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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 ( = 126, 75%) and validation set ( = 43, 25%). Multivariate logistic regression was used to construct a nomogram predictive model.
Results: The SII value in the experimental group (median: 2851.1×10/L) was significantly higher than that in the control group (median: 1898.6 × 10/L) ( = 0.019). Receiver operating characteristic (ROC) analyses showed that the best cutoff value of the SII was 2505.7 × 10/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, = 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.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9551394 | PMC |
http://dx.doi.org/10.3389/fneur.2022.945437 | DOI Listing |
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