ObjectiveTo evaluate the diagnostic value of various severity assessment scoring systems for sepsis after cardiac surgery and the predictive value for long-term prognosis.MethodsThe clinical data of patients who underwent cardiac sugeries including coronary artery bypass grafting (CABG) and (or) valve reconstruction/valve replacement were extracted from Medical Information Mark for Intensive Care-Ⅲ (MIMIC-Ⅲ). A total of 6 638 patients were enrolled in this study, including 4 558 males and 2 080 females, with an average age of 67.0±12.2 years. Discriminatory power was determined by comparing the area under the receiver operating characteristic (ROC) curve (AUC) for each scoring system individually using the method of DeLong. An X-tile analysis was used to determine the optimal cut-off point for each scoring system, and the patients were grouped by the cut-off point, and Kaplan-Meier curves and log-rank test were applied to analyze their long-term survival.ResultsCompared with the sequential organ failure assessment (SOFA) score, acute physiology score-Ⅲ (APS-Ⅲ, P<0.001), the simplified acute physiology score-Ⅱ (SAPS-Ⅱ, P<0.001) and logistic organ dysfunction score (LODS, P<0.001) were more accurate in distinguishing sepsis. Compared with the non-septic group, the 10-year overall survival rate of the septic group was lower (P<0.001). Except for the systemic inflammation response score (SIRS) system, the 10-year overall survival rates of patients in the high risk layers of SOFA (HR=2.50, 95%CI 2.23-2.80, P<0.001), SAPS (HR=2.93, 95%CI 2.64-3.26, P<0.001), SAPS-Ⅱ (HR=2.77, 95%CI 2.51-3.04, P<0.001), APS-Ⅲ (HR=2.90, 95%CI 2.63-3.20, P<0.001), LODS (HR=2.17, 95%CI 1.97-2.38, P<0.001), modified logistic organ dysfunction score (MLODS, HR=2.04, 95%CI 1.86-2.25, P<0.001) and the Oxford acute severity of illness score (OASIS, HR=2.37, 95%CI 2.16-2.60, P<0.001) systems were lower than those in the low risk layers.ConclusionCompared with SOFA score, APS-Ⅲ score may have higher value in the diagnosis of sepsis in patients who undergo isolated CABG, a valve procedure or a combination of both. Except for SIRS scoring system, SOFA, APS-Ⅲ, SAPS, SAPS-Ⅱ, LODS, MLODS and OASIS scoring systems can be applied to predict the long-term outcome of patients after cardiac surgery.
ObjectiveTo evaluate the effect of bundle strategies on the prevention and control of multidrug-resistant organisms (MDROs) in intensive care unit (ICU), in order to effectively prevent and control the severe situation of multiple drug-resistant bacteria in ICU.MethodsWe selected patients who admitted into the ICU from January 2016 to December 2017 as study subjects, and monitored 6 types of MDROs. Basic information was surveyed and collected from January to December 2016 (before intervention), while bundle strategies on MDROs were implemented from January to December 2017 (after intervention), including issusing isolation orders, hanging isolation marks, wearing isolation clothes, using medical articles exclusively, cleaning and disinfecting environment, implementing hand hygiene, etc. Then we compared the MDRO detection rate, nosocomial infection rate, MDRO nosocomial infection rate, and compliance rates of interventions between the two periods.ResultsThe MDRO detection rate before intervention was 77.10%, and that after intervention was 49.12%, the difference between the two periods was statistically significant (χ2=69.834, P<0.001). The nosocomial infection rate of ICU decreased from 23.51% before intervention to 15.23% after intervention, the MDRO nosocomial infection rate decreased from 13.70% before intervention to 5.84% after intervention, and the differences between the two periods were statistically significant (χ2=8.594, P=0.003; χ2=13.722, P<0.001). The compliance rates of doctor’s isolation orders, hanging isolation marks, wearing isolation clothes, using medical articles exclusively, cleaning and disinfecting environment, and hand hygiene, as well as the correct rate of hand hygiene after intervention (92.12%, 93.55%, 81.77%, 84.24%, 82.90%, 77.39%, and 96.37%) were significantly higher than those before intervention (31.94%, 52.00%, 23.43%, 48.18%, 67.16%, 59.46%, and 88.64%), and the differences were all statistically significant (P<0.001).ConclusionThe implementation of the above bundle strategies on the prevention and control of MDROs can decrease the MDRO detection rate and MDRO nosocomial infection rate.
ObjectiveTo analyze the trend of disease spectrum and main diagnosis and therapeutic technologies in respiratory intensive care unit (RICU) in recent years, and find out the trend of change of patient’s characteristics and commonly used interventions in order to provide evidence for planning discipline development and improving personnel training program.MethodsPatients information and main diagnosis and therapeutic technologies of 1503 inpatients in RICU of Shenzhen People's Hospital from January, 2017 to December, 2020 were collected. The changes of disease spectrum and diagnosis and treatment technologies in different years were compared and analyzed.ResultsAmong all the patients, 66.3% were directly admitted into RICU, 12.1% were transferred from respiratory department, and 21.6% were transferred from other departments. The proportion of patients with non-respiratory diseases as principal diagnosis had an increasing trend, from 18.8% in 2017 to 37.3% in 2020 (P<0.05). The diseases with most obvious increasing trend were sepsis, nervous system diseases, circulatory system diseases and extra-pulmonary malignancies (P<0.05). The use of respiratory related diagnosis and therapeutic technologies was gradually increasing, meanwhile, the use of non-traditional respiratory related technologies, especially continuous renal replacement therapy, was also increasing. There was no significant difference in fatality rate among different years (P>0.05).ConclusionsThe number of patients with extra-pulmonary diseases and the use of non-traditional respiratory related diagnosis and therapeutic technologies in RICU were increasing. The development of RICU and the allocation of technical personnel needed to be improved accordingly.
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 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.
ObjectiveTo systematically review the risk factors associated with sleep disorders in ICU patients.MethodsWe searched The Cochrane Library, PubMed, EMbase, Web of Science, CNKI, Wanfang Data, VIP and CBM databases to collect cohort studies, case-control studies and cross-sectional studies on the risk factors associated with sleep disorders in ICU patients from inception to October, 2018. Two reviewers independently screened literature, extracted data and evaluated the bias risk of included studies. Then, meta-analysis was performed by using RevMan 5.3 software.ResultsA total of 9 articles were included, with a total of 1 068 patients, including 12 risk factors. The results of meta-analysis showed that the combined effect of equipment noise (OR=0.42, 95%CI 0.26 to 0.68, P=0.000 4), patients’ talk (OR=0.53, 95%CI 0.42 to 0.66, P<0.000 01), patients’ noise (OR=0.39, 95%CI 0.21 to 0.74, P=0.004), light (OR=0.29, 95%CI 0.18 to 0.45, P<0.000 01), night treatment (OR=0.36, 95%CI 0.26 to 0.50, P<0.000 01), diseases and drug effects (OR=0.17,95%CI 0.08 to 0.36, P<0.000 01), pain (OR=0.37, 95%CI 0.17 to 0.82, P=0.01), comfort changes (OR=0.34,95%CI 0.17 to 0.67,P=0.002), anxiety (OR=0.31,95%CI 0.12 to 0.78, P=0.01), visit time (OR=0.72, 95%CI 0.53 to 0.98, P=0.04), economic burden (OR=0.63, 95%CI 0.48 to 0.82, P=0.000 5) were statistically significant risk factors for sleep disorders in ICU patients.ConclusionCurrent evidence shows that the risk factors for sleep disorders in ICU patients are environmental factors (talking voices of nurses, patient noise, and light), treatment factors (night treatment), disease factors (disease itself and drug effects, pain,) and psychological factors (visiting time, economic burden). Due to the limited quality and quantity of included studies, more high quality studies are needed to verify the above conclusions.
Objective To compare the bacterial spectrums of respiratory intensive care unit (RICU) patients derived from traditional bacterial culture and loop-mediated isothermal amplification (LAMP) assay. To analyze the relationship between clinical factors and clinical outcome of patients. Methods Data of patients in RICU with lower respiratory tract infection from October 2018 to December 2020 was collected. The bacterial spectrums obtained by traditional culture method and LAMP-based method were compared. Clinical factors were divided into two categories and taken into analysis of variance for assessing their relevance with clinical outcomes. Those with significances in analysis of variance were taken into binary logistic regression. Results A total of 117 patients were included. The ratio of patients with positive bacterial culture results was 39.13% (n=115), and that with positive LAMP assay results was 72.65% (n=117). The ratios of patients with at least two positive results for culture and LAMP were 8.70% (n=115) and 36.75% (n=117), respectively. According to chi-squared test, mechanical ventilation (χ2=5.260, P=0.022), and patients with two or more bacteria positive for LAMP assay (χ2=8.227, P=0.004) were related to higher risk of death. Mechanical ventilation and patients with two bacteria positive for LAMP assay were included in binary logistic regression. The odds ratio for death was 4.789 in patients with two or more bacteria positive by LAMP assay (95% confidence interval 1.198 - 19.144, P=0.027). Conclusions LAMP-based method is helpful in detecting more bacteria from respiratory tract specimens of RICU patients, which will be a contributor to precision medicine. Patients with at least two bacteria positive based on LAMP assay have higher risk of death.
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.