Siri

A. Kaplan, M. Haenlein

Abstract Artificial intelligence (AI)—defined as a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation—is a topic in nearly every boardroom and at many dinner tables. Yet, despite this prominence, AI is still a surprisingly fuzzy concept and a lot of questions surrounding it are still open. In this article, we analyze how AI is different from related concepts, such as the Internet of Things and big data, and suggest that AI is not one monolithic term but instead needs to be seen in a more nuanced way. This can either be achieved by looking at AI through the lens of evolutionary stages (artificial narrow intelligence, artificial general intelligence, and artificial super intelligence) or by focusing on different types of AI systems (analytical AI, human-inspired AI, and humanized AI). Based on this classification, we show the potential and risk of AI using a series of case studies regarding universities, corporations, and governments. Finally, we present a framework that helps organizations think about the internal and external implications of AI, which we label the Three C Model of Confidence, Change, and Control.

Yiyuan Xia, Chunlei Xia, Li-da Wu, Zheng Li, Hui Li, Jun-xia Zhang

Background and aim: Chronic low-grade inflammation is associated with various health outcomes, including cardiovascular diseases (CVDs) and cancers. Systemic immune inflammation index (SII) and system inflammation response index (SIRI) have lately been explored as novel prognostic markers for all-cause mortality and cardiovascular mortality. However, studies on prediction value in nationwide representative population are scarce, which limit their generalization. To bridge the knowledge gap, this study aims to prospectively assess the association of SII, SIRI with all-cause mortality and cardiovascular mortality in the National Health and Nutrition Examination Survey (NHANES). Methods: From 1999 to 2018, 42,875 adults who were free of pregnancy, CVDs (stroke, acute coronary syndrome), cancers, and had follow-up records and participated in the NHANES were included in this study. SII and SIRI were quantified by calculating the composite inflammation indicators from the blood routine. To explore the characteristics of the population in different SII or SIRI levels, we divided them according to the quartile of SII or SIRI. The associations between SII, SIRI, and all-cause mortality and cardiovascular mortality events were examined using a Cox regression model. To investigate whether there was a reliable relationship between these two indices and mortalities, we performed subgroup analysis based on sex and age. Results: A total of 42,875 eligible individuals were enrolled, with a mean age of 44 ± 18 years old. During the follow-up period of up to 20 years, 4250 deaths occurred, including 998 deaths from CVDs. Cox proportional hazards modeling showed that adults with SII levels of >655.56 had higher all-cause mortality (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.18–1.41) and cardiovascular mortality (HR, 1.33; 95% CI, 1.11–1.59) than those with SII levels of <335.36. Adults with SIRI levels of >1.43 had higher risk of all-cause (HR, 1.39; 95% CI, 1.26–1.52) and cardiovascular death (HR, 1.39; 95% CI, 1.14–1.68) than those with SIRI levels of <0.68. In general population older than 60 years, the elevation of SII or SIRI was associated with the risk of all-cause death. Conclusion: Two novel inflammatory composite indices, SII and SIRI, were closely associated with cardiovascular death and all-cause death, and more attention should be paid to systemic inflammation to provide better preventive strategies.

Rui-Hong Wang, Wan-Xin Wen, Zerui Jiang, Zhenping Du, Zhao-hui Ma, Aili Lu, Huiping Li, Fang Yuan, Shibiao Wu, Jian-wen Guo, Ye-Feng Cai, Yan-Jun Huang, Li-xin Wang, Hongji Lu

Background Inflammatory mechanisms play important roles in intracerebral hemorrhage (ICH) and have been linked to the development of stroke-associated pneumonia (SAP). The neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) are inflammatory indexes that influence systemic inflammatory responses after stroke. In this study, we aimed to compare the predictive value of the NLR, SII, SIRI and PLR for SAP in patients with ICH to determine their application potential in the early identification of the severity of pneumonia. Methods Patients with ICH in four hospitals were prospectively enrolled. SAP was defined according to the modified Centers for Disease Control and Prevention criteria. Data on the NLR, SII, SIRI and PLR were collected at admission, and the correlation between these factors and the clinical pulmonary infection score (CPIS) was assessed through Spearman’s analysis. Results A total of 320 patients were enrolled in this study, among whom 126 (39.4%) developed SAP. The results of the receiver operating characteristic (ROC) analysis revealed that the NLR had the best predictive value for SAP (AUC: 0.748, 95% CI: 0.695-0.801), and this outcome remained significant after adjusting for other confounders in multivariable analysis (RR=1.090, 95% CI: 1.029-1.155). Among the four indexes, Spearman’s analysis showed that the NLR was the most highly correlated with the CPIS (r=0.537, 95% CI: 0.395-0.654). The NLR could effectively predict ICU admission (AUC: 0.732, 95% CI: 0.671-0.786), and this finding remained significant in the multivariable analysis (RR=1.049, 95% CI: 1.009-1.089, P=0.036). Nomograms were created to predict the probability of SAP occurrence and ICU admission. Furthermore, the NLR could predict a good outcome at discharge (AUC: 0.761, 95% CI: 0.707-0.8147). Conclusions Among the four indexes, the NLR was the best predictor for SAP occurrence and a poor outcome at discharge in ICH patients. It can therefore be used for the early identification of severe SAP and to predict ICU admission.

Linguo Gu, Zhenkun Xia, Bei Qing, Wei Wang, Hongzuo Chen, Juan Wang, Ying Chen, Zhengling Gai, Rui Hu, Yunchang Yuan

Objective To examine the correlation between SIRI and the probability of cardiovascular mortality as well as all-cause mortality in individuals with chronic kidney disease. Methods A cohort of 3,262 participants from the US National Health and Nutrition Examination Survey (NHANES) database were included in the study. We categorized participants into five groups based on the stage of chronic kidney disease. A weighted Cox regression model was applied to assess the relationship between SIRI and mortality. Subgroup analyses, Kaplan–Meier survival curves, and ROC curves were conducted. Additionally, restricted cubic spline analysis was employed to elucidate the detailed association between SIRI and hazard ratio (HR). Results This study included a cohort of 3,262 individuals, of whom 1,535 were male (weighted proportion: 42%), and 2,216 were aged 60 or above (weighted proportion: 59%). Following adjustments for covariates like age, sex, race, and education, elevated SIRI remained a significant independent risk factor for cardiovascular mortality (HR=2.50, 95%CI: 1.62-3.84, p<0.001) and all-cause mortality (HR=3.02, 95%CI: 2.03-4.51, p<0.001) in CKD patients. The restricted cubic spline analysis indicated a nonlinear relationship between SIRI and cardiovascular mortality, with SIRI>1.2 identified as an independent risk factor for cardiovascular mortality in CKD patients. Conclusion Heightened SIRI independently poses a risk for both all-cause and cardiovascular mortality in chronic kidney disease patients, with potentially heightened significance in the early stages (Stage I to Stage III) of chronic kidney disease.

O. Menyhárt, J. Fekete, B. Győrffy

The overall prognosis for colorectal cancer (CRC) remains challenging as the survival time varies widely, even in patients with the same stage of disease. Recent studies suggest prognostic relevance of the novel markers of systemic inflammation, the systemic immune–inflammation index (SII), and the systemic inflammation response index (SIRI). We conducted a comprehensive meta-analysis to assess the prognostic significance of the SII and the SIRI in CRC. We searched the relevant literature for observational studies, and random effects models were employed to conduct a statistical analysis using the metaanalysisonline.com platform. Pooled effect sizes were reported with hazard ratios (HRs) and corresponding 95% confidence intervals (CI). Data from 29 studies published between 2016 and 2024, comprising 10,091 participants, were included in our meta-analysis on SII. CRC patients with high SII levels had worse disease outcomes, which were associated with poor OS (HR: 1.75; 95% CI: 1.4–2.19) and poor PFS/DFS/RFS (HR: 1.25; 95% CI: 1.18–1.33). This increased risk of worse OS was present irrespective of the treatment strategy, sample size (<220 and ≥220), and cutoff used to define high and low SII (<550 and ≥550) groups. Based on data from five studies comprising 2362 participants, we found a strong association between the high SIRI and worse OS (HR: 2.65; 95% CI: 1.6–4.38) and DFS/RFS (HR: 2.04; 95% CI: 1.42–2.93). According to our results, both the SII and SIRI hold great promise as prognostic markers in CRC. Further validations are needed for their age- and stage-specific utility in the clinical routine.