Daily Ards Research Analysis

INTRODUCTION: Poor respiratory health in childhood is common, and asthma is the most common chronic disease among children, for which there is no known cure. Maternal intake of vitamins (A, C, E) may be a modifiable nutritional exposure to reduce adverse respiratory health in offspring. OBJECTIVE: We aimed to systematically review the evidence for the association between maternal vitamin (A, C, E) intake during pregnancy (via questionnaire or blood assay) and respiratory outcomes in the offspring. METHODS: Studies identified through electronic databases were eligible if they assessed maternal levels and/or intake of vitamins A, C and/or E via dietary intake or supplements in pregnancy and respiratory outcomes in the first 5 years of life. Meta-analyses were conducted where possible. Outcomes included wheeze, cough, asthma, infant respiratory distress syndrome (RDS), respiratory tract infection (RTI) and lung function measurement. RESULTS: Of 1170 articles screened, 12 observational studies and six RCTs met the inclusion criteria (total sample size n = 58,769). Meta-analysis could not be performed for vitamin A; however, there was no evidence to suggest that maternal vitamin A intake improves early life respiratory outcomes in offspring. Two RCTs found that vitamin C supplementation (500 mg/day vs. placebo) reduced the incidence of wheeze at 12 months (n = 206 children) and 5 years (n = 213 children) in pregnancies exposed to smoking. In meta-analyses, maternal intake in the highest vitamin E quartile versus lowest reduced the odds of wheeze at 2 years by 36% (aOR: 0.64, 95% CI: 0.47-0.87, n = 2 observational studies, very low certainty); this was not true for vitamin C intake (aOR: 0.85, 95% CI: 0.63-1.16, n = 2 observational studies, very low certainty). Vitamin supplementation (C + E) was not associated with infant RDS (OR: 1.15, 95% CI: 0.80-1.64, n = 2 studies, moderate certainty) relative to placebo. CONCLUSION: There may be some benefit to vitamin C supplementation during pregnancy in the context of maternal smoking or higher maternal vitamin E intake during pregnancy, for reducing the risk of childhood wheeze in early life. This emerging evidence warrants further studies to enable translation into dietary guidelines.

BACKGROUND: The development of acute respiratory distress syndrome (ARDS) is intricate and uncertain. Although intensive care has made substantial progress in the past several decades, the in-hospital mortality rate of patients with ARDS remains as high as 40%, which imposes a large burden on hospitals and intensive care. This study aimed to develop and validate a nomogram to predict the 30-day mortality of patients with ARDS admitted in the intensive care unit (ICU). METHODS: Data of 4920 patients with ARDS were collected from the MIMIC-IV database, as well as data of 248 patients were collected from the Affiliated Hospital of Southwest Medical University. After processing these data, we performed correlation analysis between various types of variables and plotted a heat map to visualize the significance of these correlations. Subsequently, LASSO regression was used to initially screen for risk factors strongly associated with 30-day death in patients with ARDS, and a prediction model was established by multivariate logistic regression. The predictive efficacy of this model was preliminarily evaluated; internally validated; and compared with that of SOFA, APS-III, OASIS, and SAPS-II scores. In addition, it was externally validated using patient data from the ICU in China. RESULTS: The AUC of the model was 0.78; The AUC values in the internal validation and external validation sets were 0.805 and 0.742, respectively. Moreover, the model demonstrated better predictive efficacy than this three traditional disease severity scoring systems (OASIS, SAPS-II, APS-III, and SOFA), highlighting its good predictive value. CONCLUSIONS: We established a 30-day mortality risk prediction model for patients with ARDS who were first admitted to ICU by simple and easily accessible clinical data. To enhance real-world utility, we engineered an open-access mobile application that provides instant risk stratification at the bedside. This model synergizes with existing ICU scoring systems by enabling early identification of high-risk patients during initial assessment, thereby guiding timely interventions.

BACKGROUND: Early discrimination between transient tachypnea of the newborn (TTN) and respiratory distress syndrome (RDS) is critical for establishing timely targeted therapies. Our aim was to assess the efficacy of LDH, platelet indices, and systemic inflammatory indices in distinguishing neonatal RDS from TTN early. METHODS: In total, 300 neonates were enrolled in this case-control study. Lactate dehydrogenase (LDH) levels were estimated. Platelet and systemic inflammatory indices were calculated using complete blood count. RESULTS: The RDS group exhibited substantially higher serum levels of LDH, neutrophil-lymphocyte ratio (NLR), and Systemic immune-inflammation index (SII) than the TTN and control groups. Platelet-lymphocyte ratio (PLR) and monocyte-lymphocyte ratio (MLR (were significantly higher in the RDS group than in the TTN group. The RDS group also had the lowest median platelet count, platelet mass index, and WBCs/ mean platelet volume (MPV), but much higher MPV/platelet count than the TTN and control groups. The TTN group had more WBCs, lymphocyte percentage, and count, but a lower neutrophil percentage than the RDS group. The ROC curve study demonstrated that serum LDH at a cut-off level of > 660 U/L can discriminate between the RDS and TTN groups. NLR had the highest sensitivity, PLR had the highest specificity, and SII at a cut-off level > 245.57, had 67% sensitivity and 56% specificity. Significant positive correlations were detected between Downe score with NLR (r = 0.317**, p = 0.001), PLR (r = 0.261**, p = 0.009), and SII (r = 0.270**, p = 0.007). CONCLUSION: LDH levels, platelets, and systematic inflammatory indices could serve as affordable biomarkers for the early distinction between RDS and TTN.