Groll, Andreas H.

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[["dc.bibliographiccitation.firstpage","E785"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Mycoses"],["dc.bibliographiccitation.lastpage","E788"],["dc.bibliographiccitation.volume","54"],["dc.contributor.author","Daebritz, Jan"],["dc.contributor.author","Attarbaschi, Andishe"],["dc.contributor.author","Tintelnot, Kathrin"],["dc.contributor.author","Kollmar, Nina"],["dc.contributor.author","Kremens, Bernhard"],["dc.contributor.author","Loewenich, Friederike D. v."],["dc.contributor.author","Schrod, Lothar"],["dc.contributor.author","Schuster, Friedhelm"],["dc.contributor.author","Wintergerst, Uwe"],["dc.contributor.author","Weig, Michael S."],["dc.contributor.author","Lehrnbecher, Thomas"],["dc.contributor.author","Groll, Andreas H."],["dc.date.accessioned","2018-11-07T08:50:25Z"],["dc.date.available","2018-11-07T08:50:25Z"],["dc.date.issued","2011"],["dc.description.abstract","Mucormycosis is associated with high morbidity and mortality and is perceived as an emerging fungal infection. However, contemporary paediatric data are limited. We present a series of paediatric cases of mucormycosis reported from Germany and Austria collected within a voluntary epidemiological survey through standardised, anonymized case report forms. Twelve cases were reported between January 2004 and December 2008 (six men; mean age: 12.6 years, range: 0.1-17 years). Mucormycosis was proven in nine, and probable in three cases. Isolates included Lichtheimia (syn. Absidia pro parte, Mycocladus) (five), Rhizopus (three) and Mucor (one) species. Infection was limited to soft tissue in three cases, the lung in two cases, and an infected thrombus in one case; rhinocerebral disease was found in three cases, and pulmonary-mediastinal, pulmonary-cerebral and soft tissue-cerebral involvement in one case each. All three patients with isolated soft tissue infection were cured, whereas seven of the remaining patients died (one patient without follow-up). The overall mortality rate was 67%. While these data cannot provide conclusive data on incidence and disease burden of mucormycosis in paediatric patients, they reflect the continuing threat of these infections to immunocompromised patients and the need for improved diagnosis and management."],["dc.description.sponsorship","Gilead Sciences; Merck Co.; Gilead"],["dc.identifier.doi","10.1111/j.1439-0507.2011.02025.x"],["dc.identifier.isi","000296243700016"],["dc.identifier.pmid","21623951"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/21691"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","0933-7407"],["dc.title","Mucormycosis in paediatric patients: demographics, risk factors and outcome of 12 contemporary cases"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

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[["dc.bibliographiccitation.firstpage","373"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","European Journal of Clinical Pharmacology"],["dc.bibliographiccitation.lastpage","380"],["dc.bibliographiccitation.volume","73"],["dc.contributor.author","Meid, Andreas D."],["dc.contributor.author","Groll, Andreas H."],["dc.contributor.author","Schieborr, Ulrich"],["dc.contributor.author","Walker, Jochen"],["dc.contributor.author","Haefeli, Walter E."],["dc.date.accessioned","2018-11-07T10:27:05Z"],["dc.date.available","2018-11-07T10:27:05Z"],["dc.date.issued","2017"],["dc.description.abstract","Risk prediction models can be powerful tools to support clinical decision-making, to help targeting interventions, and, thus, to improve clinical and economic outcomes, provided that model performance is good and sensitivity and specificity are well balanced. Drug utilization as a potential risk factor for unplanned hospitalizations has recently emerged as a meaningful predictor variable in such models. Drug treatment is a rather unstable (i.e. time-dependent) phenomenon and most drug-induced events are concentration-dependent and therefore individual drug exposure will likely modulate the risk. This especially applies to longitudinal monitoring of appropriate drug treatment within claims data as another promising application for prediction models. To guide future research towards this direction, we firstly reviewed current risk prediction models for unplanned hospitalizations that explicitly included information on drug utilization and were surprised to find that these models rarely attempted to consider dose and frequent modulators of drug clearance such as interactions with co-medication or co-morbidities. As another example, they often presumed class effects where in fact, differences between active moieties were well established. In addition, the study designs and statistical risk analysis disregarded the fact that medication and risk modulators and, thus, adverse events can vary over time. In a simulation study, we therefore evaluated the potential benefit of time-dependent Cox models over standard binary regression approaches with a fixed follow-up period. Longitudinal drug information could be utilized much more efficiently both by precisely estimating individual drug exposure and by applying more refined statistical methodology to account for time-dependent drug utilization patterns."],["dc.identifier.doi","10.1007/s00228-016-2184-0"],["dc.identifier.isi","000394324100014"],["dc.identifier.pmid","28013365"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/43178"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Springer"],["dc.publisher.place","Heidelberg"],["dc.relation.issn","1432-1041"],["dc.relation.issn","0031-6970"],["dc.title","How can we define and analyse drug exposure more precisely to improve the prediction of hospitalizations in longitudinal (claims) data?"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

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[["dc.contributor.author","van der Wurp, Hendrik"],["dc.contributor.author","Groll, Andreas H."],["dc.contributor.author","Kneib, Thomas"],["dc.contributor.author","Marra, Giampiero"],["dc.date.accessioned","2020-04-03T10:38:13Z"],["dc.date.available","2020-04-03T10:38:13Z"],["dc.date.issued","2019-08"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63578"],["dc.title","Generalised Joint Regression for Count Data with a Focus on Modelling Football Matches"],["dc.type","preprint"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

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