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1.
Статья в английский | WPRIM | ID: wpr-1041999

Реферат

Background@#Carbapenem-resistant Pseudomonas aeruginosa (CrPA) is a leading cause of healthcare-associated urinary tract infections (UTIs). Carbapenemase production is an important mechanism that significantly alters the efficacy of frequently used anti-pseudomonal agents. Reporting the current genotypic distribution of carbapenemase-producing P.aeruginosa (CPPA) isolates in relation to antimicrobial susceptibility, UTI risk factors, and mortality is necessary to increase the awareness and control of these strains. @*Methods@#In total, 1,652 non-duplicated P. aeruginosa strains were isolated from hospitalized patients between 2015 and 2020. Antimicrobial susceptibility, carbapenemase genotypes, risk factors for UTI, and associated mortality were analyzed. @*Results@#The prevalence of carbapenem-non-susceptible P. aeruginosa isolates showed a decreasing trend from 2015 to 2018 and then increased in the background of the emergence of New Delhi metallo-β-lactamase (NDM)-type isolates since 2019. The CPPA strains showed 100.0% non-susceptibility to all tested antibiotics, except aztreonam (94.5%) and colistin (5.9%). Carbapenems were identified as a risk and common predisposing factor for UTI (odds ratio [OR] = 1.943) and mortality (OR = 2.766). Intensive care unit (ICU) stay (OR = 2.677) and white blood cell (WBC) count (OR = 1.070) were independently associated with mortality. @*Conclusions@#The changing trend and genetic distribution of CPPA isolates emphasize the need for relentless monitoring to control further dissemination. The use of carbapenems, ICU stay, and WBC count should be considered risk factors, and aggressive antibiotic stewardship programs and monitoring may serve to prevent worse outcomes.

2.
Статья | WPRIM | ID: wpr-836059

Реферат

Background@#Two methods of counting cells in body fluids were compared;manual counting using a Neubauer chamber, and automated cell countingusing an XN-350 hematology analyzer. @*Methods@#Cells from 32 body fluid samples were counted by manualexamination and by an automated analyzer. Total cells (TC), white bloodcells (WBC), red blood cells (RBC), polymorphonuclear leukocytes (PMN),mononuclear leukocytes (MN), neutrophils, lymphocytes, monocytes, andeosinophils were each counted by both methods. The results were comparedusing the Pearson correlation test, Bland-Altman regression analysis, andPassing-Bablok regression analysis. @*Results@#The two methods showed very strong correlation in TC, WBC,RBC, PMN, and MN counts, strong correlation in % neutrophils, and %lymphocytes, and weak correlation in % monocytes and % eosinophils.Using Bland-Altman regression analysis, the mean biases for TC, WBC, andRBC were -270, -257.4, and -1,256.09, respectively, and 0.15 for PMN andMN. Research parameters were compared as well: mean biases were -1.31,-2.46, -5.16, and -3.58 for % neutrophils, % monocytes, % lymphocytes,and % eosinophils, respectively. Passing-Bablok regression equationswere y=1.039x+20, y=1.037x+19, y=1.259x+0.0, y=0.983x+1.541, andy=0.983x+0.125 for TC, WBC, RBC, PMN, and MN, respectively. The equationswere y=0.955x+2.194 for % neutrophils, y=0.965x+1.184 for % monocytes,y=1.003x+0.161 for % lymphocytes, and y=x+0.75 for % eosinophils. @*Conclusions@#WBC differential count results performed by an automatedhematology analyzer generally show good correlation with our referencemethod, Neubauer chamber counting.

3.
Статья | WPRIM | ID: wpr-830348

Реферат

Background@#Carbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as an important nosocomial pathogen.The purpose of this study was to determine the effective methods for performing surveillance cultures of CRAB. @*Methods@#Nasal and rectal swabs were obtained concurrently from hospitalized intensive care unit patients colonized with CRAB. All the samples were inoculated in CHROMagar Acinetobacter medium with CR102 (CHROMagar), MacConkey agar medium supplemented with 5 µg/mL imipenem (MCA-IPM), and triptic soy broth medium supplemented with 5 µg/ mL imipenem (TSB-IPM). CRAB detection rates for each sample were compared. @*Results@#The CRAB detection rate in either one of the nasal or rectal swabs from the 37 patients tested were 89.2% (33/37) with the use of CHROMagar, 78.4% (29/37) with the use of MCA-IMP, and 86.5% (32/37) with the use of TSB-IMP. @*Conclusion@#We determined that concurrent use of both nasal and rectal swabs and CHROMagar could be an effective method for CRAB surveillance cultures.

5.
Статья в Корейский | WPRIM | ID: wpr-713613

Реферат

BACKGROUND: Different age groups may have different reference intervals. However, the currently used reference interval for complete blood count (CBC) in clinical laboratories is based on results from healthy adults between 20 and 50 years of age. In this study, we aimed to establish reference intervals for 16 CBC parameters in Korean healthy elderly individuals. METHODS: A total of 3,359 healthy adults were selected from 4,253 adults (aged ≥20 years) who underwent regular health check-ups, based on a medical examination by interview. The reference intervals for CBC in two groups (aged <60 and ≥60 years), and the partitioning of reference intervals between the two age groups were established. RESULTS: Most CBC parameters showed no significant differences in reference intervals between the two age groups. Among the men, platelet distribution width (PDW) was the only parameter that required a separate reference interval between the two age groups. Among the women, mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), and eosinophil % required separate reference intervals between the two age groups. CONCLUSIONS: The reference intervals for most CBC parameters were not significantly different between the two age groups. Except for PDW in men and MCV, MCHC, RDW, and eosinophil % in women, reference intervals for CBC parameters in individuals younger than 60 years of age could also be applied to those that are 60 years of age or older.


Тема - темы
Adult , Aged , Female , Humans , Male , Blood Cell Count , Blood Cells , Blood Platelets , Eosinophils , Erythrocyte Indices
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