Objective To verify the association between admission serum phosphate level and short-term (<30 days) mortality of severe pneumonia patients admitted to intensive care unit (ICU) / respiratory intensive care unit (RICU). Methods Severe pneumonia patients admitted to the ICU/RICU of Quanzhou First Hospital Affiliated to Fujian Medical University from November 2019 to September 2021 were included in the study. Serum phosphate was demonstrated as an independent risk factor for short-term mortality of severe pneumonia patients admitted to ICU/RICU by logical analysis and receiver operator characteristic (ROC) curve. The patients were further categorized by serum phosphate concentration to explore the relationship between serum phosphate level and short-term mortality. Results Comparison of baseline indicators at admission between the survival group (n=54) and the non survival group (n=46) revealed that there was significant difference in serum phosphate level [0.9 (0.8, 1.2) mmol/L vs. 1.2 (0.9, 1.5) mmol/L, P<0.05]. Logical analysis showed serum phosphate was an independent risk factor for short-term mortality. ROC curve showed that the prediction ability of serum phosphate was close to pneumonia severity index (PSI). After combining serum phosphate with PSI score, CURB65 score, and sequential organ failure score, the predictive ability of these scores for short-term mortality was improved. Compared with the normophosphatemia group, hyperphosphatemia was found be with significantly higher short-term mortality (85.7% vs. 47.3%, P<0.05), which is absent in hypophosphatemia (25.8%). Conclusions Serum phosphate at admission has a good predictive value on short-term mortality in severe pneumonia patients admitted to the ICU/RICU. Hyperphosphatemia at admission is associated with a higher risk of short-term death.
Objective To explore factors affecting the shunt safety of patients in emergency intensive care unit (EICU), construct a shunt safety evaluation model, and evaluate its prediction effectiveness, so as to provide a theoretical basis for the decision-making of shunt safety in EICU. Methods The demographic data, vital signs, laboratory examinations and other indicators of patients transferred to the general ward from the EICU of West China Hospital of Sichuan University from 0:00 on August 1, 2019 to 23:59 on May 31, 2021 were collected and analyzed. The short-term poor prognosis after being transferred out of the EICU was regarded as the end-point event. Of the patients, 70% were randomly selected as the model construction cohort, and 30% were the model validation cohort. In the model construction cohort, multivariate logistic regression analysis was used to screen the influencing factors affecting shunt safety, and the shunt safety evaluation model of patients in EICU was constructed. In the validation cohort, receiver operating characteristic curve was used to evaluate the effectiveness of the model in evaluating the shunt safety of patients in EICU. Results A total of 582 patients were included, of whom 59 patients (10.1%) had a poor short-term prognosis. Multivariate logistic regression analysis showed that the patients’ respiratory rate when leaving the EICU [odds ratio (OR)=0.863, 95% confidence interval (CI) (0.794, 0.938), P=0.001], Glasgow Coma Scale scores [OR=1.575, 95%CI (1.348, 1.841), P<0.001], albumin [OR=1.137, 95%CI (1.008, 1.282), P=0.036], prothrombin time [OR=0.956, 95%CI (0.914, 1.000), P=0.048] were the influencing factors of shunt safety. Based on the above indicators, a shunt safety evaluation model for patients in EICU was created. The area under the curve for the shunt safety assessment model to predict poor short-term prognosis was 0.815, the best cut-off value was 4 points, the sensitivity was 93.3%, and the specificity was 61.5%. Conclusions The patients’ respiratory rate when leaving EICU, Glasgow Coma Scale scores, albumin and prothrombin time are factors affecting the shunt safety for patients in EICU. The shunt safety assessment model can better predict the short-term poor prognosis of patients transferred from EICU to general ward.
Objective To investigate the pathogen distribution and drug resistance in ICU patients, provide reference for prevention of severe infection and empirical antibacterial treatment. Methods The patients admitted in ICU between January 2013 and December 2014 were retrospectively analyzed. The pathogenic data were collected including bacterial and fungal culture results, the flora distribution and drug resistance of pathogenic bacteria. Results A total of 2088 non-repeated strains were isolated, including 1403 (67.2%) strains of Gram-positive bacteria, 496 (23.8%) strains of Gram-negative bacteria, and 189 (9.0%) strains of fungus. There were 1324 (63.42%) strains isolated from sputum or other respiratory specimens, 487 (23.33%) strains from blood specimens, 277 (13.27%) strains from other specimens. The bacteria included Acinetobacter baumannii (17.2%), Klebsiella pneumoniae (14.8%), Pseudomonas aeruginosa (9.9%), C. albicans (6.3%), E. coli (5.6%), E. cloacae (5.4%), Epidermis staphylococcus (5.0%) and Staphylococcus aureus (4.7%). There were 15 strains of penicillium carbon resistant enterobacteriaceae bacteria (CRE) accounting for 2.3%, including 5 strains of Pneumonia klebsiella, 4 strains of E. cloacae. In 117 strains of E. coli, drug-resistant strains accounted for 86.4% including 85.5% of multiple drug-resistant strains (MDR) and 0.9% of extremely-drug resistant (XDR) strains. In 359 strains of Acinetobacter baumannii, drug-resistant strains accounted for 75.2% including 72.1% of XDR strains and 3.1% of MDR strains. MDR strains accounted for 10.6% in Pseudomonas aeruginosa. Detection rate of methicillin resistant Staphylococcus aureus (MRSA) and methicillin resistant coagulase-negative Staphylococci (MRCNS) was 49.0% and 95.5%, respectively. There were 4 strains of vancomycin resistant Enterococcus faecalis. There were 131 (69.3%) strains of C. albicans, 23 (12.2%) strains of smooth candida. C. albicans was sensitive to amphotericin and 5-fluorine cytosine, and the resistance rate was less than 1% to other antifungle agents. The resistance rate of smooth ball candida was higher than C. albicans and nearly smooth candida, but still less than 15%. Conclusions The predominant pathogens in ICU was gram-negative bacteria. The top eight pathogenic bacteria were Acinetobacter baumanni, Klebsiella pneumoniae, Pseudomonas aeruginosa, C. albicans, E. coli, E. cloacae, Epidermis staphylococcus and S. aureus. Sputum and blood are common specimens. CRE accounts for 2.3%. Drug-resistant strains are most common in E. coli mainly by MDR, followed by Acinetobacter baumannii mainly by XDR, and least in Pseudomonas aeruginosa. C. albicans is the most common fungus with low drug resitance.
Objective To discuss the effect of monitoring-training-planning (MTP) intervention model on the prevention and control of catheter–associated urinary tract infection (CAUTI) in Intensive Care Unit (ICU). Methods Patients with indwelling catheter from departments with ICU (ICU, ICU of the Department of Neurosurgery, ICU of the Department of Neurologic Medicine) between 2014 and 2015 were included in this study. Based on the inclusion criteria, target monitoring indicators were set in accordance with Hospital Infection Monitoring Norms. A total of 493 patients with indwelling catheters from January to December 2014 were subjected to target surveillance, and were used as baseline for the study. A total of 529 patients with indwelling catheters from January to December 2015 were treated with MTP intervention. The occurrence of indwelling catheter–associated urinary tract infections in the intensive care unit was compared before and after intervention. Results The incidence of indwelling catheter-associated urinary tract infections before and after MTP intervention were different, and the difference was statistically significant (P<0.05). Conclusion MTP intervention model can effectively prevent and reduce indwelling catheter-associated urinary tract infections in ICU.
Objective To analyze risk factors for prolonged stay in intensive care unit (ICU) after cardiac valvular surgery. Methods Between January 2005 and May 2005, five hundred and seven consecutive patients undergone cardiac valvular surgery were divided into two groups based on if their length of ICU stay more than 5 days (prolonged stay in ICU was defined as 5 days or more). Group Ⅰ: 75 patients required prolonged ICU stay. Group Ⅱ: 432 patients did not require prolonged ICU stay. Univariate and multivariate analysis (logistic regression) were used to identify the risk factors. Results Seventyfive patients required prolonged ICU stay. Univariate risk factors showed that age, the proportion of previous heart surgery, smoking history and repeat cardiopulmonary bypass (CPB) support, cardiothoracicratio, the CPB time and aortic crossclamping time of group Ⅰ were higher or longer than those of group Ⅱ. The heart function, left ventricular ejection fraction (LVEF), pulmonary function of group Ⅰwere worse than those of group Ⅱ(Plt;0.05, 0.01). Logistic regression identified that preoperative age≥65 years (OR=4.399), LVEF≤0.50(OR=2.788),cardiothoracic ratio≥0.68(OR=2.411), maximal voluntary ventilation observed value/predicted value %lt;71%(OR=4.872), previous heart surgery (OR=3.241) and repeat CPB support during surgery (OR=18.656) were final risk factors for prolonged ICU stay. Conclusion Prolonged ICU stay after cardiac valvular surgery can be predicted through age, LVEF, cardiothoracic ratio, maximal voluntary ventilation, previous heart surgery and repeat CPB support during surgery. The patients with these risk factors need more preoperative care and postoperative care to reduce mortality, morbidity and avoid prolonged ICU stay after cardiac valvular surgery.
ObjevtiveThe morbidity of intensive care unit-acquired swallowing disorder (ICU-ASD) was clarified through meta-analysis by synthesizing previous evidence, in order to provide an evidence-based basis for early identification and intervention of ICU-ASD. Methods A computerized search of PubMed, Embase, Web of Science, The Cochrane Library, CHINAL, China Knowledge Network, Wanfang Data Knowledge Service Platform, and Chinese Science and Technology Journal Database was conducted to retrieve the relevant literature on the morbidity of ICU-ASD published in China and abroad from the database establiment to December 2022. Considering the quality of the included literature, the Chinese database excluded master's theses and non-core journals. Meta-analysis of morbidity was performed using Stata 12.0. Results A total of 19 papers, including 4291 patients, were included. Meta-analysis showed that the overall morbidity of ICU-ASD was 36% [95% confidential interval (CI) 26% - 46%; I2=97.62%, P<0.01]. Subgroup analyses showed that the morbidity of ICU-ASD in Asian, European, South American, and North American was 39% (95%CI 28% - 50%), 23% (95%CI 8% - 44%), 52% (95%CI 46% - 57%), and 39% (95%CI 20% - 61%), respectively; and that the morbidity of male and female ICU-ASD was 36% (95%CI 24% - 48%) and 33% (95%CI 22% - 45%), respectively; the morbidity of ICU-ASD was 41% (95%CI 30% - 52%) and 31% (95%CI 18% - 44%) in the patients with and without hypertension, respectively; the morbidity of ICU-ASD was 58% (95%CI 42% - 73%) and 51% (95%CI 36% - 66%) in the patients with and without respiratory disease respectively; the morbidity of ICU-ASD in the patients with and without diabetes mellitus was 37% (95%CI 24% - 51%) and 39% (95%CI 28% - 51%), respectively; the morbidity of ICU-ASD in the patients with and without renal disease was 40% (95%CI 23% - 59%) and 35% (95%CI 24% - 46%), respectively; the morbidity of ICU-ASD in the patients with intubation caliber ≤7.5 mm and >7.5 mm was 31% (95%CI 19% - 45%) and 37% (95%CI 22% - 54%), respectively; the morbidity of ICU-ASD in the patients with and without heart failure was 58% (95%CI 30% - 84%) and 36% (95%CI 23% - 51%), respectively; and the morbidity of ICU-ASD in patients with and without arrhythmia was 36% (95%CI 11% - 65%) and 31% (95%CI 21% - 42%), respectively; the morbidity of ICU-ASD in the patients with and without neurologic disease was 48% (95%CI 24% - 72%) and 34% (95%CI 15% - 57%), respectively. Begg's test P<0.05, Egger's test P<0.05, suggesting publication bias in the study, and the cut-and-patch method corrected for an overall incidence result of 27% (95%CI 18% - 36%). Conclusions Meta-analysis reveals an overall morbidity of 36% for ICU-ASD and 27% for the cut-and-patch correction. Subgroup analysis reveals that the morbidity of ICU-ASD is significantly higher in patients with hypertension, heart failure, and neurological disorders than in patients without these disorders. Current evidence suggests that the prevalence of ICU-ASD is high and needs to be taken seriously. Timely screening and assessment of swallowing disorders is recommended for intensive care unit patients, especially those with hypertension, heart failure, and neurological disorders.
呼吸机相关肺炎( VAP) 是指应用机械通气治疗后48 h和停用机械通气拔除人工气道48 h 内发生的肺实质的感染性炎症。VAP 是机械通气治疗中常见的严重并发症。其发生率为9% ～70% [ 1] , 病死率高达20% ～71% [ 2, 3 ] 。依据其发生的时间可分为早发性VAP 和晚发性VAP。早发性VAP: 即气管插管或人工气道建立lt; 5 d 发生者, 约占VAP的1/2, 主要由插管时即定植于呼吸道内的病原体如肺炎链球菌、甲氧西林敏感金黄色葡萄球菌、流感嗜血杆菌等引起。晚发性VAP: 即气管插管或人工气道建立gt;5 d 发生者, 常由肠道革兰阴性细菌如肠杆菌科、不动杆菌属和假单胞菌属细菌所致。采取有效措施预防VAP 的发生, 对于降低病死率, 减少住院时间和医疗费用, 节约医疗资源具有重要的意义。按照随机对照临床试验中的预防措施可总分为非药物性措施与药物性措施。
Objective To explore the nurses’ cognition of busyness in intensive care unit (ICU), summarize the main busy scenes, and provide strategies for solving problems of busyness. Methods Nurses in three ICU departments of Shanghai Oriental Hospital were selected by purpose sampling method from September 2020 to January 2021. Face-to-face semi-structured in-depth interviews were conducted with nurses. The interview data were analyzed and thematically refined using the method of Colaizzi data analysis. Results A total of 10 nurses were interviewed, including 8 general nurses and 2 head nurses, all of whom were women. The cognition of busyness covered three elements: explosively increased workload, time pressure, and overwhelming information from multiple sources. Busy scenes included four themes: large amount of patients, critical conditions of patients, unstable conditions of patients, and frequent service transfer among different medical divisions. Conclusions According to the three elements of nurses’ cognition of busyness and scenes of it, nursing managers can put forward corresponding solutions. This can retain or attract more nurses to work in ICU and provide better services for patients.