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Stroke is a major healthcare problem worldwide, particularly in the elderly population. Despite limited research on the development of prediction models for mortality in elderly individuals with ischemic stroke, our study aimed to address this knowledge gap. By leveraging data from the Medical Information Mart for Intensive Care IV database, we collected comprehensive raw data pertaining to elderly patients diagnosed with ischemic stroke. Through meticulous screening of clinical variables associated with 28-day mortality, we successfully established a robust nomogram. To assess the performance and clinical utility of our nomogram, various statistical analyses were conducted, including the concordance index, integrated discrimination improvement (IDI), net reclassification index (NRI), calibration curves and decision curve analysis (DCA). Our study comprised a total of 1259 individuals, who were further divided into training (n = 894) and validation (n = 365) cohorts. By identifying several common clinical features, we developed a nomogram that exhibited a concordance index of 0.809 in the training dataset. Notably, our findings demonstrated positive improvements in predictive performance through the IDI and NRI analyses in both cohorts. Furthermore, calibration curves indicated favorable agreement between the predicted and actual incidence of mortality (P > 0.05). DCA curves highlighted the substantial net clinical benefit of our nomogram compared to existing scoring systems used in routine clinical practice. In conclusion, our study successfully constructed and validated a prognostic nomogram, which enables accurate short-term mortality prediction in elderly individuals with ischemic stroke. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A) is a form of posttranscriptional modification that plays important roles in cancer including oral squamous cell carcinoma (OSCC). Most studies to date have focused on a limited number of regulators and oncogenic pathways, thus failing to provide comprehensive insight into the dynamic effects of m6A modification. In addition, the role of m6A modification in shaping immune cell infiltration in OSCC has yet to be clarified. This study was designed to assess m6A modification dynamics in OSCC and to understand how such modifications influence clinical immunotherapeutic treatment outcomes. m6A modification patterns linked with 23 m6A regulators were analyzed in 437 OSCC patients from TCGA and GEO cohorts. These patterns were then quantified through m6A score based on algorithms derived from a principal component analysis (PCA) approach. The m6A modification patterns of OSCC samples were grouped into two clusters based on the m6A regulators expression, and immune cell infiltration was linked with the 5-year survival outcomes of patients in these clusters. 1575 genes associated with OSCC patient prognosis were identified and used to re-cluster these samples into two groups. Patients in clusters exhibiting higher levels of m6A regulator expression exhibited poorer overall survival (OS), whereas patients with high m6A scores survived for longer (p < 0.001). The overall mortality rates in the groups of patients with low and high m6A scores were 55% and 40%, respectively, and the m6A score distributions in clusters of patients grouped by m6A modification patterns and gene expression further supported the link between a high m6A score and better prognostic outcomes. Immunophenoscore (IPS) values for patients in different m6A score groups suggested that the use of PD-1-specific antibodies or CTLA-4 inhibitors alone or in combination would yield superior treatment outcomes in patients in the high-m6A score group relative to the low-m6A score group. m6A modification patterns are relevant to heterogeneity in OSCC. Detailed analyses of m6A modification patterns may thus offer novel insight regarding immune cell infiltration within the OSCC tumor microenvironment, guiding novel efforts to provide patients with more effective immunotherapeutic interventions. [ABSTRACT FROM AUTHOR]