This study retrospectively and continuously collected patients with aSAH who were hospitalized and treated at the Affiliated Yixing Hospital of Jiangsu University and the Affiliated Zhenjiang First Hospital of Jiangsu University from 1st January, 2015 to 31st December, 2022. Diagnosis, surgery, and perioperative management strictly adhered to the latest clinical practice guidelines of the Chinese Medical Association (9). The surgical approach for each case was determined by a neurosurgical team of senior neurosurgeons, based on individual patient characteristics, aneurysm features, and in accordance with available clinical guidelines. When both surgical options were deemed feasible, the final decision was made through team consensus, taking into account the preferences of the patient’s family or designated surrogate decision-maker. Postoperatively, patients typically required intensive care management, which followed guideline-based protocols and included close monitoring, appropriate sedation and analgesia, cardiovascular support, vasospasm prevention, and active management of potential complications. The study adhered to the Helsinki Declaration and obtained approval from the ethics committees of two hospitals, with approval numbers 2023043 and K-20230086-w. All participants or their authorized representatives were required to sign an informed consent form during hospitalization, ensuring their full understanding of the purpose, methods, risks, and benefits of the surgery and study, and indicating their voluntary participation.

Inclusion criteria include: (1) age 18 years or older; (2) confirmed as aSAH through laboratory and imaging examinations; (3) patients must undergo either endovascular coiling or surgical clipping treatment. Exclusion criteria include: (1) previous hospitalization for aSAH; (2) subarachnoid hemorrhage caused by other reasons, including vascular malformation, cerebral atherosclerosis, trauma, etc.; (3) the presence of severe cardiovascular, liver, kidney or other vital organ diseases; (4) loss of clinical parameters such as platelet count and D-dimer.

The study variables include demographic information (age and sex), physical examination data (body temperature and mean arterial pressure), laboratory tests (D-dimer, and platelet count), imaging examinations (length, width, height, position, etc.), past medical history (hypertension and diabetes), clinical scoring tools (GCS, Hunt–Hess, and mFS), treatment modalities (endovascular coiling and surgical clipping), and the use of stents. Patients were stratified into the endovascular coiling group and the surgical clipping group based on treatment methods.

The primary endpoint of this study was the early functional outcomes of patients 1 month after surgery. Considering that the modified Rankin Scale (mRS) is recommended for assessing neurological recovery status, this study utilized the mRS score at 1 month post-surgery as the primary endpoint, with scores ranging from 0 to 3 indicating a favorable prognosis and scores from 4 to 6 indicating an unfavorable prognosis (10).

Chi-square tests were used for categorical variables, while non-parametric tests were employed for continuous variables. Univariate and multivariate logistic regression analyses were conducted to determine independent predictive factors and calculate their relative weights on the outcome variable. Two separate nomogram models were developed to predict early functional outcomes in aSAH patients undergoing endovascular coiling and Surgical clipping, respectively. Receiver operating characteristic curves (ROC) were plotted, and the area under the curve (AUC) was calculated to assess the discriminative ability of the nomogram. Calibration curves were generated to illustrate the consistency between predicted probabilities and observed outcomes across various predicted probabilities. Decision curve analysis (DCA) was conducted to evaluate the clinical utility of the nomogram. Finally, risk stratification was performed. All statistical analyses were conducted using SPSS version 26.0 and R version 4.3.1, with statistical significance defined at the conventional threshold of p < 0.05 (two-tailed).

A total of 962 patients diagnosed with aSAH were included in the final analysis cohort (Figure 1). Overall, the proportion of early adverse outcomes in the surgical clipping group (32.7%) was higher than that in the endovascular coiling group (15.0%) (Figure 2). In patients undergoing endovascular coiling, those with poor functional outcomes tended to be older, have higher D-dimer levels, higher Hunt–Hess grades, GCS scores of 3–8, higher mFS grades, larger aneurysm volumes, were more likely to be located in the anterior cerebral artery and posterior circulation. Among patients undergoing surgical clipping, those with poor functional outcomes tended to be older, have higher Hunt–Hess grades, GCS scores of 3–8, higher mFS grades, higher D-dimer levels, and lower platelet counts (Tables 1, 2).

We utilized univariate and multivariate logistic regression models to assess the impact of clinical variables and scores on outcomes. The results revealed that, in the endovascular coiling group, age [adjusted odds ratio (OR): 1.033, 95% confidence interval (CI): 1.007–1.06, p = 0.015], Hunt–Hess grade (adjusted OR: 2.727, 95% CI: 1.172–6.154, p = 0.017), GCS score (9–12: adjusted OR: 0.308, 95% CI: 0.11–0.835, p = 0.022; 12–15: adjusted OR: 0.098, 95% CI: 0.039–0.24, p < 0.001), mFS (adjusted OR: 2.769, 95% CI: 1.382–5.959, p = 0.006), D-dimer (adjusted OR: 1.248, 95% CI: 1.106–1.412, p < 0.001), and body temperature (adjusted OR: 0.469, 95% CI: 0.274–0.784, p = 0.005) were significantly associated with early adverse functional outcomes (Table 3). Whereas, in the surgical clipping group, Hunt–Hess grade (adjusted OR: 2.369, 95% CI: 1.051–5.408, p = 0.038), GCS score (12–15: adjusted OR: 0.274, 95% CI: 0.121–0.606, p = 0.002), mFS (adjusted OR: 2.918, 95% CI:1.245–6.994, p = 0.014), and D-dimer (adjusted OR: 1.508, 95% CI: 1.304–1.766, p < 0.001) were independent predictors of early functional outcomes (Table 4). The forest plot displays the significant multivariable factors (Figures 3A,B).

We further assessed the relative impact of significant variables on early functional outcomes using multivariate logistic regression analysis. In the endovascular coiling group, the proportions of significant variables were as follows: Hunt–Hess grade contributed 32.78%, mFS contributed 31.99%, D-dimer contributed 13.73%, age contributed 11.61%, body temperature contributed 5.26%, and GCS contributed 4.63%. In the surgical clipping group, mFS contributed 38.02%, Hunt–Hess grade contributed 33.55%, D-dimer contributed 19.99%, and GCS contributed 8.44% (Figures 4A,B).

Nomogram models were developed for different groups based on early functional outcomes (Figures 5A, 6A). In the endovascular coiling group, the ROC curve indicated good predictive accuracy, with an AUC value of 0.847 (95% CI: 0.800–0.894) (Figure 5B), and the calibration curve demonstrated close alignment between the model and predictions (Figure 5C). The decision curve analysis (DCA) curve showed good clinical predictive value across different threshold probabilities (Figure 5D). Similarly, in the surgical clipping group, the ROC curve showed good predictive accuracy, with an AUC value of 0.841 (95% CI: 0.796–0.886) (Figure 6B), and the calibration curve exhibited basic alignment with predictions (Figure 6C). The DCA curve also demonstrated good clinical predictive value across different threshold probabilities (Figure 6D). In addition, by incorporating the surgical approach as an additional variable into the shared predictive factors, we developed a new, integrated nomogram model (Figure 7A). This model achieved an AUC of 0.857 for predicting poor outcomes within 1 month (Figure 7B). The calibration curve demonstrated good agreement between predicted and observed outcomes, and the DCA showed favorable clinical utility across a range of threshold probabilities (Figures 7C,D).

Based on the risk scores predicted by the nomogram, patients were categorized into three groups: low risk, medium risk, and high risk. In the endovascular coiling group, individuals in the medium-risk group faced a 2.791-fold higher risk compared to those in the low-risk category, while those in the high-risk group experienced a significantly elevated risk of 17.506 times compared to the low-risk group (Table 5). Similarly, within the surgical clipping group, participants classified in the medium-risk tier were at a 5.291-fold increased risk relative to the low-risk counterparts, with those in the high-risk category encountering an even greater risk, elevated by a substantial 26.641 times compared to the low-risk group (Table 5). These differences were statistically significant, highlighting the clinical significance of our nomogram model in integrating clinical scores and parameters.