Antimicrobial stewardship (AMS) is an important means to control bacterial resistance. The unique situation of intensive care unit (ICU) poses a challenge to AMS. This article reviews the literature on AMS in the ICU at home and abroad in recent years, and summarizes the related measures of AMS. Effective AMS measures in the ICU include setting up a multidisciplinary AMS team, using rapid microbial diagnosis technology to shorten the time of diagnosis, using non-culture methods to assess the necessity of antimicrobial therapy for patients with suspected sepsis, and evaluating the effectiveness of antimicrobial therapy as early as possible and optimizing it. These initiatives aim to increase the rational use of antimicrobials in ICU, reduce the risk of multidrug-resistant infections, and improve patients’ condition.
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 evaluate and summarize the relevant evidence of oxygenation strategies with tracheal intubation after extubation for adult in intensive care unit (ICU), and to provide evidence-based practice for the development of scientific and effective strategies tracheal intubation after extubation for ICU adult patients. Methods Evidence-based databases, related guideline websites, association websites and original databases were searched by computer for literature about oxygenation strategies with tracheal intubation after extubation for ICU adults patients was extracted. The retrieval time was from the establishment of the databases to May 2023. Two researchers trained in evidence-based practice evaluated the quality of the included literature and extracted evidence from the literature that met the quality evaluation criteria. Results A total of 18 articles were included, including 7 guidelines, 4 clinical decisions, 2 expert consensus, 4 systematic reviews and 1 randomized controlled trial. A total of 22 pieces of best evidence were formed, including 7 aspects of basic principles, evaluation, selection, parameter setting, withdrawal, effect evaluation and precautions. ConclusionThe medical staff should select the best evidence based on the actual clinical situation and the patient’s own needs, and adjust the oxygenation strategies to reduce the rate of tracheal intubation and improve the prognosis of patients.
Objective To investigate the postoperative treatment of pleuropneumonectomy for tuberculosis destroyed lung in ICU, in order to improve the therapeutical efficacy for these patients. Methods Clinical data of 52 patients who suffered from tuberculosis destroyed lung and underwent pleuropneumonectomy from June 2008 to June 2010 were analyzed retrospectively. All of subjects received routine treatment in ICU after the operation. Meanwhile，appropriate targeting treatments were applied including diagnosis and treatment of postoperative bleeding; application of fiberbronchoscope to aspirate the sputum after the operation,sequential non-invasive ventilation after the invasive ventilation for acute respiratory failure after operation ,etc.Results A total of 52 patients received the pleuropneumonectomy operation. Bleeding occurred in 11 cases after operation and stopped after the integrated therapy. 8 patients suffered from acute respiratory failure and attenuated after sequential ventilation. No patients died for postoperative bleeding or acute respiratory failure. Conclusions Patients who suffered from tuberculosis destroyed lung and received pleuropneumonectomy with postoperative bleeding and acute respiratory failure have a good prognosis after appropriate postoperative treatment in ICU.
ObjectiveTo explore the safety of ventilator support in hyperbaric oxygen chamber and the prevention of related complications.MethodsFrom July 2016 to December 2018, there were 127 intensive care unit patients underwent hyperbaric oxygen therapy with ventilator. Medical professionals in hyperbaric medicine or intensive care medicine were arranged to accompany the patients in the treatment process, to observe the patients’ condition changes closely, monitor their heart rate, respiration, blood pressure, and oxygen saturation, and perform sputum suction at any time if needed and monitor the airway peak pressure change to prevent pneumothorax.ResultsDuring the process of hyperbaric oxygen therapy, 13 patients (10.24%) were treated with analgesia/sedation for patient-ventilator asynchrony, 4 patients (3.15%) exited the champer emergently for acute left heart failure, 3 patients (2.36%) had epileptic seizures, 3 patients (2.36%) had aspiration, and 1 patient (0.79%) had breath and cardiac arrest. After emergency treatment, all the patients returned to the ward safely.ConclusionDuring the treatment of hyperbaric oxygen therapy for intensive care unit patients with ventilator, the accompany of qualified professionals in hyperbaric medicine or intensive care medicine in the hyperbaric oxygen chamber can treat the patients’ symptoms timely and reduce the risk greatly.
ObjectiveTo observe the effect of target monitoring on the patients with ventilator-associated pneumonia (VAP) in intensive care unit (ICU), analyze the risk factors and take effective measures to reduce the VAP occurrence. MethodsTarget monitoring was performed on patients with ventilator in ICU from January to July 2013 (observation group), and they were compared with those patients accepting general comprehensive monitoring in ICU from January to July 2012 (control group). The incidence of VAP was compared between the two groups. ResultsThe incidence of VAP in the observation group and the control group was 21.73‰ and 53.33‰, respectively. There was a significant difference between the observation group and the control group (P<0.05). ConclusionFor patients undergoing mechanical ventilation, target monitoring can control the risk factors and incidence of VAP, adjust the interference in time, and improve the curing rate.
ObjectiveTo identify the risk factors of Intensive Care Unit (ICU) nosocomial infection in ICU ward in a first-class hospital in Wuxi, and discuss the effective control measures, in order to provide evidence for making strategies in preventing and controlling nosocomial infection. MethodsAccording to the principle of random sampling and with the use of case-control study, a sample of 100 nosocomial infection patients were selected randomly from January 2012 to December 2014 as survey group, and another 100 patients without nosocomial infection as control group. The data were input using EpiData 2.0, and SPSS 13.0 was used for statistical analysis; t-test and χ2 test were conducted, and the risk factors were analyzed using multi-variate logistic regression model. The significant level of P-value was 0.05. ResultsBased on the results of univariate analysis, there were 13 risk factors for ICU nosocomial infection, including diabetes mellitus, hypoproteinemia, being bedridden, surgical operation, immunosuppression, glucocorticoids, organ transplantation, tracheal intubation, length of hospitalization, length of mechanical ventilation, length of central venous catheter, length of urinary catheter, and length of nasogastric tube indwelling. Multi-variate logistic analysis indicated that hospitalization of 7 days or longer[OR=1.106, 95%CI (1.025, 1.096), P=0.001], diabetes mellitus[OR=2.770, 95%CI (1.068, 7.186), P=0.036], surgical operation[OR=7.524, 95%CI (2.352, 24.063), P=0.001], mechanical ventilation of 7 days or longer[OR=1.222, 95%CI (1.116, 1.339), P<0.001], and nasogastric tube indwelling of 7 days or longer[OR=1.110, 95%CI (1.035, 1.190), P=0.003] were considered as independent risk factors for ICU nosocomial infection. ConclusionHospitalization of 7 days or longer, diabetes mellitus, surgical operation, tracheal intubation of 7 days or longer, and gastric intubation of 7 days or longer are the major risk factors for nosocomial infection in ICU ward. Advanced intervention and comprehensive prevention measures are helpful to reduce the nosocomial infection rate and ensure the safety of medical treatment.
Objective To investigate the drug resistance and homogeneous analysis of Acinetobacter baumanii in emergency intensive care unit ( EICU) . Methods Four multidrug-resistant Acinetobacter baumannii ( MDR-Ab) strains isolated fromnosocomial inpatients fromJuly 25 to September 7 in 2009 were collected and tested for drug sensitivity and MIC determination as well. The A. baumannii isolates were typed with pulsed-field gel electrophoresis ( PFGE) to determine whether they derived fromthe same clone.Results Four isolates from nosocomial inpatients were resistant to multiple antibiotics including carbapenem. The PFGE types identified from four isolates were A and B. The A. baumannii isolates did not derived from the same clone. Conclusion The prevalence of nosocomial infection is not due to transmission of the same strains among different individuals in EICU.
Objective To evaluate the sedative and analgesic efficacy and adverse effect of dexmedetomidine versus propofol on the postoperative patients in intensive care unit (ICU). Methods The relevant randomized controlled trials (RCTs) were searched in The Cochrane Library, MEDLINE, PubMed, SCI, SpringerLinker, ScinceDirect, CNKI, VIP, WanFang Data and CBM from the date of their establishment to November 2011. The quality of the included studies was evaluated after the data were extracted by two reviewers independently, and then the meta-analysis was performed by using RevMan 5.1. Results Ten RCTs involoving 793 cases were included. The qualitative analysis results showed: within a certain range of dosage as dexmedetomidine: 0.2-2.5 μg/(kg·h), and propofol: 0.8-4 mg/(kg·h), dexmedetomidine was similar to propofol in sedative effect, but dexmedetomidine group needed smaller dosage of supplemental analgesics during the period of sedative therapy. The results of meta-analysis showed: the percentage of patients needing supplemental analgesics in dexmedetomidine group was less than that in propofol group during the period of sedative therapy (OR=0.24, 95%CI 0.08 to 0.68, P=0.008). Compared with the propofol group, the duration of ICU stay was significantly shorter in the dexmedetomidine group (WMD= –1.10, 95%CI –1.88 to –0.32, P=0.006), but the mechanical ventilated time was comparable between the two groups (WMD=0.89, 95%CI –1.15 to 2.93, P=0.39); the incidence of adverse effects had no significant difference between two groups (bradycardia: OR=3.57, 95%CI 0.86 to 14.75, P=0.08; hypotension: OR=1.00, 95%CI 0.30 to 3.32, P=1.00); respiratory depression seemed to be more frequently in propofol group, which however needed further study. Mortalities were similar in both groups after the sedative therapy (OR=1.03, 95%CI 0.54 to 1.99, P=0.92). Conclusion Within an exact range of dosage, dexmedetomidine is comparable with propofol in sedative effect. Besides, it has analgesic effect, fewer adverse effects and fewer occurrences of respiratory depression, and it can save the extra dosage of analgesics and shorten ICU stay. Still, more larger-sample, multi-center RCTs are needed to provide more evidence to support this outcome.
The intensive care unit (ICU) is a highly equipment-intensive area with a wide variety of medical devices, and the accuracy and timeliness of medical equipment data collection are highly demanded. The integration of the Internet of Things (IoT) into ICU medical devices is of great significance for enhancing the quality of medical care and nursing, as well as for the advancement of digital and intelligent ICUs. This study focuses on the construction of the IOT for ICU medical devices and proposes innovative solutions, including the overall architecture design, devices connection, data collection, data standardization, platform construction and application implementation. The overall architecture was designed according to the perception layer, network layer, platform layer and application layer; three modes of device connection and data acquisition were proposed; data standardization based on Integrating the Healthcare Enterprise-Patient Care Device (IHE-PCD) was proposed. This study was practically verified in the Chinese People’s Liberation Army General Hospital, a total of 122 devices in four ICU wards were connected to the IoT, storing 21.76 billion data items, with a data volume of 12.5 TB, which solved the problem of difficult systematic medical equipment data collection and data integration in ICUs. The remarkable results achieved proved the feasibility and reliability of this study. The research results of this paper provide a solution reference for the construction of hospital ICU IoT, offer more abundant data for medical big data analysis research, which can support the improvement of ICU medical services and promote the development of ICU to digitalization and intelligence.