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Background: Millions of patients undergo cardiac surgery each year. The red blood cell distribution width (RDW) could help predict the prognosis of patients who undergo percutaneous coronary intervention or coronary artery bypass surgery. We investigated whether the RDW has robust predictive value for the 30-day mortality among patients in an intensive care unit (ICU) after undergoing cardiac surgery. Methods: Using the Medical Information Mart for Intensive Care-IV Database, we retrieved data for 11,634 patients who underwent cardiac surgery in an ICU. We performed multivariate Cox regression analysis to model the association between the RDW and 30-day mortality and plotted Kaplan-Meier curves. Subgroup analyses were stratified using relevant covariates. Receiver operating characteristic (ROC) curves were used to determine the predictive value of the RDWs. Results: The total 30-day mortality rate was 4.2% (485/11,502). The elevated-RDW group had a higher 30-day mortality rate than the normal-RDW group (P&0.001). The robustness of our data analysis was confirmed by performing subgroup analyses. Each unit increase in the RDW was associated with a 17% increase in 30-day mortality when the RDW was used as a continuous variable (adjusted hazard ratio=1.17, 95% confidence interval, 1.10-1.25). Our ROC results showed the predictive value of the RDW. Conclusions: An elevated RDW was associated with a higher 30-day mortality in patients after undergoing cardiac surgery in an ICU setting. The RDW can serve as an efficient and accessible method for predicting the mortality of patients in ICUs following cardiac surgery.
Assuntos
Procedimentos Cirúrgicos Cardíacos , Bases de Dados Factuais , Índices de Eritrócitos , Unidades de Terapia Intensiva , Estimativa de Kaplan-Meier , Modelos de Riscos Proporcionais , Curva ROC , Humanos , Feminino , Masculino , Estudos Retrospectivos , Idoso , Pessoa de Meia-Idade , Procedimentos Cirúrgicos Cardíacos/mortalidade , Área Sob a Curva , Cuidados Críticos , Prognóstico , Ponte de Artéria Coronária/mortalidade , Intervenção Coronária Percutânea/mortalidadeRESUMO
Introduction: Acute pancreatitis (AP) is a prevalent inflammatory disease that can lead to severe abdominal pain and multiple organ failure, potentially resulting in pancreatic necrosis and persistent dysfunction. A nomogram prediction model was developed to accurately evaluate the prognosis and provide therapy guidance to AP patients. Material and methods: Retrospective data extraction was performed using MIMIC-IV, an open-source clinical database, to obtain 1344 AP patient records, of which the primary dataset included 1030 patients after the removal of repeated hospitalizations. The prediction of in-hospital mortality (IHM) used the least absolute shrinkage and selection operator (LASSO) regression model to optimize feature selection. A multivariate logistic regression analysis was used to build a prediction model incorporating the selected features, and the C-index, calibration plot, and decision curve analysis (DCA) were utilized to evaluate the discrimination, calibration, and clinical applicability of the prediction model. Results: The nomogram utilized a combination of indicators, including the SAPS II score, RDW, MBP, RR, PTT, and fluid-electrolyte disorders. Impressively, the model exhibited a satisfactory diagnostic performance, with area under the curve values of 0.892 and 0.856 for the training cohort and internal validation, respectively. Moreover, the calibration plots and the Hosmer-Lemeshow goodness-of-fit (HL) test revealed a strong correlation between the predicted and actual outcomes (p = 0.73), further confirming the reliability of our model. Notably, the results of the decision curve analysis (DCA) highlighted the superiority of our model over previously described scoring methods in terms of net clinical benefit, solidifying its value in clinical applications. Conclusions: Our novel nomogram is a simple tool for accurately predicting IHM in ICU patients with AP. Treatment methods that enhance the factors involved in the model may contribute to increased in-hospital survival for these ICU patients.
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BACKGROUND: Triglyceride glucose (TyG) is associated with stroke, atherosclerosis, and adverse clinical outcomes. However, its correlation with cerebrovascular disease (CVD) mortality remains unclear. This study aimed to investigate the relationship between TyG index and mortality in patients with CVD. METHODS: Patient data sourced from the Medical Information Mart for Intensive Care -IV database were categorized based on TyG quartiles. Kaplan-Meier survival analysis was used to estimate survival disparities among the TyG subgroups. Cox proportional risk modeling was used to examine the association between the TyG index and mortality. Generalized summation models were applied to fit the smoothed curves. log-likelihood ratio test were used to analyze the non-linear relationship. RESULTS: The study comprised 1,965 patients (50.18% were male). The 28-day and 90-day mortality rates were 20.10% and 24.48%, respectively. The TyG index exhibited a linear relationship with the 28-day mortality (Hazards ratio (HR), 1.16; 95% confidence interval (CI), 0.99-1.36) and the 90-day mortality (HR, 1.18; 95% CI, 1.02-1.37). In the TyG Q4 group, each 1 mg/dl increase was linked to a 35% rise in the risk of 28-day mortality and a 38% increase in the risk of 90-day mortality. Subgroup analyses highlighted a more substantial association between TyG index and 90-day mortality in the diabetic group. CONCLUSION: Our findings underscore the positive association between TyG and the 28- and 90-day mortality rates in patients with CVD. This insight may prove pivotal for identifying at-risk populations and enhancing risk prediction in the clinical management of CVD.
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Background: The predictive value of red blood cell distribution width (RDW) for mortality in patients with sepsis-induced acute kidney injury (SI-AKI) remains unclear. The present study aimed to investigate the potential association between RDW at admission and outcomes in patients with SI-AKI. Methods: The Medical Information Mart for Intensive Care (MIMIC)-IV (version 2.0) database, released in June of 2022, provides medical data of SI-AKI patients to conduct our related research. Based on propensity score matching (PSM) method, the main risk factors associated with mortality in SI-AKI were evaluated using Cox proportional hazards regression analysis to construct a predictive nomogram. The concordance index (C-index) and decision curve analysis were used to validate the predictive ability and clinical utility of this model. Patients with SI-AKI were classified into the high- and low-RDW groups according to the best cut-off value obtained by calculating the maximum value of the Youden index. Results: A total of 7574 patients with SI-AKI were identified according to the filter criteria. Compared with the low-RDW group, the high-RDW group had higher 28-day (9.49% vs. 31.40%, respectively, P <0.001) and 7-day (3.96% vs. 13.93%, respectively, P <0.001) mortality rates. Patients in the high-RDW group were more prone to AKI progression than those in the low-RDW group (20.80% vs. 13.60%, respectively, P <0.001). Based on matched patients, we developed a nomogram model that included age, white blood cells, RDW, combined hypertension and presence of a malignant tumor, treatment with vasopressor, dialysis, and invasive ventilation, sequential organ failure assessment, and AKI stages. The C-index for predicting the probability of 28-day survival was 0.799. Decision curve analysis revealed that the model with RDW offered greater net benefit than that without RDW. Conclusion: The present findings demonstrated the importance of RDW, which improved the predictive ability of the nomogram model for the probability of survival in patients with SI-AKI.
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Introduction: Acute respiratory failure (ARF) has a high mortality rate, and currently, there is no convenient risk predictor. The coagulation disorder score was proven to be a promising metric for predicting in-hospital mortality, but its role in ARF patients remains unknown. Methods: In this retrospective study, data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Patients diagnosed with ARF and hospitalized for more than 2 days at their first admission were included. The coagulation disorder score was defined based on the sepsis-induced coagulopathy score and was calculated by parameters, namely, additive platelet count (PLT), international normalized ratio (INR), and activated partial thromboplastin time (APTT), based on which the participants were divided into six groups. Results: Overall, 5,284 ARF patients were enrolled. The in-hospital mortality rate was 27.9%. High levels of additive platelet score, INR score, and APTT score were significantly associated with increased mortality in ARF patients (P < 0.001). Binary logistic regression analysis showed that a higher coagulation disorder score was significantly related to the increased risk of in-hospital mortality in ARF patients (Model 2: coagulation disorder score = 6 vs. coagulation disorder score = 0: OR, 95% CI: 7.09, 4.07-12.34, P < 0.001). The AUC of the coagulation disorder score was 0.611 (P < 0.001), which was smaller than that of sequential organ failure assessment (SOFA) (De-long test P = 0.014) and simplified acute physiology score II (SAPS II) (De-long test P < 0.001) but larger than that of additive platelet count (De-long test P < 0.001), INR (De-long test P < 0.001), and APTT (De-long test P < 0.001), respectively. In subgroup analysis, we found that in-hospital mortality was markedly elevated with an increased coagulation disorder score in ARF patients. No significant interactions were observed in most subgroups. Of note, patients who did not administrate oral anticoagulant had a higher risk of in-hospital mortality than those who administrated oral anticoagulant (P for interaction = 0.024). Conclusion: This study found a significant positive association between coagulation disorder scores and in-hospital mortality. The coagulation disorder score was superior to the single indicators (additive platelet count, INR, or APTT) and inferior to SAPS II and SOFA for predicting in-hospital mortality in ARF patients.
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Background: Basic studies show that selective 5-hydroxytryptamine type 3 (5-HT3) serotonin-receptor antagonists can protect organs from inflammatory injury and have shown lung protection. Whether 5-HT3 receptor antagonists ondansetron benefits patients with mechanical ventilation is unclear in the intensive care unit (ICU). Methods: The Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was reviewed to identify patients on mechanical ventilation (aged >16 years) in the ICU, which was divided into two groups according to whether ondansetron is used. Demographic characteristics, medical history data, clinical parameters, diagnosis and treatment measures were included as covariates. Ondansetron use was defined as any kind of ondansetron administration regardless of the dose before the induction of mechanical ventilation. The primary outcome was in-hospital death. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated by multivariable Cox regression. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were performed to further adjust for confounding factors. Kaplan-Meier (KM) curves with log-rank test were also performed. Results: A total of 18,566 patients on mechanical ventilation were included (5,735 with ondansetron use). The overall in-hospital mortality rate of patients on mechanical ventilation was 18.9% (3,512/18,566). Approximately 13.0% (746/5,735) and 21.6% (2,766/12,831) in-hospital mortality rates occurred in the ondansetron and non-ondansetron use groups, respectively. Multivariable regression indicated that ondansetron usage was associated with a 33% and 32% lower risk of in-hospital and 60-day death (HR =0.77, 95% CI: 0.70-0.85, P<0.001; HR =0.68, 95% CI: 0.62-0.75, P<0.001) in the whole sample. Multivariable regression post-PSM indicated that ondansetron usage was associated with a 38% and 31% lower risk of in-hospital and 60-day death (HR =0.62, 95% CI: 0.56-0.68, P<0.001; HR =0.69, 95% CI: 0.62-0.77, P<0.001). Log-rank test for the KM curve of ondansetron and 60-day death was statistically significant (P<0.001). The duration of ventilator use pre- and post-PSM was statistically different (P<0.001 and P=0.007) in the two groups. Conclusions: Ondansetron usage was significantly associated with a lower mortality risk of ventilated patients in the ICU. The 5-HT3 receptor antagonist use is may be new potential adjunctive therapeutic strategy for patients on mechanical ventilation in the ICU.