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ObjectiveTo 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).MethodsThis 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.ResultsA 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

Objective: To construct and evaluate a decision tree based on biomarkers for predicting severe acute kidney injury (AKI) in critical patients., Methods: A prospectively study was conducted. Critical patients who had been admitted to the department of critical care medicine of Xiaolan Hospital of Southern Medical University from January 2017 to June 2018 were enrolled. The clinical data of the patients were recorded, and the biomarkers, including serum cystatin C (sCys C) and urinary N-acetyl-β-D-glucosaminidase (uNAG) were established immediately after admission to intensive care unit (ICU), and the end points were recorded. The test cohort was established with patient data from January to December 2017. The decision tree classification and regression tree (CART) algorithm was used, and the best cut-off values of biomarkers were used as the decision node to construct a biomarker decision tree model for predicting severe AKI. The accuracy of the decision tree model was evaluated by the overall accuracy and the receiver operating characteristic (ROC) curve. The validation cohort, established on patient data from January to June 2018, was used to further validate the accuracy and predictive ability of the decision tree., Results: In test cohort, 263 patients were enrolled, of whom 57 developed severe AKI [defined as phase 2 and 3 of Kidney Disease: Improving Global Outcomes (KDIGO) criterion]. Compared with patients without severe AKI, severe AKI patients were older [years old: 64 (49, 74) vs. 52 (41, 66)], acute physiology and chronic health evaluation II (APACHE II) score were higher [23 (19, 27) vs. 15 (11, 20)], the incidence of hypertension, diabetes and other basic diseases and sepsis were higher (64.9% vs. 40.3%, 28.1% vs. 10.7%, 63.2% vs. 29.6%), the levels of sCys C and uNAG were higher [sCys C (mg/L): 1.38 (1.12, 2.02) vs. 0.79 (0.67, 0.98), uNAG (U/mmol Cr): 5.91 (2.43, 10.68) vs. 2.72 (1.60, 3.90)], hospital mortality and 90-day mortality were higher (21.1% vs. 4.4%, 52.6% vs. 13.1%), the length of ICU stay was longer [days: 6.0 (4.0, 9.5) vs. 3.0 (1.0, 6.0)], and renal replacement therapy requirement was higher (22.8% vs. 1.9%), with statistically significant differences (all P < 0.05). ROC curve analysis showed that the areas under ROC curve (AUC) of sCys C and uNAG in predicting severe AKI were 0.857 [95% confidence interval (95%CI) was 0.809-0.897)] and 0.735 (95%CI was 0.678-0.788), and the best cut-off values were 1.05 mg/L and 5.39 U/mmol Cr, respectively. The structure of the biomarker decision tree model constructed by biomarkers were intuitive. The overall accuracy in predicting severe AKI was 86.0%, and AUC was 0.905 (95%CI was 0.863-0.937), the sensitivity was 0.912, and the specificity was 0.796. In validation cohort of 130 patients, this decision tree yielded an excellent AUC of 0.909 (95%CI was 0.846-0.952), the sensitivity was 0.906, and the specificity was 0.816, with an overall accuracy of 81.0%., Conclusions: The decision tree model based on biomarkers for predicting severe AKI in critical patients is highly accurate, intuitive and executable, which is helpful for clinical judgment and decision.