Background Malnutrition is common in patients with acute myocardial infarction (AMI) and is associated with a poor prognosis. The prognostic value of the prognostic nutritional index (PNI) in patients with AMI remains controversial. We aimed to explore the relationship between PNI and all-cause mortality in critically ill patients with AMI and evaluate the incremental prognostic value of PNI to commonly used prognostic assessment tools. Methods The Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was used to conduct a retrospective cohort analysis on 1180 critically ill patients with AMI. The primary endpoints were defined as 6-month and 1-year all-cause mortality. Cox regression analysis was used to investigate the relationship between admission PNI and all-cause mortality. The effect of adding PNI to sequential organ failure assessment (SOFA) score, or charlson comorbidity index (CCI) on its discriminative ability was assessed using C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results Multivariate cox regression analysis demonstrated that the low PNI was regarded as an independent predictor of 1-year all-cause mortality in AMI patients admitted to ICU (adjusted Hazard Ratio: 95% CI = 1.75 (1.22–2.49)). The ROC test showed that admission PNI had a moderate predictive ability to predict all-cause mortality of critically ill patients with AMI. Furthermore, the net reclassification and integrated discrimination of the CCI alone model improved significantly with PNI. [C-statistic increased from 0.669 to 0.752, p < 0.001; NRI = 0.698, p < 0.001; IDI = 0.073, p < 0.001]. When PNI was added to the SOFA score, the C-statistic significantly improved from 0.770 to 0.805 (p < 0.001), and the NRI and IDI were estimated at 0.573 (p < 0.001) and 0.041 (p < 0.001), respectively. Conclusion PNI could be a novel predictor for identifying patients at high risk of 1-year all-cause mortality in critically ill patients with AMI. The addition of PNI to the SOFA score or CCI may be useful for very early risk stratification.
Background and aims Atherosclerosis is a vital cause of cardiovascular diseases. The correlation between proteinuria and atherosclerosis, however, has not been confirmed. This study aimed to assess whether there is a relationship between proteinuria and atherosclerosis. Methods From January 2016 to September 2020, 13,545 asymptomatic subjects from four centres in southern China underwent dipstick proteinuria testing and carotid atherosclerosis examination. Data on demography and past medical history were collected, and laboratory examinations were performed. The samples consisted of 7405 subjects (4875 males and 2530 females), excluding subjects failing to reach predefined standards and containing enough information. A multivariate logistic regression model was used to adjust the influence of traditional risk factors for atherosclerosis on the results. Results Compared with proteinuria-negative subjects, proteinuria-positive subjects had a higher prevalence rate of carotid atherosclerosis. The differences were statistically significant (22.6% vs. 26.7%, χ2 = 10.03, p = 0.002). After adjusting for common risk factors for atherosclerosis, age, sex, BMI, blood lipids, blood pressure, renal function, hypertensive disease, diabetes mellitus and hyperlipidaemia, proteinuria was an independent risk factor for atherosclerosis (OR = 1.191, 95% CI 1.015–1.398, p = 0.033). The Hosmer–Lemeshow test was used to test the risk prediction model of atherosclerosis, and the results showed that the model has high goodness of fit and strong independent variable prediction ability. Conclusions Proteinuria is independently related to carotid atherosclerosis. With the increase in proteinuria level, the risk of carotid atherosclerotic plaque increases. For patients with positive proteinuria, further examination of atherosclerosis should not be ignored.
Background The prognostic value of in-hospital hemoglobin drop in non-overt bleeding patients with acute myocardial infarction (AMI) admitted to the intensive care unit (ICU) remains insufficiently investigated. Methods A retrospective analysis was performed based on the Medical Information Mart for Intensive Care (MIMIC)-IV database. 2,334 ICU-admitted non-overt bleeders diagnosed with AMI were included. In-hospital hemoglobin values (baseline value on admission and nadir value during hospitalization) were available. Hemoglobin drop was defined as a positive difference between admission and in-hospital nadir hemoglobin. The primary endpoint was 180-day all-cause mortality. The time-dependent Cox proportional hazard models were structured to analyze the connection between hemoglobin drop and mortality. Results 2,063 patients (88.39%) experienced hemoglobin drop during hospitalization. We categorized patients based on the degree of hemoglobin drop: no hemoglobin drop (n = 271), minimal hemoglobin drop (< 3 g/dl; n = 1661), minor hemoglobin drop (≥ 3 g/dl & < 5 g/dl, n = 284) and major hemoglobin drop (≥ 5 g/dl; n = 118). Minor (adjusted hazard ratio [HR] = 12.68; 95% confidence interval [CI]: 5.13–31.33; P < 0.001) and major (adjusted HR = 13.87; 95% CI: 4.50-42.76; P < 0.001) hemoglobin drops were independently associated with increased 180-day mortality. After adjusting the baseline hemoglobin level, a robust nonlinear relationship was observed in the association between hemoglobin drop and 180-day mortality, with 1.34 g/dl as the lowest value (HR = 1.04; 95% CI: 1.00-1.08). Conclusion In non-overt bleeding ICU-admitted patients with AMI, in-hospital hemoglobin drop is independently associated with higher 180-day all-cause mortality.
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