Construction of a Nomogram Prediction Model for Prognosis in Patients with Large Artery Occlusion-Acute Ischemic Stroke.

BACKGROUND: Patients with large artery occlusion-acute ischemic stroke (LAO-AIS) can experience adverse outcomes, such as brain herniation due to complications. This study aimed to construct a nomogram prediction model for prognosis in patients with LAO-AIS in order to maximize the benefits for clinical patients. METHODS: Retrospective analysis of 243 patients with LAO-AIS from January 2019 to January 2022 with medical history data and blood examination at admission. Univariate and multivariate analyses were conducted through binary logistic regression equation analysis, and a nomogram prediction model was constructed. RESULTS: Results of this study showed that hyperlipidemia (odds ratio [OR] = 2.849, 95% confidence interval [CI] = 1.100-7.375, P = 0.031), right cerebral infarction (OR = 2.144, 95% CI = 1.106-4.156, P = 0.024), D-Dimer>500 ng/mL (OR = 2.891, 95% CI = 1.398-5.980, P = 0.004), and neutrophil-lymphocyte ratio >7.8 (OR = 2.149, 95% CI = 1.093-4.225, P = 0.027) were independent risk factors for poor early prognosis in patients with LAO-AIS. In addition, hypertension (OR = 1.947, 95% CI = 1.114-3.405, P = 0.019), hyperlipidemia (OR = 2.594, 95% CI = 1.281-5.252, P = 0.008), smoking (OR = 2.414, 95% CI = 1.368-4.261, P = 0.002), D-dimer>500 ng/mL (OR = 3.170, 95% CI = 1.533-6.553, P = 0.002), and neutrophil-lymphocyte ratio >7.8 (OR = 2.144, 95% CI = 1.231-3.735, P = 0.007) were independent risk factors for poor long-term prognosis. The early prognosis nomogram receiver operating characteristic curve area under the curve value was 0.688 for the training set and 0.805 for the validation set, which was highly differentiated. The mean error was 0.025 for the training set calibration curve and 0.016 for the validation set calibration curve. Both the training and validation set decision curve analyses indicated that the clinical benefit of the nomogram was significant. The long-term prognosis nomogram receiver operating characteristic curve area under the curve values was 0.697 for the training set and 0.735 for the validation set, showing high differentiation. The mean error was 0.041 for the training set calibration curve and 0.021 for the validation set calibration curve. Both of the training and validation set decision curve analyses demonstrated a substantial clinical benefit of the nomogram. CONCLUSIONS: The nomogram prediction model based on admission history data and blood examination are easy-to-use tools that provide an accurate individualized prediction for patients with LAO-AIS and can assist in early clinical decisions and in obtaining an early prognosis.

Systemic immune inflammatory index is an independent predictor for the requirement of decompressive craniectomy in large artery occlusion acute ischemic stroke patients after mechanical thrombectomy.

Background and purpose: Following mechanical thrombectomy (MT), patients with large artery occlusive acute ischemic stroke (LAO-AIS) often have cerebral herniation due to its complications, resulting in poor prognosis. Decompressive craniectomy (DC) can markedly improve patient prognosis. This study aimed to verify the predictive value of clinical parameters such as the systemic immune-inflammatory index (SII) for DC in patients with LAO-AIS after MT. Methods: Clinical data of a total of 173 patients with LAO-AIS treated with MT between January 2020 and January 2022 were retrospectively analyzed. Patients receiving DC were grouped into an experimental group or a control group (no DC). The patients were randomly divided into the training set (n = 126, 75%) and validation set (n = 43, 25%). Multivariate logistic regression was used to construct a nomogram predictive model. Results: The SII value in the experimental group (median: 2851.1×109/L) was significantly higher than that in the control group (median: 1898.6 × 109/L) (P = 0.019). Receiver operating characteristic (ROC) analyses showed that the best cutoff value of the SII was 2505.7 × 109/L with a sensitivity of 55%, a specificity of 75.8%, and an area under the curve (AUC) of 0.649. Multivariate logistic regression indicated that the SII was an independent predictor for performing DC in patients with LAO-AIS after MT (OR = 3.579, 95% CI = 1.360-9.422, P = 0.01). The AUC was 0.728 in the training set and 0.583 in the validation set. The average error of the calibration curve was 0.032 in the training set and 0.023 in the validation set. The average error was relatively small and consistent in the training set and validation set. The C-index of the nomogram was 0.804 suggesting good accuracy. Conclusions: The SII at admission is an independent predictor for the requirement of DC in patients with LAO-AIS after MT. The SII-based nomogram helps doctors make decisions on whether DC is needed timely and rationally, and thereby may improve the prognosis of these patients.