Misuse of antibiotics by the medical profession is a global concern. Examining doctors’ knowledge about antimicrobials will be important in developing strategies to improve antibiotic use. The aim of the study was to survey Chinese doctors’ knowledge on antibiotics and reveal the factors associated with their level of knowledge. A cross-sectional survey was conducted in Shanxi in central China. A total of 761 physicians were surveyed using a structured self-administered questionnaire. A generalized linear regression model was used to identify the factors associated with doctors’ knowledge on antibiotic. Based on a full score of 10, the average score for doctors’ knowledge on antibiotics was 6.29 (SD = 1.79). Generalized linear regression analysis indicated that doctors who either worked in the internal medicine department, who were chief doctors or who received continuing education on antibiotic, had better knowledge of antibiotics. Compared with doctors working in tertiary hospitals, doctors working in secondary hospitals or primary healthcare facilities had poorer knowledge about antibiotics. Chinese doctors have suboptimal knowledge about antimicrobials. Ongoing education is effective to enhance doctors’ knowledge, but the effect remains to be further improved. More targeted interventions and education programs should improve knowledge about antimicrobials, especially for doctors working in primary healthcare institutions.

BackgroundTandem mass spectrometry (MS MS) and simple fluorometric assays are currently used in newborn screening programs to detect inborn errors of metabolism (IEM). The aim of the study was to evaluate the clinical utility of exome sequencing as a second tier screening method to assist clinical diagnosis of the newborn.MethodsA novel PCR-exome amplification and re-sequencing (PEARS) assay was designed and used to detect mutations in 122 genes associated with 101 IEM. Newborn bloodspots positive by biochemical testing were analysed by PEARS assay to detect pathogenic mutations relevant to the IEM.ResultsIn initial validation studies of genomic DNA samples, PEARS assay correctly detected 25 known mutations associated with 17 different IEM. Retrospective gene analysis of newborns with clinical phenylketonuria (PKU), identified compound heterozygote phenylalanine hydroxylase (PAH) gene mutations in eight of nine samples (89%). Prospective analysis of 211 bloodspots correctly identified the two true PKU samples, yielding positive and negative predictive values of 100%. Testing of 8 true positive MS MS samples correctly identified potentially pathogenic compound heterozygote genotypes in 2 cases of citrullinemia type 1 and one case each of methylmalonic acidemia, isobutyryl-CoA dehydrogenase deficiency, short chain acyl-CoA dehydrogenase deficiency and glutaric acid type II and heterozygous genotypes in 2 cases of autosomal dominant methioninemia. Analysis of 11 of 12 false positive MS MS samples for other IEM identified heterozygous carriers in 8 cases for the relevant genes associated with the suspected IEM. In the remaining 3 cases, the test revealed compound heterozygote mutations in other metabolic genes not associated with the suspected IEM, indicating a misinterpretation of the original MS MS data.ConclusionsThe PEARS assay has clinical utility as a rapid and cost effective second-tier test to assist the clinician to accurately diagnose newborns with a suspected IEM.Electronic supplementary materialThe online version of this article (10.1186/s12881-018-0731-5) contains supplementary material, which is available to authorized users.

Purpose: In China the number of pathologists is far from being enough to meet the demands of ongoing population based cervical cancer screening programs. This article aims to present our experience with automated quantitative cytology imaging platform, a reading system with an artificial intelligence that we currently use routinely for cervical cancer screening in Shanxi province.Methods: From 2012-2016 a total of 40 178 women were screened. Women were divided into three groups and each group had two subgroups. Smear and liquid based technique were compared using manual and automated platform.Results: Detection rates of CIN2 + and positive rates of CIN2 were higher in all three groups when automated quantitative cytology platform was used compared with groups where reading was done by the pathologist using conventional microscope. Operator's costs associated with automated quantitative cytology platform vs. conventional reading using light microscope were compared too. The overall costs of operations based on automated platform were proven to be lower.Conclusion: The use of automated platform and artificial intelligence as a means to overcome the lack of cytotechnologists and pathologists and to implement proper quality control in the large scale population based cervical cancer screening seems very promising.

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