Early identification of patients at risk for acute respiratory distress syndrome among severe pneumonia: a retrospective cohort study

Evaluating the Use of Inhaled Budesonide and Ipratropium Bromide Combination in Patients at High Risk of Acute Respiratory Distress Syndrome Development: A Randomized Controlled Trial

Objectives: There is a scarcity of pharmacological treatments that efficiently address lung injury in individuals experiencing acute respiratory distress syndrome (ARDS). Early inhaled corticosteroids and ipratropium may reduce pulmonary inflammation and injury of the lungs, minimizing the risk of ARDS. Method: This is a double-blinded randomized control trial conducted on patients at risk of ARDS. Patients were randomly allocated into two groups; the intervention group (63 patients) were administered aerosolized budesonide and ipratropium bromide, and the control group (56) were administered a placebo every eight hours for five days. Alteration in oxygen saturation divided by inspired oxygen (Fio2) (S/F) after five days was the primary outcome. Secondary outcomes included ARDS occurrence, mechanical ventilation (MV) requirement, hospital stay duration, and mortality rates. Results: Of the 604 screened, only 119 patients were included. The intervention group (63 patients) S/F ratio recovered versus the fall of the control group. Both groups had similar organ dysfunction and 28-day mortality. The intervention group had significantly (p < 0.001) fewer cases developing ARDS (9.5%) and MV (9.5%) than the control group (46.4% and 35.7%, respectively). Conclusions: The administration of inhaled budesonide and ipratropium bromide improved oxygenation, as assessed by the S/F ratio, and significantly reduced the rate of ARDS development and the requirement of MV versus the control group. Larger multi-center trials including diverse patient populations are needed to validate these results.

Machine learning-based model for predicting the occurrence and mortality of nonpulmonary sepsis-associated ARDS

OBJECTIVE

The objective was to establish a machine learning-based model for predicting the occurrence and mortality of nonpulmonary sepsis-associated ARDS.

METHODS

80% of sepsis patients selected randomly from the MIMIC-IV database, without prior pulmonary conditions and with nonpulmonary infection sites, were used to construct prediction models through machine learning techniques (including K-nearest neighbour, extreme gradient boosting, support vector machine, deep neural network, and decision tree methods). The remaining 20% of patients were utilized to validate the model's accuracy. Additionally, local data were employed for further model validation.

RESULTS

A total of 11,409 patients were included, with the most common type of infection being bloodstream infection. A total of 7,632 (66.9%) patients developed nonpulmonary sepsis-associated ARDS (NPS-ARDS). Patients with NPS-ARDS had significantly longer ICU stays (6.2 ± 5.2 days vs. 4.4 ± 3.7 days, p < 0.01) and higher 28-day mortality rates (19.5% vs. 14.9%, p < 0.01). Both internal and external validation demonstrated that the model constructed with the extreme gradient boosting method had high accuracy. In the internal validation, the model predicted NPS-ARDS and mortality in such patients with accuracies of 77.5% and 71.8%, respectively. In the external validation, the model predicted NPS-ARDS and mortality in these patients with accuracies of 78.0% and 81.4%, respectively.

CONCLUSION

The model established via the extreme gradient boosting method can predict the occurrence and mortality of nonpulmonary sepsis-associated ARDS to a certain extent.

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.

Clinical characteristics and predictors of burn complicated with smoke inhalation injury: A retrospective analysis

Fire smoke enters the human lungs through the respiratory tract. The damage to the respiratory tract and lung tissue is known as smoke inhalation injury (SII). Fire smoke can irritate airway epithelium cells, weaken endothelial cell adhesion and lyse alveolar type II epithelia cells, leading to emphysema, decreased lung function, pneumonia and risk of acute lung injury/acute respiratory distress syndrome (ARDS). The purpose of the present study was to analyze the clinical characteristics of patients with SII and the risk factors affecting their prognosis. A total of 103 patients with SII admitted between January 2016 to December 2021 to the Burns Unit of the Characteristic Medical Center of Chinese People's Armed Police Force and 983 Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army were selected for the present study. The demographics and clinical features between different severities of SII were analyzed. Univariate/multivariate logistic regression was used to analyze the potential predictors for severity, ARDS and mortality of patients with SII. Receiver operating characteristic (ROC) curves were used to screen independent risk factors and identify their prediction accuracy. It was concluded that total body surface area (TBSA), III burn area (of total %TBSA), cases of respiratory infections, ARDS morbidity, mortality, acute physiology and chronic health evaluation II, lung injury prediction score, lactic acid, white blood cells (WBC), alanine transaminase, blood urea nitrogen, serum creatinine and uric acid were indicators that were raised with increasing severity of SII. However red blood cells, hemoglobin, platelet count, total protein, albumin, and albumin/globulin were decreased with the increasing severity of SII (P<0.05). WBC >20.91 (10⁹/l) was a reliable indicator for severe SII. Lactic acid >9.60 (mmol/l) demonstrated a high degree of accuracy in predicting ARDS development in patients with SII. Hemoglobin <83.00 (g/l) showed a high degree of accuracy in predicting mortality. In summary, the highlighted assessment parameters could be used to contribute to devising improved treatment plans to preempt worsening conditions (such as shock, ARDS, multiple organ dysfunction syndrome and death).

Profound Effect of Pulmonary Surfactant on the Treatment of Preterm Infants with Respiratory Distress Syndrome

Inherited diseases caused by dysfunction of pulmonary surfactant metabolism or surfactant dysfunction have recently been considered the underlying causes of neonatal and pediatric respiratory diseases. Respiratory distress syndrome in premature infants is a common respiratory disease in pediatrics. It is caused by underdeveloped lungs in infants and a lack of active substances on the surface of the alveoli, which leads to insufficiency of lung function, which can lead to difficulty breathing, increased heart rate, facial bruising, and more. Neonatal Respiratory Distress Syndrome is a very dangerous disease with a high mortality rate and a great threat to children's lives and health. Therefore, enough attention and treatment should be caused in clinical practice. Natural pulmonary surfactant (PS) has achieved positive effects in the treatment of neonatal respiratory distress syndrome (RDS), reducing neonatal mortality, the application of mechanical ventilation, and the occurrence of late complications. To further explore the role of pulmonary surfactants in the treatment of neonatal respiratory distress syndrome, to analyze the best time to use PS to prevent RDS, this paper has selected premature infants with RDS received by the neonatal department of a hospital in a province from March 2019 to October 2020 to compare the efficacy of pulmonary surfactant (PS) in preterm infants with respiratory distress syndrome (RDS). The experiment has found that the average mechanical ventilation time (5.1 d) and oxygen therapy time (7.3 d) in the early group are shorter than the average mechanical ventilation time (6.4 d) and oxygen therapy time (10.6 d) in the late group. It has been demonstrated that early administration of pulmonary surfactant (PS) therapy is of great help in improving respiratory distress syndrome in premature infants.

Early detection of gram‑negative bacteria using metagenomic next‑generation sequencing in acute respiratory distress syndrome: A case report

Metagenomic next-generation sequencing (mNGS) is an effective method that can be used for the identification of early pathogens in patients with suspected severe pneumonia. However, the potential of mNGS for evaluating the prognosis of acute respiratory distress syndrome (ARDS) in patients with severe pneumonia remains unclear. In the present report, hospital-acquired gram-negative bacteria infections were detected in a case using metagenomic next-generation sequencing (mNGS) in a sample of bronchoalveolar fluid. This was obtained from a 58-year-old male patient with traumatic wet lung after a neurosurgery. According to the results, of which the profiles of the resistance genes were detected by mNGS, drugs designed to control infection were adjusted, namely to polymyxin B (500,000 U/12 h), azithromycin (0.5 g/24 h) and ganciclovir (0.25 g/12 h). Following adjusting treatment for 8 days, the symptoms of lung infection and hypoxemia were markedly improved, resulting in the patient being transferred out of the intensive care unit 15 days after treatment. To conclude, observations from the present report suggest that mNGS is a useful method for the early identification of pathogens in patients with pneumonia caused by ARDS. However, further studies are required to identify the complementary role of mNGS in supporting conventional microbiological methods in routine clinical practice.

Early prediction of moderate-to-severe condition of inhalation-induced acute respiratory distress syndrome via interpretable machine learning

Background

Several studies have investigated the correlation between physiological parameters and the risk of acute respiratory distress syndrome (ARDS), in addition, etiology-associated heterogeneity in ARDS has become an emerging topic quite recently; however, the intersection between the two, which is early prediction of target conditions in etiology-specific ARDS, has not been well-studied. We aimed to develop and validate a machine-learning model for the early prediction of moderate-to-severe condition of inhalation-induced ARDS.

Methods

Clinical expertise was applied with data-driven analysis. Using data from electronic intensive care units (retrospective derivation cohort) and the three most accessible vital signs (i.e. heart rate, temperature, and respiratory rate) together with feature engineering, we applied a random forest approach during the time window of 90 h that ended 6 h prior to the onset of moderate-to-severe respiratory failure (the ratio of partial pressure of arterial oxygen to fraction of inspired oxygen ≤ 200 mmHg).

Results

The trained random forest classifier was validated using two independent validation cohorts, with an area under the curve of 0.9127 (95% confidence interval 0.8713–0.9542) and 0.9026 (95% confidence interval 0.8075–1), respectively. A Stable and Interpretable RUle Set (SIRUS) was used to extract rules from the RF to provide guidelines for clinicians. We identified several predictive factors, including resp_96h_6h_min < 9, resp_96h_6h_mean ≥ 16.1, HR_96h_6h_mean ≥ 102, and temp_96h_6h_max > 100, that could be used for predicting inhalation-induced ARDS (moderate-to-severe condition) 6 h prior to onset in critical care units. (‘xxx_96h_6h_min/mean/max’: the minimum/mean/maximum values of the xxx vital sign collected during a 90 h time window beginning 96 h prior to the onset of ARDS and ending 6 h prior to the onset from every recorded blood gas test).

Conclusions

This newly established random forest‑based interpretable model shows good predictive ability for moderate-to-severe inhalation-induced ARDS and may assist clinicians in decision-making, as well as facilitate the enrolment of patients in prevention programmes to improve their outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01963-7.

Effects of aerobic exercise on lipopolysaccharide-induced experimental acute lung injury in the animal model of type 1 diabetes mellitus

NEW FINDINGS

What is the central question of this study? We evaluated the effects of diabetes and exercise on lipopolysaccharide-induced acute lung injury. By providing a comprehensive analysis of redox status, blood gases and histological parameters, we aimed to contribute to the ongoing debate in the literature. What are the main findings and its importance? We demonstrated the preventive effect of exercise, but diabetes did not alter the severity of acute lung injury.

ABSTRACT

Acute lung injury (ALI) is a life-threatening respiratory condition. Diabetes (DM) is a metabolic disease characterized by hyperglycaemia. There is an ongoing debate concerning whether there is a protective effect of diabetes in ALI. Exercise is a special type of physical activity that has numerous beneficial effects. The aim of our study was to investigate the effects of diabetes and exercise on the prognosis of ALI. Male Wistar albino rats were divided into two groups (sedentary and exercise). Both groups were divided into four subgroups: Control, ALI, DM, DM+ALI (n = 6 each). Diabetes was induced by injection of streptozotocin (50 mg/kg i.p.). The maximal exercise capacity was determined with the incremental load test. Animals were exercised on a treadmill for 45 min at 70% of maximal exercise capacity, 5 days a week for 12 weeks. Acute lung injury was induced by intratracheal injection of lipopolysaccharide (100 μg/100 g body weight) 24 h before the end of the experiment. We performed arterial blood gas analysis. Redox status was measured in both plasma and lung tissue. Malondialdehyde and 8-hydroxy-2'-deoxyguanosine levels were measured in lung tissue. Lung tissue was evaluated histologically. Acute lung injury caused significant damage in the lung tissue, which was verified histologically, with an increase in oxidative stress parameters. Exercise prevented the lung damage induced by ALI and reduced oxidative stress in the lung tissue. Diabetes did not alter the magnitude of damage done by ALI. Exercise showed a protective effect against DM and ALI in rats. The effect of DM was insignificant for the prognosis of ALI.

Can Serum Fibrinogen Predict ARDS?

Acute respiratory distress syndrome (ARDS) has a worldwide mortality of 10% to 30% with severe pneumonia being the primary cause. Diagnosis relies on clinical criteria which may lead to under-recognition and delayed evidence-based interventions. In previous studies, plasma fibrinogen was associated with progression to ARDS among patients with severe pneumonia. This is a prospective cohort study wherein we hypothesized that levels of plasma fibrinogen and change in levels of fibrinogen can predict development of ARDS among a cohort of patients with severe pneumonia based on the Infectious Diseases Society of America (IDSA) and the American Thoracic Society (ATS) consensus criteria. After acquiring consent, plasma fibrinogen levels were extracted upon enrollment and after 48 hours. These extraction times were arbitrarily chosen to determine whether levels rise or decline in relation to the course of disease. A total of 47 patients were prospectively followed within 7 days of enrollment, then divided into 2 groups, which included those who developed ARDS (n = 12, 25%) and those who did not (n = 35, 75%). Fibrinogen levels at baseline had sensitivity and specificity of 41.7% and 57.1%, respectively (P = .932) with an area under the curve (AUC) of 0.492; levels after 48 hours had sensitivity and specificity of 55.6% and 65.6%, respectively (P = .729) with an AUC of 0.538; and delta fibrinogen levels had sensitivity and specificity of 55.6% and 62.5%, respectively (P = 0.581) with an AUC of 0.561. Based on this study, plasma fibrinogen is an unreliable biomarker for predicting ARDS development in patients with severe pneumonia. In setting up this study, we experienced limitations which we had to accept but realizations of these led to the discovery of potential research areas. To our knowledge, this is the first Philippine study attempting to discover a biomarker for ARDS progression. It is recommended that further investigation on local incidence and other biomarkers for ARDS should be done.

A systematic review of biomarkers multivariately associated with acute respiratory distress syndrome development and mortality

Background

Heterogeneity of acute respiratory distress syndrome (ARDS) could be reduced by identification of biomarker-based phenotypes. The set of ARDS biomarkers to prospectively define these phenotypes remains to be established.

Objective

To provide an overview of the biomarkers that were multivariately associated with ARDS development or mortality.

Data sources

We performed a systematic search in Embase, MEDLINE, Web of Science, Cochrane CENTRAL, and Google Scholar from inception until 6 March 2020.

Study selection

Studies assessing biomarkers for ARDS development in critically ill patients at risk for ARDS and mortality due to ARDS adjusted in multivariate analyses were included.

Data extraction and synthesis

We included 35 studies for ARDS development (10,667 patients at risk for ARDS) and 53 for ARDS mortality (15,344 patients with ARDS). These studies were too heterogeneous to be used in a meta-analysis, as time until outcome and the variables used in the multivariate analyses varied widely between studies. After qualitative inspection, high plasma levels of angiopoeitin-2 and receptor for advanced glycation end products (RAGE) were associated with an increased risk of ARDS development. None of the biomarkers (plasma angiopoeitin-2, C-reactive protein, interleukin-8, RAGE, surfactant protein D, and Von Willebrand factor) was clearly associated with mortality.

Conclusions

Biomarker data reporting and variables used in multivariate analyses differed greatly between studies. Angiopoeitin-2 and RAGE in plasma were positively associated with increased risk of ARDS development. None of the biomarkers independently predicted mortality. Therefore, we suggested to structurally investigate a combination of biomarkers and clinical parameters in order to find more homogeneous ARDS phenotypes.

PROSPERO identifier

PROSPERO, CRD42017078957

Epidemiological and Clinical Profiles of Patients with Acute Respiratory Distress Syndrome Admitted to Medical Intensive Care in Qatar: A Retrospective Analysis of the Data Registry for the Year 2015

Background: Although acute respiratory distress syndrome (ARDS) is a common reason for admission to intensive care units, limited information is available about the epidemiological and clinical characteristics of these patients in Middle Eastern countries. Qatar is a high per capita income country with a large multinational expatriate population. Hamad General Hospital is our main tertiary referral center with the largest medical intensive care unit (MICU). Method: A retrospective cross-sectional study was conducted to extract data from the MICU registry for 101 patients aged >14 years who were admitted with ARDS from January 2015 to December 2015. Results: In 2015, a total of 101 (14.8%) of 682 patients admitted to MICU were diagnosed with ARDS. Males comprised 71.3% and females 28.7%. The mean age of the study population was 44.96 ± 17.97 years. Community-acquired bacterial and viral pneumonia were the most common reasons for ARDS. Crude mortality rate was 35%. The mean age of survivors was 42.09 ± 13.58 years compared with 50.36 ± 16.84 years of non-survivors (p = 0.008). Mortality was associated with increasing age, the Acute Physiologic Assessment and Chronic Health Evaluation II severity score, lower P/F ratio, higher Murray's score, higher PCO₂, lower pH, and circulatory support with vasopressors. Preexisting comorbidities did not contribute to high mortality. No difference in mortality was noted with higher versus lower positive end expiratory pressure. The prone position was used in 8% of the cases. Twenty-seven (27%) patients had undergone salvage therapy with extracorporeal membrane oxygenation (ECMO) that resulted in a survival rate of 44%. ARDS was associated with acute renal failure requiring dialysis in 28.7% of the cases, pneumothoraces in 4%, ventilator-associated pneumonia in 7.9%, and central line-associated bloodstream infection in 2%. ARDS led to a prolonged length of stay compared with the average length of stay in MICU. Conclusion: Community-acquired bacterial and viral pneumonia were the most common causes of ARDS at our center. Critical care outcome correlated with the severity of the disease. ECMO was used as salvage therapy in our center.

Serum interleukin-18: A novel prognostic indicator for acute respiratory distress syndrome

The aim of this study is to determine the biological function of serum interleukin-18 (IL-18) on prognosis in acute respiratory distress syndrome (ARDS).From October 2016 to September 2017, 150 patients with ARDS in the ICU were enrolled according to the Berlin 2012 definition. The enzyme-linked immunosorbent assay (ELISA) was used to detect the expression level of IL-18 in serum isolated from the patients. Patients were divided into survival group (82 cases) and non-survival group (68 cases) and followed up for at least 2 months. The serum IL-18 expression level on the prognosis was calculated by receiver operating characteristic curve (ROC).The expression level of serum IL-18 was significantly higher in the non-survival group than that in the survival group (P < .05). Based on the ROC curve, the sensitivity and specificity of IL-18 as a predictor of prognosis at a cutoff of 509.5 pg/mL were 88% and 82%, respectively, and the area under the curve (RUC) was 0.84 (P < .05).The expression level of serum IL-18 could be used to evaluate the possible outcomes of patients with ARDS.

Endocan, a Risk Factor for Developing Acute Respiratory Distress Syndrome among Severe Pneumonia Patients

Background

Severe pneumonia (SP) has been widely accepted as a major cause for acute respiratory distress syndrome (ARDS), and the development of ARDS is significantly associated with increased mortality. This study aimed to identify potential predictors for ARDS development in patients with SP.

Methods

Eligible SP patients at admission from January 2013 to June 2017 were prospectively enrolled, and ARDS development within hospital stay was identified. Risk factors for ARDS development in SP patients were analyzed by univariate and multivariate logistic regression analysis. The receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC) was performed for the predictive value of endocan for ARDS development.

Results

A total of 145 SP patients were eventually enrolled into the final analysis, of which 37 developed ARDS during the hospital stay. Our final multivariate logistic regression analysis suggested plasma endocan expression as the only independent risk factor for ARDS development in SP patients (OR: 1.57, 95% CI: 1.14–2.25, P=0.021). ROC curve analysis of plasma endocan resulted in an AUC of 0.754, 95% CI of 0.642–0.866, a cutoff value of 11.6 ng/mL, a sensitivity of 78.7%, and a specificity of 70.3%, respectively (P < 0.01).

Conclusions

Endocan expression at ICU admission is a reliable predictive factor in predicting ARDS in patients with SP.

The effect of diabetes on the risk and mortality of acute lung injury/acute respiratory distress syndrome: A meta-analysis

BACKGROUND

The role of pre-existing diabetes in acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is still controversial. This systematic review and meta-analysis of observational studies aimed to evaluate the effect of diabetes on the risk and mortality of ALI/ARDS.

METHODS

A comprehensive literature search was performed in PubMed, Scopus, Cochrane Central Register of Controlled Trails and Web of Science for their inception to September 2018. Summary risk estimates were calculated with a DerSimonian and Laird random-effects model. Heterogeneity was evaluated using Cochran chi-square test and the I statistic.

RESULTS

Ultimately, 14 studies with a total of 6613 ALI/ARDS cases were included. The risk of ALI/ARDS was not significantly reduced in diabetes patients (OR 0.82, 95% CI 0.57-1.18, P = .283), with obvious heterogeneity across studies (I = 72.5%, P < .001). Further analyses in the meta-analysis also showed no statistically significant associations between pre-existing diabetes and in-hospital mortality (OR 0.79, 95% CI 0.51-1.21, P = .282) or 60-day mortality of ALI/ARDS (OR 0.91, 95% CI 0.75-1.11, P = .352).

CONCLUSION

This systematic review and meta-analysis of observational studies indicates that pre-existing diabetes have no effect on the risk and mortality of ALI/ARDS.