Daily Ards Research Analysis

Acute respiratory distress syndrome (ARDS) involves impaired macrophage function in clearing apoptotic cells. The link between clinical hyperlactatemia in ARDS patients and poor outcomes prompted this study on the immunometabolic role of lactate in disease progression. In an LPS-induced ARDS mouse model, mice received either exogenous lactate or a lactate dehydrogenase inhibitor. Inflammatory cell infiltration was evaluated through flow cytometry and histological analysis with hematoxylin and eosin staining. Lactate signaling was confirmed in GPR81-deficient mice. In vitro, lactate metabolism during efferocytosis was studied using primary Alveolar Macrophages (AMs). Lactate accumulation, neutrophil infiltration, and elevated inflammatory factors were observed in this ARDS model. External lactate delayed inflammation resolution and worsened lung injury. GPR81

INTRODUCTION: Despite numerous randomized controlled trials, lung protective ventilation and prone positioning remain the only therapies shown to have a survival benefit in acute respiratory distress syndrome (ARDS). A National Heart, Lung, and Blood Institute workshop on the future of clinical research in ARDS suggested that identification of at-risk patients earlier in their clinical course would allow implementation of prevention strategies and facilitate study of these interventions. To this end, the Lung Injury Prevention Score (LIPS) was derived and validated to identify patients at risk of developing ARDS upon hospital admission, and the Emergency Department Lung Injury Prevention Score (EDLIPS) was subsequently derived and internally validated. For this study, we sought to externally validate EDLIPS. METHODS: We performed a validation study of EDLIPS, using data from a large, multicenter trial- the Vitamin D to Improve Outcomes by Leveraging Early Treatment (VIOLET) trial. After identifying patients who met VIOLET inclusion criteria while in the ED, variables comprising EDLIPS were extracted for each patient. We calculated area under the receiver operating characteristic curves (AUC) of EDLIPS for the VIOLET dataset. RESULTS: We identified a total of 1,270 patients. The mean age was 56, and 55% were male. The incidence of ARDS was 8.1%. EDLIPS discriminated patients who developed ARDS from those who did not with an AUC of 0.786 (95% CI, 0.740-0.832), nearly identical to its performance in the original study, which yielded an AUC of 0.784 (95% CI, 0.748-0.820). CONCLUSION: We successfully validated a risk-prediction model for the identification of ED patients at risk for ARDS in a large cohort of critically ill patients. The development of ARDS prevention trials will involve collaboration with other clinical groups, such as emergency physicians, to enroll patients as early as possible in their clinical course. EDLIPS is the first tool of its kind to undergo external validation, and it can aid in the identification of ED patients at risk for the development of ARDS.

BACKGROUND: Disparities in pediatric critical care outcomes are recognized, but national data describing Pediatric Acute Respiratory Distress Syndrome (PARDS) prevalence, mortality and temporal trends are limited. We described prevalence, and regional and racial/ethnic mortality disparities for algorithm-defined ARDS, a surrogate for PARDS in US children from 2016 to 2022. METHODS: We performed a retrospective cohort study using the 2016, 2019, and 2022 Kids' Inpatient Database (KID). Algorithm-defined ARDS was identified with an ICD-10 approach requiring acute respiratory failure from pulmonary, sepsis, or shock etiologies requiring invasive mechanical ventilation ≥24 h. The primary outcome was in-hospital mortality. Exposures were US region and Race/Ethnicity, modeled individually and jointly. Mixed-effect logistic regression models, adjusting for income quartile, APR-DRG severity of illness, hospital type, and complex chronic conditions, estimated adjusted mortalities and risk differences. FINDINGS: Algorithm-defined ARDS occurred in about 42,000 hospitalizations per year, with prevalence increasing from 0.68% (95% CI 0.67-0.69) in 2016 to 0.75% (0.74-0.75) in 2022. Overall mortality was 12.9% (12.5-13.3) in 2016, 12.5% (12.1-12.9) in 2019, and 13.7% (13.3-14.1) in 2022. In the joint model, relative to Northeastern White children (predicted 10.9%, 95% CI 9.72-12.1), risks were higher for Black children in the South (predicted 14.2%, ARD 3.27%, 1.74-4.79) and West (14.6%, ARD 3.69%, 1.39-6.00); Hispanic children in the West (12.6%, ARD 1.70%, 0.09-3.31), and children of Other race/ethnicity in the South (16.5%, ARD 5.57%, 3.14-7.99) and West (14.0%, ARD 3.11%, 0.96-5.25). Disparities did not meaningfully change from 2016 to 2019, while mortality increased from 2019 to 2022. INTERPRETATION: Algorithm-defined ARDS among hospitalized US children remains common and highly fatal. Persistent regional and racial/ethnic disparities highlight systemic drivers of inequity and the need for targeted interventions. FUNDING: This work was supported by the National Heart, Lung, and Blood Institute, National Institutes of Health (Award K23HL177271, PI: Keim).