Objective:To study the optimal pain control goal for preventing delirium in critical patients.Methods:A prospective cohort study were conducted. The patients admitted to general departments and transferred to the intensive care unit (ICU) due to critical illness in the First People's Hospital of Changde from January 2017 to November 2019 were enrolled. The General data of the patients were collected within 48 hours after admission. All patients admitted to the ICU were evaluated for pain level using the critical care pain observation tool (CPOT) every 8 hours by nurses, and confusion assessment method of ICU (CAM-ICU) was used to screen delirium patient every 8 hours by the leader of nursing team without knowing the pain level of the patients, until the subjects were transferred out of ICU. The receiver operating characteristic (ROC) curve was drawn, the area under ROC curve (AUC) and the optimal threshold were analyzed with delirium as the reference standard; according to the optimal threshold, multivariate Logistic regression analysis was used to evaluate the correlation between CPOT score and delirium.Results:During the study period, 575 patients were admitted to the participating departments and passed the preliminary screening according to the inclusion and exclusion criteria. During the study period, 34 patients were excluded due to incomplete data. Finally, a total of 541 patients were enrolled in the analysis, including 149 patients in delirium group and 392 patients in non-delirium group. There was no significant difference in gender, age, source of patients, education level, smoking history, drinking history, family mental history, acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score or other general information between the two groups. There were 10.1% (15/149) of patients in the delirium group used opioids, which was significantly higher than 4.3% (17/392) in the non-delirium group, and the difference was statistically significant ( P < 0.05). The CPOT score in the delirium group was significantly higher than that in the non-delirium group (4.24±1.78 vs. 2.75±1.95, P < 0.01). The patients were subdivided into young group (< 40 years old), middle-aged group (40-65 years old) and old group (> 65 years old) according to age. The analysis results were consistent with the overall analysis results. ROC curve analysis showed that the AUC of CPOT score predicting delirium was 0.719; when the best threshold value of CPOT score was 2.5, the sensitivity was 91.3%, the specificity was 49.0%, the positive predictive value was 40.5% and the negative predictive value was 93.7%. Multivariate Logistic regression analysis showed that the risk of delirium in ICU patients with CPOT score ≥ 3 was 10.043 times higher than that in patients with CPOT score < 3 [odds ratio ( OR) = 10.043, 95% confidence interval (95% CI) was 5.498-18.345, P < 0.001]. When the gender, age, APACHEⅡ score, smoking history, drinking history, opioids usage were adjusted, the risk of delirium in patients with CPOT score ≥ 3 was 10.719 times higher than that in patients with CPOT score < 3 ( OR = 10.719, 95% CI was 5.689-20.196, P < 0.001). Conclusion:The best pain control goal for preventing the occurrence of delirium in ICU patients is a CPOT score of 3 or less.

ObjectiveTo describe the novel variants of the Smqnr family of quinolone resistance genes and their distribution in clinical isolates of Stenotrophomonas maltophilia, and investigate the relationship between Smqnr and quinolone resistance. MethodsThe identification of 442 strains of Stenotrophomonas maltophilia were performed by VITEK automated identification and susceptibility. Minimum inhibitoryconcentrationsof tigecycline,chloramphenicol,ceftazidime,compoundsulfamethoxazole,ticarcillin/clavulanic acid, levofloxacin and moxifloxacin against Stenotrophomonas maltophilia were detected by standard agar dilution method. Full length of Smqnr gene was amplified by polymerase chain reaction (PCR) and sequenced. DNAMAN software was used to compare the sequence divergence and construct the genealogical tree to analyze the phylogenetic relationships of Smqnr family. Results Stenotrophomonas maltophilia was resistant to the 7 kinds of clinical antibiotics in various extent ( from 5％ to 50％ ). Levofloxacin showed s good antibacterial activity with the resistance rate of 6. 11％ (27/442), nevertheless the best was moxifloxacin with the resistance rate of 5. 88％ (25/442). Smqnr gene was detected in 114 of 442 strains of Stenotrophomonas maltophilia[25.79％ (114/442)], including 11 known genes and 20 novel variants of the Smqnr genes ( Smqnr28-47 ) which was caused by several genes mutation changing the translation of 219 amino acids. The gene detection rate of resistant, intermediate and sensitive strains was 42. 30％ (11/26), 34. 37％ (11/32) and 23.95％ (92/384), respectively. The Smqnr gene harbored the highest detection rote (37. 78％ ) in the sensitive strains of Stenotrophomonas maltophilia with minimal inhibitory concentration of 0. 125 μg/ml. Conclusions The gene coding region of Smqnr is highly polymorphic and the novel variants of Smqnr gene are caused by several genes mutation changing the translation of 219 amino acids. Smqnr gene in Stenotrophomonas maltophilia has a high detection rate and different distribution.

Since the cluster of the 2019 novel coronavirus (2019-nCoV) pneumonia, a large number of patients gathered, the mortality of critical patients has remained high and the treatment was unclear. In this outbreak, Hunan Changde region immediately set up a hospital and intensive care unit. The patients relieved through respiratory support, hemodynamics management, nutritional support, the application of antiviral drugs, analgesic and sedation. The treatment experience in severe cases of 2019-nCov pneumonia patients were summarized as follows: in terms of respiratory support, we needed to pay attention to the advantages of high-flow nasal cannula oxygen therapy (HFNC) and the intervention of mechanical ventilation, pay attention to the ventilator parameters, and adopt prone position timely. In the aspects of fluid resuscitation and volume management, we should pay attention to the characteristics of severe patients' volume status, perform early evaluation, and clinicians should focused on hemodynamic management beside the bed. In the aspect of nutritional support and evaluation and maintenance of intestinal function, early enteral nutrition should be adopted in time. However, the trade-off between the risk of intestinal function and nutritional support in patients with mechanical ventilation and the antiviral benefits of Kaletra needed to be reevaluated, the optimized way of analgesia and sedation was adopted, at the same time, the usage and side effects of antiviral drugs should be paid attention to. We should grasp the opportunity of transportation for severe patients. It is suggested that some warning scores should be used to facilitate early recognition of patients with severe infection and then they should be earlier transferred to the designated hospital for intensive care.