A prediction model for predicting the risk of acute respiratory distress syndrome in sepsis patients: a retrospective cohort study

Post-operative sepsis-induced acute respiratory distress syndrome: risk factors for a life-threatening complication

Introduction

Prevalence and mortality of the acute respiratory distress syndrome (ARDS) in intensive care units (ICU) are unacceptably high. There is scarce literature on post-operative sepsis-induced ARDS despite that sepsis and major surgery are conditions associated with ARDS. We aimed to examine the impact of post-operative sepsis-induced ARDS on 60-day mortality.

Methods

We performed a secondary analysis of a prospective observational study in 454 patients who underwent major surgery admitted into a single ICU. Patients were stratified in two groups depending on whether they met criteria for ARDS. Primary outcome was 60-day mortality of post-operative sepsis-induced ARDS. Secondary outcome measures were potential risk factors for post-operative sepsis-induced ARDS, and for 60-day mortality.

Results

Higher SOFA score (OR 1.1, 95% CI 1.0-1.3, p = 0.020) and higher lactate (OR 1.9, 95% CI 1.2-2.7, p = 0.004) at study inclusion were independently associated with ARDS. ARDS patients (n = 45) had higher ICU stay [14 (18) vs. 5 (11) days, p < 0.001] and longer need for mechanical ventilation [6 (14) vs. 1 (5) days, p < 0.001] than non-ARDS patients (n = 409). Sixty-day mortality was higher in ARDS patients (OR 2.7, 95% CI 1.1-6.3, p = 0.024). Chronic renal failure (OR 4.0, 95% CI 1.2-13.7, p = 0.026), elevated lactate dehydrogenase (OR 1.7, 95% CI 1.1-2.7, p = 0.015) and higher APACHE II score (OR 2.7, 95% CI 1.3-5.4, p = 0.006) were independently associated with 60-day mortality.

Conclusion

Post-operative sepsis-induced ARDS is associated with higher 60-day mortality compared to non-ARDS post-operative septic patients. Post-operative septic patients with higher severity of illness have a greater risk of ARDS and worse outcomes. Further investigation is needed in post-operative sepsis-induced ARDS to prevent ARDS.

Critical evaluation of established risk prediction models for acute respiratory distress syndrome in adult patients: A systematic review and meta-analysis

AIM

To assess the performance of validated prediction models for acute respiratory distress syndrome (ARDS) by systematic review and meta-analysis.

METHODS

Eight databases (Medline, CINAHL, Embase, The Cochrane Library, CNKI, WanFang Data, Sinomed, and VIP) were searched up to March 26, 2023. Studies developed and validated a prediction model for ARDS in adult patients were included. Items on study design, incidence, derivation methods, predictors, discrimination, and calibration were collected. The risk of bias was assessed by the Prediction model Risk of Bias Assessment Tool. Models with a reported area under the curve of the receiver operating characteristic (AUC) metric were analyzed.

RESULTS

A total of 25 studies were retrieved, including 48 unique prediction models. Discrimination was reported in all studies, with AUC ranging from 0.701 to 0.95. Emerged AUC value of the logistic regression model was 0.837 (95% CI: 0.814 to 0.859). Besides, the value in the ICU group was 0.856 (95% CI: 0.812 to 0.899), the acute pancreatitis group was 0.863 (95% CI: 0.844 to 0.882), and the postoperation group was 0.835 (95% CI: 0.808 to 0.861). In total, 24 of the included studies had a high risk of bias, which was mostly due to the improper methods in predictor screening (13/24), model calibration assessment (9/24), and dichotomization of continuous predictors (6/24).

CONCLUSIONS

This study shows that most prediction models for ARDS are at high risk of bias, and the discrimination ability of the model is excellent. Adherence to standardized guidelines for model development is necessary to derive a prediction model of value to clinicians.

Establishment and validation of a predictive model for respiratory failure within 48 h following admission in patients with sepsis: a retrospective cohort study

Objective: The objective of this study is to identify patients with sepsis who are at a high risk of respiratory failure. Methods: Data of 1,738 patients with sepsis admitted to Dongyang People's Hospital from June 2013 to May 2023 were collected, including the age at admission, blood indicators, and physiological indicators. Independent risk factors for respiratory failure during hospitalization in the modeling population were analyzed to establish a nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate the discriminative ability, the GiViTI calibration graph was used to evaluate the calibration, and the decline curve analysis (DCA) curve was used to evaluate and predict the clinical validity. The model was compared with the Sequential Organ Failure Assessment (SOFA) score, the National Early Warning Score (NEWS) system, and the ensemble model using the validation population. Results: Ten independent risk factors for respiratory failure in patients with sepsis were included in the final logistic model. The AUC values of the prediction model in the modeling population and validation population were 0.792 and 0.807, respectively, both with good fit between the predicted possibility and the observed event. The DCA curves were far away from the two extreme curves, indicating good clinical benefits. Based on the AUC values in the validation population, this model showed higher discrimination power than the SOFA score (AUC: 0.682; p < 0.001) and NEWS (AUC: 0.520; p < 0.001), and it was comparable to the ensemble model (AUC: 0.758; p = 0.180). Conclusion: Our model had good performance in predicting the risk of respiratory failure in patients with sepsis within 48 h following admission.

A prediction model for acute respiratory distress syndrome in immunocompetent adults with adenovirus-associated Pneumonia: a multicenter retrospective analysis

BACKGROUND

In recent years, the number of human adenovirus (HAdV)-related pneumonia cases has increased in immunocompetent adults. Acute respiratory distress syndrome (ARDS) in these patients is the predominant cause of HADV-associated fatality rates. This study aimed to identify early risk factors to predict early HAdV-related ARDS.

METHODS

Data from immunocompetent adults with HAdV pneumonia between June 2018 and May 2022 in ten tertiary general hospitals in central China was analyzed retrospectively. Patients were categorized into the ARDS group based on the Berlin definition. The prediction model of HAdV-related ARDS was developed using multivariate stepwise logistic regression and visualized using a nomogram.

RESULTS

Of 102 patients with adenovirus pneumonia, 41 (40.2%) developed ARDS. Overall, most patients were male (94.1%), the median age was 38.0 years. Multivariate logistic regression showed that dyspnea, SOFA (Sequential Organ Failure Assessment) score, lactate dehydrogenase (LDH) and mechanical ventilation status were independent risk factors for this development, which has a high mortality rate (41.5%). Incorporating these factors, we established a nomogram with good concordance statistics of 0.904 (95% CI 0.844-0.963) which may help to predict early HAdV-related ARDS.

CONCLUSION

A nomogram with good accuracy in the early prediction of ARDS in patients with HAdV-associated pneumonia may could contribute to the early management and effective treatment of severe HAdV infection.

The roles of tissue-resident macrophages in sepsis-associated organ dysfunction

Sepsis, a syndrome caused by a dysregulated host response to infection and characterized by life-threatening organ dysfunction, particularly septic shock and sepsis-associated organ dysfunction (SAOD), is a medical emergency associated with high morbidity, high mortality, and long-term sequelae. Tissue-resident macrophages (TRMs) are a subpopulation of macrophages derived primarily from yolk sac progenitors and fetal liver during embryogenesis, located primarily in non-lymphoid tissues in adulthood, capable of local self-renewal independent of hematopoiesis, and developmentally and functionally restricted to the non-lymphoid organs in which they reside. TRMs are the first line of defense against life-threatening conditions such as sepsis, tumor growth, traumatic-associated organ injury, and surgical-associated injury. In the context of sepsis, TRMs can be considered as angels or demons involved in organ injury. Our proposal is that sepsis, septic shock, and SAOD can be attenuated by modulating TRMs in different organs. This review summarizes the pathophysiological mechanisms of TRMs in different organs or tissues involved in the development and progression of sepsis.