Association between triglyceride-glucose index and all-cause mortality in critically ill patients with acute myocardial infarction: analysis of the MIMIC-IV database
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Background Currently, the clinical evidence regarding the prognostic significance of the TyG index in acute myocardial infarction (AMI) patients remains unclear. Our research analyzed the correlation between the TyG index and the risk of mortality in patients with AMI, in order to evaluate the influence of the TyG index on the prognosis of this population. Methods 1205 ICU patients with AMI were analyzed in this retrospective cohort analysis, and the necessary data were obtained from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The study conducted Kaplan-Meier analysis to compare all-cause mortality rates across four groups of patients. The study included logistic regression and Cox regression analysis to examine the correlation among the TyG index and the risk of in-hospital, 28-day, and 90-day mortality. Results In our study, 176 (14.61%) patients experienced in-hospital deaths, 198 (16.43%) patients died within 28 days of follow-up, and 189 (23.98%) patients died within 90 days of follow-up. Logistic regression and Cox proportional hazard analyses revealed that the TyG index was an independent predictor of in-hospital, 28-day, and 90-day mortality (OR: 1.406, 95% CI 1.141-1.731, p = 0.001; HR: 1.364, 95% CI 1.118-1.665, p = 0.002; HR: 1.221, 95% CI 1.024-1.445, p = 0.026, respectively). The restricted cubic spline regression model showed that the risk of in-hospital, 28-day, and 90-day mortality increased linearly with increasing TyG index. Conclusions The TyG index was significantly associated with an increased risk of mortality in AMI patients. Our findings suggested that the TyG index may be instrumental in identifying patients at high risk for adverse outcomes following AMI.Keywords:
National Death Index
Variations in the ratio of "definite" to "possible" myocardial infarction for non-fatal cases were examined in studies that used World Health Organization criteria. There were large variations in this ratio, variations which appeared to be due to differences in the ascertainment of non-fatal cases of "possible" myocardial infarction, which, in turn, contributed to reported differences in the incidence of myocardial infarction. A significant proportion of cases of "possible" myocardial infarction probably do not have ischemic heart disease at all, since, in our data, cases of "possible" myocardial infarction (non-fatal) with a hospital discharge diagnosis of chest pain (undiagnosed) had a risk of death that was no worse than that in the general population. Thus the most reproducible, and possibly most accurate estimates of the incidence of myocardial infarction may come from including only fatal cases of "possible" myocardial infarction with both fatal and non-fatal cases of "definite" myocardial infarction.
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Objective To analyze the clinical characteristics of atypical acute myocardial infarction,improve the diagnosis of myocardial infarction. Methods To analyze the main clinical characteristics of the patients with atypical acute myocardial infarction in our hospital in the past 3 years ,which compared to the typical acute myocardial infarction. Results Atypical acute myocardial infarction includes atypical symptom and atypical ECG, atypical symptoms is more prevail. Compared with typical acute myocardial infarction, the women, elderly people and hypertension patients is more common, fewer anterior myocardial infarction and poorer prognosis ( P ＜ 0.05 ). Conclusion To improve the understanding of atypical acute myocardial infarction,was benefit of reducing the misdiagnosis and mistreatment of acute myocardial infarction.
Key words:
Myocardial infarction
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In this paper, we compare logistic regression and 2 other classification methods in predicting hypertension given the genotype information. We use logistic regression analysis in the first step to detect significant single-nucleotide polymorphisms (SNPs). In the second step, we use the significant SNPs with logistic regression, support vector machines (SVMs), and a newly developed permanental classification method for prediction purposes. We also detect rare variants and investigate their impact on prediction. Our results show that SVMs and permanental classification both outperform logistic regression, and they are comparable in predicting hypertension status.
Logistic model tree
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Background: Knowledge is limited concerning the type of symptoms and the time from onset of symptoms to first medical contact at first and second myocardial infarction in the same patient. Aim: This study aimed to describe the type of symptoms and the time from onset of symptoms to first medical contact in first and second myocardial infarctions in men and women affected by two myocardial infarctions. Furthermore, the aim was to identify factors associated with prehospital delays ≥2 h at second myocardial infarction. Methods: A retrospective cohort study with 820 patients aged 31–74 years with a first and a second myocardial infarction from 1986 through 2009 registered in the Northern Sweden MONICA registry. Results: The most common symptoms reported among patients affected by two myocardial infarctions are typical symptoms at both myocardial infarction events. Significantly more women reported atypical symptoms at the second myocardial infarction compared to the first. Ten per cent of the men did not report the same type of symptoms at the first and second myocardial infarctions; the corresponding figure for women was 16.2%. The time from onset of symptoms to first medical contact was shorter at the second myocardial infarction compared to the first myocardial infarction. Patients with prehospital delay ≥2 h at the first myocardial infarction were more likely to have a prehospital delay ≥2 h at the second myocardial infarction. Conclusions: Symptoms of second myocardial infarctions are not necessarily the same as those of first myocardial infarctions. A patient’s behaviour at the first myocardial infarction could predict how he or she would behave at a second myocardial infarction.
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Background Although most people with relapsing onset multiple sclerosis (R-MS) eventually transition to secondary progressive multiple sclerosis (SPMS), little is known about disability progression in SPMS. Methods All R-MS patients in the Cardiff MS registry were included. Cox proportional hazards regression was used to examine a) hazard of converting to SPMS and b) hazard of attaining EDSS 6.0 and 8.0 in SPMS. Results 1611 R-MS patients were included. Older age at MS onset (hazard ratio [HR] 1.02, 95%CI 1.01–1.03), male sex (HR 1.71, 95%CI 1.41–2.08), and residual disability after onset (HR 1.38, 95%CI 1.11–1.71) were asso- ciated with increased hazard of SPMS. Male sex (EDSS 6.0 HR 1.41 [1.04–1.90], EDSS 8.0 HR 1.75 [1.14–2.69]) and higher EDSS at SPMS onset (EDSS 6.0 HR 1.31 [1.17–1.46]; EDSS 8.0 HR 1.38 [1.19–1.61]) were associated with increased hazard of reaching disability milestones, while older age at SPMS was associated with a lower hazard of progression (EDSS 6.0 HR 0.94 [0.92–0.96]; EDSS 8.0: HR 0.92 [0.90–0.95]). Conclusions Different factors are associated with hazard of SPMS compared to hazard of disability progres- sion after SPMS onset. These data may be used to plan services, and provide a baseline for comparison for future interventional studies and has relevance for new treatments for SPMS RobertsonNP@cardiff.ac.uk
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Objective To investigate the clinical feature of painless myocardial infarction. Methods To retrospectively study the clinical data of 33 patients who suffered from painless myocardial infarction, and compare with that of typical acute myocardial infarction patients. Results There wash' t significant difference in gender(χ2 =1.63, P >0.05) and past history (χ2 = 4.88, P > 0.05) ,the time from visit to diagnosis (t = 1.44, P > 0.05) between painless myocardial infarction patients and typical acute myocardial infarction patients. But there was significant differ-ence in the age (χ2= 5.72, P < 0.05), the visit time (t = 30.98, P < 0.05), and the prognosis (χ2 = 32.17, P <0.0 ). Conclusion Patients with painless myocardial infarction have diverse clinical manifestations. They are usu-ally aged and delayed in seeking treatment and at last have a bad prognosis.
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Myocardial Infarction; Clinical feature
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The hazard ratio and median survival time are the routine indicators in survival analysis. We briefly introduced the relationship between hazard ratio and median survival time and the role of proportional hazard assumption. We compared 110 pairs of hazard ratio and median survival time ratio in 58 articles and demonstrated the reasons for the difference by examples. The results showed that the hazard ratio estimated by the Cox regression model is unreasonable and not equivalent to median survival time ratio when the proportional hazard assumption is not met. Therefore, before performing the Cox regression model, the proportional hazard assumption should be tested first. If proportional hazard assumption is met, Cox regression model can be used; if proportional hazard assumption is not met, restricted mean survival times is suggested.风险比（hazard ratio，HR）和中位生存时间是生存分析时的常规分析和报告指标。本文简要介绍了HR和中位生存时间的关系以及比例风险假定在这两者之间的作用，分析了检索出的58篇文献中的110对风险比和中位生存时间比的差异，并通过实例阐明了产生这种差异的原因。结果表明，在不满足比例风险假定时，Cox回归模型计算得到的风险比是不合理的，且与中位生存时间之比不等价。因此，在使用Cox回归模型前，应先进行比例风险假定的检验，只有符合比例风险假定时才能使用该模型；当不符合比例风险假定时，建议使用限制性平均生存时间。.
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Objective: The objective of this study was to examine the relationship between systemic inflammation and long-term mortality in patients with hypertension. Methods: The study employed a retrospective cohort design. The study population was derived from the National Health and Nutrition Examination Survey (NHANES), and the mortality data for this population was acquired from the National Death Index (NDI) database. Systemic inflammation was quantified by the Systemic Immune Inflammation Index (SII) and the Systemic Inflammatory Response Index (SIRI), which were then categorized into four groups (Q1–Q4, with Q4 representing the highest level of SII or SIRI). Weighted Cox regression models were constructed to investigate the association between mortality and SII and SIRI, with hazard ratios (HRs) subsequently calculated. Results: A total of 7431 participants were included in the analysis. The highest quantile (Q4) of SII was associated with a higher risk of all-cause mortality (hazard ratio 1.36, 95% CI 1.1–1.69, P < 0.001). After adjustment for important covariates, the association remained significant (hazard ratio 1.70, 95% CI 1.27–2.30, P < 0.001). The highest quantile (Q4) of SIRI was also associated with the highest risk of mortality (hazard ratio 2.11, 95% CI 1.64–2.70, P < 0.001), and this association remained significant after adjustment for important covariates (hazard ratio 1.64, 95% CI 0.61–1.22, P = 0.001). Conclusion: Both SII and SIRI scores were found to be associated with mortality rates in patients with hypertension. The findings suggest that these scores may serve as complementary biomarkers to the neutrophil-to-lymphocyte ratio (NLR) for assessing mortality risk in patients with hypertension. Further investigation is warranted to elucidate the underlying mechanisms that underpin this association.
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In 1,395 patients admitted to hospital between 1976 and 1981 due to suspected acute myocardial infarction, the 5-year mortality rate was related to whether they developed infarction or not during the first 3 days. In all, patients with definite myocardial infarction had a 5-year mortality rate of 33.4% as compared with 13.3% in patients not fulfilling the criteria for this diagnosis (p less than 0.001). When separately analyzing patients with no previous myocardial infarction before admission and discharged from hospital, the corresponding mortality rate was 24.1% for myocardial infarction patients versus 8.1% in nonmyocardial infarction patients (p less than 0.001). Among all patients with nonconfirmed myocardial infarction, those who partly fulfilled the criteria (possible myocardial infarction) had a 5-year mortality rate of 16.7% as compared with 12.0% in those in whom myocardial infarction was completely ruled out (p = 0.18). Independent risk factors for death among patients not developing early infarction were high age and a clinical history of previous myocardial infarction and smoking. We conclude that in this study the long-term prognosis among patients admitted to hospital due to suspected acute myocardial infarction was clearly related to whether they developed an infarction or not during the first 3 days in hospital.
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