important limitations included unavailable ACS classification, uncertain timing of blood sampling relative to angiography and treatment, non-random exclusion of records with invalid or missing SCI components, and inability to verify unique-individual linkage. Conclusions: SCI was associated with Gensini-defined coronary anatomical burden, but its incremental discriminatory value was limited and does not support routine clinical use. Prospective multicenter studies with standardized clinical characterization and external validation are warranted.
SN - 2297-055X
ER -