A total of 178 patients with the time of mechanical ventilation beyond 48 hours in the second affiliated hospital of Wenzhou medical college from January 2010 to December 2013 were enrolled in this study,and there were fifty-six patients with ventilator-associated tracheobronchitis (VAT).The associated factors included age,sex,blood pressure,blood glucose,BMI,the time of mechanical ventilation,tracheal intubation methods,raise head to 30-45°,proton pump inhibitors (PPI),prophylactic antibiotic treatment,glasgow coma scale (GCS),acute physiology and chronic health evaluation (APECHE) Ⅱ score.The related factors of VAT were evaluated by using univariate logistical regression analysis,and the statistical significant variables were analyzed by using multivariate logistical regression analysis.By using univariate logistical regression analysis age,blood glucose,the time of mechanical ventilation,raise head to 30-45°,prophylactic antibiotic treatment,GCS and APECHE Ⅱ score were the important factors of VAT (P ＜ 0.05),but sex,blood pressure,BMI,tracheal intubation methods and PPI were insignificant related to VAT(P ＞ 0.05).By using multivariate logistical regression analysis the time of mechanical ventilation (OR =4.072,95％ CI 2.036-8.146),GCS[2.198(1.155-4.184)],age[2.128 (1.119-4.046)],APECHE Ⅱ score [2.109 (1.084-4.104)] and raise head to 30-45 ° [0.488 (0.243-0.979)] were associated independently with the VAT.The time of mechanical ventilation,GCS,age over 60 years,APECHE Ⅱ score and raise head to 30-45°were the independent factors associated with VAT.

Objective:To analyze the influencing factors of short-term prognosis, and construct a 30-day mortality risk prediction model for patients with cardiogenic shock in Xinjiang region with nomogram.Methods:The clinical data of 295 patients with cardiogenic shock from 2013 to 2019 in the First Affiliated Hospital of Xinjiang Medical University were retrospectively analyzed. Univariate and multivariate Logistic regression were used to analyze the risk factors for 30-day death in patients with cardiogenic shock, the nomogram was used to construct a prediction model for the risk of death in patients with cardiogenic shock, and the consistency coefficient and receiver operating characteristic (ROC) curve were used to evaluate the model.Results:Among 295 patients, 182 died at 30 d (death group) and 113 survived (survival group). There were statistical differences in gender, age, ICU time, systolic blood pressure, white blood cell, neutrophil count, red blood cell distribution width (RDW), prothrombin time, potassium, blood glucose, serum creatinine, total bilirubin, bicarbonate, base excess, lactic acid, brain natriuretic peptide precursor (NT-proBNP), cardiac troponin I (cTnI) and the percentage of respiratory failure, liver disease, kidney disease between death group and survival group ( P<0.01 or<0.05). Multivariate Logistic regression analysis results showed that NT-proBNP, prothrombin time, cTnI, lactic acid and systolic blood pressure were independent risk factors of death in patients with cardiogenic shock ( OR = 1.00, 1.10, 1.30, 1.29 and 1.04; 95% CI 1.00 to 1.00, 1.01 to 1.18, 1.00 to 1.68, 1.01 to 1.65 and 1.02 to 1.07; P<0.01 or<0.05). The independent factors obtained from multivariate analysis were combined with clinical practice, Akaike information criterion (AIC) analysis was conducted to select modeling variables, and the variables included in the nomogram model were NT-proBNP, prothrombin time, cTnI and lactic acid. After 500 times of internal Bootstrap self-sampling verification of the nomogram model, the C index was 0.805, area under the curve was 0.846, and the optimum threshold value was 0.486, with a sensitivity of 78.6% and a specificity of 83.1%. Conclusions:NT-proBNP, prothrombin time, cTnI and lactic acid are the related influencing factors for the short-term prognosis of patients with cardiogenic shock, and the related nomogram prediction model is constructed, which has guiding significance for the early intervention of cardiogenic shock.