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| Model construction of driving factors and nursing intervention strategies for ventilator-associated pneumonia in elderly patients with chronic obstr- uctive pulmonary disease complicated with respiratory failure undergoing mechanical ventilation |
| XU Li ZHANG Meng ZHANG Dongya |
| Department of Respiratory and Critical Care Medicine, Huaian First Hospital Affiliated to Nanjing Medical University, Jiangsu Province, Huaian 223300, China |
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Abstract Objective To establish driving factors model of ventilator-associated pneumonia (VAP) in elderly patients with chronic obstructive pulmonary disease (COPD) combined with mechanical ventilation of respiratory failure, and formulate nursing intervention strategies accordingly. Methods A total of 120 elderly patients with COPD combined with mechanical ventilation for respiratory failure admitted to the Department of Respiratory and Critical Care Medicine of Huaian First Hospital Affiliated to Nanjing Medical University from February 2019 to February 2022 were included in the study. According to the occurrence of VAP, the patients were divided into VAP group (26 cases) and non-VAP group (94 cases), and clinical data of the two groups were retrospectively collected. The factors influencing the occurrence of VAP in elderly patients with COPD combined with mechanical ventilation of respiratory failure were analyzed and the driving factors model was established according to logistic regression model, and the predictive value of receiver operator characteristics (ROC) curve was drawn to analyze the occurrence of VAP in patients. Results Age, proportion of consciousness disorder, proportion of mechanical ventilation time ＞five days, proportion of tracheotomy with mechanical ventilation tube, proportion of acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score ＞15 points, proportion of repeated hospitalization due to COPD, proportion of serum albumin level ≤30 g/L, proportion of total vein of nutritional support, and the proportion of supine in VAP group were higher than those in non-VAP group, and the oxygenation index was lower than that in non-VAP group (P＜0.05). The results of multi-factor analysis showed that age, disturbance of consciousness, mechanical ventilation time ＞ five days, tracheotomy with mechanical ventilation tube, APACHEⅡ score ＞15, multiple hospitalizations due to COPD, serum albumin level ≤30 g/L, and total vein of nutritional support were the factors influencing the occurrence of VAP in elderly patients with COPD combined with mechanical ventilation of respiratory failure (P＜0.05). According to the results of multi-factor analysis, the driving factors model was established: logit (P) =-14.690- age×0.683+disturbance of consciousness×0.706+mechanical ventilation time ＞ five days×0.648+APACHEⅡ score ＞ 15 points×0.798+serum albumin level ＜ 30 g/L×0.564+nutritional support pathway was total vein×0.733, and the area under ROC curve was 0.892 (P＜0.05). Conclusion It is of high value to establish driving factors model to predict the occurrence of VAP in elderly patients with COPD combined with mechanical ventilation of respiratory failure, and it has certain reference value for the corresponding nursing intervention strategies of high-risk patients in clinic.
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