PDF(Pubmed)
Abstract：
UNASSIGNED: Type 2 diabetes mellitus (DM) is a recognized independent risk factor for both chronic coronary syndrome (CCS) and its complication, acute coronary syndrome (ACS). Patients with DM and prediabetes (preDM) face an increased ACS risk. Inflammation plays a significant role in the pathogenesis of both CCS and ACS. This study delves into novel inflammatory markers, such as the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI, also known as SIIRI or PIV), to explore their relationship with ACS and CCS in patients that have been or have not been diagnosed with DM or preDM.
UNASSIGNED: This study included data of 493 patients with chest pain undergoing coronary angiography. They were categorized into four groups: 1) without DM/preDM and with CCS; 2) with both DM/preDM and CCS; 3) without DM/preDM and with ACS, 4) with both DM/preDM and ACS. Standard methods of statistical analysis were used to reveal possible differences between groups and to find the most influential ACS risk factors in groups with DM/preDM and without DM/preDM.
UNASSIGNED: The analysis showed no significant differences in SII, SIRI, or AISI between the respective patient groups. A logistic regression analysis generated a model incorporating SII, high-density lipoprotein, and low-density lipoprotein levels as the influential ACS risk factors for patients with DM/preDM. The model demonstrated 71.0% accuracy, 37.0% sensitivity, and 89.4% specificity.
UNASSIGNED: The findings suggest that the aforementioned inflammatory markers may have potential for distinguishing DM/preDM patients at higher risk of ACS at a low financial cost. However, further comprehensive and well-designed research is required to validate their clinical utility.
People with type 2 diabetes (DM) and prediabetes (preDM) have a higher risk of heart problems. These include chronic coronary syndrome (CCS) and acute coronary syndrome (ACS). Inflammation is a key element in these issues. We looked at 493 patients with chest pain. We divided them into groups based on diabetes status (DM/preDM vs no diabetes) and heart conditions (ACS and CCS). We explored new markers related to inflammation. These include the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) that all can be calculated from simple blood tests. We found no differences in these markers between groups. To understand ACS risk factors better, we used statistical analysis. The model found key factors for patients with DM/preDM: SII, LDL, and low-density lipoprotein levels. It was accurate (71.0%), but sensitivity was 37.0%, and specificity was 89.4%. These markers could be helpful in identifying DM/preDM patients at risk of ACS with low cost tests. We need more research to confirm their use in real-life medical settings.
UNASSIGNED: This study included data of 493 patients with chest pain undergoing coronary angiography. They were categorized into four groups: 1) without DM/preDM and with CCS; 2) with both DM/preDM and CCS; 3) without DM/preDM and with ACS, 4) with both DM/preDM and ACS. Standard methods of statistical analysis were used to reveal possible differences between groups and to find the most influential ACS risk factors in groups with DM/preDM and without DM/preDM.
UNASSIGNED: The analysis showed no significant differences in SII, SIRI, or AISI between the respective patient groups. A logistic regression analysis generated a model incorporating SII, high-density lipoprotein, and low-density lipoprotein levels as the influential ACS risk factors for patients with DM/preDM. The model demonstrated 71.0% accuracy, 37.0% sensitivity, and 89.4% specificity.
UNASSIGNED: The findings suggest that the aforementioned inflammatory markers may have potential for distinguishing DM/preDM patients at higher risk of ACS at a low financial cost. However, further comprehensive and well-designed research is required to validate their clinical utility.
People with type 2 diabetes (DM) and prediabetes (preDM) have a higher risk of heart problems. These include chronic coronary syndrome (CCS) and acute coronary syndrome (ACS). Inflammation is a key element in these issues. We looked at 493 patients with chest pain. We divided them into groups based on diabetes status (DM/preDM vs no diabetes) and heart conditions (ACS and CCS). We explored new markers related to inflammation. These include the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) that all can be calculated from simple blood tests. We found no differences in these markers between groups. To understand ACS risk factors better, we used statistical analysis. The model found key factors for patients with DM/preDM: SII, LDL, and low-density lipoprotein levels. It was accurate (71.0%), but sensitivity was 37.0%, and specificity was 89.4%. These markers could be helpful in identifying DM/preDM patients at risk of ACS with low cost tests. We need more research to confirm their use in real-life medical settings.
摘要：
■2型糖尿病（DM）是公认的慢性冠状动脉综合征（CCS）及其并发症的独立危险因素，急性冠脉综合征（ACS）。DM和糖尿病前期（preDM）患者面临ACS风险增加。炎症在CCS和ACS的发病机制中起重要作用。这项研究深入研究了新的炎症标志物，如全身免疫炎症指数(SII)，全身炎症反应指数（SIRI），和全身炎症的综合指数(AISI，也称为SIIRI或PIV)，在已诊断或未诊断为DM或DM前期的患者中，探讨其与ACS和CCS的关系。
■本研究包括493例胸痛患者行冠状动脉造影的数据。他们分为四组：1）无DM/preDM和CCS；2）同时具有DM/preDM和CCS；3）无DM/preDM和ACS，4)同时具有DM/preDM和ACS。使用标准的统计分析方法来揭示组间可能的差异，并在有DM/preDM和没有DM/preDM的组中找到最有影响力的ACS危险因素。
■分析表明SII没有显着差异，SIRI,或相应患者组之间的AISI。逻辑回归分析生成了一个包含SII的模型，高密度脂蛋白，和低密度脂蛋白水平是影响DM/preDM患者ACS的危险因素。该模型的准确率为71.0%，灵敏度为37.0%,和89.4%的特异性。
■研究结果表明，上述炎症标志物可能具有在低经济成本下区分ACS风险较高的DM/前DM患者的潜力。然而,需要进一步全面和精心设计的研究来验证其临床实用性。
患有2型糖尿病（DM）和糖尿病前期（preDM）的人患心脏病的风险更高。这些包括慢性冠脉综合征(CCS)和急性冠脉综合征(ACS)。炎症是这些问题的关键因素。我们观察了493例胸痛患者。我们根据糖尿病状态（DM/preDMvs无糖尿病）和心脏病（ACS和CCS）将他们分为几组。我们探索了与炎症相关的新标志物。这些包括全身免疫炎症指数（SII），全身炎症反应指数（SIRI），和全身炎症的综合指数（AISI），所有这些都可以通过简单的血液检查来计算。我们发现这些标记在组间没有差异。为了更好地了解ACS的危险因素，我们使用统计分析。该模型发现了DM/前DM患者的关键因素：SII，LDL,和低密度脂蛋白水平。准确（71.0%），但是灵敏度是37.0%，特异性为89.4%。这些标记可能有助于通过低成本测试识别处于ACS风险的DM/preDM患者。我们需要更多的研究来确认它们在现实生活中的应用。
■本研究包括493例胸痛患者行冠状动脉造影的数据。他们分为四组：1）无DM/preDM和CCS；2）同时具有DM/preDM和CCS；3）无DM/preDM和ACS，4)同时具有DM/preDM和ACS。使用标准的统计分析方法来揭示组间可能的差异，并在有DM/preDM和没有DM/preDM的组中找到最有影响力的ACS危险因素。
■分析表明SII没有显着差异，SIRI,或相应患者组之间的AISI。逻辑回归分析生成了一个包含SII的模型，高密度脂蛋白，和低密度脂蛋白水平是影响DM/preDM患者ACS的危险因素。该模型的准确率为71.0%，灵敏度为37.0%,和89.4%的特异性。
■研究结果表明，上述炎症标志物可能具有在低经济成本下区分ACS风险较高的DM/前DM患者的潜力。然而,需要进一步全面和精心设计的研究来验证其临床实用性。
患有2型糖尿病（DM）和糖尿病前期（preDM）的人患心脏病的风险更高。这些包括慢性冠脉综合征(CCS)和急性冠脉综合征(ACS)。炎症是这些问题的关键因素。我们观察了493例胸痛患者。我们根据糖尿病状态（DM/preDMvs无糖尿病）和心脏病（ACS和CCS）将他们分为几组。我们探索了与炎症相关的新标志物。这些包括全身免疫炎症指数（SII），全身炎症反应指数（SIRI），和全身炎症的综合指数（AISI），所有这些都可以通过简单的血液检查来计算。我们发现这些标记在组间没有差异。为了更好地了解ACS的危险因素，我们使用统计分析。该模型发现了DM/前DM患者的关键因素：SII，LDL,和低密度脂蛋白水平。准确（71.0%），但是灵敏度是37.0%，特异性为89.4%。这些标记可能有助于通过低成本测试识别处于ACS风险的DM/preDM患者。我们需要更多的研究来确认它们在现实生活中的应用。
