Cell death of alveolar lymphocytes and monocytes is negatively correlated with driving pressure and mechanical power in patients with acute respiratory distress syndrome.

BACKGROUND: Pathogenesis of acute respiratory distress syndrome (ARDS) involves immune cell death and removal from the injured lungs. ARDS severity is related to lung compliance. However, the correlation between the respiratory mechanics and alveolar immune cell death in patients with ARDS remains unclear. METHODS: Twenty-four patients with respiratory failure and ARDS were enrolled in the intensive care unit between November 2019 and November 2021. Neutrophil extracellular traps (NETs) and cell death of lymphocytes and monocytes in bronchoalveolar lavage fluid were detected on days 1 and 8. RESULTS: Lung compliance was positively correlated with the cell death percentage of alveolar CD4/CD8 lymphocytes and monocytes on day 8 (Pearson's correlation coefficient (r) = 0.554, p = 0.005; r = 0.422, p = 0.040; r = 0.569, p = 0.004, respectively). There was no association between lung compliance and the percentage of alveolar NETs on days 1 and 8. The cell death percentages of alveolar CD4/CD8 lymphocytes and monocytes were negatively correlated with driving pressure (DP) on days 1 (r = - 0.440, p = 0.032; r = - 0.613, p = 0.001; r = -0.557, p = 0.005, respectively) and 8 (r = - 0.459, p = 0.024; r = - 0.407, p = 0.048; r = - 0.607, p = 0.002, respectively). The cell death percentages of alveolar CD4/CD8 lymphocytes and monocytes were also negatively correlated with mechanical power (MP) on days 1 (r = - 0.558, p = 0.005; r = - 0.593, p = 0.002; r = - 0.571, p = 0.004, respectively) and 8 (r = - 0.539, p = 0.007; r = - 0.338, p = 0.107; r = - 0.649, p < 0.001, respectively). The percentage of alveolar NETs on days 1 and 8 was not associated with DP or MP. CONCLUSION: Patients with higher cell death rates of alveolar CD4/CD8 lymphocytes and monocytes exhibited lower DP and MP. Patients with less cell death of alveolar CD4/CD8 lymphocytes and monocytes required more DP or MP to maintain adequate ventilation.

Effects of theophylline therapy on respiratory muscle strength in patients with prolonged mechanical ventilation: A retrospective cohort study.

Mechanical ventilation may cause diaphragm weakness an effect termed ventilator-induced diaphragm dysfunction (VIDD). The prevalence of VIDD among patients receiving mechanical ventilation is very high, with the degree of diaphragmatic atrophy being associated with the length of mechanical ventilation. Theophylline is known to increase diaphragmatic contractility and reduce fatigue, so in this study, we evaluated the effect of theophylline in patients with prolonged mechanical ventilation.Patients who depended on mechanical ventilation were included in the study. We compared the maximum inspiratory pressure (PImax) values, rapid shallow breathing index (RSBI) values, and successful weaning rates of theophylline-treated and non-theophylline-treated patients.Eighty-four patients received theophylline and 76 patients did not. These 2 groups' clinical characteristics, including their PImax and RSBI at initial admission, were similar. The results showed that the theophylline-treated group had significantly better PImax and RSBI, with a higher last PImax (30.1 ±â€Š9.7 cmH2O vs 26.9 ±â€Š9.1 cmH2O; P = .034) and lower last RSBI (107.0 ±â€Š68.4 vs 131.4 ±â€Š77.7; P = .036). The improvements to each respective patient's PImax and RSBI were also significantly higher in the theophylline-treated group (PImax: 20.1 ±â€Š5.7% vs 3.2 ±â€Š1.1%, P = .005; RSBI: 11.2 ±â€Š3.0% vs 2.7 ±â€Š1.6%, P = .015). The weaning success rate of the theophylline-treated group was also higher, but not significantly so.Theophylline might improve respiratory muscle strength in patients with prolonged mechanical ventilation and it needs further prospective studies to confirm.

Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006.

BACKGROUND: Spatial analytical techniques and models are often used in epidemiology to identify spatial anomalies (hotspots) in disease regions. These analytical approaches can be used to not only identify the location of such hotspots, but also their spatial patterns. METHODS: In this study, we utilize spatial autocorrelation methodologies, including Global Moran's I and Local Getis-Ord statistics, to describe and map spatial clusters, and areas in which these are situated, for the 20 leading causes of death in Taiwan. In addition, we use the fit to a logistic regression model to test the characteristics of similarity and dissimilarity by gender. RESULTS: Gender is compared in efforts to formulate the common spatial risk. The mean found by local spatial autocorrelation analysis is utilized to identify spatial cluster patterns. There is naturally great interest in discovering the relationship between the leading causes of death and well-documented spatial risk factors. For example, in Taiwan, we found the geographical distribution of clusters where there is a prevalence of tuberculosis to closely correspond to the location of aboriginal townships. CONCLUSIONS: Cluster mapping helps to clarify issues such as the spatial aspects of both internal and external correlations for leading health care events. This is of great aid in assessing spatial risk factors, which in turn facilitates the planning of the most advantageous types of health care policies and implementation of effective health care services.