Risk Of Intensive Care Unit Mortality Research Articles

Whole blood ratio of CDK1/CX3CR1 mRNA expression combined to lactate refines the prediction of ICU mortality in septic patients in the Sepsis-3 era: a proof-of-concept study.

Transcriptomics biomarkers have been widely used to predict mortality in patients with sepsis. However, the association between mRNA levels and outcomes shows substantial variability over the course of sepsis, limiting their predictive performance. We aimed to: (a) identify and validate an mRNA biomarker signature whose association with all-cause intensive care unit (ICU) mortality is consistent at several timepoints; and (b) evaluate how this mRNA signature could be used in association with lactate levels for predictive and prognostic enrichment in sepsis. We conducted a gene expression analysis study at two timepoints (day 1 and day 2-3 following ICU admission) using microarray data from adult septic patients to identify candidate biomarkers predictive of all-cause ICU mortality. We validated mRNA biomarkers using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) on an external validation cohort. The predictive performance of the mRNA biomarkers combination was assessed in association with lactate level to refine ICU mortality prediction. Among 180 chips from 100 septic patients, we identified 39 upregulated and 2 downregulated differentially expressed genes (DEGs) in survivors vs. non-survivors, both at day 1 and days 2-3 following ICU admission. We combined CDK1, the hub gene of upregulated DEGs, and CX3CR1 and IL1b to compute expression ratios. The CDK1/CX3CR1 ratio had the best performance to predict all-cause ICU mortality, with an area under the ROC curve (AUROC) of 0.77 (95% confidence interval [CI] 0.88-0.66) at day 1 and of 0.82 (95% CI 0.91-0.72) at days 2-3 after ICU admission. This performance was better than that of each individual mRNA biomarker. In the external validation cohort, the predictive performance of the CDK1/CX3CR1 ratio, measured using RT-qPCR, was similar to that of lactate when measure at day 1, and higher when measured at days 2-3. Combining lactate levels and the CDK1/CX3CR1 ratio, we identify 3 groups of patients with an increasing risk of ICU-mortality, ranging from 9 to 60% with an intermediate-risk group mortality rate of 28%. With stable predictive performance over the first 3 days following ICU admission, the CDK1/CX3CR1 ratio identifies three groups of septic patients with increasing ICU mortality risk. In combination with lactate, this novel biomarker strategy may be useful for sepsis patient stratification for personalized medicine trials and ICU management.

Association between stress hyperglycemia ratio and mortality in patients with heart failure complicated by sepsis

Individuals afflicted with heart failure complicated by sepsis often experience a surge in blood glucose levels, a phenomenon known as stress hyperglycemia. However, the correlation between this condition and overall mortality remains unclear. 869 individuals with heart failure complicated by sepsis were identified from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and categorized into five cohorts based on their stress hyperglycemia ratio (SHR). The primary endpoints evaluated were mortality within the intensive care unit (ICU), all-cause mortality within 28 days, and all-cause mortality during hospitalization. Cox proportional hazards regression and restricted cubic spline analyses were employed to unravel the association between SHR and mortality. The ICU mortality, in-hospital mortality, and 28-day all-cause mortality were 10.01%, 13.69%, and 16.46%, respectively. Multivariable Cox proportional hazards regression analysis revealed a significant association between elevated SHR and all-cause mortality. After adjusting for confounding variables, elevated SHR was significantly associated with increased risk of ICU mortality (hazard ratio [HR] = 1.67; 95% confidence interval [CI], 1.03–2.70)), in-hospital mortality (HR = 1.53; 95% CI, 1.00-2.33)), and 28-day all-cause mortality (HR = 1.49; 95% CI, 1.02–2.17)). Restricted cubic spline analysis demonstrated a significant U-shaped relationship between SHR and the risk of all-cause mortality. This study revealed that stress hyperglycemia ratio is an independent prognostic factor in patients with heart failure complicated by sepsis. Notably, both very high and very low SHR values were associated with increased mortality risk.

Vitamin D supplementation may be beneficial in improving the prognosis of patients with sepsis-associated acute kidney injury in the intensive care unit: a retrospective study.

Vitamin D, an essential fat-soluble micronutrient, exerts diverse physiological effects including the regulation of calcium ion homeostasis, modulation of immune response, and enhancement of resistance against infectious pathogens. Empirical investigations have elucidated an association between inadequate levels of vitamin D and adverse clinical outcomes in critically ill cohorts, with a noteworthy prevalence of vitamin D deficiency observed among patients afflicted with acute kidney injury (AKI). In the context of this retrospective inquiry, our aim was to assess the potential correlation between vitamin D supplementation administered during admission to the intensive care unit (ICU) and the improvement of outcomes specifically in cases of severe AKI. This study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV), a repository of ICU patient records from Beth Israel Deaconess Medical Center (BIDMC) in the United States. We focused on patients diagnosed with epsis-associated acute kidney injury (SA-AKI), dividing them into those who received vitamin D supplementation during their ICU admission and those who did not. Our primary analysis evaluated in-hospital mortality using various statistical methods, such as Kaplan-Meier survival curves, Cox proportional hazards regression models, and subgroup analyses. To enhance the robustness of our findings, we used propensity score matching (PSM) to reduce potential biases. Secondary outcomes included 28-day, 90-day mortality rates and norepinephrine-free days at 28 days. In this investigation, a cohort of 11,896 individuals diagnosed with SA-AKI was studied. Among them, 2,724 patients received vitamin D supplementation (the vitamin D group) while 9,172 did not (the no-vitamin D group). Kaplan-Meier survival analysis indicated a significant difference in survival probabilities between the two cohorts. Upon adjusting for potential confounders using Cox regression modeling, a notably decreased risk of hospitalization and ICU mortality was observed in the vitamin D group compared to the no-vitamin D group, with an adjusted risk ratio for in-hospital mortality of 0.56 (95% CI: 0.5-0.63). These findings were consistent following PSM and subsequent adjustments for propensity score, pairwise algorithm (PA), and overlapping weights (OW) analyses, yielding hazard ratios ranging from 0.53 to 0.59, all with p-values <0.001. Notably, E-value analyses underscored the robustness of these results against potential unmeasured confounders. This study suggests that vitamin D supplementation may be associated with a reduced in-hospital mortality rate among SA-AKI patients in the ICU. Furthermore, the 28-day, 90-day mortality rates and norepinephrine days were significantly reduced in the group receiving vitamin D supplementation.

Predictive risk models for COVID-19 patients using the multi-thresholding meta-algorithm

This study aims to develop a Machine Learning model to assess the risks faced by COVID-19 patients in a hospital setting, focusing specifically on predicting the complications leading to Intensive Care Unit (ICU) admission or mortality, which are minority classes compared to the majority class of discharged patients. We operate within a multiclass framework comprising three distinct classes, and address the challenge of dataset imbalance, a common source of model bias. To effectively manage this, we introduce the Multi-Thresholding meta-algorithm (MTh), an innovative output-level methodology that extends traditional thresholding from binary to multiclass classification. This methodology dynamically adjusts class probabilities using misclassification costs, making it highly effective in imbalanced datasets. Our approach is further enhanced by integrating the simplicity, transparency, and effectiveness of Bayesian networks to create a robust predictive model. Using patient admission data, the model accurately identifies key risk and protective factors for COVID-19 outcomes. Our findings indicate that certain patient characteristics, such as high Charlson Index and pre-existing conditions, significantly influence the risk of ICU admission and mortality. Moreover, we introduce an explanatory model that elucidates the interrelationships among these factors, demonstrating the influence of therapeutic limits on the overall risk assessment of COVID-19 patients. Overall, our research provides a significant contribution to the field of Machine Learning by offering a novel solution for multiclass classification in the context of imbalanced datasets. This model not only enhances predictive accuracy but also supports critical decision-making processes in healthcare, potentially improving patient outcomes and optimizing clinical resource allocation.

A retrospective study utilized MIMIC-IV database to explore the potential association between triglyceride-glucose index and mortality in critically ill patients with sepsis

Triglyceride-glucose (TyG) index has emerged as a novel biomarker for detecting insulin resistance (IR) and has been proven to be associated with various diseases. However, its correlation with the prognosis of severe sepsis remains unraveled. This retrospective cohort study utilized patient records from the Medical Information Mart for Intensive Care (MIMIC-IV, version 2.2) to examine the outcomes of patients with sepsis. The primary outcomes were hospital mortality and intensive care unit (ICU) mortality. The correlation between the TyG index and outcomes was evaluated through the Kaplan-Meier method, the Log-rank test, and univariate and multivariate Cox regression analyses. Additionally, restricted cubic spline (RCS) regression analysis was employed to delve into the nonlinear relationship between baseline TyG index and outcomes, with trend significance assessed through quartile levels. Subgroup analyses were conducted to evaluate the consistency of the TyG index’s prognostic value across various influencing factors. The study included 1,742 patients with sepsis requiring intensive care. The in-hospital mortality rate was 19.75% (344/1,742), and the ICU mortality rate was 14.75% (257/1,742). Cox regression analysis revealed that, in comparison to the first quartile (Q1), patients in the fourth quartile (Q4) had a 63% higher risk of in-hospital mortality (HR 1.63 [95% CI 1.22 to 2.18], P < 0.01) and a 79% higher risk of ICU mortality (HR 1.79 [95% CI 1.28 to 2.51], P < 0.001). Model 3 showed that ICU mortality risks for Q4, Q3, and Q2 were 240%, 75%, and 33% higher, respectively (HR 3.40 [95% CI 2.24 to 5.16], P < 0.001; HR 1.75 [95% CI 1.16 to 2.63], P = 0.007; HR 1.33 [95% CI 1.20 to 1.53], P < 0.001). RCS regression analysis identified a nonlinear association between the TyG index and mortality (overall P < 0.001; P for nonlinearity < 0.001, with an inflection point at 8.9). Subgroup analysis showed that the effect size and direction were consistent across different subgroups, suggesting the stability of the results. This study demonstrates that a higher TyG index is significantly associated with increased in-hospital and ICU mortality risk in critically ill sepsis patients, with evidence of non-linear correlation. Therefore, the TyG index helps identify the mortality prognosis of sepsis patients in the ICU.

Ability of the SMART-COP score to predict the need for intensive care unit admission and mortality in older patients with non-ventilator-associated hospital-acquired pneumonia: A retrospective observational study.

To evaluate the ability of SMART-COP (systolic blood pressure, multilobar infiltrates, albumin, respiratory rate, tachycardia, confusion, oxygen and pH) score to predict the need for intensive care unit (ICU) admission and mortality among patients with non-ventilator-associated hospital-acquired pneumonia (NV-HAP) and to compare ICU-hospitalized patients with those followed-up in the clinic, as well as the patients who survived with those who died in the ICU, in terms of clinical and laboratory parameters. A total of 203 patients (aged > 65 years) who were diagnosed with NV-HAP while staying in the geriatric clinic were enrolled in this retrospective observational study. Patient information was retrieved from hospital files. In a total of 203 patients with NV-HAP, the rate of ICU admission was 77.3% and the rate of mortality was 40.9%. The SMART-COP score was significantly higher in those admitted to the ICU and those died in the ICU (ICU nonsurvivors). The rate of ICU mortality was 52.9%. The SMART-COP score had significantly poor to moderate ability to predict the need for ICU admission (area under the curve [AUC] = 0.583) and both in-hospital mortality (AUC = 0.633) and ICU mortality (AUC = 0.617) with low sensitivity. The regression analysis revealed that a one-unit increase in SMART-COP score resulted in a 1.2-fold increase in both the hospital and ICU mortality (P < 0.05 for both) and 1.1-fold increase in ICU admission (P = 0.154). The SMART-COP score has poor to moderate ability to predict the need for ICU admission, in-hospital mortality and ICU mortality, and a one-unit increase in the SMART-COP score significantly increases the risk of both hospital and ICU mortality. Geriatr Gerontol Int 2024; 24: 1165-1172.

Elevated Triglyceride-Glucose (TyG) Index Predicts Poor Clinical Outcomes in Critically Ill AECOPD Patients: A Retrospective Study.

The triglyceride-glucose (TyG) index is a surrogate biomarker of insulin resistance which has been widely used in intensive care unit (ICU) to predict prognosis. However, its role in critically ill acute exacerbation of COPD (AECOPD) patients remains largely unknown. A total of 645 AECOPD patients were induced in this retrospective cohort study, which extracted data from the eICU Collaborative Research Database (eICU-CRD). The TyG index was calculated as Ln (fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2). The primary endpoint includes in-hospital mortality and ICU mortality. The secondary endpoint was sepsis, acute kidney injury (AKI), and acute respiratory failure (ARF). Multivariable Cox regression analysis revealed that the TyG index was independently associated with an increased risk of in-hospital mortality (hazard ratio, HR: 1.45, 95% CI: 1.04-2.01, P = 0.028) and ICU mortality (HR: 2.13, 95% CI: 1.28-3.54, P = 0.004). Moreover, the TyG index was independently associated with an increased risk of sepsis (odds ratio, OR: 1.54, 95% CI: 1.24-1.93, P < 0.001), AKI (OR: 1.57, 95% CI: 1.26-2.02, P < 0.001) and ARF (OR: 1.50, 95% CI: 1.20-1.87, P < 0.001). Kaplan-Meier survival analysis revealed that higher TyG indexes were also related to increased in-hospital mortality and ICU mortality. In addition, the restricted cubic splines regression model demonstrated that the in-hospital mortality and ICU mortality increased linearly with increasing TyG index (P for non-linearity = 0.897, P for non-linearity = 0.897, respectively). Elevated TyG index was independently associated with an increased risk of poor clinical outcomes in critically ill AECOPD patients. A prospective study to define TyG as a biomarker for prognosis prediction in critically ill AECOPD patients is warranted.

Outcomes of Patients with End-Stage Renal Disease Hospitalized with COVID-19 in Ahvaz Razi Hospital from February 2020 to May 2021

Background: End-stage renal disease patients on maintenance hemodialysis (ESRD-HD) are at very high risk for COVID-19 infections due to their older age and comorbidities such as diabetes and hypertension. Objectives: This study aimed to investigate the outcomes of COVID-19 in ESRD-HD patients. Methods: This was a retrospective study conducted on ESRD-HD patients aged 18 years and older who were referred to Razi Hospitals in Ahvaz from February 2020 to May 2021 for hemodialysis and diagnosed with COVID-19. Patient information was extracted retrospectively from their medical records. Results: A total of 180 patients were examined. The average age of the patients was 61.5 years, and 118 (65.6%) were men. The most common underlying condition was hypertension (81.1%). The most prevalent clinical symptom was shortness of breath (70.6%), followed by cough (47.8%). Seventy-five patients (41.66%) were admitted to the intensive care unit (ICU), with an average stay of 5 days. Hypertension and ischemic heart disease were significantly more common among patients admitted to the ICU (P = 0.008 and 0.015, respectively). In-hospital mortality was 32.8%. Advanced age, fever, shortness of breath, cough, and the need for a ventilator were significant predictors of mortality in hospitalized ESRD patients with COVID-19 (P = 0.016, 0.033, 0.001, 0.012, and 0.011, respectively). Conclusions: Our study demonstrated that ESRD-HD patients with COVID-19 are at high risk for ICU admission and mortality. Advanced age and clinical symptoms such as fever, shortness of breath, cough, and the need for a ventilator significantly predict in-hospital mortality in these patients.

Effects of dexmedetomidine versus propofol on outcomes in critically ill patients with different sedation depths: a propensity score-weighted cohort study

ObjectiveWe explored the effects of dexmedetomidine (DEX) versus propofol on outcomes in critically ill patients and to assess whether these effects are dissimilar under different sedation depths. MethodsA stabilized inverse probability of treatment weighting cohort study was conducted using data from the Medical Information Mart for Intensive Care IV database from 2008 to 2019. Adult intensive care unit (ICU) patients who were administered DEX or propofol as the primary sedative were identified. Various statistical methods were used to evaluate the effects of DEX versus propofol on outcomes. ResultsData on 107 and 2318 patients in DEX and propofol groups, respectively, were analyzed. Compared to the propofol group, the DEX group exhibited longer ventilator-free days on day 28 and a shorter ICU stay. Conversely, it showed null associations of DEX with the risk of 90-day ICU mortality, the odds of persistent organ dysfunction on day 14 and acute kidney injury, and the duration of vasopressor-free days on day 28. Subgroup analyses revealed that DEX positively impacted persistent organ dysfunction on day 14, ventilator-free days on day 28, and ICU stay in the subgroup with a Richmond Agitation Sedation Scale (RASS) score of ≥−2. However, DEX negatively impacted 90-day ICU mortality, persistent organ dysfunction on day 14, and ventilator-free days on day 28 in the subgroup with a RASS score of <−2. ConclusionOur results indicated that, compared with propofol, DEX had beneficial and adverse impacts on certain ICU outcomes in critically ill patients, and these impacts appeared to depend on sedation depths.

Association between the triglyceride-glucose index and mortality in critically ill patients: A meta-analysis.

To further identify the association of the triglyceride-glucose (TyG) index with the risk of mortality among critically ill patients admitted to the intensive care unit (ICU). The PubMed, Web of Science, and EMBASE databases were searched for relevant studies up to February 2, 2024. The primary outcomes were in-hospital mortality and ICU mortality. The secondary outcomes were 30-day mortality, 90-day mortality, and 1-year mortality. The hazard ratios (HRs) with 95% confidence intervals (CIs) were combined to evaluate the associations between the TyG index and the above endpoints. All the statistical analyses were performed with STATA 15.0 software. Ten studies involving 22,694 patients were included. The pooled results demonstrated that an elevated TyG index indicated an increased risk of in-hospital mortality (HR = 1.76, 95% CI: 1.41-2.18, P < .001), ICU mortality (HR = 1.52, 95% CI: 1.33-1.74, P < .001), 30-day mortality (HR = 1.50, 95% CI: 1.02-2.19, P = .037), 90-day mortality (HR = 1.42, 95% CI: 1.01-2.00, P = .043), and 1-year mortality (HR = 1.19, 95% CI: 1.11-1.28, P < .001). Subgroup analysis for in-hospital mortality and ICU mortality based on sex, age, body mass index and hypertension showed similar results. However, subgroup analysis stratified by diabetes mellitus (DM) revealed that the associations of the TyG index with in-hospital mortality (HR = 2.21, 95% CI: 1.30-3.78, P = .004) and ICU mortality (HR = 1.93, 95% CI: 0.95-3.94, P = .070) were observed only among patients without DM. The TyG index was significantly associated with mortality among critically ill patients without DM, and an elevated TyG index predicted an increased risk of mortality.

Role of Inflammatory Markers in Severity, ICU Admission, and Mortality in COVID-19: A Systematic Review and Meta-analysis of 79,934 Patients

Introduction Despite extensive investigations into the roles of inflammatory biomarkers in the prognosis of COVID-19 through systematic reviews and meta-analyses, they are limited by small sample sizes and focus on a specific marker. This meta-analysis investigated the role of 11 inflammatory biomarkers in severity, intensive care unit (ICU) admission, and mortality among COVID-19 patients. Methods Studies up to October 25, 2023, were identified through a search of Google Scholar, limited to human studies published in English. Inclusion criteria required confirmed COVID-19 cases diagnosed via reliable laboratory methods, original articles from eligible journals, proper grouping of severity status, ICU admission, or mortality outcomes, and presentation of continuous data in mean and standard deviation, median with range, or interquartile range. Results A total of 241 studies, comprising 79,934 cases of COVID-19, were included in this study. Albumin levels significantly declined in severe, ICU, and dead cases compared to mild, moderate, non-ICU, and survived cases (p&lt;0.001). C-reactive protein (CRP), D-dimer, erythrocyte sedimentation rate (ESR), ferritin, fibrinogen, Interleukin-6 (IL-6), lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR), procalcitonin, and white blood cell (WBC) were all significantly (p&lt;0.001) increased and correlated with the severity of COVID-19. CRP, D-dimer, ferritin, fibrinogen, IL-6, LDH, NLR, procalcitonin, and WBC were all significantly (p&lt;0.05) elevated and correlated with the risk of ICU admission (except fibrinogen) and mortality in COVID-19 in both fixed and random effects. Conclusion Inflammatory biomarkers like albumin, CRP, D-dimer, ferritin, IL-6, LDH, NLR, procalcitonin, and WBC all significantly impact severity status, ICU admission, and mortality in COVID-19.

Association between hyperglycemia at ICU admission and postoperative acute kidney injury in patients undergoing cardiac surgery: Analysis of the MIMIC-IV database

BackgroundThis study aimed to explore the correlation between hyperglycemia at intensive care unit (ICU) admission and the incidence of acute kidney injury (AKI) in patients after cardiac surgery. MethodsWe conducted a retrospective cohort study, in which clinical data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Adults (≥18 years) in the database who were admitted to the cardiovascular intensive care unit after cardiac surgery were enrolled. The primary outcome was the incidence of AKI within 7 days following ICU admission. Secondary outcomes included ICU mortality, hospital mortality, ICU length of stay, and the 28-day and 90-day mortality. Multivariable Cox regression analysis was used to assess the association between ICU-admission hyperglycemia and AKI incidence within 7 days of ICU admission. Different adjustment strategies were used to adjust for potential confounders. Patients were divided into three groups according to their highest blood glucose levels recorded within 24 h of ICU admission: no hyperglycemia (<140 mg/dL), mild hyperglycemia (140–200 mg/dL), and severe hyperglycemia (≥200 mg/dL). ResultsOf the 6905 included patients, 2201 (31.9%) were female, and the median (IQR) age was 68.2 (60.1–75.9) years. In all, 1836 (26.6%) patients had severe hyperglycemia. The incidence of AKI within 7 days of ICU admission, ICU mortality, and hospital mortality was significantly higher in patients with severe admission hyperglycemia than those with mild hyperglycemia or no hyperglycemia (80.3% vs. 73.6% and 61.2%, respectively; 2.8% vs. 0.9% and 1.9%, respectively; and 3.4% vs. 1.2% and 2.5%, respectively; all P <0.001). Severe hyperglycemia was a risk factor for 7-day AKI (Model 1: hazard ratio [HR]=1.4809, 95% confidence interval [CI]: 1.3126 to 1.6707; Model 2: HR=1.1639, 95% CI: 1.0176 to 1.3313; Model 3: HR=1.2014, 95% CI: 1.0490 to 1.3760; all P <0.050). Patients with normal glucose levels (glucose levels <140 mg/dL) had a higher 28-day mortality rate than those with severe hyperglycemia (glucose levels ≥200 mg/dL) (4.0% vs. 3.8%, P <0.001). ConclusionsIn post-cardiac surgery patients, severe hyperglycemia within 24 h of ICU admission increases the risk of 7-day AKI, ICU mortality, and hospital mortality. Clinicians should be extra cautious regarding AKI among patients with hyperglycemia at ICU admission after cardiac surgery.

The role of plant-based dietary patterns in reducing COVID-19 risk and/or severity in adults: A systematic review and meta-analysis of observational studies

Background & AimsPlant-based dietary patterns (PBDs) might protect against COVID-19 risk and reduce severity of infection. This systematic review with meta-analysis aimed to examine the association between PBDs and risk of COVID-19 infection, hospitalization, intensive care unit (ICU) admission, and/or mortality, in adults. MethodsPubmed, Embase, CINAHL and Web of Science were searched for observational studies, published in English up to 3rd April 2023, comparing the highest with the lowest adherence to a specific PBD. Data were screened, extracted, and risk of bias assessed using the Newcastle-Ottawa Quality Assessment Scale, by independent reviewers. ResultsSeven studies (one cross-sectional, three case-control, and three prospective cohort), reporting on 649,315 participants, were eligible. Across them, there were 8,512 events of COVID-19 infection (six studies), and 206 events of COVID-19 hospitalization (four studies), in addition to one study reporting on a composite hospitalization outcome (740 events). The pooled analysis showed that PBDs are associated with a 59% (odds ratio (OR)=0.41, 95% confidence intervals (CI) 0.23-0.59; two studies) and 18% (OR=0.82, 95% CI 0.78-0.85; three studies) reduction in COVID-19 infection risk in case-control and cohort studies, respectively. The pooled analysis of one case-control and two cohort studies showed an inverse association between high adherence to a PBD and risk of COVID-19 hospitalization (OR=0.38, 95% CI 0.04-0.72). ConclusionFindings suggest a protective role of PBDs against the risk of COVID-19 infection and severity. More studies are needed to establish the association between PBDs and risk of ICU admission and mortality due to COVID-19.

Impact of stress hyperglycemia ratio on mortality in patients with cardiac arrest: insight from American MIMIC-IV database.

Stress hyperglycemia ratio (SHR) has shown a predominant correlation with transient adverse events in critically ill patients. However, there remains a gap in comprehensive research regarding the association between SHR and mortality among patients experiencing cardiac arrest and admitted to the intensive care unit (ICU). A total of 535 patients with their initial ICU admission suffered cardiac arrest, according to the American Medical Information Mart for Intensive Care (MIMIC)-IV database. Patients were stratified into four categories based on quantiles of SHR. Multivariable Cox regression models were used to evaluate the association SHR and mortality. The association between SHR and mortality was assessed using multivariable Cox regression models. Subgroup analyses were conducted to determine whether SHR influenced ICU, 1-year, and long-term all-cause mortality in subgroups stratified according to diabetes status. Patients with higher SHR, when compared to the reference quartile 1 group, exhibited a greater risk of ICU mortality (adjusted hazard ratio [aHR] = 3.029; 95% CI: 1.802-5.090), 1-year mortality (aHR = 3.057; 95% CI: 1.885-4.958), and long-term mortality (aHR = 3.183; 95% CI: 2.020-5.015). This association was particularly noteworthy among patients without diabetes, as indicated by subgroup analysis. Elevated SHR was notably associated with heightened risks of ICU, 1-year, and long-term all-cause mortality among cardiac arrest patients. These findings underscore the importance of considering SHR as a potential prognostic factor in the critical care management of cardiac arrest patients, warranting further investigation and clinical attention.

Revisiting the potential value of vital signs in the real-time prediction of mortality risk in intensive care unit patients

BackgroundPredicting patient mortality risk facilitates early intervention in intensive care unit (ICU) patients at greater risk of disease progression. This study applies machine learning methods to multidimensional clinical data to dynamically predict mortality risk in ICU patients.MethodsA total of 33,798 patients in the MIMIC-III database were collected. An integrated model NIMRF (Network Integrating Memory Module and Random Forest) based on multidimensional variables such as vital sign variables and laboratory variables was developed to predict the risk of death for ICU patients in four non overlapping time windows of 0–1 h, 1–3 h, 3–6 h, and 6–12 h. Mortality risk in four nonoverlapping time windows of 12 h was externally validated on data from 889 patients in the respiratory critical care unit of the Chinese PLA General Hospital and compared with LSTM, random forest and time-dependent cox regression model (survival analysis) methods. We also interpret the developed model to obtain important factors for predicting mortality risk across time windows. The code can be found in https://github.com/wyuexiao/NIMRF.ResultsThe NIMRF model developed in this study could predict the risk of death in four nonoverlapping time windows (0–1 h, 1–3 h, 3–6 h, 6–12 h) after any time point in ICU patients, and in internal data validation, it is suggested that the model is more accurate than LSTM, random forest prediction and time-dependent cox regression model (area under receiver operating characteristic curve, or AUC, 0–1 h: 0.8015 [95% CI 0.7725–0.8304] vs. 0.7144 [95%] CI 0.6824–0.7464] vs. 0.7606 [95% CI 0.7300–0.7913] vs 0.3867 [95% CI 0.3573–0.4161]; 1–3 h: 0.7100 [95% CI 0.6777–0.7423] vs. 0.6389 [95% CI 0.6055–0.6723] vs. 0.6992 [95% CI 0.6667–0.7318] vs 0.3854 [95% CI 0.3559–0.4150]; 3–6 h: 0.6760 [95% CI 0.6425–0.7097] vs. 0.5964 [95% CI 0.5622–0.6306] vs. 0.6760 [95% CI 0.6427–0.7099] vs 0.3967 [95% CI 0.3662–0.4271]; 6–12 h: 0.6380 [0.6031–0.6729] vs. 0.6032 [0.5705–0.6406] vs. 0.6055 [0.5682–0.6383] vs 0.4023 [95% CI 0.3709–0.4337]). External validation was performed on the data of patients in the respiratory critical care unit of the Chinese PLA General Hospital. Compared with LSTM, random forest and time-dependent cox regression model, the NIMRF model was still the best, with an AUC of 0.9366 [95% CI 0.9157–0.9575 for predicting death risk in 0–1 h]. The corresponding AUCs of LSTM, random forest and time-dependent cox regression model were 0.9263 [95% CI 0.9039–0.9486], 0.7437 [95% CI 0.7083–0.7791] and 0.2447 [95% CI 0.2202–0.2692], respectively. Interpretation of the model revealed that vital signs (systolic blood pressure, heart rate, diastolic blood pressure, respiratory rate, and body temperature) were highly correlated with events of death.ConclusionUsing the NIMRF model can integrate ICU multidimensional variable data, especially vital sign variable data, to accurately predict the death events of ICU patients. These predictions can assist clinicians in choosing more timely and precise treatment methods and interventions and, more importantly, can reduce invasive procedures and save medical costs.

Multidrug-resistant pathogens and ventilator-associated pneumonia in critically ill COVID-19 and non-COVID-19 patients: a prospective observational monocentric comparative study

BackgroundThe COVID-19 pandemic has increased the incidence of ventilator-associated pneumonia (VAP) among critically ill patients. However, a comparison of VAP incidence in COVID-19 and non-COVID-19 cohorts, particularly in a context with a high prevalence of multidrug-resistant (MDR) organisms, is lacking.Material and MethodsWe conducted a single-center, mixed prospective and retrospective cohort study comparing COVID-19 patients admitted to the intensive care unit (ICU) of the “Città della Salute e della Scienza” University Hospital in Turin, Italy, between March 2020 and December 2021 (COVID-19 group), with a historical cohort of ICU patients admitted between June 2016 and March 2018 (NON-COVID-19 group). The primary objective was to define the incidence of VAP in both cohorts. Secondary objectives were to evaluate the microbial cause, resistance patters, risk factors and impact on 28 days, ICU and in-hospital mortality, duration of ICU stay, and duration of hospitalization).ResultsWe found a significantly higher incidence of VAP (51.9% - n = 125) among the 241 COVID-19 patients compared to that observed (31.2% - n = 78) among the 252 NON-COVID-19 patients. The median SOFA score was significantly lower in the COVID-19 group (9, Interquartile range, IQR: 7–11 vs. 10, IQR: 8–13, p < 0.001). The COVID-19 group had a higher prevalence of Gram-positive bacteria-related VAP (30% vs. 9%, p < 0.001), but no significant difference was observed in the prevalence of difficult-to-treat (DTR) or MDR bacteria. ICU and in-hospital mortality in the COVID-19 and NON-COVID-19 groups were 71% and 74%, vs. 33% and 43%, respectively. The presence of COVID-19 was significantly associated with an increased risk of 28-day all-cause hospital mortality (Hazard ratio, HR: 7.95, 95% Confidence Intervals, 95% CI: 3.10-20.36, p < 0.001). Tracheostomy and a shorter duration of mechanical ventilation were protective against 28-day mortality, while dialysis and a high SOFA score were associated with a higher risk of 28-day mortality.ConclusionCOVID-19 patients with VAP appear to have a significantly higher ICU and in-hospital mortality risk regardless of the presence of MDR and DTR pathogens. Tracheostomy and a shorter duration of mechanical ventilation appear to be associated with better outcomes.

Between blood glucose and mortality in critically ill patients: Retrospective analysis of the MIMIC-IV database.

Mean blood glucose (MBG) level is associated with mortality among critically ill patients. We undertook a cohort study to investigate the relationship between MBG and mortality in critically ill patients. Critically ill patients were enrolled from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. MBG was calculated to represent the overall glycemic status during intensive care unit (ICU) hospitalization, and a multivariate logistic regression determined the relationship between MBG and ICU mortality in different subgroups of critically ill patients. A total of 8,973 patients were included in the study, 1,244 of whom died within 28 days, including 5,402 men and 3,571 women. Multivariate adjusted restricted cubic spline analyses suggested that the relationship between MBG and ICU mortality was a "J" shape. Logistic regression showed 28 day mortality in group 3 (glucose ≥10 mmol/L): the adjusted odds ratio was 2.06 (95% confidence interval 1.65-2.57). The results of subgroup analysis showed that hyperglycemia had a more significant impact on ICU mortality in patients without diabetes, hypoglycemia and liver disease, and the ICU mortality risk of non-diabetes patients was always higher than that of diabetes patients with the same hyperglycemia level. Current evidence suggested a J-shaped relationship between MBG and mortality in critically ill patients.

A comparison of invasive arterial blood pressure measurement with oscillometric non-invasive blood pressure measurement in patients with sepsis.

This study aimed to compare non-invasive oscillometric blood pressure (NIBP) measurement with invasive arterial blood pressure (IBP) measurement in patients with sepsis. We conducted a retrospective study to evaluate the agreement between IBP and NIBP using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Paired blood pressure measurements of mean arterial pressure (MAP), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were compared using Bland-Altman analysis and paired Student's t test. We also focus on the effect of norepinephrine (NE) on the agreement between the two methods and the association between blood pressure and mortality during intensive care unit (ICU) stay. A total of 96,673 paired blood pressure measurements from 6060 unique patients were analyzed in the study. In Bland-Altman analysis, the bias (± SD, 95% limits of agreement) was 6.21mmHg (± 12.05mmHg, -17.41 to 29.83mmHg) for MAP, 0.39mmHg (± 19.25mmHg, -37.34 to 38.12mmHg) for SBP, and 0.80mmHg (± 12.92mmHg, -24.52 to 26.12mmHg) for DBP between the two techniques. Similarly, large limits of agreement were shown in different groups of NE doses. NE doses significantly affected the agreement between IBP and NIBP. SBP between the two methods gave an inconsistent assessment of patients' risk of ICU mortality. IBP and NIBP were not interchangeable in septic patients. Clinicians should be aware that non-invasive MAP was clinically and significantly underestimated invasive MAP.

Effect of propofol versus midazolam on short-term outcomes in patients with sepsis-associated acute kidney injury.

Propofol and midazolam are commonly used sedative drugs in mechanically ventilated patients in the Intensive Care Unit (ICU). However, there is still a lack of relevant studies exploring the influence of midazolam and propofol on the prognosis of patients with Sepsis-associated Acute Kidney Injury (S-AKI). A statistical analysis was conducted on 3,745 patients with S-AKI in the Medical Information Mart for Intensive Care IV database. The patients' baseline characteristics were grouped based on the use of either propofol or midazolam as sedatives. Cox proportional hazards models, logistic regression models, and subgroup analyses were used to compare the effects of propofol and midazolam on the short-term prognosis of S-AKI patients, including 30-day mortality, ICU mortality, and duration of mechanical ventilation. In the statistical analysis, a total of 3,745 patients were included, with 649 patients using midazolam and 3,096 patients using propofol. In terms of the 30-day mortality, compared to patients using midazolam, S-AKI patients using propofol had a lower ICU mortality (hazard ratio = 0.62, 95% confidence interval: 0.52-0.74, p < 0.001), lower 30-day mortality (hazard ratio = 0.56, 95% confidence interval: 0.47-0.67, p < 0.001), and shorter mechanical ventilation time (odds ratio = 0.72, 95% confidence interval: 0.59-0.88, p < 0.001). Kaplan-Meier curves showed lower survival probabilities in the midazolam group (p < 0.001). Subgroup analyses showed that propofol was strongly protective of short-term prognosis in older, male, smaller SOFA score CCI score, no heart failure, and comorbid chronic kidney disease patients with S-AKI. Compared to midazolam, propofol was considered a protective factor for short-term mortality risk and ICU mortality risk in S-AKI patients. Additionally, S-AKI patients using propofol had a lower risk of requiring prolonged mechanical ventilation. Overall, propofol may be more beneficial for the short-term prognosis of S-AKI patients compared to midazolam.

Pulmonary embolism and risk factors of ICU admission: systematic review

To forecast mortality and identify adult patients who required admission to an intensive care unit (ICU), we compared the efficacy of the most widely used early warning scores. The present review assessed the pulmonary embolism and risk factors of ICU admission; systematic review. A search of the literature was conducted in the bibliographic databases PubMed and EMBASE between 2009 and 2022. Each reviewer verified independently that each possibly relevant title and abstract qualified. There were nine studies that were included in the review. National early warning score (NEWS) was the best indicator of ICU admission; however, the modified early warning score (MEWS) performed better in sepsis patients. According to emergency department (ED) Mortality, the NEWS was the most accurate score for predicting mortality in the entire ED population, and the mortality in emergency department sepsis score was the most accurate measure for patients with sepsis. For all endpoints, NEWS and MEWS had good outcomes in the ICU and ED. Numerous investigations should be conducted utilizing various prognostic scores on ED and ICU patients. Anemia in patients with venous thrombosis was associated with a higher risk of ICU admission and mortality.