52 research outputs found
Molecular characterization of MRSA collected during national surveillance between 2008 and 2019 in the Netherlands
BACKGROUND: Although the Netherlands is a country with a low endemic level, methicillin-resistant Staphylococcus aureus (MRSA) poses a significant health care problem. Therefore, high coverage national MRSA surveillance has been in place since 1989. To monitor possible changes in the type-distribution and emergence of resistance and virulence, MRSA isolates are molecularly characterized.METHODS: All 43,321 isolates from 36,520 persons, collected 2008-2019, were typed by multiple-locus variable number tandem repeats analysis (MLVA) with simultaneous PCR detection of the mecA, mecC and lukF-PV genes, indicative for PVL. Next-generation sequencing data of 4991 isolates from 4798 persons were used for whole genome multi-locus sequence typing (wgMLST) and identification of resistance and virulence genes.RESULTS: We show temporal change in the molecular characteristics of the MRSA population with the proportion of PVL-positive isolates increasing from 15% in 2008-2010 to 25% in 2017-2019. In livestock-associated MRSA obtained from humans, PVL-positivity increases to 6% in 2017-2019 with isolates predominantly from regions with few pig farms. wgMLST reveals the presence of 35 genogroups with distinct resistance, virulence gene profiles and specimen origin. Typing shows prolonged persistent MRSA carriage with a mean carriage period of 407 days. There is a clear spatial and a weak temporal relationship between isolates that clustered in wgMLST, indicative for regional spread of MRSA strains.CONCLUSIONS: Using molecular characterization, this exceptionally large study shows genomic changes in the MRSA population at the national level. It reveals waxing and waning of types and genogroups and an increasing proportion of PVL-positive MRSA.</p
Dissemination of extensively drug-resistant NDM-producing Providencia stuartii in Europe linked to patients transferred from Ukraine, March 2022 to March 2023
BackgroundThe war in Ukraine led to migration of Ukrainian people. Early 2022, several European national surveillance systems detected multidrug-resistant (MDR) bacteria related to Ukrainian patients.AimTo investigate the genomic epidemiology of New Delhi metallo-β-lactamase (NDM)-producing Providencia stuartii from Ukrainian patients among European countries.MethodsWhole-genome sequencing of 66 isolates sampled in 2022-2023 in 10 European countries enabled whole-genome multilocus sequence typing (wgMLST), identification of resistance genes, replicons, and plasmid reconstructions. Five blaNDM-1-carrying-P. stuartii isolates underwent antimicrobial susceptibility testing (AST). Transferability to Escherichia coli of a blaNDM-1-carrying plasmid from a patient strain was assessed. Epidemiological characteristics of patients with NDM-producing P. stuartii were gathered by questionnaire.ResultswgMLST of the 66 isolates revealed two genetic clusters unrelated to Ukraine and three linked to Ukrainian patients. Of these three, two comprised blaNDM-1-carrying-P. stuartii and the third blaNDM-5-carrying-P. stuartii. The blaNDM-1 clusters (PstCluster-001, n = 22 isolates; PstCluster-002, n = 8 isolates) comprised strains from seven and four countries, respectively. The blaNDM-5 cluster (PstCluster-003) included 13 isolates from six countries. PstCluster-001 and PstCluster-002 isolates carried an MDR plasmid harbouring blaNDM-1,blaOXA-10, blaCMY-16, rmtC and armA, which was transferrable in vitro and, for some Ukrainian patients, shared by other Enterobacterales. AST revealed PstCluster-001 isolates to be extensively drug-resistant (XDR), but susceptible to cefiderocol and aztreonam-avibactam. Patients with data on age (n = 41) were 19-74 years old; of 49 with information on sex, 38 were male.ConclusionXDR P. stuartii were introduced into European countries, requiring increased awareness and precautions when treating patients from conflict-affected areas.</p
Dissemination of extensively drug-resistant NDM-producing Providencia stuartii in Europe linked to patients transferred from Ukraine, March 2022 to March 2023
BackgroundThe war in Ukraine led to migration of Ukrainian people. Early 2022, several European national surveillance systems detected multidrug-resistant (MDR) bacteria related to Ukrainian patients.AimTo investigate the genomic epidemiology of New Delhi metallo-β-lactamase (NDM)-producing Providencia stuartii from Ukrainian patients among European countries.MethodsWhole-genome sequencing of 66 isolates sampled in 2022-2023 in 10 European countries enabled whole-genome multilocus sequence typing (wgMLST), identification of resistance genes, replicons, and plasmid reconstructions. Five blaNDM-1-carrying-P. stuartii isolates underwent antimicrobial susceptibility testing (AST). Transferability to Escherichia coli of a blaNDM-1-carrying plasmid from a patient strain was assessed. Epidemiological characteristics of patients with NDM-producing P. stuartii were gathered by questionnaire.ResultswgMLST of the 66 isolates revealed two genetic clusters unrelated to Ukraine and three linked to Ukrainian patients. Of these three, two comprised blaNDM-1-carrying-P. stuartii and the third blaNDM-5-carrying-P. stuartii. The blaNDM-1 clusters (PstCluster-001, n = 22 isolates; PstCluster-002, n = 8 isolates) comprised strains from seven and four countries, respectively. The blaNDM-5 cluster (PstCluster-003) included 13 isolates from six countries. PstCluster-001 and PstCluster-002 isolates carried an MDR plasmid harbouring blaNDM-1,blaOXA-10, blaCMY-16, rmtC and armA, which was transferrable in vitro and, for some Ukrainian patients, shared by other Enterobacterales. AST revealed PstCluster-001 isolates to be extensively drug-resistant (XDR), but susceptible to cefiderocol and aztreonam-avibactam. Patients with data on age (n = 41) were 19-74 years old; of 49 with information on sex, 38 were male.ConclusionXDR P. stuartii were introduced into European countries, requiring increased awareness and precautions when treating patients from conflict-affected areas.</p
The Medical Segmentation Decathlon
International challenges have become the de facto standard for comparative
assessment of image analysis algorithms given a specific task. Segmentation is
so far the most widely investigated medical image processing task, but the
various segmentation challenges have typically been organized in isolation,
such that algorithm development was driven by the need to tackle a single
specific clinical problem. We hypothesized that a method capable of performing
well on multiple tasks will generalize well to a previously unseen task and
potentially outperform a custom-designed solution. To investigate the
hypothesis, we organized the Medical Segmentation Decathlon (MSD) - a
biomedical image analysis challenge, in which algorithms compete in a multitude
of both tasks and modalities. The underlying data set was designed to explore
the axis of difficulties typically encountered when dealing with medical
images, such as small data sets, unbalanced labels, multi-site data and small
objects. The MSD challenge confirmed that algorithms with a consistent good
performance on a set of tasks preserved their good average performance on a
different set of previously unseen tasks. Moreover, by monitoring the MSD
winner for two years, we found that this algorithm continued generalizing well
to a wide range of other clinical problems, further confirming our hypothesis.
Three main conclusions can be drawn from this study: (1) state-of-the-art image
segmentation algorithms are mature, accurate, and generalize well when
retrained on unseen tasks; (2) consistent algorithmic performance across
multiple tasks is a strong surrogate of algorithmic generalizability; (3) the
training of accurate AI segmentation models is now commoditized to non AI
experts
Common Limitations of Image Processing Metrics:A Picture Story
While the importance of automatic image analysis is continuously increasing,
recent meta-research revealed major flaws with respect to algorithm validation.
Performance metrics are particularly key for meaningful, objective, and
transparent performance assessment and validation of the used automatic
algorithms, but relatively little attention has been given to the practical
pitfalls when using specific metrics for a given image analysis task. These are
typically related to (1) the disregard of inherent metric properties, such as
the behaviour in the presence of class imbalance or small target structures,
(2) the disregard of inherent data set properties, such as the non-independence
of the test cases, and (3) the disregard of the actual biomedical domain
interest that the metrics should reflect. This living dynamically document has
the purpose to illustrate important limitations of performance metrics commonly
applied in the field of image analysis. In this context, it focuses on
biomedical image analysis problems that can be phrased as image-level
classification, semantic segmentation, instance segmentation, or object
detection task. The current version is based on a Delphi process on metrics
conducted by an international consortium of image analysis experts from more
than 60 institutions worldwide.Comment: This is a dynamic paper on limitations of commonly used metrics. The
current version discusses metrics for image-level classification, semantic
segmentation, object detection and instance segmentation. For missing use
cases, comments or questions, please contact [email protected] or
[email protected]. Substantial contributions to this document will be
acknowledged with a co-authorshi
Understanding metric-related pitfalls in image analysis validation
Validation metrics are key for the reliable tracking of scientific progress
and for bridging the current chasm between artificial intelligence (AI)
research and its translation into practice. However, increasing evidence shows
that particularly in image analysis, metrics are often chosen inadequately in
relation to the underlying research problem. This could be attributed to a lack
of accessibility of metric-related knowledge: While taking into account the
individual strengths, weaknesses, and limitations of validation metrics is a
critical prerequisite to making educated choices, the relevant knowledge is
currently scattered and poorly accessible to individual researchers. Based on a
multi-stage Delphi process conducted by a multidisciplinary expert consortium
as well as extensive community feedback, the present work provides the first
reliable and comprehensive common point of access to information on pitfalls
related to validation metrics in image analysis. Focusing on biomedical image
analysis but with the potential of transfer to other fields, the addressed
pitfalls generalize across application domains and are categorized according to
a newly created, domain-agnostic taxonomy. To facilitate comprehension,
illustrations and specific examples accompany each pitfall. As a structured
body of information accessible to researchers of all levels of expertise, this
work enhances global comprehension of a key topic in image analysis validation.Comment: Shared first authors: Annika Reinke, Minu D. Tizabi; shared senior
authors: Paul F. J\"ager, Lena Maier-Hei
Canagliflozin and renal outcomes in type 2 diabetes and nephropathy
BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years
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