Development and Internal Validation of a Clinical Prediction Model for Coronary Slow Flow Phenomenon in Type 2 Diabetes: A Retrospective Observational Study.
- 1Department of Cardiology, the Fifth Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
- 2Department of Cardiovascular Medicine, Shaanxi Provincial People's Hospital, Xi'an, People's Republic of China.
Abstract
Background
Patients with type 2 diabetes mellitus (T2DM) may exhibit coronary slow flow phenomenon (CSFP) despite the absence of obstructive epicardial coronary stenosis. Dedicated prediction tools remain limited. This study aimed to develop and internally validate a model for estimating the probability of TIMI frame count (TFC)-defined CSFP in patients with T2DM.Methods
Among 501 patients with T2DM undergoing coronary angiography at a single center in Xinjiang, China (2021-2025), 429 met eligibility criteria. CSFP was defined as maximum coronary stenosis <40% and TFC >27 frames in at least one major coronary artery. Patients were randomly divided into training (n = 300) and validation (n = 129) cohorts. Predictors selected by penalized regression were entered into multivariable logistic regression. Performance was assessed using area under the receiver operating characteristic curve (ROC-AUC), area under the precision-recall curve (AUC-PR), calibration, bootstrap-corrected concordance index, and decision curve analysis; additional analyses were complementary.Results
CSFP occurred in 44 patients (14.7%) in the training cohort and 16 (12.4%) in the validation cohort. The final model included smoking history, systolic blood pressure, hemoglobin A1c, lymphocyte count, and uric acid. ROC-AUC was 0.832 (95% confidence interval [CI]: 0.774-0.889) in the training cohort and 0.840 (95% CI: 0.733-0.946) in the validation cohort; AUC-PR was 0.467 and 0.542, respectively. Calibration was acceptable (Brier scores 0.101 and 0.084); bootstrap-corrected concordance indices were 0.827 and 0.846. Decision curve analysis suggested net benefit across clinically relevant thresholds. Given the limited number of CSFP events in the validation cohort, validation estimates should be interpreted cautiously.Conclusion
We developed and internally validated a five-variable model for estimating the probability of TFC-defined CSFP in patients with T2DM. The model was translated into a nomogram and web-based calculator as a complementary tool for individualized risk characterization. External validation is required before broader clinical application.
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BibTeX
@article{hu2026development,
title = {{Development and Internal Validation of a Clinical Prediction Model for Coronary Slow Flow Phenomenon in Type 2 Diabetes: A Retrospective Observational Study.}},
author = {Su Hu and Chang-Shun Yan and Tong Xu and Yao Li and Tian Tian and Na Zhao and Gui-Qiu Cao},
journal = {International journal of general medicine},
year = {2026},
month = oct,
doi = {10.2147/ijgm.s640373},
url = {https://europepmc.org/article/MED/42928914},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Development and Internal Validation of a Clinical Prediction Model for Coronary Slow Flow Phenomenon in Type 2 Diabetes: A Retrospective Observational Study.
AU - Su Hu
AU - Chang-Shun Yan
AU - Tong Xu
AU - Yao Li
AU - Tian Tian
AU - Na Zhao
AU - Gui-Qiu Cao
PY - 2026
DA - 2026/10/21
JO - International journal of general medicine
DO - 10.2147/ijgm.s640373
UR - https://europepmc.org/article/MED/42928914
AB - Background Patients with type 2 diabetes mellitus (T2DM) may exhibit coronary slow flow phenomenon (CSFP) despite the absence of obstructive epicardial coronary stenosis. Dedicated prediction tools remain limited. This study aimed to develop and internally validate a model for estimating the probability of TIMI frame count (TFC)-defined CSFP in patients with T2DM.Methods Among 501 patients with T2DM undergoing coronary angiography at a single center in Xinjiang, China (2021-2025), 429 met eligibility criteria. CSFP was defined as maximum coronary stenosis <40% and TFC >27 frames in at least one major coronary artery. Patients were randomly divided into training (n = 300) and validation (n = 129) cohorts. Predictors selected by penalized regression were entered into multivariable logistic regression. Performance was assessed using area under the receiver operating characteristic curve (ROC-AUC), area under the precision-recall curve (AUC-PR), calibration, bootstrap-corrected concordance index, and decision curve analysis; additional analyses were complementary.Results CSFP occurred in 44 patients (14.7%) in the training cohort and 16 (12.4%) in the validation cohort. The final model included smoking history, systolic blood pressure, hemoglobin A1c, lymphocyte count, and uric acid. ROC-AUC was 0.832 (95% confidence interval [CI]: 0.774-0.889) in the training cohort and 0.840 (95% CI: 0.733-0.946) in the validation cohort; AUC-PR was 0.467 and 0.542, respectively. Calibration was acceptable (Brier scores 0.101 and 0.084); bootstrap-corrected concordance indices were 0.827 and 0.846. Decision curve analysis suggested net benefit across clinically relevant thresholds. Given the limited number of CSFP events in the validation cohort, validation estimates should be interpreted cautiously.Conclusion We developed and internally validated a five-variable model for estimating the probability of TFC-defined CSFP in patients with T2DM. The model was translated into a nomogram and web-based calculator as a complementary tool for individualized risk characterization. External validation is required before broader clinical application.
SN - 1178-7074
ER -