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[This corrects the article DOI: 10.3389/fmed.2022.876207.].
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Background: Bloodstream infections (BSI) are one of the common causes of morbidity and mortality in hospitals; however, the pathogenic spectrum and bacterial antibiotic resistance vary across the world. Therefore, identifying the pathogenic spectrum and changes in bacterial antibiotic resistance is critical in controlling BSI and preventing the irrational use of antibiotics. This study evaluated the microbiological and clinical data of BSI patients in the intensive care unit (ICU) of Tianjin Medical University General Hospital in Tianjin, China, to guide the selection of empirical antibiotic therapy. Methods: This study retrospectively analyzed the distribution and antibiotic resistance of pathogens based on the clinical data of BSI patients presented in the ICU of a tertiary teaching hospital from 2018 to 2020. Test performance for the prediction of pathogen species was assessed by receiver operating characteristic (ROC) analysis. Results: The analysis of the data of 382 BSI cases (10.40 cases per thousand patient day) revealed the most frequently isolated microorganisms to be Klebsiella pneumonia (11.52%), followed by Escherichia coli (9.95%), Staphylococcus epidermidis (9.95%), Candida parapsilosis (8.12%), and Enterococcus faecium (8.12%). Out of the isolated E. coli and K. pneumonia strains, 52.63, and 36.36%, respectively, were extended-spectrum ß-lactamase (ESBL) positive. The antibiotic-resistance rate of the ESBL-positive strains was 30.56% for piperacillin/tazobactam, 5.56% for imipenem, and 11.11% for tigecycline. In addition, most A. baumannii belonged to the group of multidrug-resistant (MDR) strains, with an antibiotic-resistance rate of 90.48% for meropenem and 16.00% for amikacin. However, polymyxin-resistant A. baumannii strains were not detected. Four strains of methicillin-resistant S. aureus (MRSA) (4/21, 19.05%) and one strain of vancomycin-resistant enterococci (VRE) were detected, with a resistance rate of 4.76 and 2.32%, respectively. Among the isolated 55 fungal strains, C. parapsilosis was the most common one (30/55, 56.36%), with an antibiotic-resistance rate of 5.77% for voriconazole, fluconazole, and itraconazole. The presence of amphotericin B-or flucytosine-resistant strains was not observed. Compared with the patients with Gram-positive and fungal pathogens, patients with Gram-negative bacteria exhibited the highest sequential organ failure assessment (SOFA) score (P < 0.001), lowest Glasgow Coma Scale (GCS) (P = 0.010), lowest platelet (PLT) value (P < 0.001), highest plasma creatinine (Cr) value (P = 0.016), and the highest procalcitonin (PCT) value (P < 0.001). The AUC in the ROC curve was 0.698 for the differentiation of Gram-negative BSI from Gram-positive BSI. A cutoff value of 8.47 ng/mL for PCT indicated a sensitivity of 56.9% and a specificity of 75.5%. The AUC in the ROC curve was 0.612 for the differentiation of bacteremia from fungemia. A cutoff value of 4.19 ng/mL for PCT indicated a sensitivity of 56.8% and a specificity of 62.7%. Conclusion: Among the bloodstream infection strains in ICU, Gram-negative bacteria have the highest drug resistance rate, and will cause more serious brain damage, renal function damage and thrombocytopenia. So clinician should pay more attention to the treatment of Gram-negative bacteria in patients with bloodstream infection in ICU. The test index of PCT can be used to distinguish Gram-negative bacteremia from Gram-positive and bacteremia from fungemia but not as an effective indicator, thereby indicating the need for further large-scale research.
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BACKGROUND: Acute respiratory distress syndrome (ARDS) is injury of alveolar epithelial cells and capillary endothelial cells caused by various factors, including endogenous and exogenous lung factors, leading to diffuse pulmonary interstitial and alveolar edema, and acute respiratory failure. ARDS involves alveolar epithelial cells and pulmonary interstitial capillary endothelial cells. Circulating endothelial cells (CECs) are the only marker that directly reflects vascular endothelial injury in vivo. There have been few studies on the correlation between peripheral blood CECs and ARDS at home and abroad. The lungs are the organs with the highest capillary density and the most endothelial cells, thus, it is speculated that when ARDS occurs, CECs are stimulated and damaged, and released into the circulatory system. AIM: To explore the correlation between CEC level and severity of ARDS in patients postoperatively. METHODS: Blood samples were collected from all patients on day 2 (d2) and day 5 (d5) after surgery. The control group comprised 32 healthy volunteers. Number of CECs was measured by flow cytometry, and operation time was recorded. Changes in various indexes of patients were monitored, and diagnosis of ARDS was determined based on ARDS Berlin definition. We comprised d2 CECs in different groups, correlation between operation time and d2 CECs, ARDS of different severity by d2 CECs, and predictive value of d2 CECs for ARDS in postoperative patients. RESULTS: The number of d2 CECs in the ARDS group was significantly higher than that in the healthy control group (P < 0.001). The number of d2 CECs in the ARDS group was significantly higher than that in the non-ARDS group (P < 0.001). The number of d2 CECs in the non-ARDS group was significantly higher than that in the healthy control group (P < 0.001). Operation time was positively correlated with number of CECs on d2 (rs = 0.302, P = 0.001). The number of d2 CECs in the deceased group was significantly higher than that in the improved group (P < 0.001). There was no significant difference in number of d2 CECs between patients with mild and moderate ARDS. The number of d2 CECs in patients with severe ARDS was significantly higher than that in patients with mild and moderate ARDS (P = 0.041, P = 0.037). There was no significant difference in number of d5 and d2 CECs in the non-ARDS group after admission to intensive care. The number of d5 CECs was higher than the number of d2 CECs in the ARDS improved group (P < 0.001). The number of d5 CECs was higher than the number of d2 CECs in the ARDS deceased group (P = 0.002). If the number of CECs was > 1351/mL, sensitivity and specificity of predicting ARDS were 80.8% and 78.1%, respectively. CONCLUSION: Changes in number of CECs might predict occurrence and adverse outcome of ARDS after surgery, and higher numbers of CECs indicate worse prognosis of ARDS.
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OBJECTIVE: To determine the respiratory indices capable of improving predictive accuracy of extubation success through serial measurements of during spontaneous breathing trial (SBT) in automatic tube compensation (ATC) pattern of mechanical ventilation. METHODS: For this prospective observational study, patients ventilated over 48 hours were enrolled according to the weaning criterion and underwent a 60 minutes spontaneous breathing trial (SBT) in ATC pattern (ATC = 100%, FiO2 = 0.4, PEEP = 0 cm H2O, PS = 0 cm H2O). During SBT, heart rate (HR) and mean artery pressure (MAP) were monitored continuously and minute volume (VE), respiratory rate (RR), tidal volume of spontaneous breath (VT), rapid shallow breathing index (RSBI), change and rate of change (ΔRSBI60_1 and ΔRSBI60_1/RSBI1, etc.) were recorded or calculated at the first, 30(th) and 60(th) minute of SBT. Patients tolerating the trial were extubated immediately. Clinical data and respiratory indices during SBT were compared between patients in extubation success group and those in extubation failure group. Predictive accuracy of extubation success was assessed by area under the receiver operating characteristic (ROC) curve (AUC) for each index. RESULTS: The duration of mechanical ventilation was longer in patients of extubation failure group than that of extubation success group (10.75 ± 2.73: 7.47 ± 5.11, P = 0.035) and extubation failure rate was 17.14%. During SBT, RSBI increased initially and then decreased in patients of extubation success group, but increased continuously in patients of extubation failure group. There were significant difference of ΔRSBI60_1 and ΔRSBI60_1/RSBI1 in patients between extubation success and failure groups (-11.5 ± 16.6: 12.1 ± 38.9, P = 0.001 and -17 ± 26: 13 ± 39, P = 0.028). AUCs of RSBI60, ΔRSBI60_1 and ΔRSBI60_1/RSBI1 were 0.75, 0.73 and 0.72 and the sensitivity, specificity and diagnostic accuracy 81.0%, 66.7% and 78.5% respectively. CONCLUSION: It is important to observe change of various respiratory indices dynamically during SBT in patients ventilated in ATC pattern. ΔRSBI60_1 and ΔRSBI60_1/RSBI1 have greater predictive value for extubation success. Stable or decreased RSBI60 means higher extubation success rate.
