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Aim: Higher nitric oxide (NO) levels correlate with adverse sepsis outcomes but are challenging to measure. Methemoglobin (MetHb), a measurable product of NO, has not been utilized for risk stratification.Methodology: All patients with sepsis admitted to the intensive care unit (ICU) that had at least one MetHb measurement within 24 h of ICU admission were retrospectively analyzed. We assessed the epidemiology and associations of MetHb with hospital mortality.Results: Among 7724 patients, 1046 qualified. Those with MetHb ≥1.6% showed significantly higher mortality and fewer days alive outside the hospital by day 28. MetHb levels ≥1.6% independently predicted increased 28-day mortality.Conclusion: Our findings suggest MetHb, easily obtainable from arterial blood gases, can significantly enhance sepsis risk stratification.

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Background: The inflammatory response holds paramount significance in the context of intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates. Biological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) play crucial roles in influencing the systemic inflammatory response following ICH. This study aims to compare the predictive efficacy of NLR, PLR, LMR, SII, and SIRI concerning the risk of mortality in the intensive care unit (ICU) among critically ill patients with ICH. Such a comparison seeks to elucidate their early warning capabilities in the management and treatment of ICH. Methods: Patients with severe ICH requiring admission to the ICU were screened from the Medical Information Marketplace for Intensive Care (MIMIC-IV) database. The outcomes studied included ICU mortality and 30 day ICU hospitalization rates, based on tertiles of the NLR index level. To explore the relationship between the NLR index and clinical outcomes in critically ill patients with ICH, we utilized receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and multivariate logistic regression analysis. Results: A total of 869 patients (51.9% male) were included in the study, with an ICU mortality rate of 22.9% and a 30 day ICU hospitalization rate of 98.4%. Among the five indicators examined, both the ROC curve and DCA indicated that NLR (AUC: 0.660, 95%CI: 0.617-0.703) had the highest predictive ability for ICU mortality. Moreover, this association remained significant even after adjusting for other confounding factors during multivariate analysis (HR: 3.520, 95%CI: 2.039-6.077). Based on the results of the multivariate analysis, incorporating age, albumin, lactic acid, NLR, and GCS score as variables, we developed a nomogram to predict ICU mortality in critically ill patients with ICH. Conclusion: NLR emerges as the most effective predictor of ICU mortality risk among critically ill patients grappling with ICH when compared to the other four indicators. Furthermore, the integration of albumin and lactic acid indicators into the NLR nomogram enhances the ability to promptly identify ICU mortality in individuals facing severe ICH.

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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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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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How to cite this article: Arunachala S, Kumar J. mNUTRIC Score in ICU Mortality Prediction: An Emerging Frontier or Yet Another Transient Trend? Indian J Crit Care Med 2024;28(5):422-423.

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Objective: To investigate the potential prognostic value of mean blood glucose (MBG) in hospital for prognosis of COVID-19 adult patients in the intensive unit care unit (ICU). Methods: A single-site and retrospective study enrolled 107 patients diagnosed as COVID-19 from department of critical care medicine in the Second Xiangya Hospital between October 2022 and June 2023. Demographic information including glucose during ICU hospitalization, comorbidity, clinical data, types of medications and treatment, and clinical outcome were collected. The multivariate logistic and cox regression was used to explore the relationship between blood glucose changes and clinical outcomes of COVID-19 during ICU stay. Results: In total, 107 adult patients confirmed with COVID-19 were included. Multivariate logistic regression results showed an increase in MBG was associated with ICU mortality rate. Compared with normal glucose group (MBG <= 7.8 mmol/L), the risk of ICU mortality, 7-day mortality and 28-day mortality from COVID-19 were significantly increased in high glucose group (MBG >7.8mmol/L). Conclusion: MBG level during ICU hospitalization was strongly correlated to all-cause mortality and co-infection in COVID-19 patients. These findings further emphasize the importance of overall glucose management in severe cases of COVID-19.

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The development of reliable mortality risk stratification models is an active research area in computational healthcare. Mortality risk stratification provides a standard to assist physicians in evaluating a patient's condition or prognosis objectively. Particular interest lies in methods that are transparent to clinical interpretation and that retain predictive power once validated across diverse datasets they were not trained on. This study addresses the challenge of consolidating numerous ICD codes for predictive modeling of ICU mortality, employing a hybrid modeling approach that integrates mechanistic, clinical knowledge with mathematical and machine learning models . A tree-structured network connecting independent modules that carry clinical meaning is implemented for interpretability. Our training strategy utilizes graph-theoretic methods for data analysis, aiming to identify the functions of individual black-box modules within the tree-structured network by harnessing solutions from specific max-cut problems. The trained model is then validated on external datasets from different hospitals, demonstrating successful generalization capabilities, particularly in binary-feature datasets where label assessment involves extrapolation.

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INTRODUCTION: Organophosphorus poisoning (OPP) stands as a significant health concern in numerous regions, especially in developing nations. Despite the rising complexities and case fatalities associated with exposure, the treatment approach has remained unchanged for many years. Based on clinical insights, certain pharmacologic agents have demonstrated utility in enhancing outcomes and reducing complications arising from this type of exposure. OBJECTIVES: The objective of this study is to compare the outcome of N-acetyl cysteine in the treatment of acute organophosphate poisoning cases. In terms of a) its impact on the requirement of atropine, b) Length of hospital stay, and mortality. METHODS: The study was conducted in the intensive care unit (ICU) of the General Hospital Lahore. Thirty patients with a history and clinical presentation indicative of acute organophosphorus poisoning were randomly divided into two groups in a 1:1 ratio. The treatment group received parenteral administration of atropine, pralidoxime, and N-acetylcysteine (NAC) as an adjuvant, and the control group received standard treatment for acute organophosphate (OP) toxicity. RESULT: Throughout the study duration, 30 patients suffering acute organophosphate (OP) toxicity (14 men, 16 women) were examined, with an age mean of (25.83±11.59) years. In the interventional group, only four patients required ICU admission, but in the control group, eight patients were admitted to ICU. The correlation result between the dose of atropine and length of hospital stays was not statistically significant between both study groups (<0.005). Plasma Cholinesterase (PChE) level (KU L-1) and total dose of Pralidoxime (g) were statistically significant in the length of hospital stay. The data was not normally distributed, so the non-parametric tests were applied. The Wilcoxon ranked test showed significant improvement in both the controlled and interventional groups because the p-value was (<0.005). Intergroup comparison analyzed by using the Mann-Whitney U test showed a significant reduction in the severity and other associated symptoms in the interventional group because the p-value was (0.001). CONCLUSION: The outcome demonstrated that the NAC group had a decreased demand for atropine rather than Pralidoxime. In the NAC group, the length of hospital stay and mortality was decreased. The administration of NAC to the present study procedure for acute organophosphate (OP) poisoning is suggested.

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Background: The provision of intensive care services is advancing globally. However, in resource-limited settings, it is lagging far behind and intensive care unit mortality is still higher due to various reasons. This study aimed to assess determinants of mortality among medical patients admitted to the intensive care unit. Methods: A five-year facility-based retrospective Cohort Study was conducted. A total of 546 medical patients admitted to the intensive care unit from March 2017 to February 2022 were included. Document review using a structured questionnaire was implemented to collect data. Data entered into Epi Data were analyzed by STATA and summarized using frequency tables and graphs. Binary and multivariate logistic regression analyses were performed to identify determinants of mortality. Results: The overall mortality was 35.9%. Approximately half of the deaths were attributed to septic shock, congestive heart failure, severe community-acquired pneumonia, and stroke. The most common immediate cause of death was cardio-respiratory arrest. Source of admission, GCS level at admission, duration of ICU stay, treatment with inotropes, septic shock, and retroviral infection status were found to have a statistically significant association with ICU mortality. Conclusion and Recommendations: This study revealed a significantly higher mortality rate among patients admitted to the intensive care unit. Early identification and admission of patients to the intensive care unit are important factors that could decrease mortality. Patient selection is essential since some patients with a high likelihood of mortality might not benefit from intensive care unit admission in an area with high resource limitations.

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BACKGROUND: Group A Streptococcus is responsible for severe and potentially lethal invasive conditions requiring intensive care unit (ICU) admission, such as streptococcal toxic shock-like syndrome (STSS). A rebound of invasive group A streptococcal (iGAS) infection after COVID-19-associated barrier measures has been observed in children. Several intensivists of French adult ICUs have reported similar bedside impressions without objective data. We aimed to compare the incidence of iGAS infection before and after the COVID-19 pandemic, describe iGAS patients' characteristics, and determine ICU mortality associated factors. METHODS: We performed a retrospective multicenter cohort study in 37 French ICUs, including all patients admitted for iGAS infections for two periods: two years before period (October 2018 to March 2019 and October 2019 to March 2020) and a one-year after period (October 2022 to March 2023) COVID-19 pandemic. iGAS infection was defined by Group A Streptococcus isolation from a normally sterile site. iGAS infections were identified using the International Classification of Diseases and confirmed with each center's microbiology laboratory databases. The incidence of iGAS infections was expressed in case rate. RESULTS: Two hundred and twenty-two patients were admitted to ICU for iGAS infections: 73 before and 149 after COVID-19 pandemic. Their case rate during the period before and after COVID-19 pandemic was 205 and 949/100,000 ICU admissions, respectively (p < 0.001), with more frequent STSS after the COVID-19 pandemic (61% vs. 45%, p = 0.015). iGAS patients (n = 222) had a median SOFA score of 8 (5-13), invasive mechanical ventilation and norepinephrine in 61% and 74% of patients. ICU mortality in iGAS patients was 19% (14% before and 22% after COVID-19 pandemic; p = 0.135). In multivariate analysis, invasive mechanical ventilation (OR = 6.08 (1.71-21.60), p = 0.005), STSS (OR = 5.75 (1.71-19.22), p = 0.005), acute kidney injury (OR = 4.85 (1.05-22.42), p = 0.043), immunosuppression (OR = 4.02 (1.03-15.59), p = 0.044), and diabetes (OR = 3.92 (1.42-10.79), p = 0.008) were significantly associated with ICU mortality. CONCLUSION: The incidence of iGAS infections requiring ICU admission increased by 4 to 5 after the COVID-19 pandemic. After the COVID-19 pandemic, the rate of STSS was higher, with no significant increase in ICU mortality rate.

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BACKGROUND: This study investigates the impact of nontuberculous mycobacterial lung disease (NTM-LD) on mortality and mechanical ventilation use in critically ill patients. METHODS: We enrolled patients with NTM-LD or tuberculosis (TB) in intensive care units (ICU) and analysed their association with 30-day mortality and with mechanical ventilator-free survival (VFS) at 30 days after ICU admission. RESULTS: A total of 5996 ICU-admitted patients were included, of which 541 (9.0 %) had TB and 173 (2.9 %) had NTM-LD. The overall 30-day mortality was 22.2 %. The patients with NTM-LD had an adjusted hazard ratio (aHR) of 1.49 (95 % CI, 1.06-2.05), and TB patients had an aHR of 2.33 (95 % CI, 1.68-3.24), compared to ICU patients with negative sputum mycobacterial culture by multivariable Cox proportional hazard (PH) regression. The aHR of age<65 years, obesity, idiopathic pulmonary fibrosis, end-stage kidney disease, active cancer and autoimmune disease and diagnosis of respiratory failure were also significantly positively associated with ICU 30-day mortality. In multivariable Cox PH regression for VFS at 30 days in patients requiring invasive mechanical ventilation, NTM-LD was negatively associated with VFS (aHR 0.71, 95 % CI: 0.56-0.92, p = 0.009), while TB showed no significant association. The diagnosis of respiratory failure itself predicted unfavourable outcome for 30-day mortality and a negative impact on VFS at 30 days. CONCLUSIONS: NTM-LD and TB were not uncommon in ICU and both were correlated with increasing 30-day mortality in ICU patients. NTM-LD was associated with a poorer outcome in terms of VFS at 30 days.

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BACKGROUND: Critical illness and care within the intensive care unit (ICU) leads to profound changes in the composition of the gut microbiome. The impact of such changes on the patients and their subsequent disease course remains uncertain. We hypothesized that specific changes in the gut microbiome would be more harmful than others, leading to increased mortality in critically ill patients. METHODS: This was a prospective cohort study of critically ill adults in the ICU. We obtained rectal swabs from 52 patients and assessed the composition the gut microbiome using 16 S rRNA gene sequencing. We followed patients throughout their ICU course and evaluated their mortality rate at 28 days following admission to the ICU. We used selbal, a machine learning method, to identify the balance of microbial taxa most closely associated with 28-day mortality. RESULTS: We found that a proportional ratio of four taxa could be used to distinguish patients with a higher risk of mortality from patients with a lower risk of mortality (p = .02). We named this binarized ratio our microbiome mortality index (MMI). Patients with a high MMI had a higher 28-day mortality compared to those with a low MMI (hazard ratio, 2.2, 95% confidence interval 1.1-4.3), and remained significant after adjustment for other ICU mortality predictors, including the presence of the acute respiratory distress syndrome (ARDS) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score (hazard ratio, 2.5, 95% confidence interval 1.4-4.7). High mortality was driven by taxa from the Anaerococcus (genus) and Enterobacteriaceae (family), while lower mortality was driven by Parasutterella and Campylobacter (genera). CONCLUSIONS: Dysbiosis in the gut of critically ill patients is an independent risk factor for increased mortality at 28 days after adjustment for clinically significant confounders. Gut dysbiosis may represent a potential therapeutic target for future ICU interventions.

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Objective: The study aimed to evaluate the relationship between serum sodium and mortality in critically ill patients with non-traumatic subarachnoid hemorrhage. Methods: This is a retrospective investigation of critically ill non-traumatic patients with subarachnoid hemorrhage (SAH) utilizing the MIMIC-IV database. We collected the serum sodium levels at admission and determined the all-cause death rates for the ICU and hospital. We employed a multivariate Cox proportional hazard regression model and Kaplan-Meier survival curve analysis to ascertain the relationship between serum sodium and all-cause mortality. In order to evaluate the consistency of correlations, interaction and subgroup analyses were also conducted. Results: A total of 864 patients with non-traumatic SAH were included in this study. All-cause mortality in the ICU and hospital was 32.6% (282/864) and 19.2% (166/864), respectively. Sodium levels at ICU admission showed a statistically significant J-shaped non-linear relationship with ICU and hospital mortality (non-linear P-value < 0.05, total P-value < 0.001) with an inflection point of ~141 mmol/L, suggesting that mortality was higher than normal serum sodium levels in hypernatremic patients. Multivariate analysis after adjusting for potential confounders showed that high serum sodium levels (≥145 mmol/L) were associated with an increased risk of all-cause mortality in the ICU and hospital compared with normal serum sodium levels (135-145 mmol/L), [hazard ratio (HR) = 1.47, 95% CI: 1.07-2.01, P = 0.017] and (HR = 2.26, 95% CI:1.54-3.32, P < 0.001). Similarly, Kaplan-Meier (K-M) survival curves showed lower survival in patients with high serum sodium levels. Stratified analysis further showed that the association between higher serum sodium levels and hospital all-cause mortality was stronger in patients aged < 60 years with a hospital stay of <7 days. Conclusion: High serum sodium levels upon ICU admission are related to higher ICU and hospital all-cause mortality in patients with non-traumatic SAH. A new reference is offered for control strategies to correct serum sodium levels.

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BACKGROUND: Sepsis is one of the leading contributors to global mortality and morbidity, causing multi-organ failure, mainly involving cardiovascular failure, both systolic and diastolic dysfunction, leading to adverse clinical outcomes. There is little clinical data on the correlation with the mortality of patients with type 2 diabetes mellitus (T2DM) with sepsis and septic shock and left ventricular diastolic dysfunction. Our study sought to assess whether the severity of diastolic dysfunction could predict 28-day mortality. METHODOLOGY: The study included T2DM patients admitted to the intensive care unit (ICU) with sepsis and septic shock defined according to the Third International Consensus Definitions for Sepsis and Septic Shock at a tertiary care center in northern India. A total of 132 patients (age = 61.01 ± 13.12 years; 62% male; mean APACHE II (Acute Physiology and Chronic Health Evaluation II) score = 25.74 ± 4.79; Sequential Organ Failure Assessment (SOFA) score = 12.34 ± 3.36) underwent transthoracic echocardiography within two hours of ICU admission till 28 days of admission or till mortality occurred. Clinical variables (APACHE II and SOFA score) and cardiac biomarkers, such as N-terminal pro-B-type natriuretic peptide (NT-pro-BNP), troponin I, and creatine phosphokinase-MB, were measured at the time of admission and after 72 hours to compare with mortality. Diastolic dysfunction was defined according to the American Society of Echocardiography (ASE) 2009 guidelines, classifying subjects into grade 0 (normal), if early diastolic velocity (e') ≥ 8 cm/s; grade 1 (impaired relaxation), if e' < 8 cm/s and early (E) to late (A) ventricular filling velocities (E/A) ratio < 0.8; grade 2 (pseudo normal), if e' < 8 cm/s, E/A = 0.8-1.5, and peak E-wave velocity by the peak e' velocity (E/e') ratio = 9-12; and grade 3 (restrictive), if e' < 8 cm/s, E/A > 2, deceleration time (DT) < 160 ms, and E/e' ≥ 13. RESULTS: Thirty-seven (40.65%) out of 132 patients had diastolic dysfunction on initial echocardiography, while 54 (59.34%) had diastolic dysfunction on at least subsequent echocardiography. Total mortality was 68.93% with the highest mortality (100%) observed among those with grade 3 diastolic dysfunction. The 28-day mortality with diastolic dysfunction in sepsis and septic shock patients showed significant results (p < 0.001), indicating that with a higher E/A ratio or higher grade of diastolic dysfunction with the increase in SOFA score, the early ICU mortality is the highest and have the shortest duration of ICU stay with mean ± SD = 6.2 ± 2.48, as compared to other grades with 100% mortality. Also, the cardiac biomarker NT-pro-BNP was markedly elevated with a mean ± SD value of 503 ± 269.3 pg/ml, indicating early predicted mortality. No correlation was detected between mortality and the mean levels of fasting blood sugar, postprandial blood sugar, and glycosylated hemoglobin. CONCLUSION: Our study concluded that diastolic dysfunction is an important and strongest independent mortality predictor in patients with T2DM with severe sepsis and septic shock, and the higher the grade of diastolic dysfunction, the higher the mortality with the lowest mean ICU stay.

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PURPOSE: This study aimed to construct a mortality model for the risk stratification of intensive care unit (ICU) patients with sepsis by applying a machine learning algorithm. METHODS: Adult patients who were diagnosed with sepsis during admission to ICU were extracted from MIMIC-III, MIMIC-IV, eICU, and Zigong databases. MIMIC-III was used for model development and internal validation. The other three databases were used for external validation. Our proposed model was developed based on the Extreme Gradient Boosting (XGBoost) algorithm. The generalizability, discrimination, and validation of our model were evaluated. The Shapley Additive Explanation values were used to interpret our model and analyze the contribution of individual features. RESULTS: A total of 16,741, 15,532, 22,617, and 1,198 sepsis patients were extracted from the MIMIC-III, MIMIC-IV, eICU, and Zigong databases, respectively. The proposed model had an area under the receiver operating characteristic curve (AUROC) of 0.84 in the internal validation, which outperformed all the traditional scoring systems. In the external validations, the AUROC was 0.87 in the MIMIC-IV database, better than all the traditional scoring systems; the AUROC was 0.83 in the eICU database, higher than the Simplified Acute Physiology Score III and Sequential Organ Failure Assessment (SOFA),equal to 0.83 of the Acute Physiology and Chronic Health Evaluation IV (APACHE-IV), and the AUROC was 0.68 in the Zigong database, higher than those from the systemic inflammatory response syndrome and SOFA. Furthermore, the proposed model showed the best discriminatory and calibrated capabilities and had the best net benefit in each validation. CONCLUSIONS: The proposed algorithm based on XGBoost and SHAP-value feature selection had high performance in predicting the mortality of sepsis patients within 24 h of ICU admission.

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Background: The Coronavirus Disease 2019 (COVID-19) pandemic has highlighted the challenges of the healthcare system in Iraq, which has limited intensive care unit beds, medical personnel, and equipment, contributing to high infection rates and mortality. The main purpose of the study was to describe the clinical characteristics, the length of Intensive Care Unit (ICU) stay, and the mortality outcomes of COVID-19 patients admitted to the ICU during the first wave and two subsequent surges, spanning from September 2020 to October 2021, in addition to identify potential risk factors for ICU mortality. Methods: This retrospective cohort study analyzed data from COVID-19 patients admitted to the COVID-19 ICU at Al-Kindi Ministry of Health hospital in Baghdad, Iraq, between September 2020 and October 2021. Results: The study included 936 COVID-19 patients admitted to the ICU at Al-Kindi Hospital. Results showed a high mortality rate throughout all waves, with 60% of deaths due to respiratory failure. Older age, male gender, pre-existing medical conditions, ICU procedures, and complications were associated with increased odds of ICU mortality. The study also found a decrease in the number of complications and ICU procedures between the first and subsequent waves. There was no significant difference in the length of hospital stay between patients admitted during different waves. Conclusion: Despite improvements in critical care practices, the mortality rate did not significantly decrease during the second and third waves of the pandemic. The study highlights the challenges of high mortality rates among critical COVID-19 patients in low-resource settings and the importance of effective data collection to monitor clinical presentations and identify opportunities for improvement in ICU care.

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Blue-green cytoplasmic neutrophilic inclusion bodies, previously described as "green crystals of death," are a rare but likely underreported finding in critically ill patients. This finding is associated with high mortality, ranging from 31% to 100% in published case studies. These inclusion bodies have been most strongly associated with acute liver injury and lactic acidosis, but they have also been reported in critically ill patients secondary to other etiologies. Here, we report a case of blue-green neutrophilic inclusion bodies in a patient with aspiration pneumonia and severe pneumoperitoneum secondary to bowel perforation. These blue-green neutrophilic inclusion bodies offer high prognostic value for physicians, and their presence should be considered a "critical result," indicating the severity of the patient's illness.

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The aim of this study is to investigate the effectiveness of prolonged versus standard course oseltamivir treatment among critically ill patients with severe influenza. A retrospective study of a prospectively collected database including adults with influenza infection admitted to 184 intensive care units (ICUs) in Spain from 2009 to 2018. Prolonged oseltamivir was defined if patients received the treatment beyond 5 days, whereas the standard-course group received oseltamivir for 5 days. The primary outcome was all-cause ICU mortality. Propensity score matching (PSM) was constructed, and the outcome was investigated through Cox regression and RCSs. Two thousand three hundred and ninety-seven subjects were included, of whom 1943 (81.1%) received prolonged oseltamivir and 454 (18.9%) received standard treatment. An optimal full matching algorithm was performed by matching 2171 patients, 1750 treated in the prolonged oseltamivir group and 421 controls in the standard oseltamivir group. After PSM, 387 (22.1%) patients in the prolonged oseltamivir and 119 (28.3%) patients in the standard group died (p = 0.009). After adjusting confounding factors, prolonged oseltamivir significantly reduced ICU mortality (odds ratio [OR]: 0.53, 95% confidence interval [CI]: 0.40-0.69). Prolonged oseltamivir may have protective effects on survival at Day 10 compared with a standard treatment course. Sensitivity analysis confirmed these findings. Compared with standard treatment, prolonged oseltamivir was associated with reduced ICU mortality in critically ill patients with severe influenza. Clinicians should consider extending the oseltamivir treatment duration to 10 days, particularly in higher-risk groups of prolonged viral shedding. Further randomized controlled trials are warranted to confirm these findings.

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PURPOSE: To determine whether a positive fluid balance is associated with AKI and mortality in sepsis and septic shock patients. METHODS: A retrospective chart review of 482 patients treated for sepsis or septic shock. Patients were stratified according to quartiles of cumulative fluid balance on days 1 and 3. Logistic models were built to explore the association between fluid balance, AKI, and ICU mortality. RESULTS: During the first days of ICU admission, fluid input did not differ between survivors and non-survivors, yet a significant difference in output resulted in a more positive fluid balance in non-survivors on day 1 (37.24 ± 31.98 ml/kg vs. 24.97 ± 23.76 ml/kg, p < 0.001) and day 3 (83.33 ± 70.86 ml/kg vs. 62.20 ± 45.90 ml/kg, P = 0.005). Using a logistic regression model, a positive fluid balance on day three was independently associated with higher ICU mortality (odds ratio 1.007 for every one ml/kg, P = 0038) and AKIN stage III (odds ratio 1.006 for every one ml/kg, p = 0.031). CONCLUSION: In patients with sepsis and septic shock, a more positive fluid balance is associated with an increased incidence of acute kidney injury and death after correction for possible confounders.

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BACKGROUND: Tissue Doppler-derived left ventricular systolic velocity (mitral S') has shown excellent correlation to left ventricular ejection fraction (LVEF) in non-critically patients. However, their correlation in septic patients remains poorly understood and its impact on mortality is undetermined. We investigated the relationship between mitral S' and LVEF in a large cohort of critically-ill septic patients. METHODS: We conducted a retrospective cohort study between 01/2011 and 12/2020. All adult patients (≥ 18 years) who were admitted to the medical intensive care unit (MICU) with sepsis and septic shock that underwent a transthoracic echocardiogram (TTE) within 72 h were included. Pearson correlation test was used to assess correlation between average mitral S' and LVEF. Pearson correlation was used to assess correlation between average mitral S' and LVEF. We also assessed the association between mitral S', LVEF and 28-day mortality. RESULTS: 2519 patients met the inclusion criteria. The study population included 1216 (48.3%) males with a median age of 64 (IQR: 53-73), and a median APACHE III score of 85 (IQR: 67, 108). The median septal, lateral, and average mitral S' were 8 cm/s (IQR): 6.0, 10.0], 9 cm/s (IQR: 6.0, 10.0), and 8.5 cm/s (IQR: 6.5, 10.5), respectively. Mitral S' was noted to have moderate correlation with LVEF (r = 0.46). In multivariable logistic regression analysis, average mitral S' was associated with an increase in both 28-day ICU and in-hospital mortality with odds ratio (OR) 1.04 (95% CI 1.01-1.08, p = 0.02) and OR 1.04 (95% CI 1.01-1.07, p = 0.02), respectively. CONCLUSIONS: Even though mitral S' and LVEF may be related, they are not exchangeable and were only found to have moderate correlation in this study. LVEF is U-shaped, while mitral S' has a linear relation with 28-day ICU mortality. An increase in average mitral S' was associated with higher 28-day mortality.