| 1. |
- Cole, Michelle J., et al.
(author)
-
Ten years of external quality assessment (EQA) of Neisseria gonorrhoeae antimicrobial susceptibility testing in Europe elucidate high reliability of data
- 2019
-
In: BMC Infectious Diseases. - : BioMed Central. - 1471-2334. ; 19:1
-
Journal article (peer-reviewed)abstract
- BACKGROUND: Confidence in any diagnostic and antimicrobial susceptibility testing data is provided by appropriate and regular quality assurance (QA) procedures. In Europe, the European Gonococcal Antimicrobial Susceptibility Programme (Euro-GASP) has been monitoring the antimicrobial susceptibility in Neisseria gonorrhoeae since 2004. Euro-GASP includes an external quality assessment (EQA) scheme as an essential component for a quality-assured laboratory-based surveillance programme. Participation in the EQA scheme enables any problems with the performed antimicrobial susceptibility testing to be identified and addressed, feeds into the curricula of laboratory training organised by the Euro-GASP network, and assesses the capacity of individual laboratories to detect emerging new, rare and increasing antimicrobial resistance phenotypes. Participant performance in the Euro-GASP EQA scheme over a 10 year period (2007 to 2016, no EQA in 2013) was evaluated.METHODS: Antimicrobial susceptibility category and MIC results from the first 5 years (2007-2011) of the Euro-GASP EQA were compared with the latter 5 years (2012-2016). These time periods were selected to assess the impact of the 2012 European Union case definitions for the reporting of antimicrobial susceptibility.RESULTS: dilutions of the modal MIC, respectively. The most common method used was Etest on GC agar base. There was a shift to using breakpoints published by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) in the latter 5 years, however overall impact on the validity of results was limited, as the percentage categorical agreement and MIC concordance changed very little between the two five-year periods.CONCLUSIONS: The high level of comparability of results in this EQA scheme indicates that high quality data are produced by the Euro-GASP participants and gives confidence in susceptibility and resistance data generated by laboratories performing decentralised testing.
|
|
| 2. |
- Banhart, Sebastian, et al.
(author)
-
Molecular epidemiological typing of Neisseria gonorrhoeae isolates identifies a novel association between genogroup G10557 (G7072) and decreased susceptibility to cefixime, Germany, 2014 to 2017
- 2020
-
In: Eurosurveillance. - : European Centre for Disease Prevention and Control. - 1025-496X .- 1560-7917. ; 25:41
-
Journal article (peer-reviewed)abstract
- Background: Emerging antimicrobial resistance (AMR) challenges gonorrhoea treatment and requires surveillance.AimThis observational study describes the genetic diversity of Neisseria gonorrhoeae isolates in Germany from 2014 to 2017 and identifies N. gonorrhoeae multi-antigen sequence typing (NG-MAST) genogroups associated with AMR or some patient demographics.Methods: 1,220 gonococcal isolates underwent AMR testing and NG-MAST. Associations between genogroups and AMR or sex/age of patients were statistically assessed.Results: Patients' median age was 32 years (interquartile range: 25-44); 1,078 isolates (88.4%) originated from men. In total, 432 NG-MAST sequence types including 156 novel ones were identified, resulting in 17 major genogroups covering 59.1% (721/1,220) of all isolates. Genogroups G1407 and G10557 (G7072) were significantly associated with decreased susceptibility to cefixime (Kruskal-Wallis chi-squared: 549.3442, df: 16, p < 0.001). Their prevalences appeared to decline during the study period from 14.2% (15/106) to 6.2% (30/481) and from 6.6% (7/106) to 3.1% (15/481) respectively. Meanwhile, several cefixime susceptible genogroups' prevalence seemed to increase. Proportions of isolates from men differed among genogroups (Fisher's exact test, p < 0.001), being e.g. lower for G25 (G51) and G387, and higher for G5441 and G2992. Some genogroups differed relative to each other in affected patients' median age (Kruskal-Wallis chi-squared: 47.5358, df: 16, p < 0.001), with e.g. G25 (G51) and G387 more frequent among ≤ 30 year olds and G359 and G17420 among ≥ 40 year olds.Conclusion: AMR monitoring with molecular typing is important. Dual therapy (ceftriaxone plus azithromycin) recommended in 2014 in Germany, or only the ceftriaxone dose of this therapy, might have contributed to cefixime-resistant genogroups decreasing.
|
|
| 3. |
- Haenssle, H A, et al.
(author)
-
Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.
- 2018
-
In: Annals of Oncology. - : Elsevier BV. - 1569-8041 .- 0923-7534. ; 29:8, s. 1836-1842
-
Journal article (peer-reviewed)abstract
- Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking.Google's Inception v4 CNN architecture was trained and validated using dermoscopic images and corresponding diagnoses. In a comparative cross-sectional reader study a 100-image test-set was used (level-I: dermoscopy only; level-II: dermoscopy plus clinical information and images). Main outcome measures were sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for diagnostic classification (dichotomous) of lesions by the CNN versus an international group of 58 dermatologists during level-I or -II of the reader study. Secondary end points included the dermatologists' diagnostic performance in their management decisions and differences in the diagnostic performance of dermatologists during level-I and -II of the reader study. Additionally, the CNN's performance was compared with the top-five algorithms of the 2016 International Symposium on Biomedical Imaging (ISBI) challenge.In level-I dermatologists achieved a mean (±standard deviation) sensitivity and specificity for lesion classification of 86.6% (±9.3%) and 71.3% (±11.2%), respectively. More clinical information (level-II) improved the sensitivity to 88.9% (±9.6%, P=0.19) and specificity to 75.7% (±11.7%, P<0.05). The CNN ROC curve revealed a higher specificity of 82.5% when compared with dermatologists in level-I (71.3%, P<0.01) and level-II (75.7%, P<0.01) at their sensitivities of 86.6% and 88.9%, respectively. The CNN ROC AUC was greater than the mean ROC area of dermatologists (0.86 versus 0.79, P<0.01). The CNN scored results close to the top three algorithms of the ISBI 2016 challenge.For the first time we compared a CNN's diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians' experience, they may benefit from assistance by a CNN's image classification.This study was registered at the German Clinical Trial Register (DRKS-Study-ID: DRKS00013570; https://www.drks.de/drks_web/).
|
|
