Correlation of oxygenation indices in invasive mechanical ventilated adult patients.

BACKGROUND: Mechanical ventilation is essential for managing acute respiratory failure, but traditional methods of assessing oxygenation, like the PaO2/FiO2 ratio, pose challenges due to invasiveness and cost. OBJECTIVE: This single-centre prospective observational study aimed to assess the potential of the non-invasive Oxygen Saturation Index (OSI), utilising SpO2 measurements, to diagnose hypoxemia in mechanically ventilated adults. The study sought to establish correlations between OSI, oxygenation index (OI), PaO2/FiO2 ratio and SpO2/FiO2 ratio. METHODS: From August 2022 to July 2023, data was collected from 1055 mechanically ventilated intensive care unit patients. Statistical analysis included correlation tests, receiver operating curve (ROC) analysis and cut-off value determination for hypoxemia diagnosis. RESULTS: We found that the P/F ratio had a statistically significant negative correlation with OI (correlation coefficient -0.832, P value: 0.000 in hypoxemic group and correlation coefficient -0.888, P value: 0.000 in the non-hypoxemic group), and OSI (correlation coefficient -0.746, P value: 0.000 in hypoxemic group and correlation coefficient -0.629, P value: 0.000 in non-hypoxemic group) and has a positive correlation with P/F ratio (correlation coefficient 0.92, P value: 0.000 in hypoxemic group and correlation coefficient -0.67, P value: 0.000 in non-hypoxemic group). OI and OSI had a statistically significant correlation (correlation coefficient 0.955, P value: 0.000 in hypoxemic group and correlation coefficient 0.815, P value: 0.000 in non-hypoxemic group). on ROC analysis P/F ratio was the most accurate in predicting hypoxia followed by OI and OSI. with a cut-off value, of OI being 7.07, and that for OSI being 3.90, at an 80% sensitivity level to diagnose hypoxemia. CONCLUSION: OSI can serve as a dependable surrogate for OI, simplifying ARDS severity assessment. The P/F ratio is the most accurate predictor of hypoxia. Further research, especially in larger multicentre studies, is needed to validate these findings and explore the long-term clinical implications of using OSI for oxygenation monitoring in mechanically ventilated patients.

Panoramic visual statistics shape retina-wide organization of receptive fields.

Statistics of natural scenes are not uniform-their structure varies dramatically from ground to sky. It remains unknown whether these nonuniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. Using the mouse (Mus musculus) as a model species, we show that receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon, in agreement with our predictions. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell types.

Analyzing the barriers for aquaponics adoption using integrated BWM and fuzzy DEMATEL approach in Indian context.

Aquaponic system in greenhouses which can recycle and reuse the water and nutrients is gaining importance across the world to counter the uncertainties due to weather fluctuations. However, there is a slow pace of growth in aquaculture practices around the globe in general and India in particular. There are many barriers to adopt the aquaponic culture. In this study an analysis of the barriers for aquaponics culture in Indian context during the COVID-19 period is presented. Literature review and interactions with various stakeholders help to find out the list of potential factors while gauging the success of their prospective aquaponics project. The "best-worst" methodology (BWM) is employed for ranking of barriers, whereas categorizing of barriers is carried out with the help of fuzzy DEMATEL. Furthermore, the results of this research work are of great value to corporations or start-up companies looking to invest in this technology as well as to farmers who wish to adopt this farming technique.

Effect of Urinary Trypsin Inhibitor (Ulinastatin) Therapy in COVID-19.

Purpose: End-organ damage in coronavirus disease-2019 (COVID-19) is linked to "cytokine storm" and excessive release of inflammatory mediators. Various novel therapies have been used in COVID-19 including urinary trypsin inhibitor therapy. This study explores the efficacy of ulinastatin in COVID-19. Materials and methods: We retrieved the medical records of patients admitted during one month and did a propensity score analysis to create matched treatment and control groups. We analyzed these groups and the outcomes were presented with appropriate statistics. Survival curve was prepared to compare the survival effect of ulinastatin therapy at the end of hospitalization, among both the groups. Results: A total of 736 patients were admitted, and after adjusting the data with propensity score matching, 55 cases were selected by the system. On the final outcome analysis, we found that intensive care unit (ICU) length of stay [median (interquartile range) days 3 (3.5-7.8) vs 2 (0-4); p-value 0.28] in control vs intervention groups, and in hospital mortality (odds ratio: 0.491, CI 95%: 0.099-2.44, p-value 0.435) were not statistically different among the groups. In survival plot analysis also, there was no statistical difference (p-value 0.414) among both the groups.Conclusion: In this retrospective study, we conclude that the final outcome of the ICU length of stay, and overall, in hospital mortality were not different among both the groups. Hence, adequately powered randomized control trials are urgently required to confirm any benefit of ulinastatin therapy in COVID-19 treatment. How to cite this article: Jain A, Kasliwal R, Jain SS, Jain R, Gupta D, Gupta P, et al. Effect of Urinary Trypsin Inhibitor (Ulinastatin) Therapy in COVID-19. Indian J Crit Care Med 2022;26(6):696-703.

Comparison of Predictive Ability of Epidemiological Factors, Inflammatory Biomarkers, and CT Severity Score for Mortality in COVID-19.

INTRODUCTION: COVID-19 patients are categorized as per their clinical severity and their level of care is decided based on the clinical severity. Apart from clinical severity of patients, a need for robust predictors was also felt for early categorization and accurate prediction of final fatal outcome in hospitalized patients. MATERIAL AND METHOD: In this retrospective observational cohort study all the adult patients admitted during November month were included. Available data for epidemiological factors, inflammatory biomarkers and CT severity score were collected and analyzed by univariate and multivariate logistic regression analysis to know predictive ability of each variable. A Receiver operating characteristic analysis was done to compare the predictive ability of each factor for final outcome of death. RESULTS: We analyzed records of 735 total patients. Most of them were male (72.38%), have a median (IQR) age of 60 years (50-69). Diabetes (42.85%), and hypertension (39.86%) were the most common co-morbidities. After univariate and multivariate regression analysis we could find that CRP, D-Dimer and CT severity score levels only can predict final outcome of death. During multivariate regression and receiver operative characteristic (ROC) analysis also, age and Charlson's co-morbidity index failed to predict in hospital mortality. CRP and D-Dimer on admission positively predicts final outcome of in hospital mortality with AUROC of 0.749(p=0.007, CI 0.61-0.88), and 0.864(p= 0.000, CI 0.74-0.99) respectively. Whereas, CT severity score had AUROC 0.73 (p= 0.014, CI 0.575-0.83). Cut off for CRP was 45 mg/L (Sn 0.8, Sp 0.56), D-dimer was 1000 µg/L (Sn:0.8, Sp: 0.9), and CT severity score was 15 (Sn 0.8, Sp 0.58). CONCLUSION: CRP level of 45 mg/l, D-dimer level of 1000 µg/L and CT severity level of >15 at the time of admission can be added to conventional clinical severity algorithm to more accurately predicting final outcome and stratifying the level of care offered at the time of admission, and hence may improve odds off survival.