Mortality In Intensive Care Unit Patients Research Articles

The association between enteral nutrition with survival of critical patients with COVID-19.

Coronavirus disease 2019 (COVID-19) results in several complications and mortality in intensive care unit (ICU) patients. Limited studies have investigated the effect of enteral nutrition (EN) on the survival of COVID-19 patients in the ICU. The aim of this study was to investigate the association of EN with biochemical and pathological indices associated with mortality in ICU patients with COVID-19. This case-control study was conducted on 240 patients with COVID-19 hospitalized in the ICU including 120 eventual nonsurvived as the cases and 120 survived patients as the controls. All of the patients received EN as a high protein high volume or standard formula. Data on general information, anthropometric measurements, and the results of lab tests were collected. The recovered patients received significantly more high protein (60.8% vs. 39.6%, p = .004) and high volume (61.6% vs. 42.3%, p = .005) formula compared to the nonsurvived group. Mortality was inversely associated with high volume (odds ratio [OR]: 0.45 confidence interval [CI]95%, p = .008) and high protein (OR: 0.42 CI95%, p = .003) formula. The results remained significant after adjusting for age and sex. Further adjustment for underlying diseases, smoking, body mass index, and the acute physiology and chronic health evaluation II (APACHE II) score did not change the results. The findings of the study showed that there was a significant inverse association between mortality and high volume and high protein formula in patients with COVID-19. Further investigation is warranted.

Did COVID-19 ICU patient mortality risk increase as Colorado hospitals filled? A retrospective cohort study

ObjectivesTo assess whether increasing levels of hospital stress—measured by intensive care unit (ICU) bed occupancy (primary), ventilators in use and emergency department (ED) overflow—were associated with decreasing COVID-19 ICU patient...

Relationship between lactate-to-albumin ratio and 28-day mortality in patients with exacerbation of chronic obstructive pulmonary disease admitted to the Intensive Care Unit

AimTo explore the predictive value of lactate-to-albumin ratio (LAR) on 28-day mortality in patients with exacerbation of chronic obstructive pulmonary disease (AECOPD) admitted to the Intensive Care Unit (ICU).MethodsAccording to ICD-9 and ICD-10 diagnosis codes, patients diagnosed with AECOPD in the Medical Information Mart for Intensive Care IV (v.2.2) database were selected. The primary endpoint was 28-day mortality after ICU admission. We used receiver operating characteristic (ROC) curve, Kaplan–Meier (K–M) survival curve, logistic regression analyses and subgroup analysis to assess predictive power of LAR.Results606 patients were included in this study. The 28-day mortality was 29.7%. The area under the ROC curves (AUC) for LAR were 0.641 [95% confidence interval (CI) 0.592–0.689], which was comparable with OASIS (AUC: 0.662; 95% CI 0.616–0.709; p = 0.471) and SOFA (AUC: 0.660; 95% CI 0.612–0.708; p = 0.500). The cutoff value of LAR was 0.645 by ROC curve. The high-LAR group showed a bad prognosis in K–M analysis (p < 0.001). Multivariate logistic regression shown that LAR was significantly associated with a poor outcome (odds ratio: 1.77; 95% CI 1.16–2.71; p = 0.008). Subgroup analysis showed no significant interaction of LAR with each subgroup (p for interaction: 0.175–0.775).ConclusionLAR is a rational and easily accessible marker, which is remarkably associated with 28-day mortality in ICU patients with AECOPD.

Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis.

Liver cirrhosis patients admitted to intensive care unit (ICU) have a high mortality rate. To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis. We extracted demographic, etiological, vital sign, laboratory test, comorbidity, complication, treatment, and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and electronic ICU (eICU) collaborative research database (eICU-CRD). Predictor selection and model building were based on the MIMIC-IV dataset. The variables selected through least absolute shrinkage and selection operator analysis were further screened through multivariate regression analysis to obtain final predictors. The final predictors were included in the multivariate logistic regression model, which was used to construct a nomogram. Finally, we conducted external validation using the eICU-CRD. The area under the receiver operating characteristic curve (AUC), decision curve, and calibration curve were used to assess the efficacy of the models. Risk factors, including the mean respiratory rate, mean systolic blood pressure, mean heart rate, white blood cells, international normalized ratio, total bilirubin, age, invasive ventilation, vasopressor use, maximum stage of acute kidney injury, and sequential organ failure assessment score, were included in the multivariate logistic regression. The model achieved AUCs of 0.864 and 0.808 in the MIMIC-IV and eICU-CRD databases, respectively. The calibration curve also confirmed the predictive ability of the model, while the decision curve confirmed its clinical value. The nomogram has high accuracy in predicting in-hospital mortality. Improving the included predictors may help improve the prognosis of patients.

Monocyte distribution width (MDW) kinetic for monitoring sepsis in intensive care unit.

Monocyte distribution width (MDW) is a measure of monocyte anisocytosis. In this study, we assessed the role of MDW, in comparison to C-reactive protein (CRP), procalcitonin (PCT), and lactate, as a screening and prognostic biomarker of sepsis in intensive care unit (ICU) by longitudinally measuring it in the first 5days of hospital stay. We considered all consecutive patients admitted to the ICU. At admission, patients were classified as septic or not according to Sepsis-3 criteria. MDW, CRP, PCT, and lactate were measured daily in the first 5days of hospitalization. ICU mortality was also recorded. We included 193 patients, 62 with sepsis and 131 without sepsis (controls). 58% and 26 % of the patients, with and without sepsis respectively, died during ICU stay. MDW showed the highest accuracy for sepsis detection, superior to CRP, PCT, and lactate (AUC of 0.840, 0.755, 0.708, 0.622, respectively). At admission, no biomarker predicts ICU mortality in patients with sepsis. The kinetic of all biomarkers during the first 5days of hospitalization was associated with ICU mortality. Noteworthy, above all, the kinetic of MDW showed the best accuracy. Specifically, an increase or decrease in MDW from day 1-4 and 5 was significantly associated with mortality or survival, respectively. MDW is a reliable diagnostic and prognostic sepsis biomarker, better than traditional biomarkers.

Association Between the Red Blood Cell Distribution Width and 30-Day Mortality in Intensive Care Patients Undergoing Cardiac Surgery: A Retrospective Observational Study Based on the Medical Information Mart for Intensive Care-IV Database.

Millions of patients undergo cardiac surgery each year. The red blood cell distribution width (RDW) could help predict the prognosis of patients who undergo percutaneous coronary intervention or coronary artery bypass surgery. We investigated whether the RDW has robust predictive value for the 30-day mortality among patients in an intensive care unit (ICU) after undergoing cardiac surgery. Using the Medical Information Mart for Intensive Care-IV Database, we retrieved data for 11,634 patients who underwent cardiac surgery in an ICU. We performed multivariate Cox regression analysis to model the association between the RDW and 30-day mortality and plotted Kaplan-Meier curves. Subgroup analyses were stratified using relevant covariates. Receiver operating characteristic (ROC) curves were used to determine the predictive value of the RDWs. The total 30-day mortality rate was 4.2% (485/11,502). The elevated-RDW group had a higher 30-day mortality rate than the normal-RDW group (P<0.001). The robustness of our data analysis was confirmed by performing subgroup analyses. Each unit increase in the RDW was associated with a 17% increase in 30-day mortality when the RDW was used as a continuous variable (adjusted hazard ratio=1.17, 95% confidence interval, 1.10-1.25). Our ROC results showed the predictive value of the RDW. An elevated RDW was associated with a higher 30-day mortality in patients after undergoing cardiac surgery in an ICU setting. The RDW can serve as an efficient and accessible method for predicting the mortality of patients in ICUs following cardiac surgery.

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.

Stress hyperglycemia is associated with poor outcome in critically ill patients with pulmonary hypertension.

Stress hyperglycemia is common in critically ill patients and is associated with poor prognosis. Whether this association exists in pulmonary hypertension (PH) patients is unknown. The present cohort study investigated the association of stress hyperglycemia with 90-day all-cause mortality in intensive care unit (ICU) patients with PH. Data of the study population were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. A new index, the ratio of admission glucose to HbA1c (GAR), was used to evaluate stress hyperglycemia. The study population was divided into groups according to GAR quartiles (Q1-Q4). The outcome of interest was all-cause mortality within 90 days, which was considered a short-term prognosis. A total of 53,569 patients were screened. Ultimately, 414 PH patients were enrolled; 44.2% were male, and 23.2% were admitted to the cardiac ICU. As the GAR increased from Q2 to Q4, the groups had lower creatinine levels, longer ICU stays, and a higher proportion of renal disease. After adjusting for confounding factors such as demographics, vital signs, and comorbidities, an elevated GAR was associated with an increased risk of 90-day mortality. Stress hyperglycemia assessed by the GAR was associated with increased 90-day mortality in ICU patients with PH.

Association between mechanical power and intensive care unit mortality in Korean patients under pressure-controlled ventilation.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029-1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Assessment of Nutritional Risk Scores (the Nutritional Risk Screening 2002 and Modified Nutrition Risk in Critically Ill Scores) as Predictors of Mortality in Critically Ill Patients on Extracorporeal Membrane Oxygenation.

Nutritional risk is associated with intensive care unit (ICU) stay and mortality, the Nutritional Risk Screening 2002 (NRS 2002) and the modified Nutritional Risk in the Critically Ill (mNUTRIC) score are assessment instruments and useful in predicting the risk regarding mortality in ICU patients. Our aim was to assess the effects of mNUTRIC and NRS 2002 on mortality in patients on extracorporeal membrane oxygenation (ECMO). A retrospective cohort study was performed and 78 patients were included for final analysis. In the current study, the NRS 2002 and the mNUTRIC score within 24 hours before starting ECMO were applied to assess patients' nutritional status on ECMO and explore the relationship between nutritional status and patient outcomes. This study suggests that both mNUTRIC and NRS 2002 scores were found to be significant independent risk and prognostic factors for in-hospital and 90 day morality among ECMO patients based on multivariable logistic regression analysis (p < 0.05), with those in the high-risk group having higher in-hospital and 90 day mortality rates than those identified as being at low risk (p < 0.001). In comparison to the NRS 2002 score, the mNUTRIC score demonstrated a superior prognostic ability in ECMO patients.

The impact of nontuberculous mycobacterial lung disease in critically ill patients: Significance for survival and ventilator use

BackgroundThis study investigates the impact of nontuberculous mycobacterial lung disease (NTM-LD) on mortality and mechanical ventilation use in critically ill patients. MethodsWe 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. ResultsA 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. ConclusionsNTM-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.

Heart rate complexity helps mortality prediction in the intensive care unit: A pilot study using artificial intelligence

BackgroundIn intensive care units (ICUs), accurate mortality prediction is crucial for effective patient management and resource allocation. The Simplified Acute Physiology Score II (SAPS-2), though commonly used, relies heavily on comprehensive clinical data and blood samples. This study sought to develop an artificial intelligence (AI) model utilizing key hemodynamic parameters to predict ICU mortality within the first 24 h and assess its performance relative to SAPS-2. MethodsWe conducted an analysis of select hemodynamic parameters and the structure of heart rate curves to identify potential predictors of ICU mortality. A machine-learning model was subsequently trained and validated on distinct patient cohorts. The AI algorithm’s performance was then compared to the SAPS-2, focusing on classification accuracy, calibration, and generalizability. Measurements and main resultsThe study included 1298 ICU admissions from March 27th, 2015, to March 27th, 2017. An additional cohort from 2022 to 2023 comprised 590 patients, resulting in a total dataset of 1888 patients. The observed mortality rate stood at 24.0%. Key determinants of mortality were the Glasgow Coma Scale score, heart rate complexity, patient age, duration of diastolic blood pressure below 50 mmHg, heart rate variability, and specific mean and systolic blood pressure thresholds. The AI model, informed by these determinants, exhibited a performance profile in predicting mortality that was comparable, if not superior, to the SAPS-2. ConclusionsThe AI model, which integrates heart rate and blood pressure curve analyses with basic clinical parameters, provides a methodological approach to predict in-hospital mortality in ICU patients. This model offers an alternative to existing tools that depend on extensive clinical data and laboratory inputs. Its potential integration into ICU monitoring systems may facilitate more streamlined mortality prediction processes.

The role of thyroid hormones in assessing the survival of intensive care unit patients

Background/Aim. Patients in intensive care units (ICUs) often exhibit disturbances in the concentration of thyroid hormones (THs), even if they had no previous thyroid disorders. The aim of the study was to determine whether there is a correlation between THs and the survival rate in the ICU and whether these hormones have predictive capability for mortality rate assessment. Methods. The study included 41 patients (23 women and 18 men) divided into two groups: survivors (70.7%) and non-survivors (29.3%). In peripheral blood samples taken within the first 24 hrs after ICU admission, TH levels were measured: triiodothyronine (T3), thyroxine (T4), free T3 (FT3), free T4 (FT4), and thyroid stimulating hormone (TSH), as well as procalcitonin (PCT). The Sequential Organ Failure Assessment Score (SOFAS) was calculated for each patient. Results. A statistically significant difference between the study groups (survivor vs. non-survivor patients, p &lt; 0.05) was found for PCT, SOFAS, T3, T4, and FT4. The area under the receiver operating characteristic (ROC) curve (AUC) - (AUROC) for the SOFAS was 0.991 [95% confidence interval (CI): 0.898-1.000, p &lt; 0.001], for T3 was 0.727 (95% CI: 0.566-0.854, p = 0.0097), for T4 was 0.793 (95% CI: 0.638-0.903, p = 0.0008), for FT3 was 0.707 (95% CI: 0.544-0.8389, p = 0.0299), and for FT4 was 0.795 (95% CI: 0.640-0.904, p = 0.0005). Compared to other parameters, T3 had higher sensitivity (91.67%), FT4 had higher specificity (93.10%), while SOFAS had both the highest sensitivity (91.67%) and specificity (96.55%) in relation to all other tested parameters. Multiple linear regression analysis showed that FT4 and T4 were significant predictors of survival time (? = -0.362, p = 0.012 and ? = -0.356, p = 0.014, respectively). Conclusion. Among all examined THs, only FT4 and T4 showed strong predictive potential for assessing mortality in ICU patients. This study has highlighted the significance of assessing THs levels in critically ill patients. This is crucial because it opens the possibility of implementing specific therapies to rectify issues stemming from hormonal deficiencies.

Heart rate/temperature ratio: A practical prognostic indicator for critically ill patients with sepsis

BackgroundWe hypothesize that the heart rate/temperature ratio can predict intensive care unit (ICU) mortality in critical ill patients with sepsis. We aimed to explore the association between the heart rate/temperature ratio and ICU mortality in patients with sepsis. MethodsWe conducted this study utilizing a comprehensive critical care medicine database. The primary endpoint assessed was ICU mortality. A multivariable logistic regression model was employed to determine the independent impact of the heart rate to temperature ratio on ICU mortality. ResultsThe study included 12,321 patients. A nonlinear relationship was observed between the heart rate/temperature ratio and ICU mortality, with an inflection point identified at 2.22. The results from the Multivariable logistic regression analysis revealed that the heart rate/temperature ratio independently contributed to the risk of ICU mortality. In model II, there was a 55 % higher ICU mortality rate with a heart rate/temperature ratio greater than 2.22 than with that less than 2.22 (odds ratio [OR] = 1.55, 95 % confidence interval [CI] 1.35–1.77). Moreover, an elevated heart rate/temperature ratio as a continuous variable showed a positive association with ICU mortality (OR = 2.14; 95 % CI: 1.87–2.45). The impact of the heart rate/temperature ratio on ICU mortality remained consistent across all subgroup variables. The sensitivity analysis results consistently supported the primary outcome, with an E value of 2.47. This suggests that the influence of unmeasured confounders on the observed outcomes was minimal, thereby confirming the robustness of the findings. ConclusionsThe heart rate/temperature ratio is a readily available and convenient indicator in a clinical setting. Elevated heart rate/temperature ratios, particularly those exceeding 2.22, are strongly linked to a high ICU mortality rate among critically ill sepsis patients.

Independent Predictors of Mortality in ICU Patients with COVID-19

Objective: Early identification of Coronavirus disease 2019 (COVID-19) patients at high mortality risk can improve patient care and prevent deaths. To identify prognostic predictors that increase COVID-19 patient mortality risk in the Intensive Care Unit (ICU).&#x0D; Methods: Retrospective analysis of clinical characteristics and serological biomarkers of ICU-COVID-19 patients was performed in a tertiary hospital from 24 March 2020 to 20 December 2020. Analysis was conducted on two groups of study participants: survivors and deceased. Multivariate logistic regression was used to determine mortality risk. In order to determine prognostic predictors, the ANOVA test was used to compare the data of serological biomarkers on the day of patients' admission to the ICU and on the 5th day of follow-up.&#x0D; Results: A total of 335 patients (54.65%) were in the deceased group, and 278 (45.35%) were in the survivors group. A statistically significant difference was found between the deceased and survivor groups regarding mean age (p

Evaluation of the FAST HUG implementation effect on the mortality and length of stay in admitted patient in Intensive Care Unit (ICU) of a hospital

Objective: We aimed to determine new version of the FAST HUG implementation effect on the mortality and length of stay in admittedpatient in Intensive Care Unit (ICU) of a hospital. Methods: We conducted a prospective cohort study on 406 patients who admitted in medical and surgical ICU of Imam Hossein Hospitalof Tehran province in Iran from July 1, 2022, to September 30, 2022. We identified predictors of ICU mortality by logistic regression model,predictors of 28-day mortality/re-hospitalization/recovery by generalized ordered logit model, predictors of length of stay (LOS) by linearregression, predictors of mechanical ventilation by generalized ordered logit and predictors of SOFA score by hurdle model. Results: This mnemonic had protective impact (OR = 0.56, P-value = 0.01) on the 28-days mortality. One unit increase in mean of FAST HUGscore had a preventive effect on the outcome of death (OR = 0.21). Surgical admission type (Coefficient = –3.24, P-value = 0.00) and FASTHUG implementation (Coefficient =1.58, P-value= 0.0) were strongest factors on the LOS. Conclusion: Our study results approved the importance of the FAST HUG implementation on the decrease of patient mortality in ICU and28 days after discharge. Additionally, this checklist had a statistically significant role in declining SOFA scores in ICU patients.

The association between serum chloride and mortality in ICU patients with heart failure: The impact of bicarbonate

ObjectiveTo assess whether serum chloride predicts risk of death in intensive care unit (ICU) patients with heart failure (HF) and the effect of bicarbonate on the efficacy of serum chloride in predicting risk of death in ICU patients. MethodsA total of 9364 HF patients hospitalized in the ICU were enrolled. Patients were divided into hypochloremia (< 96 mEq/L), normal chloride (96–108 mEq/L), and hyperchloremia (> 108 mEq/L) groups. Similarly, we divided the serum bicarbonate level into three groups: low bicarbonate (< 22 mEq/L), medium bicarbonate (22–26 mEq/L), and high bicarbonate (> 26 mEq/L). The outcome of this study was in-hospital mortality. Then, we analyzed the association between abnormal serum chloride and mortality according to the category of serum bicarbonate and assessed the interaction effect. Restricted cubic spline (RCS) was used to show possible nonlinear associations. ResultsIn the overall study population, hypochloremia was associated with a higher risk of in-hospital mortality than normal chloride (odds ratio [OR] 1.54, 95% confidence interval [CI] 1.26–1.86, P < 0.001), hyperchloremia was not significantly related to in-hospital mortality (OR 1.00, 95% CI 0.85–1.19, P = 0.962). However, a linear association between serum chloride and in-hospital mortality was found in the low and normal bicarbonate groups (all P for nonlinear >0.05). ConclusionsHypochloremia is associated with in-hospital mortality and longer hospital stay in critically ill patients with HF. In addition, risk of death in the low and medium serum bicarbonate groups decreased with increasing serum chloride level.

The Relationship of ABO and Rh Blood Group Types With Severe COVID-19 Disease Mortality in ICU Patients: Insights From a Single-Center Experience in Southern Saudi Arabia.

Introduction The global COVID-19 pandemic has triggered an unprecedented public health crisis, emphasizing the need to understand factors influencing disease outcomes. This study explores the role of genetic variations in blood group antigens, particularly ABO and RhD, in shaping mortality rates among critically ill COVID-19 patients in the southern region of Saudi Arabia. Methods Utilizing a retrospective, noninterventional approach, we analyzed medical records of 594 COVID-19 patients admitted to the intensive care unit (ICU) at Aseer Central Hospital from August 2020 to April 2021. The cohort, with a mean age of 60.5 years, consisted of a predominantly male population. Results The study encompassed a diverse age range of 18 to 103 years, with a mean age of 60.5 ± 17.3 years. Of the 594 patients, 398 (67%) were male, and only 5 (0.8%) had a history of smoking. Blood group distribution revealed 275 (48.4%) with O-, 189 (33.3%) with A+, and 51 (9%) with AB- types. Predominant chronic conditions included diabetes mellitus (35.5%). Tragically, 320 patients (54.6%) experienced mortality, with a 100% mortality rate for the B+ blood group and 92.9% for O- blood group. Conclusion This analysis establishes significant statistical links, underscoring the pivotal role of blood type, particularly the Rh factor, in influencing mortality risk among critically ill COVID-19 patients. These findings contribute valuable insights into risk stratification and personalized care for severe cases, emphasizing the importance of genetic considerations in understanding disease outcomes.

Interleukin 33, soluble suppression of tumorigenicity 2, interleukin 27, and galectin 3 as predictors for outcome in patients admitted to intensive care units.

Intensive care units (ICUs) are expert hospital areas that provide treatment and 24 h care for people who are very sick. Sepsis represents a serious, severe condition and it can lead to septic shock and multiple organ dysfunction syndromes and is one of the most common reasons for patients' hospitalization in ICUs. We wanted to explore the prognostic values of interleukin (IL) 33, soluble suppression of tumorigenicity 2 (sST2), IL 27, and galectin 3 in critically-ill patients. We assumed that these parameters in combination or alone could predict mortality in ICU patients. This research represents a clinical non-randomized prospective study, performed at the Medical Military Academy, a tertiary care hospital in Belgrade, Serbia. The patients were divided in four groups: patients with sepsis (peritonitis, pancreatitis, trauma) and patients without sepsis (trauma). Total number of patients enrolled in the study was 151 and average years of patients were 56.48. The values greater than the cut-off were the predictors of mortality. The IL-33, IL-27 as well as galectin-3 can successfully predict the outcome of critically-ill patients in ICUs. The sST2, cannot predict death in critically-ill patients as a single prognostic factor. However, the combination of at least two biomarkers: IL-33, sST2, IL-27, and galectin-3, gives very significant results in predicting the outcome in patients admitted to ICUs.

Investigating the Relationship between Red Cell Width Distribution (RDW) and Outcome in Ventilator-Associated Pneumonia: A Prospective Cross-Sectional Study

Background: Ventilator-associated pneumonia (VAP) is a consequence of mechanical ventilation, which can be fatal. Several markers are available to predict outcomes related to VAP. Choosing a predictor that is inexpensive, affordable, and accurate is advantageous. This study aimed to examine red cell distribution width (RDW) as a predictor of mortality in patients with VAP.&#x0D; Methods: This prospective cohort study was conducted among 49 patients in the intensive care unit (ICU) of Valiasr Hospital in Tehran. A researcher-made checklist was used to collect RDW and other marker data, as well as mortality outcomes and length of stay (LOS) in the ICU. The Pearson correlation coefficient in the SPSS software and the regression model in the Eviews software were used to examine the relationship between markers and different outcomes.&#x0D; Results: Of a total of 49 patients (57.1% male; mean age = 54 ± 16), the length of ICU stays ranged from 7 to 14 days. According to the Pearson correlation coefficient, a significant association between RDW and mortality (P =.009) was noted. But no significant relationship between RDW and length of stay in the ICU (P =.81) was noted. Additionally, the regression model showed a positive relationship between RDW and white blood cells (WBC), lactate, and sequential organ failure assessment (SOFA).&#x0D; Conclusion: Our study showed a positive but weak correlation between RDW and ICU mortality in patients with VAP. Due to its availability and low cost of measurement, RDW is an appropriate option for predicting mortality risk in patients who are admitted to the ICU and develop VAP.