May the neutrophil-to-lymphocyte ratio at admission predict the occurrence and the severity of ARDS after blunt chest trauma patients? A retrospective study

TM9SF1 offers utility as an efficient predictor of clinical severity and mortality among acute respiratory distress syndrome patients

Introduction

Acute respiratory distress syndrome (ARDS) is a major cause of death among critically ill patients in intensive care settings, underscoring the need to identify biomarkers capable of predicting ARDS patient clinical status and prognosis at an early time point. This study specifically sought to explore the utility and clinical relevance of TM9SF1 as a biomarker for the early prediction of disease severity and prognostic outcomes in patients with ARDS.

Methods

This study enrolled 123 patients with severe ARDS and 116 patients with non-severe ARDS for whom follow-up information was available. The mRNA levels of TM9SF1 and cytokines in peripheral blood mononuclear cells from these patients were evaluated by qPCR. The predictive performance of TM9SF1 and other clinical indicators was evaluated using received operating characteristic (ROC) curves. A predictive nomogram was developed based on TM9SF1 expression and evaluated for its ability in the early prediction of severe disease and mortality in patients with ARDS.

Results

TM9SF1 mRNA expression was found to be significantly increased in patients with severe ARDS relative to those with non-severe disease or healthy controls. ARDS severity increased in correspondence with the level of TM9SF1 expression (odds ratio [OR] = 2.43, 95% confidence interval [CI] = 2.15-3.72, P = 0.005), and high TM9SF1 levels were associated with a greater risk of mortality (hazard ratio [HR] = 2.27, 95% CI = 2.20-4.39, P = 0.001). ROC curves demonstrated that relative to other clinical indicators, TM9SF1 offered superior performance in the prediction of ARDS severity and mortality. A novel nomogram incorporating TM9SF1 expression together with age, D-dimer levels, and C-reactive protein (CRP) levels was developed and was used to predict ARDS severity (AUC = 0.887, 95% CI = 0.715-0.943). A separate model incorporating TM9SF1 expression, age, neutrophil-lymphocyte ratio (NLR), and D-dimer levels (C-index = 0.890, 95% CI = 0.627-0.957) was also developed for predicting mortality.

Conclusion

Increases in ARDS severity and patient mortality were observed with rising levels of TM9SF1 expression. TM9SF1 may thus offer utility as a novel biomarker for the early prediction of ARDS patient disease status and clinical outcomes.

Influence of systemic inflammatory indices on hospital stay and dialysis post-earthquake: A clinical study

Natural disasters pose significant challenges to medical response due to the surge of patients and emergent injuries. Amid such scenarios, where personnel for patient monitoring might be scarce, effective biomarkers are crucial for guiding treatment plans and predicting patient prognosis. We aimed to evaluate the correlation between systemic inflammatory indices and morbidity in earth-quake-induced crush injuries. Additionally, we assessed the potential of these indices as prognostic markers for adverse outcomes. We studied 140 patients with earthquake-related crush injuries (ECR) admitted between February and March 2023 and compared them to 200 healthy controls (CG) chosen using a simple random method. Using the complete blood count data upon admission, we computed and statistically compared indices including NLR (neutrophil lymphocyte ratio), PLR (platelet lymphocyte ratio), MLR (monocyte lymphocyte ratio), SII (systemic immune-inflammatory index), SIRI (systemic inflammatory response index), and PIV (pan-immune inflammation value). Regression analyses determined the prediction of hospitalization duration and dialysis necessity. PLR and MLR upon admission significantly predicted the length of hospital stay. MLR and SIRI were significant predictors for dialysis requirement, with Exp(B) values of 0.306 (p = 0.024) and 1.261 (p = 0.038), respectively. Systemic inflammatory indices can serve as valuable prognostic tools in disaster scenarios. Utilizing these indices can enhance patient management, effectively allocate resources, and potentially save lives in the aftermath of earthquakes.

Blood Count-Derived Inflammatory Markers Correlate with Lengthier Hospital Stay and Are Predictors of Pneumothorax Risk in Thoracic Trauma Patients

(1) Background: Trauma is one of the leading causes of death worldwide, with the chest being the third most frequent body part injured after abdominal and head trauma. Identifying and predicting injuries related to the trauma mechanism is the initial step in managing significant thoracic trauma. The purpose of this study is to assess the predictive capabilities of blood count-derived inflammatory markers at admission. (2) Materials and Methods: The current study was designed as an observational, analytical, retrospective cohort study. It included all patients over the age of 18 diagnosed with thoracic trauma, confirmed with a CT scan, and admitted to the Clinical Emergency Hospital of Targu Mureş, Romania. (3) Results: The occurrence of posttraumatic pneumothorax is highly linked to age (p = 0.002), tobacco use (p = 0.01), and obesity (p = 0.01). Furthermore, high values of all hematological ratios, such as the NLR, MLR, PLR, SII, SIRI, and AISI, are directly associated with the occurrence of pneumothorax (p < 0.001). Furthermore, increased values of the NLR, SII, SIRI, and AISI at admission predict a lengthier hospitalization (p = 0.003). (4) Conclusions: Increased neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), aggregate inflammatory systemic index (AISI), and systemic inflammatory response index (SIRI) levels at admission highly predict the occurrence of pneumothorax, according to our data.

Prognostic value of glucose-to-lymphocyte ratio in critically ill patients with acute respiratory distress syndrome: A retrospective cohort study

Background

There is need to identify biomarkers for prognosis of acute respiratory distress syndrome (ADRS). This may allow early and accurate identification of patients with high‐risk ARDS to guide adjustment of clinical treatment and nursing intervention, which would ultimately improve prognosis of patients with ARDS. Biomarkers based on a combination of fasting glucose and lymphocyte counts to predict prognosis in critically ill patients with ARDS remain undefined. In this study, we investigated the association between glucose‐to‐lymphocyte ratio (GLR) and in‐hospital mortality.

Methods

The study obtained data from Medical Information Mart for Intensive Care‐IV (MIMIC‐IV Version 1.0) database. We defined the GLR as fasting glucose/lymphocyte count and the patient in‐hospital mortality was considered as the outcome. In addition, we employed linear and logistic regression models for analysis.

Results

In total, 1,085 patients with ARDS were included in this study. The eligible participants included 498 female and 587 males, with a mean age of 64.2 ± 17.5 years. Logistic regression analysis demonstrated that higher GLR was an independent risk factor for all‐cause mortality (OR =1.67, 95% CI: 1.26–2.22) after adjusting for age, sex, anion gap, white blood cell count, congestive heart failure, sequential organ failure assessment (SOFA), SBP, DBP, and respiratory rate in both the dichotomized group and subgroups. We also analyzed the in‐hospital mortality to ROC curves by comparing the value between SOFA + GLR and SOFA. The area under the curve (AUC) was 0.6991 for the SOFA + GLR (95% CI: 0.6634–0.7348), and 0.6613 for the SOFA (95% CI: 0.6238–0.6988).

Conclusion

Our data showed that the GLR was an independent predictor of in‐hospital mortality for patients with ARDS. The GLR is an integrated, readily available clinical biomarker for mortality in patients with ARDS.