DESIGN: Prospective cohort study.
SETTING: The study included 317 ICUs of 96 hospitals in 44 cities in 9 countries of Asia: China, India, Malaysia, Mongolia, Nepal, Pakistan, Philippines, Sri Lanka, Thailand, and Vietnam.
PARTICIPANTS: Patients aged >18 years admitted to ICUs.
RESULTS: In total, 157,667 patients were followed during 957,517 patient days, and 8,157 HAIs occurred. In multiple logistic regression, the following variables were associated with an increased mortality risk: central-line-associated bloodstream infection (CLABSI; aOR, 2.36; P < .0001), ventilator-associated event (VAE; aOR, 1.51; P < .0001), catheter-associated urinary tract infection (CAUTI; aOR, 1.04; P < .0001), and female sex (aOR, 1.06; P < .0001). Older age increased mortality risk by 1% per year (aOR, 1.01; P < .0001). Length of stay (LOS) increased mortality risk by 1% per bed day (aOR, 1.01; P < .0001). Central-line days increased mortality risk by 2% per central-line day (aOR, 1.02; P < .0001). Urinary catheter days increased mortality risk by 4% per urinary catheter day (aOR, 1.04; P < .0001). The highest mortality risks were associated with mechanical ventilation utilization ratio (aOR, 12.48; P < .0001), upper middle-income country (aOR, 1.09; P = .033), surgical hospitalization (aOR, 2.17; P < .0001), pediatric oncology ICU (aOR, 9.90; P < .0001), and adult oncology ICU (aOR, 4.52; P < .0001). Patients at university hospitals had the lowest mortality risk (aOR, 0.61; P < .0001).
CONCLUSIONS: Some variables associated with an increased mortality risk are unlikely to change, such as age, sex, national economy, hospitalization type, and ICU type. Some other variables can be modified, such as LOS, central-line use, urinary catheter use, and mechanical ventilation as well as and acquisition of CLABSI, VAE, or CAUTI. To reduce mortality risk, we shall focus on strategies to reduce LOS; strategies to reduce central-line, urinary catheter, and mechanical ventilation use; and HAI prevention recommendations.
PURPOSE: The purpose of this study is twofold. First, it aimed to measure the renal length and calculate the renal volume of normal Thai children using 2-dimensional ultrasonography (2D-US) and study their correlations with somatic parameters. Second, it aimed to compare the age-specific renal size of normal Thai children with the published data of their Western and Chinese counterparts.
METHODS: A total of 321 children (150 boys, 171 girls; age, 6-15 years) with a normal renal profile were prospectively recruited. All subjects underwent 2D-US by an experienced pediatric radiologist and the renal length, width, and depth were measured. Renal volume was calculated using the ellipsoid formula as recommended. The data were compared between the left and right kidneys, the sexes, and various somatic parameters. The age-specific renal lengths were compared using a nomogram derived from a Western cohort that is currently referred by many Thailand hospitals, while the renal volumes were compared with the published data of a Chinese cohort.
RESULTS: No statistically significant difference (P<0.05) was found between sexes or the right and left kidneys. The renal sizes had strong correlations with height, weight, body surface area, and age but not with body mass index. The renal length of the Thai children was moderately correlated (r=0.59) with that of the Western cohort, while the age-specific renal volume was significantly smaller (P<0.05) than that of the Chinese children.
CONCLUSION: Therefore, we concluded that the age-specific renal length and volume obtained by 2D-US would vary between children in different regions and may not be suitably used as an international standard for diagnosis, although further studies may be needed to confirm our findings.
OBJECTIVE: To establish age- and gender-specific normal PVR urine volume in adolescents.
MATERIAL AND METHODS: Healthy adolescents aged 12-18 years were recruited to undergo two uroflowmetry and PVR studies whenever they felt the urge to urinate. Adolescents with neurological disorders, known LUT dysfunction or UTI were excluded.
RESULTS: A total of 1050 adolescents were invited, but only 651 consented. Fourteen participants were excluded due to low bladder volume (BV 100 ml (n = 5) and missing information (n = 6). Ultimately, 894 uroflowmetry and PVR from 605 adolescents (mean age 14.6 ± 1.5 years) were analyzed. PVRs were higher in adolescents aged 15-18 years than in those aged 12-14 years (P 20 ml (7% BV) for males of both the age groups, and PVR >25 ml (9% BV) and PVR >35 ml (>10% BV) for females aged 12-14 and 15-18 years, respectively. Further investigation may be warranted if the repeat PVR is above the 95th percentile, i.e., PVR >30 ml (8% BV) and >30 ml (11% BV) for males aged 12-14 and 15-18 years, respectively, and PVR >35 ml (11% BV) and >45 ml (13% BV) for females aged 12-14 and 15-18 years, respectively.
CONCLUSION: PVR increases with age and varies by gender; thus, age-and gender-specific reference values should be used. Further data from other countries is required to determine whether the study's recommendations can be applied globally.
METHODS: Adults were recruited to undergo uroflowmetry and PVR. Those with neurological disorders, malignancy, diabetes, known lower urinary tract dysfunction, and urinary tract infection within the previous 3 months, were excluded from the study. Constipation was defined as Rome IV ≥ 2.
RESULTS: Of the 883 adults enrolled in this study, 194 (22.3%) did not complete the questionnaires or perform the uroflowmetry, 103 (11.7%) met ≥1 exclusion criteria and thus were excluded. In addition, 30 and 38 uroflowmetry were excluded due to artifacts and low bladder volume (BV) (<100 mL), respectively. Finally, 515 uroflowmetry and PVR data from adults aged 36-89 (mean: 59.0 ± 9.5) were examined. There was a significant nonlinear relationship between BV and PVR (p
Methods: A total of 11 isolates from respiratory cultures in intensive care unit of a 24 bed tertiary hospital obtained over a one months period and one isolate obtained from the nebuliser during environmental screening were investigated. The bacteria were identified by Phoenix 100 system. The clonal relatedness was evaluated by PFGE and semi-automated repetitive sequence-based PCR. Genotyping tests were repeated for 10 serial subcultures.
Results: PFGE and DiversiLab yielded 10 genotypic profiles for 12 isolates. Four to eight different genotypes were observed from 10 subcultures of the same isolate.
Conclusion: We conclude that, high genetic diversity and supposed multiclonal appearance of the outbreak isolates may be due to changing profiles during subcultures most probably depending on hypermutation.