What are the prognostic factors affecting 30-day mortality in geriatric patients with respiratory failure in the Intensive Care Unit?

Association of Inflammatory and Metabolic Markers with Mortality in Patients with Postoperative Femur Fractures in the Intensive Care Unit

Background and Objectives: Postoperative femur fracture in elderly patients is associated with high morbidity and mortality, especially in the intensive care unit (ICU). Various factors, including demographic and laboratory parameters, may influence mortality in this population. The aim of this study was to evaluate the association of inflammatory and metabolic markers with mortality in ICU patients with postoperative femur fractures and to identify key predictors to enhance risk stratification and improve patient outcomes. Materials and Methods: In this retrospective single-center study, we analyzed 121 patients aged over 65 years with postoperative femur fractures who were admitted to the ICU between January 2023 and January 2024. Demographic and clinical data, including comorbidities, Charlson Comorbidity Index (CCI), and Acute Physiology and Chronic Health Evaluation (APACHE II) score, were collected. Laboratory parameters such as white blood cell count (WBC), albumin, C-reactive protein (CRP), D-dimer, Pan-Immune-Inflammation Value (PIV), CRP-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR), and others were analyzed. Linear regression, logistic regression, and Receiver Operating Characteristic (ROC) analyses were performed to determine the predictive value of these markers for ICU mortality. Results: The mean age of the patients was 76.3 ± 9.6 years, and 52.1% were female. The most common comorbidities were hypertension (67.8%) and diabetes (49.6%). ICU mortality occurred in 24 patients (20%). Significant predictors of mortality included higher CRP (>62.8 mg/L), NLR (>10.0), PIV (>450), and APACHE II scores (>23) (p < 0.001 for all). Lower albumin levels (<2.5 g/dL) were strongly associated with increased mortality (p < 0.001). ROC analysis demonstrated that the APACHE II score had the highest predictive accuracy for mortality (AUC = 0.83), followed by albumin (AUC = 0.79) and PIV (AUC = 0.76). Extended ICU stay (>10 days) was also significantly correlated with increased mortality (p < 0.001). Conclusions: This study successfully demonstrates the utility of combining traditional clinical markers, such as APACHE II score, with novel inflammatory markers, such as PIV, CAR, and NLR, in predicting mortality in ICU patients following femur fracture surgery. The integration of emerging biomarkers with well-established scoring systems offers enhanced predictive accuracy and provides valuable insights into patient management.

Correlation between the neutrophil-to-lymphocyte ratio and the 90-day all-cause mortality in patients with acute respiratory failure: a retrospective analysis based on the MIMIC-IV Database

INTRODUCTION

This study aims to examine the impact of the neutrophil-to-lymphocyte ratio (NLR) on 90-day all-cause mortality in individuals suffering from acute respiratory failure (ARF).

METHODS

Retrospectively including ARF patients from the MIMIC IV database, we classified them into the survivor and non-survivor cohorts according to their 90-day all-cause mortality rate. Demographic information, comorbidity, laboratory parameters, and other indices were collected.

RESULTS

A total of 3941 patients aged 65.0 years were enrolled in this. Multivariate COX regression analysis identified age(HR = 1.034, 95%CI:1.025-1.042,P < 0.001), history of chronic obstructive pulmonary disease(HR = 1.406, 95%CI:1.051-1.879,P = 0.022), history of hypertension(HR = 1.287, 95%CI:1.021-1.622,P = 0.032), history of type 2 diabetes mellitus(HR = 1.389, 95%CI:1.073-1.798,P = 0.013),history of coronary heart disease(HR = 2.138, 95%CI:1.639-2.788,P < 0.001), respiratory rate(HR = 1.043, 95%CI:1.026-1.01,P < 0.001), platelets (HR = 0.998, 95%CI: 0.997-0.999,P = 0.001), hemoglobin(HR = 0.859, 95%CI:0.820-0.901,P < 0.001), serum sodium (HR = 0.959, 95%CI:=0.041) and NLR(Q4, in comparison to Q1, HR = 1.627, 95%CI:1.167-2.268,P = 0.004) as independent predictors of the 90-day all-cause mortality rate. The relationship between NLR and mortality was observed to be non-linear(P-non-linear = 0.008) based on RCS curve analysis, with a threshold value of 12.8. A high NLR above this threshold was significantly associated with increased 90-day mortality rate after adjustment for covariates(HR = 1.535, 95%CI:1.196-1.968,P < 0.001).

CONCLUSION

The role of NLR as a risk factor in predicting 90-day all-cause mortality in ARF patients highlights its potential clinical usefulness in assessing patient prognosis.

Effect of predictive nursing based on risk early warning system on patients with acute respiratory failure in Intensive Care Unit

Background & Objective

Acute respiratory failure (ARF) is a life-threatening condition that necessitates intensive care and often results in high morbidity and mortality. Predictive nursing, combined with a risk early warning system, offers a proactive approach to patient care that could potentially improve outcomes in patients with ARF. However, the efficiency of this approach in intensive care settings is still unclear. This study aimed to analyze the effect of predictive nursing based on risk early warning system in patients with acute respiratory failure in intensive care unit (ICU) setting.

Methods

A retrospective cohort study included records of 368 patients admitted to ICU of a tertiary care hospital due to ARF from January 2021 to January 2023. Patients were divided into two groups based on the received care: standard care (control group, n=197) and predictive nursing care based on a risk early warning system (observation group, n=171). Data on demographics, clinical characteristics, complications, Acute Physiology, Age and Chronic Health Evaluation-II (APACHE-II) and Sequential Organ Failure Assessment (SOFA) scores, and duration of hospitalization were collected and analyzed.

Results

The observation group exhibited significantly lower incidence of complications related to ventilator use and shorter durations of mechanical ventilation, ICU stay, and total hospitalization compared to the control group (p<0.001). Furthermore, patients in the observation group had significantly lower APACHE-II and SOFA scores and blood lactate levels at both one week and two weeks post-intervention.

Conclusion

Predictive nursing care based on a risk early warning system significantly improved clinical outcomes and reduced mortality rates in ICU patients with ARF. The results underscore the potential of integrating predictive nursing care into routine practice, thereby transforming the care paradigm for ICU patients with ARF. Future research should explore the applicability of predictive nursing for other clinical conditions and in various healthcare settings.

Blood urea nitrogen-to-albumin ratio independently predicts 30-day mortality in acute respiratory failure patients: a retrospective cohort study

Background

It is crucial to identify patients at high risk for acute respiratory failure (ARF) to provide appropriate and optimal clinical treatment. While previous studies have explored the use of prognostic biomarkers based on a combination of blood urea nitrogen (BUN) and albumin levels, no reports to date have evaluated its utility across a wide range of ARF etiologies in a large and diverse critical care population. Therefore, we aimed to ascertain the association between the BUN-to-albumin ratio (BAR) and mortality in these patients.

Methods

Data recorded in the first 24 h following intensive care unit (ICU) admission, including demographics, vital signs, laboratory test results, comorbidities, and score systems were retrieved from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. A general additive model was used to determine whether there was a non-linear relationship between BAR and 30-day mortality. A multivariate Cox analysis was performed to measure the association between them.

Results

The study enrolled 9,734 patients with ARF. In comparison to survivors, non-survivors exhibited higher BAR [10.79 (6.25-18.81) vs. 7.35 (4.48-13.62), P<0.001]. The correlation between baseline BAR and 30-day all-cause mortality in patients with ARF was non-linear, with a significant inflection point (11.76 mg/g). The Kaplan-Meier curve demonstrated that ARF patients had higher 30-day all-cause mortality rates when they had higher BAR levels (>11.76 mg/g) with hazard ratio (HR) 1.54 [95% confidence interval (CI): 1.39-1.70].

Conclusions

A high BAR was linked to a higher risk of mortality in ARF patients. BAR is a straightforward and possibly useful prognostic biomarker for ARF.

Correlations between APACHE-II score and pressure parameters of mechanical ventilation in patients with ARDS and their value in prognostic evaluation

Objective

To investigate the correlations between APACHE-II score and pressure parameters of mechanical ventilation in patients with acute respiratory distress syndrome (ARDS) and their value in prognostic evaluation.

Methods

This was a retrospective study. The clinical data of 79 patients with ARDS treated in Shengzhou Hospital of Traditional Chinese Medicine from April 2020 to April 2022 were analyzed retrospectively. According to whether their APACHE-II scores were higher than 15, they were divided into low score group (n= 20) and high score group (n= 59). The plateau pressure (Pplat), driving pressure(ΔP) and mean airway pressure (Pmean) were compared. The correlation between APACHE-II score and pressure parameters of mechanical ventilation was analyzed. Based on the follow-up of 28-d survival, their Pplat, ΔP, Pmean and APACHE-II scores were compared. The value of APACHE-II score and pressure parameters in the prognostic evaluation of ARDS patients was analyzed.

Results

Pplat, ΔP and Pmean in the low score group were significantly lower than those in the high score group(P<0.05). Pplat, ΔP, Pmean and APACHE-II score in the survival group were significantly lower than those in the control group(P<0.05). APACHE-II score showed significantly positive correlations with Pplat, ΔP and Pmean. The AUC of Pmean, Pplat, ΔP and APACHE-II score in predicting the prognosis and diagnosis of ARDS patients was 0.761, 0.833, 0.754 and 0.832, respectively.

Conclusion

APACHE-II score of ARDS patients shows significantly positive correlations with pressure parameters of mechanical ventilation, and has diagnostic value for the prognosis of ARDS patients.

Clinical profile, outcomes and predictors of mortality in elderly patients admitted to the emergency medicine intensive care unit of a teaching hospital - A single-center registry

Aim:

Emergency intensive care of the elderly is often complicated and multifaceted. Understanding the clinical profile of elderly patients admitted in an emergency department-intensive care unit (ED-ICU) is crucial in planning health policies in geriatric emergency medicine. Thus, the aim of the study was to create a local registry of elderly people utilizing the ED-ICU services and to understand the rate and predictors of mortality.

Methods:

A retrospective chart analysis was performed including all patients aged ≥60 years who had an ED-ICU admission during a 6-month period (August 2018–January 2019). A structured case record form was used to capture information such as basic demography, clinical profile, and outcomes.

Results:

Total number of records considered for final analysis were 503. Mortality was seen in 21.07% (n = 106/503). The most common presenting complaint and cause of death was breathing difficulty (n = 48/503; 29.42%) and pneumonia (n = 41/106; 38.67%), repectively. The significant predictors of mortality [adjusted odds ratio; 95% confidence intervals; P value] were hypertension (2.195; 1.255, 3.840; 0.006), chronic liver disease (CLD) (4.324; 1.170, 15.979; 0.028), malignancy (2.854; 1.045, 7.796; 0.041), requiring noninvasive ventilation (NIV) (2.618; 1.449, 4.730; 0.001), requiring intubation (6.638; 3.705, 11.894; <0.001), and requiring vasopressors (3.583; 1.985, 6.465; <0.001).

Conlusion:

Approximately one in every five elderly patients getting admitted in ED-ICU died, and respiratory illness was the common diagnosis leading to death. Those with comorbidities such as hypertension, CLD, or malignancy and those requiring NIV, intubation, or vasopressors had higher mortality.