Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Antwerp University Hospital

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (7/7 displayed)

  • 2022Study of nanosecond of annealing on silicon doped hafnium oxide film crystallization and capacitor reliability10citations
  • 2021Impact of the Nonlinear Dielectric Hysteresis Properties of a Charge Trap Layer in a Novel Hybrid High-Speed and Low-Power Ferroelectric or Antiferroelectric HSO/HZO Boosted Charge Trap Memory7citations
  • 2020Relationship between mortality after ICD implantation and center volume in Belgiumcitations
  • 2020Squeeze-winding: A new manufacturing route for biomimetic fiber-reinforced structures11citations
  • 2020A Study on the Temperature-Dependent Operation of Fluorite-Structure-Based Ferroelectric HfO2 Memory FeFET: Pyroelectricity and Reliability20citations
  • 2016Vibronic coupling in molecules and in solids.19citations
  • 2015Erbium-doped slot waveguides containing size-controlled silicon nanocrystals3citations

Places of action

Chart of shared publication
Royet, A-S.
1 / 2 shared
Kampfe, T.
2 / 2 shared
Czernohorsky, M.
3 / 3 shared
Sunbul, A.
1 / 1 shared
Lederer, M.
2 / 10 shared
Rudolph, M.
3 / 17 shared
Kerdiles, S.
1 / 5 shared
Prabhu, A.
1 / 1 shared
Lehninger, D.
3 / 12 shared
Grenouillet, L.
1 / 3 shared
Sourav, D.
1 / 1 shared
Olivo, R.
3 / 10 shared
Seidel, K.
3 / 14 shared
Kuhnel, K.
2 / 2 shared
Ali, T.
3 / 10 shared
Charpin-Nicolle, C.
1 / 1 shared
Muller, F.
1 / 3 shared
Eng, L. M.
2 / 5 shared
Mertens, K.
1 / 6 shared
Schramm, P.
1 / 1 shared
Metzger, J.
2 / 5 shared
Houdt, J. Van
1 / 1 shared
Oehler, S.
1 / 2 shared
Binder, R.
2 / 2 shared
Biedermann, K.
1 / 1 shared
Muller, J.
1 / 6 shared
Mairesse, G.
1 / 1 shared
Blankoff, I.
1 / 1 shared
Vandekerckhove, Y.
1 / 1 shared
Vijgen, J.
1 / 1 shared
Willems, R.
1 / 1 shared
Waroux, J. B. Le Polain De
1 / 1 shared
Ingelaere, S.
1 / 1 shared
E., Vellwock A.
1 / 4 shared
Libonati, F.
1 / 12 shared
Ziegmann, G.
1 / 8 shared
Colombo, C.
1 / 18 shared
El Louizi, F.
1 / 1 shared
Vergani, L.
1 / 11 shared
Mart, C.
1 / 2 shared
Kämpfe, T.
1 / 10 shared
Müller, J.
1 / 24 shared
Müller, F.
1 / 11 shared
Pätzold, B.
1 / 1 shared
Steinke, P.
1 / 1 shared
Kühnel, K.
1 / 3 shared
Edwards, P.
1 / 50 shared
Grochala, W.
1 / 5 shared
Beyer, J.
1 / 3 shared
Heitmann, J.
1 / 14 shared
Johnson, B. C.
1 / 5 shared
Mccallum, J. C.
1 / 4 shared
Klemm, V.
1 / 68 shared
Rafaja, David
1 / 293 shared
Chart of publication period
2022
2021
2020
2016
2015

Co-Authors (by relevance)

  • Royet, A-S.
  • Kampfe, T.
  • Czernohorsky, M.
  • Sunbul, A.
  • Lederer, M.
  • Rudolph, M.
  • Kerdiles, S.
  • Prabhu, A.
  • Lehninger, D.
  • Grenouillet, L.
  • Sourav, D.
  • Olivo, R.
  • Seidel, K.
  • Kuhnel, K.
  • Ali, T.
  • Charpin-Nicolle, C.
  • Muller, F.
  • Eng, L. M.
  • Mertens, K.
  • Schramm, P.
  • Metzger, J.
  • Houdt, J. Van
  • Oehler, S.
  • Binder, R.
  • Biedermann, K.
  • Muller, J.
  • Mairesse, G.
  • Blankoff, I.
  • Vandekerckhove, Y.
  • Vijgen, J.
  • Willems, R.
  • Waroux, J. B. Le Polain De
  • Ingelaere, S.
  • E., Vellwock A.
  • Libonati, F.
  • Ziegmann, G.
  • Colombo, C.
  • El Louizi, F.
  • Vergani, L.
  • Mart, C.
  • Kämpfe, T.
  • Müller, J.
  • Müller, F.
  • Pätzold, B.
  • Steinke, P.
  • Kühnel, K.
  • Edwards, P.
  • Grochala, W.
  • Beyer, J.
  • Heitmann, J.
  • Johnson, B. C.
  • Mccallum, J. C.
  • Klemm, V.
  • Rafaja, David
OrganizationsLocationPeople

article

Relationship between mortality after ICD implantation and center volume in Belgium

  • Mairesse, G.
  • Blankoff, I.
  • Vandekerckhove, Y.
  • Vijgen, J.
  • Willems, R.
  • Waroux, J. B. Le Polain De
  • Ingelaere, S.
  • Hoffmann, R.
Abstract

<jats:title>Abstract</jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>In Belgium ICD implantation is restricted to 23 centers. A previous analysis of our group based on aggregated results per center showed that 3y mortality varied significantly between centers ranging from 7.5 to 23.4%. Multivariate analysis demonstrated that volume, infection rate and a higher proportion of implantations in primary prevention were predictors of 3y-mortality. These findings needed to be confirmed on a patient level since they could be caused by inter-patient rather than inter-hospital differences.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The QERMID-ICD database is a retrospective database of all patients implanted with an ICD in Belgium managed by the governmental health care institution (RIZIV/INAMI). Participation is mandatory for reimbursement. We analyzed data of 9896 new implantations performed between 2010 and 2016. Following patient characteristics were available: demographics (gender, NYHA class, primary vs secondary prevention, underlying heart disease, type of device, QRS duration, age and ejection fraction (EF)), comorbidities (atrial fibrillation, diabetes, COPD, neurological disease, oncological disease and renal failure), volume of center (low &amp;lt; median of 65 primo-implantations/year vs high &amp;gt;65 implantations/year) and the average income of the arrondissement in which the patient lived (low income &amp;lt; p25, median p25-p75, high &amp;gt; p75). The primary endpoint was 3y-mortality. Chi-squared test and Mann-Whitney U test with correction for multiple testing were used and multivariate logistic regression was performed to determine the corrected odds ratio for 3-year mortality. Finally, Kaplan-Meier survival analysis was performed.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Low volume centers treated different patients than high volume centers. They implant more primary prevention (66.5 vs. 61.6%), more often patients with ischemic cardiomyopathy (49.8 vs 47.9%), less often arrhythmogenic heart disease (13.2 vs 16.6%) and patients with more co-morbidities and from communities with lower average income. High volume centers used more cardiac resynchronization therapy (26.8 vs 22.5%) despite no difference in QRS width. 1 and 3-y mortality were significantly higher in the low volume centers, respectively 5.6 vs. 4.4% and 16 vs. 11.1%. This was also confirmed in Kaplan Meier survival analysis. In multivariate logistic regression underlying heart disease, income, age, EF, NYHA class, CRT, indication and most comorbidities were significantly associated with mortality, but center volume remained an independent risk factor for 3-y mortality (OR = 0.749 (0.702–0.937), p&amp;lt;0.001).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Patients treated in low and high-volume centers in Belgium are different. However, there remained an association between volume and mortality of centers when controlling for these differences. Further research to elucidate if this association is due to statistical limitations of our analysis, referral bias or differences in quality of care is necessary.</jats:p></jats:sec><jats:sec><jats:title>Funding Acknowledgement</jats:title><jats:p>Type of funding source: None</jats:p></jats:sec>

Topics
  • impedance spectroscopy
  • laser emission spectroscopy
  • size-exclusion chromatography