Publications by authors named "A Isabel Koch"
The recent expansion of mpox in Africa is characterized by a dramatic increase in zoonotic transmission (clade Ia) and the emergence of a new clade Ib that is transmitted from human-to-human (H2H) by close contact. Clade Ia does not pose a threat in areas without zoonotic reservoir. But clade Ib may spread widely, as did the clade IIb that since 2022 has spread globally among MSM.
View Article and Find Full Text PDFPurpose: In order to obtain sustainable healthcare, engagement of patients in patient safety improvement is vital. Drawing upon a multi-perspective approach, this study aimed to investigate perspectives of patients and healthcare professionals on key implementation factors (ie, barriers and facilitators) for effective patient engagement (PE) in healthcare organizations to improve patient safety.
Patients And Methods: A two-round Delphi technique comprising semi-structured interviews and an online survey was applied to consolidate the individual perspectives of stakeholders and establish consensus on factors (expected, potential or experienced) that facilitate or mitigate successful implementation of PE in healthcare organizations (ie, all types, including hospital and outpatient medical practices).
Background: Intracerebral schwannomas are rare tumors resembling their peripheral nerve sheath counterparts but localized in the CNS. They are not classified as a separate tumor type in the 2021 WHO classification. This study aimed to compile and characterize these rare neoplasms morphologically and molecularly.
View Article and Find Full Text PDFBackground: Radiotherapy is essential for treating head and neck cancer but often leads to severe toxicity. Traditional predictors include anatomical location, tumor extent, and dosimetric data. Recently, biomarkers have been explored to better predict and understand toxicity.
View Article and Find Full Text PDFArticle Synopsis
- ACLF is a complex condition characterized by acute worsening of liver disease and organ failure, prompting this study to create a machine learning model to predict patient mortality in the ICU.
- The research analyzed data from 206 ICU patients at RWTH Aachen University Hospital and developed a predictive model using logistic regression, achieving an impressive accuracy with an AUROC of 0.96.
- The resulting Aachen ACLF ICU (ACICU) score outperforms existing mortality predictors and provides a user-friendly tool for assessing the likelihood of mortality in critically ill patients with ACLF.