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Objective To study the correlation of bone age and bone mineral density with age, height and weight of short children. Methods Sixty-four short children who were consulted and treated at the author's hospital from January 2016 to October 2018 were selected as research subjects. The general information including age, sex, height and weight of the children were recorded. The ultrasound bone density test was carried out at the same time. The bone mineral density and bone age were evaluated through plain carpal bone radiograph. The relationship between different bone age and bone mineral density value with age, height and weight was analyzed. Results The actual age of the enrolled children was positively correlated with bone mineral density and bone age (boys r=0.658, 0.919, girls r=0.641, 0.906). The height of the enrolled children was positively correlated with bone mineral density and bone age (boy r=0.561, 0.326, girls r=0.586, 0.349). The weight of the enrolled children was positively correlated with bone mineral density and bone age (boys r=0.340, 0.314, girls r=0.395, 0.282). Conclusion The bone age and bone mineral density of short children were positively correlated with their age, height and weight. In clinical diagnosis and treatment, the use of bone age and bone mineral density as a guide can produce more significant effects, which can be used as scientific indicators for the evaluation and prediction of short children.
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Objective:To assess the bacterial profiles and antimicrobial susceptibility patterns in uropathogens, and help to inform the empiric treatment decisions for urinary tract infection in outpatient settings.Methods:A single institutional retrospective analysis was performed on positive urine cultures from outpatient settings between January 1998 and December 2018. To analyze changes over time, trends analysis were undertaken on bacterial profiles, antimicrobial susceptibility and resistance.Results:A total of 1.172 pathogenic bacteria were isolated after exclusion of duplicate strains originated from the same patient, including 991(84.6%) Gram-negative bacterial strains and 181(15.4%) Gram-positive strains. The most common Gram-negative uropathogens were Escherichia coli (60.8%) and Klebsiella pneumonia (8.1%). Enterococcus faecalis (4.6%) was the predominant Gram-positive strain. The detection rate of Escherichia coli increased significantly, from 50.8% to 63.2% ( χ2=7.978, P=0.046), and no significant difference was observed in the distribution of major uropathogenic bacteria over the 20 years (all P>0.05). The proportion of extended-spectrum β-lactamase (ESBLs) producing strains increased significantly across the 20 years ( P<0.05). The resistance rates of Escherichia coli to amoxicillin and clavulanate potassium, aztreonam, ceftazidime, ciprofloxacin and sulbactam + cefoperazone increased significantly (all P<0.05). All the isolates sustained high susceptibility to tazobactam + piperacillin, amikacin, imipenem and nitrofurantoin (95.0%, 95.7%, 97.9% and 91.1%). Similar to those of Escherichia coli, Klebsiella pneumoniae remained a high and stable sensitivity to tazobactam+piperacillin, amikacin and imipenem during the 20 years (79.1%, 88.0% and 80.3%). However, the proportion of ESBLs producing strains increased significantly ( P<0.05). Among Gram-positive bacteria isolates, the sensitivity rates of Enterococcus faecalis to ampicillin, nitrofurantoin and penicillin G were 100.0%. No vancomycin resistant strain was detected in Gram-positive bacteria. Conclusions:From 1998 to 2018, Escherichia coli and Klebsiella pneumoniae are the most common Gram-negative bacteria uropathogens obtained in outpatient settings. Significant increases of resistance to some antimicrobial agents such as second- and third-generation cephalosporins and fluoroquinolones are observed during the 20 years and high susceptibilities to tazobactam+piperacillin, amikacin, imipenem and nitrofurantoin sustain over time. Local treatment strategies of urinary tract infections on outpatient basis should be made according to epidemiology of drug resistance and individual characteristics to control the spread and curb the prevalence of drug resistant.
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Objective:To establish the fingerprint analysis method for the root of Rosa laevigata Michx from different regions by UPLC. Methods:The column was ACQUITY UPLC? Phenyl(2.1 mm × 100 mm,1.7 μm). The mobile phase consisted of methanol-water with gradient elution. The flow rate was 0. 2 ml·min-1 , the detection wavelength was 210 nm, the column temperature was 30℃, and the injection volume was 3 μl. Results:The fingerprint consisted of 15 common peaks. The range of similarity for twelve bat-ches of the root of R. laevigata Michx was 0. 489-0. 942. And the reference fingerprint of the root of R. laevigata Michx was estab-lished by UPLC. Conclusion:The fingerprint method is simple and reproducible, which can provide basis for the quality control and the medicinal resources exploration.