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1,083 results on '"P, Gastmeier"'

1. Gram-negative bloodstream infections in six German university hospitals, 2016–2020: clinical and microbiological features

Author

Mischnik, Alexander, Baltus, Hannah, Walker, Sarah V., Behnke, Michael, Gladstone, Beryl Primrose, Chakraborty, Trinad, Falgenhauer, Linda, Gastmeier, Petra, Gölz, Hanna, Göpel, Siri, Häcker, Georg A., Higgins, Paul G., Imirzalioglu, Can, Käding, Nadja, Kramme, Evelyn, Peter, Silke, Rieg, Siegbert, Rohde, Anna M., Seifert, Harald, Tacconelli, Evelina, Tobys, David, Trauth, Janina, Vehreschild, Maria J. G. T., Xanthopoulou, Kyriaki, Rupp, Jan, and Kern, Winfried V.

Published
2024
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2. Epidemiological trends and susceptibility patterns of bloodstream infections caused by Enterococcus spp. in six German university hospitals: a prospectively evaluated multicentre cohort study from 2016 to 2020 of the R-Net study group

Author

Hornuss, Daniel, Göpel, Siri, Walker, Sarah V., Tobys, David, Häcker, Georg, Seifert, Harald, Higgins, Paul G., Xanthopoulou, Kyriaki, Gladstone, Beryl Primrose, Cattaneo, Chiara, Mischnik, Alexander, Rohde, Anna M., Imirzalioglu, Can, Trauth, Janina, Fritzenwanker, Moritz, Falgenhauer, Jane, Gastmeier, Petra, Behnke, Michael, Kramme, Evelyn, Käding, Nadja, Rupp, Jan, Peter, Silke, Schmauder, Kristina, Eisenbeis, Simone, Kern, Winfried V., Tacconelli, Evelina, and Rieg, Siegbert

Published
2024
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10. Critical Assessment of Metagenome Interpretation: the second round of challenges

Author

Meyer, Fernando, Fritz, Adrian, Deng, Zhi-Luo, Koslicki, David, Lesker, Till Robin, Gurevich, Alexey, Robertson, Gary, Alser, Mohammed, Antipov, Dmitry, Beghini, Francesco, Bertrand, Denis, Brito, Jaqueline J, Brown, C Titus, Buchmann, Jan, Buluç, Aydin, Chen, Bo, Chikhi, Rayan, Clausen, Philip TLC, Cristian, Alexandru, Dabrowski, Piotr Wojciech, Darling, Aaron E, Egan, Rob, Eskin, Eleazar, Georganas, Evangelos, Goltsman, Eugene, Gray, Melissa A, Hansen, Lars Hestbjerg, Hofmeyr, Steven, Huang, Pingqin, Irber, Luiz, Jia, Huijue, Jørgensen, Tue Sparholt, Kieser, Silas D, Klemetsen, Terje, Kola, Axel, Kolmogorov, Mikhail, Korobeynikov, Anton, Kwan, Jason, LaPierre, Nathan, Lemaitre, Claire, Li, Chenhao, Limasset, Antoine, Malcher-Miranda, Fabio, Mangul, Serghei, Marcelino, Vanessa R, Marchet, Camille, Marijon, Pierre, Meleshko, Dmitry, Mende, Daniel R, Milanese, Alessio, Nagarajan, Niranjan, Nissen, Jakob, Nurk, Sergey, Oliker, Leonid, Paoli, Lucas, Peterlongo, Pierre, Piro, Vitor C, Porter, Jacob S, Rasmussen, Simon, Rees, Evan R, Reinert, Knut, Renard, Bernhard, Robertsen, Espen Mikal, Rosen, Gail L, Ruscheweyh, Hans-Joachim, Sarwal, Varuni, Segata, Nicola, Seiler, Enrico, Shi, Lizhen, Sun, Fengzhu, Sunagawa, Shinichi, Sørensen, Søren Johannes, Thomas, Ashleigh, Tong, Chengxuan, Trajkovski, Mirko, Tremblay, Julien, Uritskiy, Gherman, Vicedomini, Riccardo, Wang, Zhengyang, Wang, Ziye, Wang, Zhong, Warren, Andrew, Willassen, Nils Peder, Yelick, Katherine, You, Ronghui, Zeller, Georg, Zhao, Zhengqiao, Zhu, Shanfeng, Zhu, Jie, Garrido-Oter, Ruben, Gastmeier, Petra, Hacquard, Stephane, Häußler, Susanne, Khaledi, Ariane, Maechler, Friederike, Mesny, Fantin, Radutoiu, Simona, Schulze-Lefert, Paul, Smit, Nathiana, and Strowig, Till

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Networking and Information Technology R&D (NITRD), Archaea, Metagenome, Metagenomics, Reproducibility of Results, Sequence Analysis, DNA, Software, Technology, Medical and Health Sciences, Developmental Biology, Biological sciences
Abstract

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

Published
2022

15. Resolving colistin resistance and heteroresistance in Enterobacter species

Author

Doijad, Swapnil Prakash, Gisch, Nicolas, Frantz, Renate, Kumbhar, Bajarang Vasant, Falgenhauer, Jane, Imirzalioglu, Can, Falgenhauer, Linda, Mischnik, Alexander, Rupp, Jan, Behnke, Michael, Buhl, Michael, Eisenbeis, Simone, Gastmeier, Petra, Gölz, Hanna, Häcker, Georg Alexander, Käding, Nadja, Kern, Winfried V., Kola, Axel, Kramme, Evelyn, Peter, Silke, Rohde, Anna M., Seifert, Harald, Tacconelli, Evelina, Vehreschild, Maria J. G. T., Walker, Sarah V., Zweigner, Janine, Schwudke, Dominik, and Chakraborty, Trinad

Published
2023
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19. Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning‐enabled molecular diagnostics

Author

Khaledi, Ariane, Weimann, Aaron, Schniederjans, Monika, Asgari, Ehsaneddin, Kuo, Tzu‐Hao, Oliver, Antonio, Cabot, Gabriel, Kola, Axel, Gastmeier, Petra, Hogardt, Michael, Jonas, Daniel, Mofrad, Mohammad RK, Bremges, Andreas, McHardy, Alice C, and Häussler, Susanne

Subjects
Microbiology, Biological Sciences, Genetics, Vaccine Related, Infectious Diseases, Antimicrobial Resistance, Emerging Infectious Diseases, Prevention, Biotechnology, Human Genome, Clinical Research, Biodefense, Detection, screening and diagnosis, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, 4.1 Discovery and preclinical testing of markers and technologies, Infection, Good Health and Well Being, Anti-Bacterial Agents, Drug Resistance, Bacterial, Genome, Bacterial, Machine Learning, Microbial Sensitivity Tests, Pathology, Molecular, Pseudomonas aeruginosa, Transcriptome, antibiotic resistance, biomarkers, clinical isolates, machine learning, molecular diagnostics, Medical and Health Sciences, Biochemistry and cell biology
Abstract

Limited therapy options due to antibiotic resistance underscore the need for optimization of current diagnostics. In some bacterial species, antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug-resistant clinical Pseudomonas aeruginosa isolates. By training machine learning classifiers on information about the presence or absence of genes, their sequence variation, and expression profiles, we generated predictive models and identified biomarkers of resistance to four commonly administered antimicrobial drugs. Using these data types alone or in combination resulted in high (0.8-0.9) or very high (> 0.9) sensitivity and predictive values. For all drugs except for ciprofloxacin, gene expression information improved diagnostic performance. Our results pave the way for the development of a molecular resistance profiling tool that reliably predicts antimicrobial susceptibility based on genomic and transcriptomic markers. The implementation of a molecular susceptibility test system in routine microbiology diagnostics holds promise to provide earlier and more detailed information on antibiotic resistance profiles of bacterial pathogens and thus could change how physicians treat bacterial infections.

Published
2020

25. Risk factors for nosocomial SARS-CoV-2 infections in patients: results from a retrospective matched case–control study in a tertiary care university center

Author

Aghdassi, Seven Johannes Sam, Schwab, Frank, Peña Diaz, Luis Alberto, Brodzinski, Annika, Fucini, Giovanni-Battista, Hansen, Sonja, Kohlmorgen, Britta, Piening, Brar, Schlosser, Beate, Schneider, Sandra, Weikert, Beate, Wiese-Posselt, Miriam, Wolff, Sebastian, Behnke, Michael, Gastmeier, Petra, and Geffers, Christine

Published
2022
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26. Key summary of German national treatment guidance for hospitalized COVID-19 patients: Key pharmacologic recommendations from a national German living guideline using an Evidence to Decision Framework (last updated 17.05.2021)

Author

Malin, Jakob J., Spinner, Christoph D., Janssens, Uwe, Welte, Tobias, Weber-Carstens, Steffen, Schälte, Gereon, Gastmeier, Petra, Langer, Florian, Wepler, Martin, Westhoff, Michael, Pfeifer, Michael, Rabe, Klaus F., Hoffmann, Florian, Böttiger, Bernd W., Weinmann-Menke, Julia, Kersten, Alexander, Berlit, Peter, Krawczyk, Marcin, Nehls, Wiebke, Fichtner, Falk, Laudi, Sven, Stegemann, Miriam, Skoetz, Nicole, Nothacker, Monika, Marx, Gernot, Karagiannidis, Christian, and Kluge, Stefan

Published
2022
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28. Occurrence and trends of Clostridioides difficile infections in hospitalized patients: a prospective multi-centre cohort study in six German university hospitals, 2016–2020.

Author

Jazmati, N., Mischnik, A., Kern, W.V., Behnke, M., Chakraborty, T., Dinkelacker, A., Eisenbeis, S., Falgenhauer, J., Gastmeier, P., Häcker, G., Imirzalioglu, C., Käding, N., Kramme, E., Peter, S., Piepenbrock, E., Rupp, J., Schneider, C., Schwab, F., Seifert, H., and Tacconelli, E.

Abstract

For Clostridioides difficile infections (CDIs) in Germany no longitudinal multi-centre studies with standardized protocols for diagnosing CDI are available. Recent evaluations of general surveillance databases in Germany indicate a downward trend in CDI rates. We aimed to describe the actual burden and trends of CDI in German university hospitals from 2016 to 2020. Our study was a prospective multi-centre study covering six German university hospitals. We report the data in total, stratified by year, by medical specialty as well as by CDI severity. Multi-variable regression analyses were performed to assess risk factors for severe CDI. We registered 3780 CDI cases among 1,436,352 patients. The median length of stay (LOS) of CDI cases was 20 days (interquartile range 11–37) compared with a general LOS of 4.2 days. In-hospital all-cause mortality in CDI patients was 11.7% (N = 444/3780), while mortality attributed to CDI was 0.4% (N = 16/3761). CDI recurrence rate was comparatively low at 7.2%. The incidence density of severe healthcare-associated healthcare onset (HAHO)-CDI showed a significant decrease from 2.25/10,000 patient days (pd) in 2016 to 1.49/10,000 pd in 2020 (trend calculation P =0.032). Compared with a European point-prevalence study in 2013/2014, where overall CDI incidence density was 11.2 cases/10,000 pd in Germany (EUCLID), we see in our study halved overall CDI rates of 5.6 cases/10,000 pd in 2020. Our study shows current data on the distribution of CDI cases in German university hospitals and thus provides international comparative data on the key indicators of CDI. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Correction to: Key summary of German national treatment guidance for hospitalized COVID‑19 patients: Key pharmacologic recommendations from a national German living guideline using an Evidence to Decision Framework (last updated 17.05.2021)

Author

Malin, Jakob J., Spinner, Christoph D., Janssens, Uwe, Welte, Tobias, Weber-Carstens, Steffen, Schälte, Gereon, Gastmeier, Petra, Langer, Florian, Wepler, Martin, Westhoff, Michael, Pfeifer, Michael, Rabe, Klaus F., Hoffmann, Florian, Böttiger, Bernd W., Weinmann-Menke, Julia, Kersten, Alexander, Berlit, Peter, Krawczyk, Marcin, Nehls, Wiebke, Fichtner, Falk, Laudi, Sven, Stegemann, Miriam, Skoetz, Nicole, Nothacker, Monika, Marx, Gernot, Karagiannidis, Christian, and Kluge, Stefan

Published
2022
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43. Healthcare-Associated Infections and the Use of Antibiotics in German Hospitals: Results of the Point Prevalence Survey of 2022 and Comparison With Earlier Findings.

Author

Aghdassi, Seven Johannes Sam, Hansen, Sonja, Peña Diaz, Luis Alberto, Gropmann, Alexander, Saydan, Selin, Geffers, Christine, Gastmeier, Petra, Piening, Brar, and Behnke, Michael

Abstract

Background: A national point prevalence survey (PPS) of healthcare-associated infections (HAI) and antibiotic use (AU) was carried out in Germany in 2022 in the framework of the European PPS conducted by the European Centre for Disease Prevention and Control (ECDC). The objective was to determine the prevalence of HAI and AU in German hospitals and to compare the obtained values with those of the most recent previous PPS, which was carried out in 2016. Methods: The German National Reference Center for the Surveillance of Nosocomial Infections was entrusted with the organization of the PPS of 2022. As recommended by the ECDC, each hospital in a representative sample of 50 hospitals was invited to participate, and all other interested hospitals in Germany were also able to participate if desired. The data were collected by specially trained hospital staff in May, June, and July 2022. The definitions and methods put forth by the ECDC were used. Results: Data from 66 586 patients in 252 hospitals were included. The prevalence of HAI in all participating hospitals was 4.9%, and that of AU was 26.9%. The HAI and AU prevalences were essentially unchanged in comparison to 2016. The most common types of HAI were surgical site infection (23.5%), lower respiratory tract infection (21.6%), and urinary tract infection (19.0%). Conclusion: HAI were just as frequent in 2022 as in 2016, affecting approximately one in twenty hospitalized patients on any given day. Cite this as: Aghdassi SJS, Hansen S, Peña Diaz LA, Gropmann A, Saydan S, Geffers C, Gastmeier P, Piening B, Behnke M: Healthcare-associated infections and the use of antibiotics in German hospitals--results of the point prevalence survey of 2022 and comparison with earlier findings. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Patient engagement with surgical site infection prevention: an expert panel perspective

Author

E. Tartari, V. Weterings, P. Gastmeier, J. Rodríguez Baño, A. Widmer, J. Kluytmans, and A. Voss

Subjects
Surgical site infection, Surgical wound infection, Patient participation, Empowered patient, Patient involvement, Patient education, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Despite remarkable developments in the use of surgical techniques, ergonomic advancements in the operating room, and implementation of bundles, surgical site infections (SSIs) remain a substantial burden, associated with increased morbidity, mortality and healthcare costs. National and international recommendations to prevent SSIs have been published, including recent guidelines by the World Health Organization, but implementation into clinical practice remains an unresolved issue. SSI improvement programs require an integrative approach with measures taken during the pre-, intra- and postoperative care from the numerous stakeholders involved. The current SSI prevention strategies have focused mainly on the role of healthcare workers (HCWs) and procedure related risk factors. The importance and influence of patient participation is becoming an increasingly important concept and advocated as a means to improve patient safety. Novel interventions supporting an active participative role within SSI prevention programs have not been assessed. Empowering patients with information they require to engage in the process of SSI prevention could play a major role for the implementation of recommendations. Based on available scientific evidence, a panel of experts evaluated options for patient involvement in order to provide pragmatic recommendations for pre-, intra- and postoperative activities for the prevention of SSIs. Recommendations were based on existing guidelines and expert opinion. As a result, 9 recommendations for the surgical patient are presented here, including a practice brief in the form of a patient information leaflet. HCWs can use this information to educate patients and allow patient engagement.

Published
2017
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