The setting and adjustment of ventilator parameters need to rely on a large amount of clinical data and rich experience. This paper explored the problem of difficult decision-making of ventilator parameters due to the time-varying and sudden changes of clinical patient’s state, and proposed an expert knowledge-based strategies for ventilator parameter setting and stepless adaptive adjustment based on fuzzy control rule and neural network. Based on the method and the real-time physiological state of clinical patients, we generated a mechanical ventilation decision-making solution set with continuity and smoothness, and automatically provided explicit parameter adjustment suggestions to medical personnel. This method can solve the problems of low control precision and poor dynamic quality of the ventilator’s stepwise adjustment, handle multi-input control decision problems more rationally, and improve ventilation comfort for patients.
Hot topics on the diagnosis and antimicrobial therapy of ventilator-associated pneumonia, including clinical diagnostic criteria, evaluation of biomarkers, ventilator associated events, clinical pulmonary infection score, ventilator-associated tracheobronchitis, microbiological diagnosis and duration of therapy were discussed. The viewpoints in the guidelines of America, Europe and Japan were also reviewed.
Objective To evaluate the effect of auto adjusted triggering mechanism on the triggering balance of sensitivity and anti-interference in non invasive ventilator field. Methods Taking the breathing simulator as the experimental platform, for the same ventilator, the experiments of "automatic adjustment mode" and "manual adjustment mode" were carried out in a self-control manner, comparing the sensitivity and anti-interference indexes of the experimental group and the control group in the triggering stage. The results were statistically analyzed. Results In case of large air leakage, for ventilator of "A40", the group of "automatic adjustment mode" presented auto-triggered cycle and the group of "manual adjustment mode" (the inspiratory trigger sensitivity was adjusted to 5 to 9 L/min) could provide breathing assistance ventilation. While for ventilator of "VENT", both the group of "automatic adjustment mode" and the group of "manual adjustment mode" (the inspiratory trigger sensitivity was adjusted to 1 to 8 arbitrary unit) appear auto-triggered cycle. In case of medium air leakage, for ventilator of "A40", the trigger delay time, trigger pressure and trigger work of the "manual adjustment mode" group (the inspiratory trigger sensitivity was adjusted to 3 to 5 L/min) were significantly less than those of the "automatic adjustment mode" group, and the trigger delay time, trigger work of the "manual adjustment mode" group (the inspiratory trigger sensitivity was adjusted to 8 to 9 L/min) were significantly higher than those of the "automatic adjustment mode" group; While for ventilator of "VENT", compared with the inspiratory trigger sensitivity of the "automatic adjustment mode" group and the "manual adjustment mode" group (the inspiratory trigger sensitivity was adjusted to 4 arbitrary unit), the trigger delay time, trigger pressure and trigger work were not statistically significant. In case of small air leakage, for ventilator of "A40", the trigger delay time and trigger work of the "manual adjustment mode" group (the inspiratory trigger sensitivity was adjusted to 2 to 6 L/min) were significantly less than those in the "automatic adjustment mode" group, and the trigger pressure of "manual adjustment mode" group (the inspiratory trigger sensitivity was adjusted to 2 to 5 L/min and 7 L/min) was significantly lower than that of "automatic adjustment mode" group. While for ventilator of "VENT", the trigger delay time, trigger pressure and trigger work of the "manual adjustment" group (the inspiratory trigger sensitivity was adjusted to 1 to 2 arbitrary unit) were less than those of the experimental group, and they were statistically significant. Conclusions In case of large air leakage, ventilator of "VENT" can not provide breathing assistance ventilation no matter which inspiratory trigger mode. While ventilator of "A40" should be used the "manual adjustment mode", and adjust the inspiratory trigger sensitivity to the less sensitive arbitrary unit to increase its performance of anti-interference. In case of medium air leakage, for both ventilator of "A40" and ventilator of "VENT", it is better to use "automatic adjustment" mode for breathing assistance ventilation. In case of small air leakage, for both ventilator of "A40" and ventilator of "VENT", it is better to use "manual adjustment" mode for breathing assistance ventilation and we should adjust the inspiratory trigger sensitivity to the higher sensitive arbitrary without auto-triggered cycle.
【摘要】 目的 探讨加强护理干预措施对呼吸机相关性肺炎发病率的影响。 方法 将2007年1月-2008年12月收住在重症监护病房行有创机械通气治疗的96例患者，随机分为对照组和治疗组，每组48例，比较不同护理干预对呼吸机相关性肺炎的影响。 结果 对照组VAP发生率52%（25/48），治疗组VAP发生率23%（11/48），两组比较有统计学意义（χ2=8.711，P=0.003）。 结论 针对VAP感染的环节加强气管导管气囊的管理、吸痰、口腔护理等干预措施可以有效降低VAP的发生率。【Abstract】 Objective To investigate the impact of nursing intervention on ventilation-associated pneumonia. Methods A total of 96 patients from January 2007 to December 2008 who had undergone invasive mechanical ventilation in ICU were randomly divided into a trial group and a control group with 48 patients in each. The impact of the different nursing intervention on ventilator-associated pneumonia were compared. Results The incidence of ventilator associated pneumonia (VAP) was 52% (25/48) in the control group, and 23% (11/48) in the trial group;the difference between the two groups was statistically significant (χ2=8.711，P=0.003). Conclusion The nursing intervention in VAP infection chain, such as the management of tracheal suction catheter balloon, aspiration of sputum, and oral care interventions, can reduce the incidence of VAP effectively.
ObjectiveTo analyze the influencing factors of ventilator-associated pneumonia (VAP) in comprehensive intensive care units (ICUs) in a certain district of Shanghai, and to provide evidence for developing targeted measures to prevent and reduce the occurrence of VAP.MethodsThe target surveillance data of 1 567 inpatients with mechanical ventilation over 48 hours in comprehensive ICUs of 5 hospitals in the district from January 2015 to December 2017 were retrospectively analyzed to determine whether VAP occurred. The data were analyzed with SPSS 21.0 software to describe the occurrence of VAP in patients and to screen the influencing factors of VAP.ResultsThere were 133 cases of VAP in the 1 567 patients, with the incidence of 8.49% and the daily incidence of 6.01‰; the incidence of VAP decreased year by year from 2015 to 2017 (χ2trend=11.111, P=0.001). The mortality rate was 12.78% in VAP patients while was 7.25% in non-VAP patients; the difference was significant (χ2=5.223, P=0.022). A total of 203 pathogenic bacteria were detected in patients with VAP, mainly Gram-negative bacteria (153 strains, accounting for 75.37%). The most common pathogen was Pseudomonas aeruginosa. The single factor analysis showed that gender, age, Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ score, the length of ICU stay, and the length of mechanical ventilation were the influencing factors of VAP (χ2=9.572, 5.237, 34.759, 48.558, 44.960, P<0.05). Multiple logistic regression analysis found that women [odds ratio (OR)=1.608, 95% confidence interval (CI) (1.104, 2.340), P=0.013], APACHE Ⅱ score >15 [OR=4.704, 95%CI (2.655, 8.335), P<0.001], the length of ICU stay >14 days [OR=2.012, 95%CI (1.188, 3.407), P=0.009], and the length of mechanical ventilation >7 days [OR=2.646, 95%CI (1.439, 4.863), P=0.002] were independent risk factors of VAP.ConclusionsNosocomial infection caused by mechanical ventilation in this area has a downward trend, and the mortality rate of patients with VAP is higher. For the patients treated with mechanical ventilation in ICU, we should actively treat the primary disease, shorten the length of ICU stay and the length of mechanical ventilation, and strictly control the indication of withdrawal, thereby reduce the occurrence of VAP.
Objective To observe the effects of exogenous pulmonary surfactant (PS) on ventilation-induced lung injury (VILI) in rats, and to investigate its possible mechanisms. Methods A total of 40 Wistar rats were divided into 4 groups with randomized blocks method: control group, high tidal volume (HV) group, VILI group, and PS group, with 10 rats in each group. The control group was subjected to identical surgical procedure but was never ventilated. After 30 min of mechanical ventilation (MV) with Vt 45 ml/kg, the rats in HV group were killed immediately; rats in the VILI group were continually ventilated for up to 150 min with Vt 16 ml/kg; in the PS group, 100 mg/kg of PS administered intratracheally and with the same settings as VILI group. Mean artery pressure (MAP), blood gas analysis, lung wet to dry weight ratios (W/D), thorax-lung compliance, and cell counts in bronchoalveolar lavage fluid (BALF) were determined. Nuclear factor-κB(NF-κB) activity in lungs was measured by enzyme-linked immunosorbent assay (ELISA), interleukin-8(IL-8) in serum and BALF was determined by radioimmunoassay (RIA). Pathological examination of the lung was performed. Results Injurious ventilation significantly decreased MAP and PaO2/FiO2, but increased NF-κB activity and W/D. MAP and PaO2/FiO2 improved, but NF-κB activity, IL-8 in serum and BALF, and cell counts in BALF reduced significantly in PS group compared with those in VILI group. Histological studies showed reduced pulmonary edema and atelectasis in the PS group. Conclusion PS administered intratracheally can suppress the increased activity of NF-κB induced by VILI, exogenous PS can be used to treat VILI.
Traditional manual testing of ventilator performance is labor-intensive, time-consuming, and prone to errors in data recording, making it difficult to meet the current demands for testing efficiency in the development and manufacturing of ventilators. Therefore, in this study we designed an automated testing system for essential performance parameters of ventilators. The system mainly comprises a ventilator airflow analyzer, an automated switch module for simulated lungs, and a test control platform. Under the control of testing software, this system can perform automated tests of critical performance parameters of ventilators and generate a final test report. To validate the effectiveness of the designed system, tests were conducted on two different brands of ventilators under four different operating conditions, comparing tidal volume, oxygen concentration, and positive end expiratory pressure accuracy using both the automated testing system and traditional manual methods. Bland-Altman statistical analysis indicated good consistency between the accuracy of automated tests and manual tests for all respiratory parameters. In terms of testing efficiency, the automated testing system required approximately one-third of the time needed for manual testing. These results demonstrate that the designed automated testing system provides a novel approach and means for quality inspection and measurement calibration of ventilators, showing broad application prospects.