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BACKGROUND: Recent research indicates that systemic inflammation significantly affects the overall prognosis of individuals with aneurysmal subarachnoid hemorrhage. To delve deeper into this issue, a retrospective study was undertaken. The study aimed to investigate the relationship between fibrinogen and neutrophil/lymphocyte ratio scores, D-dimer/Albumin ratios, and the Glasgow Outcome Scale at 6 months post-discharge for patients with aSAH. METHODS: A retrospective analysis was conducted on 321 patients who experienced aneurysmal subarachnoid hemorrhage. These patients were monitored using the Glasgow Outcome Scale six months after being discharged from Huizhou Central People's Hospital. Patients with GOS scores between 1 and 3 were classified as having a poor prognosis, while those with scores ranging from 4 to 5 were considered to have a good prognosis. To create distinct sets, patients were randomly divided into both training and validation groups. The best cut-off value for the D-dimer/Albumin ratio was established through ROC curves, and the scores for fibrinogen and the neutrophil/lymphocyte ratio were calculated. Utilizing multivariate logistic regression analysis, independent risk factors linked to an unfavorable prognosis in aSAH patients were identified. A nomogram model was developed and validated based on these findings, providing an improved approach for evaluating the prognostic influence of risk factors. To gauge the model's predictive performance, several analytical tools such as ROC curves, calibration curves, and decision curve analysis were employed. This comprehensive approach ensured a thorough assessment of the prognostic prediction capabilities of the model. RESULTS: Multivariate regression analysis revealed that Age (OR=3.87, 95%CI=1.54-9.73, p=0.004), Pneumonia (OR=3.54, 95%CI=1.41-8.86, p=0.007), WFNS (OR=3.24, 95%CI=1.23-8.54, p=0.017), DAR (OR=2.88, 95%CI=1.13-7.34, p=0.027), and F-NLR (OR=3.12, 95%CI=1.22-7.97, p=0.017) were identified as independent risk factors influencing the prognosis of patients with aSAH. Additionally, the area under the ROC curve was 0.866 (95%CI=0.805-0.927) for the training set and 0.924 (95%CI=0.849-0.999) for the validation set. The calibration curve analysis demonstrated a minor error of 0.02 for the training set and 0.051 for the validation set. Furthermore, both the training set and validation set displayed significant clinical benefits according to the DCA curves, underscoring the meaningful utility of the developed nomogram. CONCLUSIONS: Fibrinogen and neutrophil/lymphocyte ratio scores, and the D-dimer/Albumin ratio emerged as significant independent risk factors for prognosticating the outcomes of patients with aSAH. Leveraging these factors, a robust nomogram model was meticulously developed, showcasing its impressive precision in prognostic predictions. These results underscore the promising clinical applicability of these biomarkers as effective prognostic indicators for individuals afflicted by aSAH.
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Glioma is the most common primary brain tumor. Filamin-binding LIM protein 1 (FBLIM1) has been identified in multiple cancers and is suspected of playing a part in the development of tumors. However, the potential function of FBLIM1 mRNA in glioma has not been investigated. In this study, the clinical information and transcriptome data of glioma patients were, respectively, retrieved from the TCGA and CGGA databases. The expression level of FBLIM1 mRNA was shown to be aberrant in a wide variety of malignancies. Significantly, when glioma samples were compared to normal brain samples, FBLIM1 expression was shown to be significantly elevated in the former. A poor prognosis was related to high FBLIM1 expression, which was linked to more advanced clinical stages. Notably, multivariate analyses demonstrated that FBLIM1 expression was an independent predictor for the overall survival of glioma patients. Immune infiltration analysis disclosed that FBLIM1 expression had relevance with many immune cells. The results of RT-PCR suggested that FBLIM1 expression was markedly elevated in glioma specimens. Functional experiments unveiled that the knockdown of FBLIM1 mRNA suppressed glioma cell proliferation. In general, we initially discovered that FBLIM1 mRNA might be a possible prognostic marker in glioma.
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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 (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.