Drug repurposing of cyclin-dependent kinase inhibitors for neutrophilic acute respiratory distress syndrome and psoriasis.

BACKGROUND: Neutrophilic inflammation, characterized by dysregulated neutrophil activation, triggers a variety of inflammatory responses such as chemotactic infiltration, oxidative bursts, degranulation, neutrophil extracellular traps (NETs) formation, and delayed turnover. This type of inflammation is pivotal in the pathogenesis of acute respiratory distress syndrome (ARDS) and psoriasis. Despite current treatments, managing neutrophil-associated inflammatory symptoms remains a significant challenge. AIM OF REVIEW: This review emphasizes the role of cyclin-dependent kinases (CDKs) in neutrophil activation and inflammation. It aims to highlight the therapeutic potential of repurposing CDK inhibitors to manage neutrophilic inflammation, particularly in ARDS and psoriasis. Additionally, it discusses the necessary precautions for the clinical application of these inhibitors due to potential off-target effects and the need for dose optimization. KEY SCIENTIFIC CONCEPTS OF REVIEW: CDKs regulate key neutrophilic functions, including chemotactic responses, degranulation, NET formation, and apoptosis. Repurposing CDK inhibitors, originally developed for cancer treatment, shows promise in controlling neutrophilic inflammation. Clinical anticancer drugs, palbociclib and ribociclib, have demonstrated efficacy in treating neutrophilic ARDS and psoriasis by targeting off-label pathways, phosphoinositide 3-kinase (PI3K) and phosphodiesterase 4 (PDE4), respectively. While CDK inhibitors offer promising therapeutic benefits, their clinical repurposing requires careful consideration of off-target effects and dose optimization. Further exploration and clinical trials are necessary to ensure their safety and efficacy in treating inflammatory conditions.

Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach.

Acute respiratory distress syndrome (ARDS) is a devastating critical care syndrome with significant morbidity and mortality. The objective of this study was to evaluate the predictive values of dynamic clinical indices by developing machine-learning (ML) models for early and accurate clinical assessment of the disease prognosis of ARDS. We conducted a retrospective observational study by applying dynamic clinical data collected in the ARDSNet FACTT Trial (n = 1000) to ML-based algorithms for predicting mortality. In order to compare the significance of clinical features dynamically, we further applied the random forest (RF) model to nine selected clinical parameters acquired at baseline and day 3 independently. An RF model trained using clinical data collected at day 3 showed improved performance and prognostication efficacy (area under the curve [AUC]: 0.84, 95% CI: 0.78-0.89) compared to baseline with an AUC value of 0.72 (95% CI: 0.65-0.78). Mean airway pressure (MAP), bicarbonate, age, platelet count, albumin, heart rate, and glucose were the most significant clinical indicators associated with mortality at day 3. Thus, clinical features collected early (day 3) improved performance of integrative ML models with better prognostication for mortality. Among these, MAP represented the most important feature for ARDS patients' early risk stratification.

Chest CT Findings at Six Months Following COVID-19 ARDS - Correlation With the mMRC Dyspnea Scale and Pulmonary Function Tests.

Background: Many survivors of severe COVID-19 pneumonia experience lingering respiratory issues. There is limited research on follow-up chest imaging findings in patients with COVID-19 ARDS, particularly in relation to their mMRC dyspnea scores and pulmonary function tests (PFTs). This study addresses this gap by investigating the clinical characteristics, mMRC dyspnea scores, PFTs, and chest CT findings of COVID-19 ARDS patients at the 6 months post-recovery. By analyzing these variables together, we aim to gain a better understanding of the long-term health consequences of COVID-19 ARDS. Methods: This prospective observational study included 56 subjects with COVID-19 ARDS with dyspnea at the six-month follow-up visits. These patients were evaluated by chest CT, mMRC dyspnea scale, and PFT. The CT severity score was calculated individually for each of the four major imaging findings - ground glass opacities (GGOs), parenchymal/atelectatic bands, reticulations/septal thickening, and consolidation - using a modified CT severity scoring system. Statistics were carried out to find any association between individual CT chest findings and the mMRC dyspnea scale and forced vital capacity (FVC). p values < 0.05 were considered statistically significant. Results: Our study population had a mean age of 55.86 ± 9.60 years, with 44 (78.6%) being men. Grades 1, 2, 3, and 4 on the mMRC dyspnea scale were seen in 57.1%, 30.4%, 10.7%, and 1.8% of patients respectively. Common CT findings observed were GGOs (94.6%), reticulations/septal thickening (96.4%), parenchymal/atelectatic bands (92.8%), and consolidation (14.3%). The mean modified CT severity scores for GGOs, reticulations/septal thickening, parenchymal/atelectatic bands, and consolidation were 10.32 ± 5.51 (range: 0-21), 7.66 ± 4.33 (range: 0-19), 4.77 ± 3.03 (range: 0-14) and 0.29 ± 0.91 (range 0-5) respectively. Reticulations/septal thickening (p = 0.0129) and parenchymal/atelectatic bands (p = 0.0453) were associated with an increased mMRC dyspnea scale. Parenchymal/atelectatic bands were also associated with abnormal FVC (<80%) (p = 0.0233). Conclusion: Six-month follow-up chest CTs of COVID-19 ARDS survivors with persistent respiratory problems showed a statistically significant relationship between increased mMRC dyspnea score and imaging patterns of reticulations/septal thickening and parenchymal/atelectatic bands; while parenchymal/atelectatic bands also showed a statistically significant correlation with reduced FVC.

Circulating Biomarkers of Endothelial Dysfunction Associated With Ventilatory Ratio and Mortality in ARDS Resulting From SARS-CoV-2 Infection Treated With Antiinflammatory Therapies.

BACKGROUND: The association of plasma biomarkers and clinical outcomes in ARDS resulting from SARS-CoV-2 infection predate the evidence-based use of immunomodulators. RESEARCH QUESTION: Which plasma biomarkers are associated with clinical outcomes in patients with ARDS resulting from SARS-CoV-2 infection treated routinely with immunomodulators? STUDY DESIGN AND METHODS: We collected plasma from patients with ARDS resulting from SARS-CoV-2 infection within 24 h of admission to the ICU between December 2020 and March 2021 (N = 69). We associated 16 total biomarkers of inflammation (eg, IL-6), coagulation (eg, D-dimer), epithelial injury (eg, surfactant protein D), and endothelial injury (eg, angiopoietin-2) with the primary outcome of in-hospital mortality and secondary outcome of ventilatory ratio (at baseline and day 3). RESULTS: Thirty patients (43.5%) died within 60 days. All patients received corticosteroids and 6% also received tocilizumab. Compared with survivors, nonsurvivors demonstrated a higher baseline modified Sequential Organ Failure Assessment score (median, 8.5 [interquartile range (IQR), 7-9] vs 7 [IQR, 5-8]); P = .004), lower Pao2 to Fio2 ratio (median, 153 [IQR, 118-182] vs 184 [IQR, 142-247]; P = .04), and higher ventilatory ratio (median, 2.0 [IQR, 1.9-2.3] vs 1.5 [IQR, 1.4-1.9]; P < .001). No difference was found in inflammatory, coagulation, or epithelial biomarkers between groups. Nonsurvivors showed higher median neural precursor cell expressed, developmentally down-regulated 9 (NEDD9) levels (median, 8.4 ng/mL [IQR, 7.0-11.2 ng/mL] vs 6.9 ng/mL [IQR, 5.5-8.0 ng/mL]; P = .0025), von Willebrand factor domain A2 levels (8.7 ng/mL [IQR, 7.9-9.7 ng/mL] vs 6.5 ng/mL [IQR, 5.7-8.7 ng/mL]; P = .007), angiopoietin-2 levels (9.0 ng/mL [IQR, 7.9-14.1 ng/mL] vs 7.0 ng/mL [IQR, 5.6-10.6 ng/mL]; P = .01), and syndecan-1 levels (15.9 ng/mL [IQR, 14.5-17.5 ng/mL] vs 12.6 ng/mL [IQR, 10.5-16.1 ng/mL]; P = .01). Only NEDD9 level met the adjusted threshold for significance (P < .003). Plasma NEDD9 level was associated with 60-day mortality (adjusted OR, 9.7; 95% CI, 1.6-60.4; P = .015). Syndecan-1 level correlated with both baseline (ρ = 0.4; P = .001) and day 3 ventilatory ratio (ρ = 0.5; P < .001). INTERPRETATION: Biomarkers of inflammation, coagulation, and epithelial injury were not associated with clinical outcomes in a small cohort of patients with ARDS uniformly treated with immunomodulators. However, endothelial biomarkers, including plasma NEDD9, were associated with 60-day mortality.

Role of Alveolar-Arterial Difference in Estimation of Extravascular Lung Water in COVID-19-Related ARDS.

BACKGROUND: The dominant feature of COVID-19-associated ARDS is gas exchange impairment. Extravascular lung water index is a surrogate for lung edema and reflects the level of alveolocapillary disruption. The primary aim was the prediction of extravascular lung water index by the alveolar-arterial oxygen difference. The secondary aims were in determining the relationship between the extravascular lung water index and other oxygenation parameters, the FIO2 , end-tidal oxygen concentration, pulmonary oxygen gradient (FIO2 minus end-tidal oxygen concentration), and PaO2 . METHODS: This observational prospective single-center study was performed at the Department of Anaesthesiology and Intensive Care, The University Hospital in Ostrava, The Czech Republic, during the COVID-19 pandemic, from March 20, 2020, until May 24, 2021. RESULTS: The relationship between the extravascular lung water index and alveolar-arterial oxygen difference showed only a mild-to-moderate correlation (r = 0.33, P < .001). Other extravascular lung water index correlations were as follows: FIO2 (r = 0.33, P < .001), end-tidal oxygen concentration (r = 0.26, P = .0032), FIO2 minus end-tidal oxygen concentration (r = 0.15, P = .0624), and PaO2 (r = -0.15, P = .01). CONCLUSIONS: The alveolar-arterial oxygen difference does not reliably correlate with the extravascular lung water index and the degree of lung edema in COVID-19-associated ARDS.

PD-L1 and PD-1 Are Associated with Clinical Outcomes and Alveolar Immune Cell Activation in ARDS.

The relationship between the Programmed Death-Ligand 1 (PD-L1)/Programmed Death-1 (PD-1) pathway, lung inflammation, and clinical outcomes in acute respiratory distress syndrome (ARDS) is poorly understood. We sought to determine whether PD-L1/PD-1 in the lung or blood is associated with ARDS and associated severity. We measured soluble PD-L1 (sPD-L1) in plasma and lower respiratory tract samples (ARDS1 (n = 59) and ARDS2 (n = 78)) or plasma samples alone (ARDS3 (n = 149)) collected from subjects with ARDS and tested for associations with mortality using multiple regression. We used mass cytometry to measure PD-L1/PD-1 expression and intracellular cytokine staining in cells isolated from bronchoalveolar lavage fluid (BALF) (n = 18) and blood (n = 16) from critically-ill subjects with or without ARDS enrolled from a fourth cohort. Higher plasma levels of sPD-L1 were associated with mortality in ARDS1, ARDS2, and ARDS3. In contrast, higher levels of sPD-L1 in the lung were either not associated with mortality (ARDS2) or were associated with survival (ARDS1). Alveolar PD-1POS T cells had more intracellular cytokine staining compared with PD-1NEG T cells. Subjects without ARDS had a higher ratio of PD-L1POS alveolar macrophages to PD-1POS T cells compared with subjects with ARDS. We conclude that sPD-L1 may have divergent cellular sources and/or functions in the alveolar vs. blood compartments given distinct associations with mortality. Alveolar leukocyte subsets defined by PD-L1/PD-1 cell-surface expression have distinct cytokine secretion profiles, and the relative proportions of these subsets are associated with ARDS.

Absolute values of regional ventilation-perfusion mismatch in patients with ARDS monitored by electrical impedance tomography and the role of dead space and shunt compensation.

BACKGROUND: Assessment of regional ventilation/perfusion (V'/Q) mismatch using electrical impedance tomography (EIT) represents a promising advancement for personalized management of the acute respiratory distress syndrome (ARDS). However, accuracy is still hindered by the need for invasive monitoring to calibrate ventilation and perfusion. Here, we propose a non-invasive correction that uses only EIT data and characterized patients with more pronounced compensation of V'/Q mismatch. METHODS: We enrolled twenty-one ARDS patients on controlled mechanical ventilation. Cardiac output was measured invasively, and ventilation and perfusion were assessed by EIT. Relative V'/Q maps by EIT were calibrated to absolute values using the minute ventilation to invasive cardiac output (MV/CO) ratio (V'/Q-ABS), left unadjusted (V'/Q-REL), or corrected by MV/CO ratio derived from EIT data (V'/Q-CORR). The ratio between ventilation to dependent regions and perfusion reaching shunted units ( V D ' /QSHUNT) was calculated as an index of more effective hypoxic pulmonary vasoconstriction. The ratio between perfusion to non-dependent regions and ventilation to dead space units (QND/ V DS ' ) was calculated as an index of hypocapnic pneumoconstriction. RESULTS: Our calibration factor correlated with invasive MV/CO (r = 0.65, p < 0.001), showed good accuracy and no apparent bias. Compared to V'/Q-ABS, V'/Q-REL maps overestimated ventilation (p = 0.013) and perfusion (p = 0.002) to low V'/Q units and underestimated ventilation (p = 0.011) and perfusion (p = 0.008) to high V'/Q units. The heterogeneity of ventilation and perfusion reaching different V'/Q compartments was underestimated. V'/Q-CORR maps eliminated all these differences with V'/Q-ABS (p > 0.05). Higher V D ' / Q SHUNT correlated with higher PaO2/FiO2 (r = 0.49, p = 0.025) and lower shunt fraction (ρ = - 0.59, p = 0.005). Higher Q ND / V DS ' correlated with lower PEEP (ρ = - 0.62, p = 0.003) and plateau pressure (ρ = - 0.59, p = 0.005). Lower values of both indexes were associated with less ventilator-free days (p = 0.05 and p = 0.03, respectively). CONCLUSIONS: Regional V'/Q maps calibrated with a non-invasive EIT-only method closely approximate the ones obtained with invasive monitoring. Higher efficiency of shunt compensation improves oxygenation while compensation of dead space is less needed at lower airway pressure. Patients with more effective compensation mechanisms could have better outcomes.

Trimethoprim-sulfamethoxazole acute respiratory distress syndrome requiring lung transplantation.

Trimethoprim-sulfamethoxazole (TMP-SMX) acute respiratory distress syndrome (ARDS) is a rare, but severe complication of a commonly prescribed antibiotic. TMP-SMX typically affects young, otherwise well patients with a specific human leukocyte antigen type (HLA-B*07:02 and HLA-C*07:02). The condition is poorly understood with a unique pathological appearance and mechanism that remains unclear. Mortality rate is greater than one third. We describe the case of a previously well 18-year-old woman treated with a prolonged course of TMP-SMX for a complex urinary tract infection who developed rapidly progressive respiratory failure requiring prolonged intensive care admission, extra-corporeal membranous oxygenation, and eventual lung transplantation. No targeted treatment exists, further research is required to better understand disease pathogenetic mechanisms and potential therapeutic interventions.

The impact of positive end-expiratory pressure on right ventricular function in patients with moderate-to-severe ARDS: a prospective paired-design study.

Objective: To determine the effects of varying positive end-expiratory pressures (PEEPs) on right ventricular function, hemodynamics, oxygenation, and the incidence of acute cor pulmonale (ACP) in patients with moderate-to-severe acute respiratory distress syndrome (ARDS). Methods: This prospective paired-design study involved patients with moderate-to-severe ARDS in the ICU. Participants received lung-protective ventilation and hemodynamic monitoring. During the study, mechanical ventilation was administered with PEEPs of 5 cmH2O, 10 cmH2O, and 15 cmH2O, while maintaining an end-inspiratory plateau pressure ≤ 30 cmH2O. Various assessments, including transthoracic echocardiography, cardiac output measurement, and blood gas analysis, were conducted at baseline and after 1 h of ventilation at each PEEP. Subsequently, variations in ventilation oxygenation, echocardiographic parameters, and hemodynamic indicators under different PEEPs were analyzed to explore the potential effects of PEEP on right ventricular function and hemodynamics, as well as the incidence of ACP. Results: A total of 317 ARDS patients were screened. Among them, 104 met the diagnostic criteria for moderate-to-severe ARDS, and 52 completed the study. The baseline PEEP of these 52 participants, acquired before commencement, was 11.5 ± 1.7 cmH2O, and the incidence of ACP was 25.0% (13/52). Intensive care unit mortality, overall hospital mortality, and 28-day mortality rates were 19.2% (10/52), 21.2% (11/52), and 32.7% (17/52), respectively. During the study, ACP incidences at PEEPs of 5 cmH2O, 10 cmH2O, and 15 cmH2O were 17.3% (9/52), 21.2% (11/52), and 38.5% (20/52), respectively. Meanwhile, the PaO2/FiO2 ratio improved with increasing PEEP, reaching 162.0 (140.9, 174.0), 171.0 (144.0, 182.0), and 176.5 (151.0, 196) mmHg at PEEPs of 5 cmH2O, 10 cmH2O, and 15 cmH2O, respectively. In addition, higher PEEPs were associated with a slight increase in PaCO2, showing statistically significant differences compared to moderate and low PEEPs. Compared to a PEEP of 5 cmH2O or 10 cmH2O, right ventricular function exhibited substantial changes at 15 cmH2O PEEP, manifested as increased pulmonary artery systolic pressure, enlarged right ventricular end-diastolic area, and decreased tricuspid annular plane systolic excursion, all with significant differences. Conversely, variations in left ventricular end-diastolic area and ejection fraction were not statistically significant. In terms of hemodynamics, increasing PEEP resulted in a decline in cardiac index (CI), with statistically significant differences between different PEEPs. Specifically, compared to the value at a PEEP of 5 cmH2O, the CI at a PEEP of 15 cmH2O decreased by 14.3% (2.63 [2.20, 2.95] vs. 3.07 [2.69, 3.67], p < 0.001). The decline in the stroke volume index with PEEP was more obvious (22.1 [18.4, 27.1] vs. 27.0 [24.2, 33.0], p < 0.001), reaching 18.1%. Additionally, both end-diastolic volume index and extravascular lung water index decreased significantly with increasing PEEP, while the pulmonary vascular permeability index remained unaffected. Conclusion: Different PEEPs can affect the incidence of ACP in patients with moderate-to-severe ARDS. High PEEP improves oxygenation and reduces extravascular lung water without significantly affecting the pulmonary vascular permeability index and left ventricular systolic function. Nevertheless, it can cause right ventricular dilation, as well as substantial declines in right ventricular systolic function and CI, thereby causing ACP.

Increased impairment of cerebral autoregulation in COVID-19 associated pulmonary failure requiring extracorporeal membrane oxygenation.

Introduction: Cerebrovascular complications are feared but also commonly reported in patients with COVID-19 requiring extracorporeal membrane oxygenation (ECMO) support therapy. Besides other reasons, a connection between impaired cerebral autoregulation and SARS-CoV-2 infection as a mechanism for an increase in cerebrovascular complications has been hypothesized. Methods: In an observational single-center study, we investigated a cohort of 48 patients requiring veno-venous ECMO support therapy with (n = 31) and without SARS-CoV-2 infection (n = 17). Cerebral autoregulation was assessed with the cerebral oximetry-derived autoregulation index (ORx) based on a moving correlation between arterial pressure and cerebral oximetry. Results: Patients with ECMO support therapy and SARS-CoV-2 experienced more time with impaired cerebral autoregulation than without SARS-CoV-2 [17 ± 9 vs. 13 ± 9% (p = 0.027)]. Patients with SARS-CoV-2 suffering from cerebrovascular complications had more time with impaired autoregulation than non SARS-CoV-2 patients with these complications (19 ± 9 vs. 10 ± 4%, p = 0.032). Conclusion: Our results suggest a connection between SARS-CoV-2 and impaired cerebral autoregulation as well as cerebrovascular complications in SARS-CoV-2 patients.

Pulmonary herpes simplex virus and cytomegalovirus in patients with acute respiratory distress syndrome related to COVID-19.

PURPOSE: Human herpesviruses, particularly cytomegalovirus (CMV) and herpes simplex virus (HSV), frequently reactivate in critically ill patients, including those with acute respiratory distress syndrome (ARDS) related to coronavirus disease 2019 (COVID-19). The clinical interpretation of pulmonary herpesvirus reactivation is challenging and there is ongoing debate about its association with mortality and benefit of antiviral medication. We aimed to quantify the incidence and pathogenicity of pulmonary CMV and HSV reactivations in critically ill COVID-19 patients. METHODS: Mechanically ventilated COVID-19 patients seropositive for CMV or HSV were included in this observational cohort study. Diagnostic bronchoscopy with bronchoalveolar lavage was performed routinely and analyzed for alveolar viral loads and inflammatory biomarkers. Utilizing joint modeling, we explored the dynamic association between viral load trajectories over time and mortality. We explored alveolar inflammatory biomarker dynamics between reactivated and non-reactivated patients. RESULTS: Pulmonary reactivation (> 104 copies/ml) of CMV occurred in 6% of CMV-seropositive patients (9/156), and pulmonary reactivation of HSV in 37% of HSV-seropositive patients (63/172). HSV viral load dynamics prior to or without antiviral treatment were associated with increased 90-day mortality (hazard ratio [HR] 1.24, 95% confidence interval [CI] 1.04-1.47). The alveolar concentration of several inflammatory biomarkers increased with HSV reactivation, including interleukin (IL)-6, IL-1ß, granulocyte colony stimulating factor (G-CSF), and tumor necrosis factor (TNF). CONCLUSION: In mechanically ventilated COVID-19 patients, HSV reactivations are common, while CMV reactivations were rare. HSV viral load dynamics prior to or without antiviral treatment are associated with mortality. Alveolar inflammation is elevated after HSV reactivation.

The Ventilatory Ratio as a Predictor of Successful Weaning from a Veno-Venous Extracorporeal Membrane Oxygenator.

Background: Veno-venous extracorporeal membrane oxygenation (VV-ECMO) is a critical intervention for patients with severe lung failure, especially acute respiratory distress syndrome (ARDS). The weaning process from ECMO relies largely on expert opinion due to a lack of evidence-based guidelines. The ventilatory ratio (VR), which correlates with dead space and mortality in ARDS, is calculated as [minute ventilation (mL/min) x arterial pCO2 (mmHg)]/[predicted body weight × 100 × 37.5]. Objectives: The aim of this study was to determine whether the VR alone can serve as a reliable predictor of safe or unsafe liberation from VV-ECMO in critically ill patients. Methods: A multicenter retrospective analysis was conducted, involving ARDS patients undergoing VV-ECMO weaning at Massachusetts General Hospital (January 2016 - December 2020) and at the University Hospital Aachen (January 2012-December 2021). Safe liberation was defined as no need for ECMO recannulation within 48 h after decannulation. Clinical parameters were obtained for both centers at the same time point: 30 min after the start of the SGOT (sweep gas off trial). Results: Of the patients studied, 83.3% (70/84) were successfully weaned from VV-ECMO. The VR emerged as a significant predictor of unsafe liberation (OR per unit increase: 0.38; CI: 0.17-0.81; p = 0.01). Patients who could not be safely liberated had longer ICU and hospital stays, with a trend towards higher mortality (38% vs. 13%; p = 0.05). Conclusions: The VR may be a valuable predictor for safe liberation from VV-ECMO in ARDS patients, with higher VR values associated with an elevated risk of unsuccessful weaning and adverse clinical outcomes.

Platelet Indices as Novel Surrogate Markers for the Prognosis of COVID-19 Infection: An Observational Study.

Background  The new severe acute respiratory syndromecoronavirus 2 (SARS-CoV-2) causes severe acute respiratory illness accountable for causing the coronavirus disease 2019 (COVID-19) illness. Thrombotic issues, acute respiratory distress syndrome (ARDS), and cytokine storm are significant contributors to morbidity and mortality in patients with COVID-19. Elevated D-dimer levels and prothrombin times are further indicators of abnormal coagulation parameters in COVID-19 patients. This study aimed to study the platelet indices as prognostic markers in COVID-19 infection. Methods In this prospective observational study, 150 real-time reverse transcription-polymerase chain reaction (RT-PCR)-positive COVID-19 patients were enrolled between October 2020 and September 2021. All the subjects were screened and explained the study procedure in their native language. Following enrolment, a detailed history and physical examination were performed. Subsequently, laboratory investigations were performed, and patients were subjected to high-resolution computed tomography (HRCT) examination to classify patients into mild, moderate, and severe according to the severity of the illness. The platelet indices taken into account were plateletcrit (PCT) in percentage, platelet count (PLT) in lakh per microlitre, mean platelet volume (MPV) in femtolitres, and platelet distribution width (PDW) in femtolitres. Results The mean PLT was significantly greater among survivors than non-survivors (2.03 ± 0.72 versus 1.76 ± 0.47; p-value = 0.018). The mean MPV (10.42 ± 0.53 versus 9.22 ± 0.64; p-value <0.0001) and PDW (17.99 ± 1.53 versus 16.54 ± 0.91 fl; p-value <0.0001) were significantly greater among non-survivors than survivors. However, the mean PCT was significantly greater among survivors than non-survivors (0.22 ± 0.03% versus 0.18 ± 0.33%; p-value <0.0001). At a cut-off of 0.213, the sensitivity and specificity of PCT in predicting death were found to be 79.2% and 74.5%, respectively. At a cut-off of 16.75, the sensitivity and specificity of PDW in predicting death were found to be 68.8% and 59.8%, respectively. The findings demonstrated a relationship between elevated MPV and PDW and mortality and severe COVID-19 infection. Increased PCT was connected to higher survival, with a specificity and sensitivity of 87.5% and 75.5%, respectively, and MPV >9.75 may predict death. PDW >16.75 exhibited a specificity and sensitivity of 68.8% and 59.8%, respectively, in predicting death. With comparable sensitivity and specificity of 79.2% and 74.5%, PCT >0.213 may predict death. Conclusion In severely sick COVID-19 patients, platelet indices should be routinely calculated and can be utilized as simple, low-cost prognostic indicators.

A Proof of Concept Study on the Comfort and Usability of a Supportive Pillow for Pregnant Patients with COVID-19 Acute Respiratory Distress Syndrome.

Background: The prone position has been seen to benefit patients experiencing acute respiratory distress syndrome. However, performing this position in pregnant patients has been difficult and raises safety concerns. Objective: The current study aimed to test the use of a supportive pillow (Prone Pillow for Pregnant Patients or 4P) to address concerns regarding pregnant patients in prone position. Methods: The study prospectively evaluated the use of the prone pillow for patient comfort and usability among healthcare workers with qualitative and quantitative measures. Results: A total of three patients were recruited alongside 16 healthcare workers assisting pregnant patients to the prone position. Overall, awake pregnant patients found the pillow to be comfortable while healthcare workers perceived the pillow to be useful in improving quality of care among awake and intubated pregnant patients. CONCLUSION: The 4P is a potentially useful and beneficial product in placing pregnant patients in the prone position during episodes of acute respiratory distress. However, due to the limited sample size, more clinical trials are needed to evaluate the impact of this innovation in improving patient and healthcare worker safety.

Modeling lung endothelial dysfunction in sepsis-associated ARDS using a microphysiological system.

Endothelial dysfunction is a critical feature of acute respiratory distress syndrome (ARDS) associated with higher disease severity and worse outcomes. Preclinical in vivo models of sepsis and ARDS have failed to yield useful therapies in humans, perhaps due to interspecies differences in inflammatory responses and heterogeneity of human host responses. Use of microphysiological systems (MPS) to investigate lung endothelial function may shed light on underlying mechanisms and targeted treatments for ARDS. We assessed the response to plasma from critically ill sepsis patients in our lung endothelial MPS through measurement of endothelial permeability, expression of adhesion molecules, and inflammatory cytokine secretion. Sepsis plasma induced areas of endothelial cell (EC) contraction, loss of cellular coverage, and luminal defects. EC barrier function was significantly worse following incubation with sepsis plasma compared to healthy plasma. EC ICAM-1 expression, IL-6 and soluble ICAM-1 secretion increased significantly more after incubation with sepsis plasma compared with healthy plasma. Plasma from sepsis patients who developed ARDS further increased IL-6 and sICAM-1 compared to plasma from sepsis patients without ARDS and healthy plasma. Our results demonstrate the proof of concept that lung endothelial MPS can enable interrogation of specific mechanisms of endothelial dysfunction that promote ARDS in sepsis patients.

ARDSFlag: an NLP/machine learning algorithm to visualize and detect high-probability ARDS admissions independent of provider recognition and billing codes.

BACKGROUND: Despite the significance and prevalence of acute respiratory distress syndrome (ARDS), its detection remains highly variable and inconsistent. In this work, we aim to develop an algorithm (ARDSFlag) to automate the diagnosis of ARDS based on the Berlin definition. We also aim to develop a visualization tool that helps clinicians efficiently assess ARDS criteria. METHODS: ARDSFlag applies machine learning (ML) and natural language processing (NLP) techniques to evaluate Berlin criteria by incorporating structured and unstructured data in an electronic health record (EHR) system. The study cohort includes 19,534 ICU admissions in the Medical Information Mart for Intensive Care III (MIMIC-III) database. The output is the ARDS diagnosis, onset time, and severity. RESULTS: ARDSFlag includes separate text classifiers trained using large training sets to find evidence of bilateral infiltrates in radiology reports (accuracy of 91.9%±0.5%) and heart failure/fluid overload in radiology reports (accuracy 86.1%±0.5%) and echocardiogram notes (accuracy 98.4%±0.3%). A test set of 300 cases, which was blindly and independently labeled for ARDS by two groups of clinicians, shows that ARDSFlag generates an overall accuracy of 89.0% (specificity = 91.7%, recall = 80.3%, and precision = 75.0%) in detecting ARDS cases. CONCLUSION: To our best knowledge, this is the first study to focus on developing a method to automate the detection of ARDS. Some studies have developed and used other methods to answer other research questions. Expectedly, ARDSFlag generates a significantly higher performance in all accuracy measures compared to those methods.

Daptomycin eosinophilic pneumonia, a systematic review of the literature and case series.

PURPOSE: Daptomycin-induced eosinophilic pneumonia (DIEP) is a rare yet severe adverse event that requires rapid recognition and management. Diagnosing a definite case is challenging and involves meeting the American Thoracic Society (ATS) criteria, although alternative criteria have been suggested. This study aims to conduct a systematic review of literature and includes a case series. METHODS: Six cases of DIEP identified at Perugia Hospital, Perugia, Italy have been described. A systematic review was carried out adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement guidelines. RESULTS: a total of 74 cases of DIEP were analysed. Using ATS clinical criteria, 15 were classified as definite (20.3%), 54 as probable (73.0%), and 5 as possible (6.8%). Phillips criteria and the Lyon Algorithm identified 43/74 (58.2%) and 64/67 (95.5%) cases as definite, respectively. Bronchoalveolar lavage (BAL) was performed in 43 cases, revealing an average eosinophil count of 28.6% (SD 24.4). Radiological findings highlighted recurring features like bilateral opacities (68.1%), ground-glass opacities (41.7%), patchy infiltrates (30.6%), and peripheral predominance (19.4%). Upon suspicion, daptomycin was discontinued; 20 cases required no additional treatment, 38 received corticosteroids, and 12 received both corticosteroids and antibiotics. Recovery rates were high across all treatment types (≥ 73.7%). Most reports described rapid improvement post-withdrawal (within 96 h). CONCLUSIONS: DIEP is a rare, fast-progressing condition where early diagnosis and prompt treatment are vital. Diagnosis relies on clinical, laboratory, and radiological evaluations. Stopping daptomycin is essential, with corticosteroids often necessary. Further research is needed to enhance diagnostic accuracy for this disease.

Integrative multi-omics analysis unravels the host response landscape and reveals a serum protein panel for early prognosis prediction for ARDS.

BACKGROUND: The multidimensional biological mechanisms underpinning acute respiratory distress syndrome (ARDS) continue to be elucidated, and early biomarkers for predicting ARDS prognosis are yet to be identified. METHODS: We conducted a multicenter observational study, profiling the 4D-DIA proteomics and global metabolomics of serum samples collected from patients at the initial stage of ARDS, alongside samples from both disease control and healthy control groups. We identified 28-day prognosis biomarkers of ARDS in the discovery cohort using the LASSO method, fold change analysis, and the Boruta algorithm. The candidate biomarkers were validated through parallel reaction monitoring (PRM) targeted mass spectrometry in an external validation cohort. Machine learning models were applied to explore the biomarkers of ARDS prognosis. RESULTS: In the discovery cohort, comprising 130 adult ARDS patients (mean age 72.5, 74.6% male), 33 disease controls, and 33 healthy controls, distinct proteomic and metabolic signatures were identified to differentiate ARDS from both control groups. Pathway analysis highlighted the upregulated sphingolipid signaling pathway as a key contributor to the pathological mechanisms underlying ARDS. MAP2K1 emerged as the hub protein, facilitating interactions with various biological functions within this pathway. Additionally, the metabolite sphingosine 1-phosphate (S1P) was closely associated with ARDS and its prognosis. Our research further highlights essential pathways contributing to the deceased ARDS, such as the downregulation of hematopoietic cell lineage and calcium signaling pathways, contrasted with the upregulation of the unfolded protein response and glycolysis. In particular, GAPDH and ENO1, critical enzymes in glycolysis, showed the highest interaction degree in the protein-protein interaction network of ARDS. In the discovery cohort, a panel of 36 proteins was identified as candidate biomarkers, with 8 proteins (VCAM1, LDHB, MSN, FLG2, TAGLN2, LMNA, MBL2, and LBP) demonstrating significant consistency in an independent validation cohort of 183 patients (mean age 72.6 years, 73.2% male), confirmed by PRM assay. The protein-based model exhibited superior predictive accuracy compared to the clinical model in both the discovery cohort (AUC: 0.893 vs. 0.784; Delong test, P < 0.001) and the validation cohort (AUC: 0.802 vs. 0.738; Delong test, P = 0.008). INTERPRETATION: Our multi-omics study demonstrated the potential biological mechanism and therapy targets in ARDS. This study unveiled several novel predictive biomarkers and established a validated prediction model for the poor prognosis of ARDS, offering valuable insights into the prognosis of individuals with ARDS.

Unmasking Negative Pressure Pulmonary Edema Following Hanging: A Case Series.

Pulmonary edema is a rare mechanism of death that develops after partial hanging, a potential complication that physicians should consider early in the management of these patients. This case series discusses the presentation, evaluation, and treatment course of three patients who had attempted suicide by hanging and were admitted to the hospital. These patients were admitted to the intensive care unit after being stabilized and supportive treatment was provided. In all the cases, a radiological scan of the chest revealed diffuse infiltrates consistent with pulmonary edema on both sides, features of which were also noted during a diagnostic bronchoscopy. After providing the best intensive care in the hospital, two patients clinically improved, and one patient succumbed to cardiac arrest. As most patients will be brought dead to the hospital following hanging, negative pressure pulmonary edema remains underdiagnosed. Thus, this case series enumerates the possible etiologies of negative pressure pulmonary edema and its contribution to death following suicidal hanging.

A novel clinical prediction model for in-hospital mortality in sepsis patients complicated by ARDS: A MIMIC IV database and external validation study.

Background: Sepsis complicated by ARDS significantly increases morbidity and mortality, underscoring the need for robust predictive models to enhance patient management. Methods: We collected data on 6390 patients with ARDS-complicated sepsis from the MIMIC IV database. Following rigorous data cleaning, including outlier management, handling missing values, and transforming variables, we conducted univariate analysis and logistic multivariate regression. We employed the LASSO machine learning algorithm to identify risk factors closely associated with patient outcomes. These factors were then used to develop a new clinical prediction model. The model underwent preliminary assessment and internal validation, and its performance was further tested through external validation using data from 225 patients at a major tertiary hospital in China. This validation assessed the model's discrimination, calibration, and net clinical benefits. Results: The model, illustrated by a concise nomogram, demonstrated significant discrimination with an area under the curve (AUC) of 0.711 in the internal validation set and 0.771 in the external validation set, outperforming conventional severity scores such as the SOFA and SAPS II. It also showed good calibration and net clinical benefits. Conclusions: Our model serves as a valuable tool for identifying sepsis patients with ARDS at high risk of in-hospital mortality. This could enable the implementation of personalized treatment strategies, potentially improving patient outcomes.