Effect of Cilostazol on Delayed Cerebral Infarction in Aneurysmal Subarachnoid Hemorrhage Using Explainable Predictive Modeling
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Collection
2.2. Statistical Analysis
2.3. Hybrid Approach for Feature Analysis and DCI Effect Prediction
2.3.1. XAI
SHAP
LIME
2.3.2. K-Fold Cross-Validation and Programming Environment
3. Results
3.1. Statistical Analysis
3.2. Global Feature Analysis of the Risk Factors Related to DCI Using XAI
3.3. Local Feature Analysis of the Risk Factors Related to DCI
3.4. Performance Evaluation Using ML Modeling
4. Discussion
4.1. Conventional Analysis of Cilostazol Effect on DCI in Patients with aSAH
4.2. Explainable Modeling in Patients with aSAH
4.3. In-Depth Understanding of Global and Local Interpretations of Risk Factors
4.4. Prediction Analysis of DCI Probability by Aneurysm Size
4.5. Hyperparameter Tuning within XAI and the Limitation of this Study
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristics | Nimodipine Only (n = 232) | Cilostazol and Nimodipine (n = 89) | p-Value | Data Type | Value |
---|---|---|---|---|---|
Age, y, mean (SD) | 55.47 (12.756) | 55.37 (14.150) | 0.952 | Float | 21–94 |
Sex, female, n (%) | 147 (63.4) | 51 (57.3) | 0.318 | Binary | 1: male; 2: female |
GCS on admission, mean (SD) | 12.81 (3.248) | 13.25 (3.185) | 0.279 | Integer | 1–15 |
Aneurysm size, mm, mean (SD) | 5.63 (3.016) | 6.55 (4.123) | 0.029 | Float | 0.6–27 |
Hunt–Hess grade | N/A | N/A | 0.142 | Integer | 1–5 |
1 | 12 | 1 | |||
2 | 115 | 57 | |||
3 | 67 | 20 | |||
4 | 33 | 9 | |||
5 | 5 | 2 | |||
Fisher grade | N/A | N/A | 0.068 | Integer | 1–4 |
1 | 14 | 6 | |||
2 | 18 | 12 | |||
3 | 103 | 26 | |||
4 | 97 | 45 | |||
Location | N/A | N/A | 0.007 | Integer | 1: ACA; 2: MCA; 3: ICA; 4: VA or BA |
ACA | 86 | 40 | |||
MCA | 60 | 10 | |||
ICA | 74 | 28 | |||
VA or BA | 12 | 11 | |||
HTN, n (%) | 95 (40.9) | 35 (39.3) | 0.791 | Binary | 0 or 1 |
DM, n (%) | 25 (10.8) | 13 (14.6) | 0.342 | Binary | 0 or 1 |
Hyperlipidemia, n (%) | 17 (7.3) | 12 (13.5) | 0.085 | Binary | 0 or 1 |
Smoking, n (%) | 76 (32.8) | 37 (41.6) | 0.139 | Binary | 0 or 1 |
Clip/coil, n (%) | 169 (72.8)/63 (27.2) | 16 (18.0)/73 (82.0) | 0 | Binary | 0 or 1 |
ACV | 68 (29.3) | 12 (13.5) | 0.003 | Binary | 0 or 1 |
DCI | 48 (20.7) | 7 (7.9) | 0.006 | Binary | 0 or 1 |
Variables | OR | 95% CI | p-Value |
---|---|---|---|
Cilostazol with nimodipine | 0.556 | 0.351–0.879 | 0.012 |
Female sex | 3.713 | 1.683–8.191 | 0.001 |
Age | 0.972 | 0.946–0.999 | 0.042 |
Aneurysm size | 1.106 | 1.008–1.214 | 0.034 |
Treatment method | 1.1 | 0.483–2.502 | 0.821 |
Models | Accuracy | Sensitivity | Specificity |
---|---|---|---|
XGBoost | 0.91 | 0.70 | 0.95 |
Logistic regression | 0.92 | 0.80 | 0.95 |
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Kim, K.H.; Lee, B.-J.; Koo, H.-W. Effect of Cilostazol on Delayed Cerebral Infarction in Aneurysmal Subarachnoid Hemorrhage Using Explainable Predictive Modeling. Bioengineering 2023, 10, 797. https://doi.org/10.3390/bioengineering10070797
Kim KH, Lee B-J, Koo H-W. Effect of Cilostazol on Delayed Cerebral Infarction in Aneurysmal Subarachnoid Hemorrhage Using Explainable Predictive Modeling. Bioengineering. 2023; 10(7):797. https://doi.org/10.3390/bioengineering10070797
Chicago/Turabian StyleKim, Kwang Hyeon, Byung-Jou Lee, and Hae-Won Koo. 2023. "Effect of Cilostazol on Delayed Cerebral Infarction in Aneurysmal Subarachnoid Hemorrhage Using Explainable Predictive Modeling" Bioengineering 10, no. 7: 797. https://doi.org/10.3390/bioengineering10070797