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Background: This study aimed to investigate whether dexmedetomidine provides survival benefit in critically ill patients with sepsis-induced coagulopathy (SIC). Methods: Patients with sepsis-induced coagulopathy admitted to the ICU were identified from the Medical Information Marketplace for Intensive Care (MIMIC)-IV database. They were divided into two groups: patients who started dexmedetomidine within 48 h of ICU admission and lasted for more than 4 h and patients who did not receive dexmedetomidine as a control group. The primary outcome was 28-day hospital mortality, the secondary outcome was in-hospital mortality, and the extended outcomes included duration of mechanical ventilation and vasopressor use, ICU stay, and hospital stay. Propensity score matching (PSM) analysis was used to match patients who received dexmedetomidine with those who did not, and multivariable Cox models and logistics models were used to account for baseline differences and unmeasured confounders. An external validation was performed with the Critical care database comprising patients with infection at Zigong Fourth People's Hospital. Results: After PSM, 592 patients who received dexmedetomidine were matched with 592 patients who did not receive dexmedetomidine. In the primary and secondary endpoints, dexmedetomidine was associated with a lower risk of 28-day hospital mortality (19.3% vs. 14.2%, hazard ratio (HR) 0.71; P = 0.020) and in-hospital mortality (22.3% vs. 16.4%, odds ratio (OR) 0.68; P = 0.017) in patients with SIC. Regarding the extended outcome, dexmedetomidine was also associated with a longer length of hospital stay (median 12.54 days vs. 14.87 days, P = 0.002) and longer ICU stay (median 5.10 days vs. 6.22 days, P = 0.009). In addition, the duration of mechanical ventilation was significantly increased in the dexmedetomidine group (median 41.62 h vs. 48.00 h, p = 0.022), while the duration of vasopressor use was not significantly different (median 36.67 h vs. 39.25 h, p = 0.194). Within 48 h of ICU stay, receiving a dose of dexmedetomidine greater than 0.474 µg/kg/h and continuous dexmedetomidine administration for 24-48 h may be associated with 28-day hospitalization outcomes in patients with SIC. External cohort validation also found that the use of dexmedetomidine after admission to the ICU can reduce 28-day mortality in patients with SIC. Conclusion: Dexmedetomidine administration is associated with reduced 28-day hospital mortality and in-hospital mortality in critically ill patients with SIC, and these findings deserve further verification in randomized controlled trials.
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Aim: To compare the effects of midazolam, propofol, and dexmedetomidine monotherapy and combination therapy on the prognosis of intensive care unit (ICU) patients receiving continuous mechanical ventilation (MV). Methods: 11,491 participants from the Medical Information Mart for Intensive Care (MIMIC)-IV database 2008-2019 was included in this retrospective cohort study. The primary outcome was defined as incidence of ventilator-associated pneumonia (VAP), in-hospital mortality, and duration of MV. Univariate and multivariate logistic regression analyses were utilized to evaluate the association between sedation and the incidence of VAP. Univariate and multivariate Cox analyses were performed to investigate the correlation between sedative therapy and in-hospital mortality. Additionally, univariate and multivariate linear analyses were conducted to explore the relationship between sedation and duration of MV. Results: Compared to patients not receiving these medications, propofol alone, dexmedetomidine alone, combination of midazolam and dexmedetomidine, combination of propofol and dexmedetomidine, combination of midazolam, propofol and dexmedetomidine were all association with an increased risk of VAP; dexmedetomidine alone, combination of midazolam and dexmedetomidine, combination of propofol and dexmedetomidine, combination of midazolam, propofol and dexmedetomidine may be protective factor for in-hospital mortality, while propofol alone was risk factor. There was a positive correlation between all types of tranquilizers and the duration of MV. Taking dexmedetomidine alone as the reference, all other drug groups were found to be associated with an increased risk of in-hospital mortality. The administration of propofol alone, in combination with midazolam and dexmedetomidine, in combination with propofol and dexmedetomidine, in combination with midazolam, propofol and dexmedetomidine were associated with an increased risk of VAP compared to the use of dexmedetomidine alone. Conclusion: Dexmedetomidine alone may present as a favorable prognostic option for ICU patients with mechanical ventilation MV.
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Objective: This research aimed to investigate the association between the blood urea nitrogen-to-creatinine (BUN/Cr) ratio and the rate of in-hospital mortality in patients with acute ischemic stroke (AIS) and atrial fibrillation (AF), who are also receiving care in intensive care unit (ICU). Methods: A retrospective study was conducted using the MIMIC-IV database. We collected data on BUN/Cr levels at admission for patients with AIS and concurrent AF. To assess the association between BUN/Cr and in-hospital mortality rate, statistical analysis was conducted employing multivariable logistic regression models and restricted cubic spline models. These models were utilized to investigate the potential relationship and provide insights into the impact of BUN/Cr on the likelihood of in-hospital mortality. Interaction and subgroup analyses were performed to evaluate the consistency of the correlation. Results: There were a total of 856 patients (age ≥ 18 years) with a median age of 78.0 years, of which 466 (54.4%) were female. Out of 856 patients, 182 (21.26%) died in the hospital. Upon controlling for confounding factors, the multivariable logistic regression analysis elucidated that patients falling within the third trisection (Q3 > 22.41 mg/dL) exhibited a noticeably increased susceptibility to in-hospital mortality when contrasted with their counterparts positioned in the second trisection (Q2: 17.2-22.41 mg/dL) (OR = 2.02, 95% CI: 1.26-3.26, p = 0.004). A non-linear J-shaped relationship was observed between BUN/Cr at ICU admission and in-hospital mortality rate (p = 0.027), with a turning point at 19.63 mg/dL. In the threshold analysis, there was a 4% rise in in-hospital mortality for each 1 mg/dL increase in BUN/Cr (OR: 1.04, 95% CI: 1.01-1.06, p = 0.012). Conclusion: In patients with AIS complicated by AF, BUN/Cr at admission shows a J-shaped correlation with in-hospital mortality rate. When BUN/Cr exceeds 19.63 mg/dL, the in-hospital mortality rate increases.
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Introduction: Influenza is an important global health concern, particularly in critically ill patients. The anion gap, a marker of metabolic acidosis, is associated with mortality in various critical illnesses. However, its association with mortality in critically ill patients with influenza remains unclear. This study investigated the association between the anion gap on admission and 28-day mortality in critically ill patients with influenza. Methods: A retrospective cohort study was conducted using data from MIMIC-IV database. Patients admitted to the intensive care unit (ICU) with influenza were included. The anion gap was measured within the first 24 h of ICU admission. The primary outcome was the 28-day mortality. The secondary outcomes were 60-day mortality and in-hospital mortality. Multivariable Cox regression was used to assess the association between the anion gap and mortality. Results: A total of 276 critically ill patients with influenza were included in the study. The mean age was 65 years, and 60 % were male. The overall 28-day mortality was 15.5 %. A greater anion gap on admission was associated with significantly increased 28-day mortality in the unadjusted analysis (hazard ratio [HR], 1.11; 95 % confidence interval [CI], 1.03-1.2; p < 0.001). The association remained significant after adjusting for age, sex, race, and illness severity (adjusted HR, 1.09; 95 % CI, 1.02-1.17; p = 0.017). Subgroup analysis showed consistent results across the different groups. Conclusion: A greater anion gap on admission was independently associated with increased 28-day mortality in critically ill patients with influenza. These findings suggest that the anion gap can be used as a prognostic marker in patients with influenza, aiding in risk stratification and guiding clinical management.
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This article presents our experience in development an ontological model can be used in clinical decision support systems (CDSS) creating. We have used the largest international biomedical terminological metathesaurus the Unified Medical Language System (UMLS) as the basis of our model. This metathesaurus has been adapted into Russian using an automated hybrid translation system with expert control. The product we have created was named as the National Unified Terminological System (NUTS). We have added more than 33 million scientific and clinical relationships between NUTS terms, extracted from the texts of scientific articles and electronic health records. We have also computed weights for each relationship, standardized their values and created symptom checker in preliminary diagnostics based on this. We expect, that the NUTS allow solving task of named entity recognition (NER) and increasing terms interoperability in different CDSS.
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Registros Eletrônicos de Saúde , Bases de Conhecimento , Unified Medical Language System , Sistemas de Apoio a Decisões Clínicas , Processamento de Linguagem Natural , Humanos , Federação Russa , Vocabulário ControladoRESUMO
BACKGROUND: The correlation between lipid profiles and sepsis has received increasing attention. The ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) is one of the key lipid profiles. However, in-depth exploration of the correlation between NHHR and the mortality risk of patients with sepsis is limited. METHODS: Data from the MIMIC-IV (v2.2) database, we review the NHHR relevance and the sepsis severity index using Spearman's correlation analysis. Additionally, we research NHHR associated with sepsis patients' survival rate of 28 days using Cox regression analyses of continuous and categorical models. To further validate our findings, we conducted subgroup and sensitivity analyses. RESULTS: The study involved 3,142 patients diagnosed with sepsis, according to 28 days after in-hospital survival condition, divided into two groups. In this study, 2932 patients were in the survival group and 210 patients died within 28 days (mortality group). Of note, the mean NHHR of patients in the mortality group exceeded that of the survival group (3.5 vs. 2.9). Additionally, NHHR was positively correlated with the severity index. After adjusting for demographic and laboratory data, an increased NHHR was positively correlated with higher sepsis mortality risk (OR = 1.06; 95% CI: 1.02-1.11; P = 0.013). Subgroup analysis shown the same results. Contributors were be categorized into two groups based on NHHR levels, with a threshold of 2.61. Contrast the mortality risk between low-NHHR group and high-NHHR group, high-NHHR show greater mortality risk on 28-day, 60-day, 90-day, in ICU, and in hospital. CONCLUSION: Elevated NHHR is to be correlated with an increased risk of mortality in patients with sepsis. Further research on NHHR may contribute to advancements in sepsis prevention and treatment.
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HDL-Colesterol , Sepse , Humanos , Sepse/mortalidade , Sepse/sangue , Masculino , Feminino , HDL-Colesterol/sangue , Idoso , Pessoa de Meia-Idade , Bases de Dados Factuais , Índice de Gravidade de Doença , Modelos de Riscos Proporcionais , Fatores de RiscoRESUMO
Background: The ideal timing for commencing enteral nutrition (EN) in critically ill stroke patients in the intensive care unit (ICU) remains a subject of debate, with ongoing controversy regarding the impact of early EN (EEN) initiation. In this study, we investigated the association between the timing of EN initiation and 28-day mortality using data from the MIMIC-IV database. Methods: This study employed a retrospective cohort design using the MIMIC-IV database to identify stroke patients who received EN during their hospital stay. The main focus of this investigation was to examine 28-day mortality among these patients following hospital admission. Various demographic, clinical, laboratory, and intervention variables were considered as covariates. The Cox regression analysis was employed to assess the correlation between the timing of EN initiation and 28-day mortality, and restricted cubic splines (RCS) analysis was used to test for non-linear correlation. Patients were then stratified into two cohorts depending on the timing of EN initiation: within 2 days (n = 564) and beyond 2 days (n = 433). A multivariate Cox regression analysis was used to investigate the difference in 28-day mortality between the groups. Results: A total of 997 participants were included in this study, with 318 (31.9%) dying within 28 days. We observed that the timing of EN initiation correlated with 28-day mortality, but this correlation was not significant after adjusting for covariates (crude HR: 0.94, 95% CI: 0.88-1, p = 0.044; adjusted HR: 0.96, 95% CI: 0.9-1.02, p = 0.178). The RCS analysis showed that the correlation was not non-linear. Notably, in the multivariate regression models, early EN initiation was associated with a higher mortality rate compared to late EN initiation [odds ratio (OR) = 1.34, 95% CI: 1.06-1.67, p = 0.012]. After adjusting for various confounding factors in the multivariate Cox regression models, we identified that patients in the early EN group had a 28% higher risk of mortality than those in the reference group (OR = 1.27, 95% CI: 1-1.61, p = 0.048). These associations remained consistent across various patient characteristics, as revealed through stratified analyses. Conclusions: Early commencement of EN in critically ill stroke patients may be linked to a higher risk of 28-day mortality, highlighting the need for further investigation and a more nuanced consideration of the optimal timing for commencing EN in this patient population.
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Background: Estimated pulse wave velocity (ePWV), which measures vascular aging, is an independent predictor of cardiovascular death. Nevertheless, the relationship between ePWV and all-cause mortality among patients suffering from non-traumatic subarachnoid hemorrhages (NSAH) remains obscure. Consequently, the objective of this study is to ascertain whether ePWV exerts influence on the prognosis of individuals afflicted with NSAH. Methods: Through the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, 644 eligible participants were included. The Kaplan-Meier survival curve method was employed to assess the disparity in survival status between the low and high ePWV cohorts. The Cox proportional hazard model was employed to investigate the association between ePWV and inpatient mortality among critically ill patients diagnosed with NSAH. The Restricted Cubic Spline (RCS) model was employed to examine the dose-response correlation. Subsequently, multivariate Cox regression analysis was performed to identify independent prognostic factors. Lastly, the impact of ePWV on inpatient mortality across various subgroups was evaluated through stratified analysis. Results: Participants were categorized into two groups, delineated by their ePWV levels: a low ePWV level group and a high ePWV level group. Survival analysis unveiled that individuals with high ePWV exhibited a diminished survival rate compared to their counterparts with low ePWV. Following adjustment, low ePWV was significantly linked with a reduced risk of inpatient mortality among patients with NSAH (HR = 0.54, 95% CI = 0.32-0.89, p = 0.016). Simultaneously, analysis employing the RCS model further substantiated a linear escalation in the risk of inpatient mortality with increasing ePWV values. Conclusion: Elevated ePWV levels have been identified as an independent risk factor for the rise in inpatient mortality among NSAH patients and as a significant predictor of the clinical outcome of NSAH.
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BACKGROUND: Carotid-femoral pulse wave velocity has been identified as an autonomous predictor of cardiovascular mortality and kidney injury. This important clinical parameter can be non-invasively estimated using the calculated pulse wave velocity (ePWV). The objective of this study was to examine the correlation between ePWV and in-hospital as well as one-year mortality among critically ill patients with chronic kidney disease (CKD) and atherosclerotic heart disease (ASHD). METHODS: This study included a cohort of 1173 patients diagnosed with both CKD and ASHD, sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The four groups divided into quartiles according to ePWV were compared using a Kaplan-Meier survival curve to assess variations in survival rates. Cox proportional hazards models were employed to analyze the correlation between ePWV and in-hospital as well as one-year mortality among critically ill patients with both CKD and ASHD. To further investigate the dose-response relationship, a restricted cubic splines (RCS) model was utilized. Additionally, stratification analyses were performed to examine the impact of ePWV on hospital and one-year mortality across different subgroups. RESULTS: The survival analysis results revealed a negative correlation between higher ePWV and survival rate. After adjusting for confounding factors, higher ePWV level (ePWV > 11.90 m/s) exhibited a statistically significant association with an increased risk of both in-hospital and one-year mortality among patients diagnosed with both CKD and ASHD (HR = 4.72, 95% CI = 3.01-7.39, p < 0.001; HR = 2.04, 95% CI = 1.31-3.19, p = 0.002). The analysis incorporating an RCS model confirmed a linear escalation in the risk of both in-hospital and one-year mortality with rising ePWV values (P for nonlinearity = 0.619; P for nonlinearity = 0.267). CONCLUSIONS: The ePWV may be a potential marker for the in-hospital and one-year mortality assessment of CKD with ASHD, and elevated ePWV was strongly correlated with an elevated mortality risk in patients diagnosed with both CKD and ASHD.
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Mortalidade Hospitalar , Análise de Onda de Pulso , Insuficiência Renal Crônica , Humanos , Masculino , Feminino , Estudos Retrospectivos , Pessoa de Meia-Idade , Insuficiência Renal Crônica/mortalidade , Insuficiência Renal Crônica/fisiopatologia , Insuficiência Renal Crônica/complicações , Idoso , Estado Terminal/mortalidade , Aterosclerose/mortalidade , Bases de Dados Factuais , Estimativa de Kaplan-Meier , Modelos de Riscos Proporcionais , Fatores de RiscoRESUMO
Objective: Coagulopathy score has been applied as a new prognostic indicator for sepsis, heart failure and acute respiratory failure. However, its ability to forecast intensive care unit (ICU) mortality in patients with an acute cerebral hemorrhage (ICH) has not been assessed. The purpose of this study was to clarify the relationship between ICU mortality and early coagulation problem score. Methods: Data from the Medical Information Mart for Intensive Care (MIMIC-IV) (v2.0) database were used in this retrospective cohort analysis. The association between the coagulation disorder score and ICU mortality was examined using multivariate logistic regression. Furthermore, the impact of additional variables on the results was investigated by a subgroup analysis. Results: 3174 patients (57.3 % male) were enrolled in total. The ICU mortality reached 18.2 %. After adjusting for potential confounders, the ICU mortality of patients rose with the increase of coagulation disorder score. The ROC curve revealed the predictive accuracy of coagulation dysfunction score to mortality in patients with ICU. The coagulation disorder score had a lower AUC value (0.601, P < 0.001) than the SAPSII(AUCs of 0.745[95 % CI, 0.730-0.761]) and the combined indicators(AUCs of 0.752[95 % CI, 0.737-0.767]), but larger than single indicators platelet, INR and APTT. In the subgroup analysis, most subgroups showed no significant interaction, but only age showed significant interaction in the adjusted model. Conclusion: The coagulopathy score and ICU mortality were found to be strongly positively correlated in this study, and its ability to predict ICU mortality was better than that of a single measure (platelet, INR, or APTT), but worse than that of the SAPSII score, GCS system.
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Research on the severity and prognosis of sepsis with or without progressive delirium is relatively insufficient. We constructed a prediction model of the risk factors for 28-day mortality in patients who developed sepsis or sepsis-associated delirium. The modeling group of patients diagnosed with Sepsis-3 and patients with progressive delirium of related indicators were selected from the MIMIC-IV database. Relevant independent risk factors were determined and integrated into the prediction model. Receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow (HL) test were used to evaluate the prediction accuracy and goodness-of-fit of the model. Relevant indicators of patients with sepsis or progressive delirium admitted to the intensive care unit (ICU) of a 3A hospital in Xinjiang were collected and included in the verification group for comparative analysis and clinical validation of the prediction model. The total length of stay in the ICU, hemoglobin levels, albumin levels, activated partial thrombin time, and total bilirubin level were the five independent risk factors in constructing a prediction model. The area under the ROC curve of the predictive model (0.904) and the HL test result (χ2 = 8.518) indicate a good fit. This model is valuable for clinical diagnosis and treatment and auxiliary clinical decision-making.
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Delírio , Unidades de Terapia Intensiva , Curva ROC , Sepse , Humanos , Fatores de Risco , Sepse/mortalidade , Sepse/complicações , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Delírio/mortalidade , Delírio/diagnóstico , Bases de Dados Factuais , Prognóstico , Mortalidade Hospitalar , Tempo de Internação , Idoso de 80 Anos ou maisRESUMO
PROBLEM: Sepsis, a life-threatening condition, accounts for the deaths of millions of people worldwide. Accurate prediction of sepsis outcomes is crucial for effective treatment and management. Previous studies have utilized machine learning for prognosis, but have limitations in feature sets and model interpretability. AIM: This study aims to develop a machine learning model that enhances prediction accuracy for sepsis outcomes using a reduced set of features, thereby addressing the limitations of previous studies and enhancing model interpretability. METHODS: This study analyzes intensive care patient outcomes using the MIMIC-IV database, focusing on adult sepsis cases. Employing the latest data extraction tools, such as Google BigQuery, and following stringent selection criteria, we selected 38 features in this study. This selection is also informed by a comprehensive literature review and clinical expertise. Data preprocessing included handling missing values, regrouping categorical variables, and using the Synthetic Minority Over-sampling Technique (SMOTE) to balance the data. We evaluated several machine learning models: Decision Trees, Gradient Boosting, XGBoost, LightGBM, Multilayer Perceptrons (MLP), Support Vector Machines (SVM), and Random Forest. The Sequential Halving and Classification (SHAC) algorithm was used for hyperparameter tuning, and both train-test split and cross-validation methodologies were employed for performance and computational efficiency. RESULTS: The Random Forest model was the most effective, achieving an area under the receiver operating characteristic curve (AUROC) of 0.94 with a confidence interval of ±0.01. This significantly outperformed other models and set a new benchmark in the literature. The model also provided detailed insights into the importance of various clinical features, with the Sequential Organ Failure Assessment (SOFA) score and average urine output being highly predictive. SHAP (Shapley Additive Explanations) analysis further enhanced the model's interpretability, offering a clearer understanding of feature impacts. CONCLUSION: This study demonstrates significant improvements in predicting sepsis outcomes using a Random Forest model, supported by advanced machine learning techniques and thorough data preprocessing. Our approach provided detailed insights into the key clinical features impacting sepsis mortality, making the model both highly accurate and interpretable. By enhancing the model's practical utility in clinical settings, we offer a valuable tool for healthcare professionals to make data-driven decisions, ultimately aiming to minimize sepsis-induced fatalities.
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Unidades de Terapia Intensiva , Aprendizado de Máquina , Sepse , Humanos , Sepse/mortalidade , Prognóstico , Adulto , Masculino , Pessoa de Meia-Idade , Feminino , IdosoRESUMO
Background: Frailty is a severe, common co-morbidity associated with congestive heart failure (CHF). This retrospective cohort study assesses the association between frailty and the risk of mortality in critically ill CHF patients. Methods: Eligible patients with CHF from the Medical Information Base for Intensive Care IV database were retrospectively analyzed. The frailty index based on laboratory tests (FI_Lab) index was calculated using 33 variables to assess frailty status. The primary outcomes were in-hospital mortality and one-year mortality. The secondary outcomes were the incidence of acute kidney injury (AKI) and the administration of renal replacement therapy (RRT) in patients with concurrent AKI. Survival disparities among the FI_Lab subgroups were estimated with Kaplan-Meier survival analysis. The association between the FI_Lab index and mortality was examined with Cox proportional risk modeling. Results: A total of 3273 adult patients aged 18 years and older were enrolled in the study, with 1820 men and 1453 women included. The incidence rates of in-hospital mortality and one-year mortality rate were 0.96 per 1,000 person-days and 263.8 per 1,000 person-years, respectively. Multivariable regression analysis identified baseline FI_Lab > 0.45 as an independent risk factor predicting in-hospital mortality (odds ratio = 3.221, 95% CI 2.341-4.432, p < 0.001) and one-year mortality (hazard ratio=2.152, 95% CI: 1.730-2.678, p < 0.001). In terms of predicting mortality, adding FI_Lab to the six disease severity scores significantly improved the overall performance of the model (all p < 0.001). Conclusions: We established a positive correlation between the baseline FI_Lab and the likelihood of adverse outcomes in critical CHF patients. Given its potential as a reliable prognostic tool for such patients, further validation of FI_Lab across multiple centers is recommended for future research.
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Estado Terminal , Fragilidade , Insuficiência Cardíaca , Mortalidade Hospitalar , Humanos , Masculino , Insuficiência Cardíaca/mortalidade , Feminino , Idoso , Estado Terminal/mortalidade , Fragilidade/mortalidade , Fragilidade/complicações , Estudos Retrospectivos , Pessoa de Meia-Idade , Idoso de 80 Anos ou mais , Bases de Dados Factuais , Fatores de Risco , Prognóstico , Injúria Renal Aguda/mortalidade , Injúria Renal Aguda/terapiaRESUMO
Background: Sepsis is a life-threatening condition that requires rapid assessment to reduce mortality. This study investigates the relationship between the Neutrophil-to-Monocyte/Lymphocyte Ratio (NMLR) upon ICU admission and 28-day mortality in sepsis patients. Methods: A retrospective analysis was performed using clinical data from sepsis patients in the Medical Information Mart for Intensive Care IV (MIMIC-IV). Multivariate logistic regression, sensitivity analyses, and Restricted Cubic Spline (RCS) models were employed to explore the relationship between ICU admission NMLR and 28-day mortality. Kaplan-Meier method and inverse probability weighting (IPW) were used to adjust for confounders and estimate survival outcomes. Receiver operating characteristic (ROC) curve evaluating the predictive value of NLMR for 28-day mortality in ICU sepsis patients. Subgroup analyses considered factors like age, sex, race, comorbidities, and disease severity. Results: In total, 8,710 patients were included. Increased NMLR was associated with higher 28-day all-cause mortality, confirmed by multiple logistic regression models. In Model 3, after adjusting for confounders, each standard deviation increase in NMLR was associated with a 1.5% increase in 28-day mortality risk. Kaplan-Meier and IPW survival analyses showed higher 28-day all-cause mortality in patients with elevated NMLR levels at ICU admission compared to those with lower levels (p < 0.0001, p = 0.031). RCS models suggested a potential non-linear relationship between NMLR and 28-day mortality. ROC curve for the NMLR model, with an AUC of 0.658 (95% CI: 0.642-0.673). Sensitivity analyses confirmed the association even after excluding patients with myocardial infarction and severe liver disease. Conclusion: Elevated NMLR at ICU admission is significantly associated with increased 28-day all-cause mortality in sepsis patients, suggesting its potential as an early prognostic indicator for risk assessment and intervention.
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Background: Acute heart failure necessitates intensive care, and arterial catheterization is a commonly performed invasive procedure in the intensive care unit (ICU). We aimed to investigate the association between arterial catheterization and outcomes in acute heart failure patients without shock. Methods: We utilized MIMIC-IV database records for acute heart failure patients at Beth Israel Deaconess Medical Center from 2008 to 2019. Employing doubly robust estimation, we examined the relationship between arterial catheterization and outcomes, including 28-day, 90-day, in-hospital mortality, and ICU-free days within 28 days. Results: Of 6936 patients identified, 2078 met inclusion criteria; 347 underwent arterial catheterization during their ICU stay. We observed no significant difference in 28-day mortality (odds ratio [OR]: 0.61, 95 % confidence interval [CI]: 0.31-1.21, P = 0.155), though catheterization was associated with reduced in-hospital mortality (OR: 0.41, 95 % CI: 0.14-0.65, P = 0.02). No significant effects were observed on 90-day mortality or ICU-free days within 28 days. Conclusion: Our findings suggest that arterial catheterization is not associated with 28- and 90-day mortality rates in acute heart failure patients without shock but is linked to lower in-hospital mortality. Additional research and consensus are required to determine the appropriate utilization of arterial catheterization in patients.
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Background: The lactate to hematocrit ratio (LHR) has not been assessed for predicting all-cause death in sepsis patients. This study aims to evaluate the relationship between LHR and 30-day all-cause mortality in sepsis patients. Methods: This retrospective study used the data from Medical information mart for intensive care IV (MIMIC-IV, version 2.0). Our study focused on adult sepsis patients who were initially hospitalized in the Intensive care unit (ICU). The prognostic significance of admission LHR for 30-day all-cause mortality was evaluated using a multivariate Cox regression model, ROC curve analysis, Kaplan-Meier curves, and subgroup analyses. Results: A total of 3,829 sepsis patients participated in this study. Among the cohort, 8.5% of individuals died within of 30 days (p < 0.001). The area under the curve (AUC) for LHR was 74.50% (95% CI: 71.6-77.50%), higher than arterial blood lactate (AUC = 71.30%), hematocrit (AUC = 64.80%), and shows no significant disadvantage compared to qSOFA, SOFA, and SAPS II. We further evaluated combining LHR with qSOFA score to predict mortality in sepsis patients, which shows more clinical significance. ROC curve analysis showed that 6.538 was the optimal cutoff value for survival and non-survival groups. With LHR ≥6.538 vs. LHR <6.538 (p < 0.001). Subgroup analysis showed significant interactions between LHR, age, sex, and simultaneous acute respiratory failure (p = 0.001-0.005). Conclusion: LHR is an independent predictor of all-cause mortality in sepsis patients after admission, with superior predictive ability compared to blood lactate or hematocrit alone.
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Background: Acute kidney injury (AKI), a prevalent postoperative complication, predominantly manifests as stage 1, characterized by a mild elevation in serum creatinine (SCr). There is yet to be a consensus regarding the association between stage 1 AKI and adverse outcomes in surgical patients. Methods: This retrospective study enrolled adult patients who underwent at least one surgery during hospitalization from the MIMIC IV database. AKI was diagnosed when the KDIGO creatinine criteria were satisfied within 7 days after surgery. Stage 1a AKI was defined as an absolute increase in SCr of 26.5 µmol/L, and stage 1b was defined as a 50% relative increase. Stage 1 AKI was also divided into transient and persistent substages based on whether the AKI recovered within 48 h after onset. The association between stage 1 AKI and its substages and in-hospital mortality was evaluated. Results: Among 49,928 patients enrolled, 9755 (19.5%) developed AKI within 7 days after surgery, of which 7659 (78.5%) presented with stage 1 AKI. The median follow-up was 369 (367, 372) days. Stage 1 AKI was significantly associated with in-hospital mortality after adjustment (aHR, 2.73; 95% CI, 2.29, 3.26). Subgroup analyses showed that the risk of stage 1 AKI on in-hospital mortality was attenuated by age ≥ 65 years (p for interaction = 0.017) or a baseline eGFR < 60 mL/min per 1.73 m2 (p for interaction = 0.001). Compared with non-AKI, patients with stage 1b (aHR, 3.06; 95% CI, 2.56, 3.66) and persistent stage 1 (aHR, 2.03; 95% CI, 1.61, 2.57) AKI had an increased risk of in-hospital mortality; however, this risk was not significant in those with stage 1a (aHR, 1.01; 95% CI, 0.68, 1.51) and transient stage 1 (aHR, 1.11; 95% CI, 0.79, 1.57) AKI. Conclusions: Stage 1 AKI exhibits an independent correlation with a heightened mortality risk among surgical patients. Consequently, a tailored adaptation of the KDIGO AKI classification may be necessitated for the surgical population, particularly those presenting with decreased baseline kidney function.
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BACKGROUND: Atrial fibrillation (AF) is the most common heart arrhythmia worldwide and is linked to a higher risk of mortality and morbidity. To predict AF and AF-related complications, clinical risk scores are commonly employed, but their predictive accuracy is generally limited, given the inherent complexity and heterogeneity of patients with AF. By classifying different presentations of AF into coherent and manageable clinical phenotypes, the development of tailored prevention and treatment strategies can be facilitated. In this study, we propose an artificial intelligence (AI)-based methodology to derive meaningful clinical phenotypes of AF in the general and critical care populations. METHODS: Our approach employs generative topographic mapping, a probabilistic machine learning method, to identify micro-clusters of patients with similar characteristics. It then identifies macro-cluster regions (clinical phenotypes) in the latent space using Ward's minimum variance method. We applied it to two large cohort databases (UK-Biobank and MIMIC-IV) representing general and critical care populations. FINDINGS: The proposed methodology showed its ability to derive meaningful clinical phenotypes of AF. Because of its probabilistic foundations, it can enhance the robustness of patient stratification. It also produced interpretable visualisation of complex high-dimensional data, enhancing understanding of the derived phenotypes and their key characteristics. Using our methodology, we identified and characterised clinical phenotypes of AF across diverse patient populations. INTERPRETATION: Our methodology is robust to noise, can uncover hidden patterns and subgroups, and can elucidate more specific patient profiles, contributing to more robust patient stratification, which could facilitate the tailoring of prevention and treatment programs specific to each phenotype. It can also be applied to other datasets to derive clinically meaningful phenotypes of other conditions. FUNDING: This study was funded by the DECIPHER project (LJMU QR-PSF) and the EU project TARGET (10113624).
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Although accumulating researches were done for investigating the relationship between triglyceride-glucose index (TyG index) and different diseases, none of the researches have been made in sepsis yet. In this study, we aimed to explore the relationship between TyG index and clinical outcomes in sepsis based on a large critical care public database. Sepsis patients in Medical Information Mart for Intensive Care IV (MIMIC-IV) Database were included. The exposure was TyG index, which was calculated by the equation: ln (TG (mg/dL) × FBG (mg/dL)/2). The outcomes were in-hospital mortality and 1-year mortality. The relationship between TyG index and outcomes was performed by Cox regression analysis. Smooth fitting curves were constructed by using generalized additive model. Kaplan-Meier analyses for cumulative hazard of 1-year mortality in different groups were done. 1103 sepsis patients were included with a median TyG index of 9.78. The mortalities of in-hospital and 1-year were 37.53% (n = 414) and 42.25% (n = 466), respectively. After adjusting confounders, there was a significantly negative relationship between TyG index and mortalities of in-hospital and 1-year. With the per unit increment in TyG index, the risk of in-hospital and 1-year mortality both decreased by 21% (HR = 0.79, 95% CI: 0.66-0.94, p = 0.0086 and HR = 0.79, 95% CI: 0.66-0.94, p = 0.0080, respectively). A negative relationship between TyG index and clinical outcomes in sepsis was found.
Assuntos
Glicemia , Mortalidade Hospitalar , Sepse , Triglicerídeos , Humanos , Sepse/sangue , Sepse/mortalidade , Sepse/diagnóstico , Triglicerídeos/sangue , Masculino , Feminino , Pessoa de Meia-Idade , Estudos Retrospectivos , Glicemia/metabolismo , Idoso , Estimativa de Kaplan-Meier , Prognóstico , Modelos de Riscos ProporcionaisRESUMO
BACKGROUND: Triglyceride-glucose (TyG) index is linked to a poor prognosis for cardiovascular condition and is a valid indicator of insulin resistance. This study evaluated the potential predicting usefulness of the TyG index for all-cause mortality, both short- and long-term, for those concerning critical coronary artery disease (CAD). METHODS: In this study, information from 5452 critically-ill individuals with CAD in intensive care units were gathered from the Medical Information Marketplace in Intensive Care (MIMIC-IV) database. Depending on the TyG index degree, the patients were categorized into three categories. Clinical outcomes included short-term (30-day) and long-term (365-day) all-cause mortality. The corresponding relationships involving the TyG index and clinical outcomes were examined by deploying restricted cubic spline (RCS) regression analysis and Cox proportional risk regression. RESULTS: An increased TyG index was associated with increased 30-day (Tertile 1: 6.1%, Tertile 2: 7.3%, Tertile 3: 9.2%, P = 0.001) and 365-day (Tertile 1: 15.2%, Tertile 2: 17.0%, Tertile 3: 19.6%, P = 0.002) death rates across all causes. Cox regression with multiple variables indicates that higher TyG indices were linked to higher all-caused mortality hazard ratios throughout the short and long terms, with a larger predictive value for the former. RCS regression analyses suggested that the risk of death was notably and linearly that is associated with TyG index. CONCLUSIONS: The TyG index is a reliable predictor of all-cause mortality at different stages in critically ill CAD patients, with a higher predictive ability for short-term mortality. Early intervention in patients with elevated TyG index may improve their survival outcomes. Future research should delve into understanding its pathophysiological mechanisms and develop intervention strategies based on the TyG index, providing new insights and strategies to enhance the outlook for critically ill CAD patients.