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184 results on '"Kludt, E"'

9. Impact of the corona pandemic on cancer patients: results from a German cross-sectional pilot study

Author

Gaisser, A, Eckford, R, Kludt, E, Baumann, M, Weg-Remers, S, and Schlander, M

Subjects
ddc: 610, Medicine and health
Abstract

Background: In March 2020 the spread of a novel corona virus, Sars-Cov2, was declared a global pandemic. Consequently, policy makers have prioritized health care services to treat serious cases and limit the infection rate. This has led to shortages and affected the care for other vulnerable patients, [for full text, please go to the a.m. URL]

Published
2021
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11. Predictive models for cochlear implant outcomes: Performance, generalizability, and the impact of cohort size

Author

Shafieibavani, E, Goudey, B, Kiral, I, Zhong, P, Jimeno-Yepes, A, Swan, A, Gambhir, M, Buechner, A, Kludt, E, Eikelboom, RH, Sucher, C, Gifford, RH, Rottier, R, Plant, K, Anjomshoa, H, Shafieibavani, E, Goudey, B, Kiral, I, Zhong, P, Jimeno-Yepes, A, Swan, A, Gambhir, M, Buechner, A, Kludt, E, Eikelboom, RH, Sucher, C, Gifford, RH, Rottier, R, Plant, K, and Anjomshoa, H

Abstract

While cochlear implants have helped hundreds of thousands of individuals, it remains difficult to predict the extent to which an individual's hearing will benefit from implantation. Several publications indicate that machine learning may improve predictive accuracy of cochlear implant outcomes compared to classical statistical methods. However, existing studies are limited in terms of model validation and evaluating factors like sample size on predictive performance. We conduct a thorough examination of machine learning approaches to predict word recognition scores (WRS) measured approximately 12 months after implantation in adults with post-lingual hearing loss. This is the largest retrospective study of cochlear implant outcomes to date, evaluating 2,489 cochlear implant recipients from three clinics. We demonstrate that while machine learning models significantly outperform linear models in prediction of WRS, their overall accuracy remains limited (mean absolute error: 17.9-21.8). The models are robust across clinical cohorts, with predictive error increasing by at most 16% when evaluated on a clinic excluded from the training set. We show that predictive improvement is unlikely to be improved by increasing sample size alone, with doubling of sample size estimated to only increasing performance by 3% on the combined dataset. Finally, we demonstrate how the current models could support clinical decision making, highlighting that subsets of individuals can be identified that have a 94% chance of improving WRS by at least 10% points after implantation, which is likely to be clinically meaningful. We discuss several implications of this analysis, focusing on the need to improve and standardize data collection.

Published
2021

12. A MultiCenter Analysis of Factors Associated with Hearing Outcome for 2,735 Adults with Cochlear Implants

Author

Goudey, B, Plant, K, Kiral, I, Jimeno-Yepes, A, Swan, A, Gambhir, M, Buechner, A, Kludt, E, Eikelboom, RH, Sucher, C, Gifford, RH, Rottier, R, Anjomshoa, H, Goudey, B, Plant, K, Kiral, I, Jimeno-Yepes, A, Swan, A, Gambhir, M, Buechner, A, Kludt, E, Eikelboom, RH, Sucher, C, Gifford, RH, Rottier, R, and Anjomshoa, H

Abstract

While the majority of cochlear implant recipients benefit from the device, it remains difficult to estimate the degree of benefit for a specific patient prior to implantation. Using data from 2,735 cochlear-implant recipients from across three clinics, the largest retrospective study of cochlear-implant outcomes to date, we investigate the association between 21 preoperative factors and speech recognition approximately one year after implantation and explore the consistency of their effects across the three constituent datasets. We provide evidence of 17 statistically significant associations, in either univariate or multivariate analysis, including confirmation of associations for several predictive factors, which have only been examined in prior smaller studies. Despite the large sample size, a multivariate analysis shows that the variance explained by our models remains modest across the datasets (R2=0.12-0.21). Finally, we report a novel statistical interaction indicating that the duration of deafness in the implanted ear has a stronger impact on hearing outcome when considered relative to a candidate's age. Our multicenter study highlights several real-world complexities that impact the clinical translation of predictive factors for cochlear implantation outcome. We suggest several directions to overcome these challenges and further improve our ability to model patient outcomes with increased accuracy.

Published
2021

22. Untersuchung zur Durchführbarkeit von App-basierter Nachsorge bei Cochlea-Implantat-Patienten

Author

Kludt, E, Gärtner, L, Lenarz, T, and Büchner, A

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Einleitung: Cochlea-Implantat (CI)-Patienten sind auf eine lebenslange Nachsorge für ihr Implantat angewiesen. Nach der Aktivierung des CI erfolgt die Nachsorge der erwachsenen Patienten engmaschig im Abstand von 3 bis 6 Monaten und geht dann in eine ein- bis zweijährige Nachsorge über.[zum vollständigen Text gelangen Sie über die oben angegebene URL], 23. Jahrestagung der Deutschen Gesellschaft für Audiologie

Published
2020
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23. Untersuchung zum subjektiven Lautstärkeeindruck bei Messung von ECAP-Schwellen mittels AutoNRT

Author

Kludt, E, Gärtner, L, Lenarz, T, and Büchner, A

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Einleitung: Die Ermittlung von elektrisch evozierten Summenaktionspotentiale (ECAP) - Schwellen hat sich als eine wichtige objektive Methode in der intra- und postoperativen Diagnostik von Cochlea Implantat (CI) Patienten etabliert. Es werden Versuche unternommen mit den mittels AutoNRT Algorithmus [zum vollständigen Text gelangen Sie über die oben angegebene URL], 23. Jahrestagung der Deutschen Gesellschaft für Audiologie

Published
2020
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24. Treatment alternatives for mixed hearing loss

Author

Rocha Felix, T, Busch, S, Kludt, E, Waldmann, B, Lenarz, T, and Maier, H

Subjects
ddc: 610, otorhinolaryngologic diseases, 610 Medical sciences, Medicine
Abstract

Introduction. Several treatment alternatives are currently available for patients suffering from mixed hearing loss. These include power hearing aids (PHAs), bone conduction implants (BCIs) and active middle-ear implants (AMEIs). Otologists have the difficult task of selecting one of multiple devices[for full text, please go to the a.m. URL], 23. Jahrestagung der Deutschen Gesellschaft für Audiologie

Published
2020
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36. Molekulare Tests als Voraussetzung für personalisierte Krebsmedizin – Anliegen und Interessen von ratsuchenden Patienten und Angehörigen

Author

Krieghoff-Henning, E, Kludt, E, and Weg-Remers, S

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Hintergrund/Fragestellung: Immer häufiger wird die Krebstherapie auf Basis von komplexen molekularen Tests individuell angepasst. Dies erschwert es Betroffenen, sich informiert an medizinischen Entscheidungen zu beteiligen. Das benötigte Wissen sollten die behandelnden Ärzte vermitteln.[zum vollständigen Text gelangen Sie über die oben angegebene URL], EbM und Digitale Transformation in der Medizin; 20. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin

Published
2019
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