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2. The effect of isolation precautions on care processes and medical outcomes in patients colonized with MRSA

Author

Labus, David, Weinhold, Leonie, and Heller, Joerg

Subjects
methicillin-resistant staphylococcus aureus, patient isolation, infection control, outcome and process assessment (health care), diagnostic techniques and procedures, patient safety, Medicine, Public aspects of medicine, RA1-1270, Microbiology, QR1-502
Abstract

Background: Isolation precautions used in methicillin-resistant (MRSA) infection control are effective in inhibiting pathogen transmission, but may cause unintended consequences in medical care. In addition, while costs attributed to MRSA are known to be substantial, little is known about their reimbursement in the German Diagnosis Related Groups (G-DRG) payment system. The aim of our study was to examine the effect of isolation precautions used in MRSA infection control on care processes, patient outcomes and deliver reliable data on MRSA-attributed reimbursement.Methods: A retrospective, matched cohort study of inpatients admitted to a general care teaching hospital in Bad Neuenahr, Germany, between January 1, 2016, and December 31, 2017 was performed. Patients isolated for MRSA colonization were matched to non-isolated controls based on age, gender, MRSA-adjusted Patient Clinical Complexity Level (Ma-PCCL) and Major Diagnostic Category (MDC). Main outcome measures on care processes and patient outcomes included adverse events, patient complaints, 30-day readmission rates, length of stay, type of discharge, and performance of instrument-based diagnostics. MRSA-attributed reimbursement was measured by conducting two separate G-DRG groupings, one with inclusion of MRSA-related codes and one without. Results: A total of 26,059 patients were admitted to Maria Hilf Hospital in Bad Neuenahr, Germany, during the study period. We identified 304 patients isolated for MRSA colonization. Compared to non-isolated matched controls, those on isolation precautions for MRSA colonization acquired about 45% more pressure ulcers and experienced significant delays in the performance of radiological diagnostics and echocardiographs. Patients isolated for MRSA colonization received about 49% fewer echocardiographs and had about 38% fewer abdominal ultrasound exams performed compared to non-isolated matched controls. A non-significant tendency towards fewer discharges to rehabilitation clinics and higher mortality rates were observed in patients isolated for MRSA colonization. Reimbursements were negligibly affected when MRSA-related codes were integrated by the grouper.Conclusion: Isolation precautions are associated with adverse consequences for care processes. These consequences need to be mitigated in order to justify placing patients at risk.

Published
2019
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4. Accounting for Time Dependency in Meta-Analyses of Concordance Probability Estimates

Author

Schmid, Matthias, Friede, Tim, Klein, Nadja, and Weinhold, Leonie

Subjects
Statistics - Methodology
Abstract

Recent years have seen the development of many novel scoring tools for disease prognosis and prediction. To become accepted for use in clinical applications, these tools have to be validated on external data. In practice, validation is often hampered by logistical issues, resulting in multiple small-sized validation studies. It is therefore necessary to synthesize the results of these studies using techniques for meta-analysis. Here we consider strategies for meta-analyzing the concordance probability for time-to-event data ("C-index"), which has become a popular tool to evaluate the discriminatory power of prediction models with a right-censored outcome. We show that standard meta-analysis of the C-index may lead to biased results, as the magnitude of the concordance probability depends on the length of the time interval used for evaluation (defined e.g. by the follow-up time, which might differ considerably between studies). To address this issue, we propose a set of methods for random-effects meta-regression that incorporate time directly as covariate in the model equation. In addition to analyzing nonlinear time trends via fractional polynomial, spline, and exponential decay models, we provide recommendations on suitable transformations of the C-index before meta-regression. Our results suggest that the C-index is best meta-analyzed using fractional polynomial meta-regression with logit-transformed C-index values. Classical random-effects meta-analysis (not considering time as covariate) is demonstrated to be a suitable alternative when follow-up times are small. Our findings have implications for the reporting of C-index values in future studies, which should include information on the length of the time interval underlying the calculations.

Published
2022

6. Deselection of Base-Learners for Statistical Boosting -- with an Application to Distributional Regression

Author

Strömer, Annika, Staerk, Christian, Klein, Nadja, Weinhold, Leonie, Titze, Stephanie, and Mayr, Andreas

Subjects
Statistics - Methodology, Statistics - Applications
Abstract

We present a new procedure for enhanced variable selection for component-wise gradient boosting. Statistical boosting is a computational approach that emerged from machine learning, which allows to fit regression models in the presence of high-dimensional data. Furthermore, the algorithm can lead to data-driven variable selection. In practice, however, the final models typically tend to include too many variables in some situations. This occurs particularly for low-dimensional data (p

Published
2022

8. Accounting for Time Dependency in Meta-Analyses of Concordance Probability Estimates

Author

Schmid, Matthias, Friede, Tim, Klein, Nadja, and Weinhold, Leonie

Abstract

Recent years have seen the development of many novel scoring tools for disease prognosis and prediction. To become accepted for use in clinical applications, these tools have to be validated on external data. In practice, validation is often hampered by logistical issues, resulting in multiple small-sized validation studies. It is therefore necessary to synthesize the results of these studies using techniques for meta-analysis. Here we consider strategies for meta analyzing the concordance probability for time-to-event data ("C-index"), which has become a popular tool to evaluate the discriminatory power of prediction models with a right-censored outcome. We show that standard meta-analysis of the C-index may lead to biased results, as the magnitude of the concordance probability depends on the length of the time interval used for evaluation (defined e.g., by the follow-up time, which might differ considerably between studies). To address this issue, we propose a set of methods for random-effects meta-regression that incorporate time directly as covariate in the model equation. In addition to analyzing nonlinear time trends via fractional polynomial, spline, and exponential decay models, we provide recommendations on suitable transformations of the C-index before meta-regression. Our results suggest that the C-index is best meta-analyzed using fractional polynomial meta-regression with logit-transformed C-index values. Classical random-effects meta-analysis (not considering time as covariate) is demonstrated to be a suitable alternative when follow-up times are small. Our findings have implications for the reporting of C-index values in future studies, which should include information on the length of the time interval underlying the calculations.

Published
2023
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10. Author Correction: Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Author

de Rojas, Itziar, Moreno-Grau, Sonia, Tesi, Niccolo, Grenier-Boley, Benjamin, Andrade, Victor, Jansen, Iris E., Pedersen, Nancy L., Stringa, Najada, Zettergren, Anna, Hernández, Isabel, Montrreal, Laura, Antúnez, Carmen, Antonell, Anna, Tankard, Rick M., Bis, Joshua C., Sims, Rebecca, Bellenguez, Céline, Quintela, Inés, González-Perez, Antonio, Calero, Miguel, Franco-Macías, Emilio, Macías, Juan, Blesa, Rafael, Cervera-Carles, Laura, Menéndez-González, Manuel, Frank-García, Ana, Royo, Jose Luís, Moreno, Fermin, Huerto Vilas, Raquel, Baquero, Miquel, Diez-Fairen, Mónica, Lage, Carmen, García-Madrona, Sebastián, García-González, Pablo, Alarcón-Martín, Emilio, Valero, Sergi, Sotolongo-Grau, Oscar, Ullgren, Abbe, Naj, Adam C., Lemstra, Afina W., Benaque, Alba, Pérez-Cordón, Alba, Benussi, Alberto, Rábano, Alberto, Padovani, Alessandro, Squassina, Alessio, de Mendonça, Alexandre, Arias Pastor, Alfonso, Kok, Almar A. L., Meggy, Alun, Pastor, Ana Belén, Espinosa, Ana, Corma-Gómez, Anaïs, Martín Montes, Angel, Sanabria, Ángela, DeStefano, Anita L., Schneider, Anja, Haapasalo, Annakaisa, Kinhult Ståhlbom, Anne, Tybjærg-Hansen, Anne, Hartmann, Annette M., Spottke, Annika, Corbatón-Anchuelo, Arturo, Rongve, Arvid, Borroni, Barbara, Arosio, Beatrice, Nacmias, Benedetta, Nordestgaard, Børge G., Kunkle, Brian W., Charbonnier, Camille, Abdelnour, Carla, Masullo, Carlo, Martínez Rodríguez, Carmen, Muñoz-Fernandez, Carmen, Dufouil, Carole, Graff, Caroline, Ferreira, Catarina B., Chillotti, Caterina, Reynolds, Chandra A., Fenoglio, Chiara, Van Broeckhoven, Christine, Clark, Christopher, Pisanu, Claudia, Satizabal, Claudia L., Holmes, Clive, Buiza-Rueda, Dolores, Aarsland, Dag, Rujescu, Dan, Alcolea, Daniel, Galimberti, Daniela, Wallon, David, Seripa, Davide, Grünblatt, Edna, Dardiotis, Efthimios, Düzel, Emrah, Scarpini, Elio, Conti, Elisa, Rubino, Elisa, Gelpi, Ellen, Rodriguez-Rodriguez, Eloy, Duron, Emmanuelle, Boerwinkle, Eric, Ferri, Evelyn, Tagliavini, Fabrizio, Küçükali, Fahri, Pasquier, Florence, Sanchez-Garcia, Florentino, Mangialasche, Francesca, Jessen, Frank, Nicolas, Gaël, Selbæk, Geir, Ortega, Gemma, Chêne, Geneviève, Hadjigeorgiou, Georgios, Rossi, Giacomina, Spalletta, Gianfranco, Giaccone, Giorgio, Grande, Giulia, Binetti, Giuliano, Papenberg, Goran, Hampel, Harald, Bailly, Henri, Zetterberg, Henrik, Soininen, Hilkka, Karlsson, Ida K., Alvarez, Ignacio, Appollonio, Ildebrando, Giegling, Ina, Skoog, Ingmar, Saltvedt, Ingvild, Rainero, Innocenzo, Rosas Allende, Irene, Hort, Jakub, Diehl-Schmid, Janine, Van Dongen, Jasper, Vidal, Jean-Sebastien, Lehtisalo, Jenni, Wiltfang, Jens, Thomassen, Jesper Qvist, Kornhuber, Johannes, Haines, Jonathan L., Vogelgsang, Jonathan, Pineda, Juan A., Fortea, Juan, Popp, Julius, Deckert, Jürgen, Buerger, Katharina, Morgan, Kevin, Fließbach, Klaus, Sleegers, Kristel, Molina-Porcel, Laura, Kilander, Lena, Weinhold, Leonie, Farrer, Lindsay A., Wang, Li-San, Kleineidam, Luca, Farotti, Lucia, Parnetti, Lucilla, Tremolizzo, Lucio, Hausner, Lucrezia, Benussi, Luisa, Froelich, Lutz, Ikram, M. Arfan, Deniz-Naranjo, M. Candida, Tsolaki, Magda, Rosende-Roca, Maitée, Löwenmark, Malin, Hulsman, Marc, Spallazzi, Marco, Pericak-Vance, Margaret A., Esiri, Margaret, Bernal Sánchez-Arjona, María, Dalmasso, Maria Carolina, Martínez-Larrad, María Teresa, Arcaro, Marina, Nöthen, Markus M., Fernández-Fuertes, Marta, Dichgans, Martin, Ingelsson, Martin, Herrmann, Martin J., Scherer, Martin, Vyhnalek, Martin, Kosmidis, Mary H., Yannakoulia, Mary, Schmid, Matthias, Ewers, Michael, Heneka, Michael T., Wagner, Michael, Scamosci, Michela, Kivipelto, Miia, Hiltunen, Mikko, Zulaica, Miren, Alegret, Montserrat, Fornage, Myriam, Roberto, Natalia, van Schoor, Natasja M., Seidu, Nazib M., Banaj, Nerisa, Armstrong, Nicola J., Scarmeas, Nikolaos, Scherbaum, Norbert, Goldhardt, Oliver, Hanon, Oliver, Peters, Oliver, Skrobot, Olivia Anna, Quenez, Olivier, Lerch, Ondrej, Bossù, Paola, Caffarra, Paolo, Dionigi Rossi, Paolo, Sakka, Paraskevi, Mecocci, Patrizia, Hoffmann, Per, Holmans, Peter A., Fischer, Peter, Riederer, Peter, Yang, Qiong, Marshall, Rachel, Kalaria, Rajesh N., Mayeux, Richard, Vandenberghe, Rik, Cecchetti, Roberta, Ghidoni, Roberta, Frikke-Schmidt, Ruth, Sorbi, Sandro, Hägg, Sara, Engelborghs, Sebastiaan, Helisalmi, Seppo, Botne Sando, Sigrid, Kern, Silke, Archetti, Silvana, Boschi, Silvia, Fostinelli, Silvia, Gil, Silvia, Mendoza, Silvia, Mead, Simon, Ciccone, Simona, Djurovic, Srdjan, Heilmann-Heimbach, Stefanie, Riedel-Heller, Steffi, Kuulasmaa, Teemu, del Ser, Teodoro, Lebouvier, Thibaud, Polak, Thomas, Ngandu, Tiia, Grimmer, Timo, Bessi, Valentina, Escott-Price, Valentina, Giedraitis, Vilmantas, Deramecourt, Vincent, Maier, Wolfgang, Jian, Xueqiu, Pijnenburg, Yolande A. L., Kehoe, Patrick Gavin, Garcia-Ribas, Guillermo, Sánchez-Juan, Pascual, Pastor, Pau, Pérez-Tur, Jordi, Piñol-Ripoll, Gerard, Lopez de Munain, Adolfo, García-Alberca, Jose María, Bullido, María J., Álvarez, Victoria, Lleó, Alberto, Real, Luis M., Mir, Pablo, Medina, Miguel, Scheltens, Philip, Holstege, Henne, Marquié, Marta, Sáez, María Eugenia, Carracedo, Ángel, Amouyel, Philippe, Schellenberg, Gerard D., Williams, Julie, Seshadri, Sudha, van Duijn, Cornelia M., Mather, Karen A., Sánchez-Valle, Raquel, Serrano-Ríos, Manuel, Orellana, Adelina, Tárraga, Lluís, Blennow, Kaj, Huisman, Martijn, Andreassen, Ole A., Posthuma, Danielle, Clarimón, Jordi, Boada, Mercè, van der Flier, Wiesje M., Ramirez, Alfredo, Lambert, Jean-Charles, van der Lee, Sven J., and Ruiz, Agustín

Published
2023
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14. A Random Forest Approach for Modeling Bounded Outcomes

Author

Weinhold, Leonie, Schmid, Matthias, Wright, Marvin N., and Berger, Moritz

Subjects
Statistics - Methodology
Abstract

Random forests have become an established tool for classification and regression, in particular in high-dimensional settings and in the presence of complex predictor-response relationships. For bounded outcome variables restricted to the unit interval, however, classical random forest approaches may severely suffer as they do not account for the heteroscedasticity in the data. A random forest approach is proposed for relating beta distributed outcomes to explanatory variables. The approach explicitly makes use of the likelihood function of the beta distribution for the selection of splits during the tree-building procedure. In each iteration of the tree-building algorithm one chooses the combination of explanatory variable and splitting rule that maximizes the log-likelihood function of the beta distribution with the parameter estimates derived from the nodes of the currently built tree. Several simulation studies demonstrate the properties of the method and compare its performance to classical random forest approaches as well as to parametric regression models., Comment: 19 pages, 5 figures

Published
2019

17. New insights into the genetic etiology of Alzheimer’s disease and related dementias

Author

Bellenguez, Céline, Küçükali, Fahri, Jansen, Iris E., Kleineidam, Luca, Moreno-Grau, Sonia, Amin, Najaf, Naj, Adam C., Campos-Martin, Rafael, Grenier-Boley, Benjamin, Andrade, Victor, Holmans, Peter A., Boland, Anne, Damotte, Vincent, van der Lee, Sven J., Costa, Marcos R., Kuulasmaa, Teemu, Yang, Qiong, de Rojas, Itziar, Bis, Joshua C., Yaqub, Amber, Prokic, Ivana, Chapuis, Julien, Ahmad, Shahzad, Giedraitis, Vilmantas, Aarsland, Dag, Garcia-Gonzalez, Pablo, Abdelnour, Carla, Alarcón-Martín, Emilio, Alcolea, Daniel, Alegret, Montserrat, Alvarez, Ignacio, Álvarez, Victoria, Armstrong, Nicola J., Tsolaki, Anthoula, Antúnez, Carmen, Appollonio, Ildebrando, Arcaro, Marina, Archetti, Silvana, Pastor, Alfonso Arias, Arosio, Beatrice, Athanasiu, Lavinia, Bailly, Henri, Banaj, Nerisa, Baquero, Miquel, Barral, Sandra, Beiser, Alexa, Pastor, Ana Belén, Below, Jennifer E., Benchek, Penelope, Benussi, Luisa, Berr, Claudine, Besse, Céline, Bessi, Valentina, Binetti, Giuliano, Bizarro, Alessandra, Blesa, Rafael, Boada, Mercè, Boerwinkle, Eric, Borroni, Barbara, Boschi, Silvia, Bossù, Paola, Bråthen, Geir, Bressler, Jan, Bresner, Catherine, Brodaty, Henry, Brookes, Keeley J., Brusco, Luis Ignacio, Buiza-Rueda, Dolores, Bûrger, Katharina, Burholt, Vanessa, Bush, William S., Calero, Miguel, Cantwell, Laura B., Chene, Geneviève, Chung, Jaeyoon, Cuccaro, Michael L., Carracedo, Ángel, Cecchetti, Roberta, Cervera-Carles, Laura, Charbonnier, Camille, Chen, Hung-Hsin, Chillotti, Caterina, Ciccone, Simona, Claassen, Jurgen A. H. R., Clark, Christopher, Conti, Elisa, Corma-Gómez, Anaïs, Costantini, Emanuele, Custodero, Carlo, Daian, Delphine, Dalmasso, Maria Carolina, Daniele, Antonio, Dardiotis, Efthimios, Dartigues, Jean-François, de Deyn, Peter Paul, de Paiva Lopes, Katia, de Witte, Lot D., Debette, Stéphanie, Deckert, Jürgen, del Ser, Teodoro, Denning, Nicola, DeStefano, Anita, Dichgans, Martin, Diehl-Schmid, Janine, Diez-Fairen, Mónica, Rossi, Paolo Dionigi, Djurovic, Srdjan, Duron, Emmanuelle, Düzel, Emrah, Dufouil, Carole, Eiriksdottir, Gudny, Engelborghs, Sebastiaan, Escott-Price, Valentina, Espinosa, Ana, Ewers, Michael, Faber, Kelley M., Fabrizio, Tagliavini, Nielsen, Sune Fallgaard, Fardo, David W., Farotti, Lucia, Fenoglio, Chiara, Fernández-Fuertes, Marta, Ferrari, Raffaele, Ferreira, Catarina B., Ferri, Evelyn, Fin, Bertrand, Fischer, Peter, Fladby, Tormod, Fließbach, Klaus, Fongang, Bernard, Fornage, Myriam, Fortea, Juan, Foroud, Tatiana M., Fostinelli, Silvia, Fox, Nick C., Franco-Macías, Emlio, Bullido, María J., Frank-García, Ana, Froelich, Lutz, Fulton-Howard, Brian, Galimberti, Daniela, García-Alberca, Jose Maria, García-González, Pablo, Garcia-Madrona, Sebastian, Garcia-Ribas, Guillermo, Ghidoni, Roberta, Giegling, Ina, Giorgio, Giaccone, Goate, Alison M., Goldhardt, Oliver, Gomez-Fonseca, Duber, González-Pérez, Antonio, Graff, Caroline, Grande, Giulia, Green, Emma, Grimmer, Timo, Grünblatt, Edna, Grunin, Michelle, Gudnason, Vilmundur, Guetta-Baranes, Tamar, Haapasalo, Annakaisa, Hadjigeorgiou, Georgios, Haines, Jonathan L., Hamilton-Nelson, Kara L., Hampel, Harald, Hanon, Olivier, Hardy, John, Hartmann, Annette M., Hausner, Lucrezia, Harwood, Janet, Heilmann-Heimbach, Stefanie, Helisalmi, Seppo, Heneka, Michael T., Hernández, Isabel, Herrmann, Martin J., Hoffmann, Per, Holmes, Clive, Holstege, Henne, Vilas, Raquel Huerto, Hulsman, Marc, Humphrey, Jack, Biessels, Geert Jan, Jian, Xueqiu, Johansson, Charlotte, Jun, Gyungah R., Kastumata, Yuriko, Kauwe, John, Kehoe, Patrick G., Kilander, Lena, Ståhlbom, Anne Kinhult, Kivipelto, Miia, Koivisto, Anne, Kornhuber, Johannes, Kosmidis, Mary H., Kukull, Walter A., Kuksa, Pavel P., Kunkle, Brian W., Kuzma, Amanda B., Lage, Carmen, Laukka, Erika J., Launer, Lenore, Lauria, Alessandra, Lee, Chien-Yueh, Lehtisalo, Jenni, Lerch, Ondrej, Lleó, Alberto, Longstreth, Jr, William, Lopez, Oscar, de Munain, Adolfo Lopez, Love, Seth, Löwemark, Malin, Luckcuck, Lauren, Lunetta, Kathryn L., Ma, Yiyi, Macías, Juan, MacLeod, Catherine A., Maier, Wolfgang, Mangialasche, Francesca, Spallazzi, Marco, Marquié, Marta, Marshall, Rachel, Martin, Eden R., Montes, Angel Martín, Rodríguez, Carmen Martínez, Masullo, Carlo, Mayeux, Richard, Mead, Simon, Mecocci, Patrizia, Medina, Miguel, Meggy, Alun, Mehrabian, Shima, Mendoza, Silvia, Menéndez-González, Manuel, Mir, Pablo, Moebus, Susanne, Mol, Merel, Molina-Porcel, Laura, Montrreal, Laura, Morelli, Laura, Moreno, Fermin, Morgan, Kevin, Mosley, Thomas, Nöthen, Markus M., Muchnik, Carolina, Mukherjee, Shubhabrata, Nacmias, Benedetta, Ngandu, Tiia, Nicolas, Gael, Nordestgaard, Børge G., Olaso, Robert, Orellana, Adelina, Orsini, Michela, Ortega, Gemma, Padovani, Alessandro, Paolo, Caffarra, Papenberg, Goran, Parnetti, Lucilla, Pasquier, Florence, Pastor, Pau, Peloso, Gina, Pérez-Cordón, Alba, Pérez-Tur, Jordi, Pericard, Pierre, Peters, Oliver, Pijnenburg, Yolande A. L., Pineda, Juan A., Piñol-Ripoll, Gerard, Pisanu, Claudia, Polak, Thomas, Popp, Julius, Posthuma, Danielle, Priller, Josef, Puerta, Raquel, Quenez, Olivier, Quintela, Inés, Thomassen, Jesper Qvist, Rábano, Alberto, Rainero, Innocenzo, Rajabli, Farid, Ramakers, Inez, Real, Luis M., Reinders, Marcel J. T., Reitz, Christiane, Reyes-Dumeyer, Dolly, Ridge, Perry, Riedel-Heller, Steffi, Riederer, Peter, Roberto, Natalia, Rodriguez-Rodriguez, Eloy, Rongve, Arvid, Allende, Irene Rosas, Rosende-Roca, Maitée, Royo, Jose Luis, Rubino, Elisa, Rujescu, Dan, Sáez, María Eugenia, Sakka, Paraskevi, Saltvedt, Ingvild, Sanabria, Ángela, Sánchez-Arjona, María Bernal, Sanchez-Garcia, Florentino, Juan, Pascual Sánchez, Sánchez-Valle, Raquel, Sando, Sigrid B., Sarnowski, Chloé, Satizabal, Claudia L., Scamosci, Michela, Scarmeas, Nikolaos, Scarpini, Elio, Scheltens, Philip, Scherbaum, Norbert, Scherer, Martin, Schmid, Matthias, Schneider, Anja, Schott, Jonathan M., Selbæk, Geir, Seripa, Davide, Serrano, Manuel, Sha, Jin, Shadrin, Alexey A., Skrobot, Olivia, Slifer, Susan, Snijders, Gijsje J. L., Soininen, Hilkka, Solfrizzi, Vincenzo, Solomon, Alina, Song, Yeunjoo, Sorbi, Sandro, Sotolongo-Grau, Oscar, Spalletta, Gianfranco, Spottke, Annika, Squassina, Alessio, Stordal, Eystein, Tartan, Juan Pablo, Tárraga, Lluís, Tesí, Niccolo, Thalamuthu, Anbupalam, Thomas, Tegos, Tosto, Giuseppe, Traykov, Latchezar, Tremolizzo, Lucio, Tybjærg-Hansen, Anne, Uitterlinden, Andre, Ullgren, Abbe, Ulstein, Ingun, Valero, Sergi, Valladares, Otto, Broeckhoven, Christine Van, Vance, Jeffery, Vardarajan, Badri N., van der Lugt, Aad, Dongen, Jasper Van, van Rooij, Jeroen, van Swieten, John, Vandenberghe, Rik, Verhey, Frans, Vidal, Jean-Sébastien, Vogelgsang, Jonathan, Vyhnalek, Martin, Wagner, Michael, Wallon, David, Wang, Li-San, Wang, Ruiqi, Weinhold, Leonie, Wiltfang, Jens, Windle, Gill, Woods, Bob, Yannakoulia, Mary, Zare, Habil, Zhao, Yi, Zhang, Xiaoling, Zhu, Congcong, Zulaica, Miren, Farrer, Lindsay A., Psaty, Bruce M., Ghanbari, Mohsen, Raj, Towfique, Sachdev, Perminder, Mather, Karen, Jessen, Frank, Ikram, M. Arfan, de Mendonça, Alexandre, Hort, Jakub, Tsolaki, Magda, Pericak-Vance, Margaret A., Amouyel, Philippe, Williams, Julie, Frikke-Schmidt, Ruth, Clarimon, Jordi, Deleuze, Jean-François, Rossi, Giacomina, Seshadri, Sudha, Andreassen, Ole A., Ingelsson, Martin, Hiltunen, Mikko, Sleegers, Kristel, Schellenberg, Gerard D., van Duijn, Cornelia M., Sims, Rebecca, van der Flier, Wiesje M., Ruiz, Agustín, Ramirez, Alfredo, and Lambert, Jean-Charles

Published
2022
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19. Peer‐to‐peer validation of Ki‐67 scoring in a pathology quality circle as a tool to assess interobserver variability: are we better than we thought?

Author

Bernhardt, Marit, Weinhold, Leonie, Sanders, Christine, Hommerding, Oliver, Lau, Jan‐Frederic, Toma, Marieta, Tischler, Verena, Schmid, Matthias, Zienkiewicz, Tomasz, Hildenbrand, Ralf, Gerlach, Peter, Zhou, Hui, Braun, Martin, Müller, Gunnar, Sieber, Erich, Marko, Christian, and Kristiansen, Glen

Subjects
*INTRACLASS correlation, *NEUROENDOCRINE tumors, *SQUAMOUS cell carcinoma, *NUCLEAR proteins, *CELL proliferation
Abstract

Ki‐67, a nuclear protein expressed in all stages of cellular proliferation, is a valuable tool to assess tumor proliferation and has been linked to more aggressive tumor behavior. However, interlaboratory staining heterogeneity and inter‐observer variability challenge its reproducibility. Round Robin tests are a suitable tool to standardize and harmonize immunohistochemical and molecular analyses in histopathology. The study investigates the interrater and interlaboratory reproducibility of Ki‐67‐scoring using both manual and automated approaches. Unstained TMA slides comprising diverse tumor types (breast cancer, neuroendocrine tumors, lymphomas, and head and neck squamous cell carcinoma) were distributed to six pathology laboratories, each employing their routine staining protocols. Manual and automated scoring methods were applied, and interrater and interlaboratory agreement assessed using intraclass correlation coefficients (ICC). The results highlight good‐to‐excellent reliability overall, with automated scoring demonstrating higher consistency (ICC 0.955) than manual scoring (ICC 0.871). Results were more variable when looking at the individual entities. Reliability remained good for lymphomas (ICC 0.878) and breast cancer (ICC 0.784) and was poor in well‐differentiated neuroendocrine tumors (ICC 0.354). This study clearly advocates standardized practices and training to ensure consistency in Ki‐67‐assessment, and it demonstrates that this can be achieved in a peer‐to‐peer approach in local quality‐circles. [ABSTRACT FROM AUTHOR]

Published
2024
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20. Prognostic Characteristics of Metabolic Dysfunction-Associated Steatotic Liver in Patients with Obesity Who Undergo One Anastomosis Gastric Bypass Surgery: A Secondary Analysis of Randomized Controlled Trial Data.

Author

Crommen, Silke, Rheinwalt, Karl Peter, Plamper, Andreas, Rösler, Daniela, Weinhold, Leonie, Metzner, Christine, and Egert, Sarah

Abstract

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is closely associated with obesity and insulin resistance (IR). Identifying characteristics that predict a higher risk of fibrosis using noninvasive methods is particularly important. Methods: We performed a secondary analysis of data from an RCT of 48 patients after one anastomosis gastric bypass (OAGB) surgery, supplemented with specifically formulated probiotics and micronutrients or control treatment for 12 weeks. Patients were categorized using alanine aminotransferase (ALAT; >35 U/L for women, >50 U/L for men), higher NAFLD fibrosis score (NFS) > −1.455), and IR (HOMA-IR > 2.0). This trial was registered at Clinicaltrials.gov (ID: NCT03585413). Results: Abnormal ALAT was associated with high triglycerides, blood pressure (BP), glucose, and fatty liver index (FLI). NFS > −1.455 was linked to higher age, body mass, waist circumference, and FLI, and lower albumin and platelet count. HOMA-IR > 2.0 was associated with higher BP and triglycerides, lower HDL-cholesterol, higher serum transaminases, and higher probabilities of steatosis and fibrosis. Twelve weeks postoperatively, patients with NFS > −1.455 showed greater reductions in body mass, systolic BP, serum insulin, and HbA1c, whereas those with NFS ≤ −1.455 showed improvements in FLI and lipid metabolism but had high glucose concentrations. Patients with HOMA-IR ≤ 2.0 also had high glucose concentrations. Conclusions: The evaluation of common biomarker scores for fibrosis and IR may help clinicians to recognize severe NAFLD and improve the outcomes of OAGB surgery. [ABSTRACT FROM AUTHOR]

Published
2024
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26. A Statistical Model for the Analysis of Beta Values in DNA Methylation Studies

Author

Weinhold, Leonie, Wahl, Simone, and Schmid, Matthias

Subjects
Statistics - Methodology
Abstract

Background: The analysis of DNA methylation is a key component in the development of personalized treatment approaches. A common way to measure DNA methylation is the calculation of beta values, which are bounded variables of the form M = (M + U) that are generated by Illumina's 450k BeadChip array. The statistical analysis of beta values is considered to be challenging, as traditional methods for the analysis of bounded variables, such as M-value regression and beta regression, are based on regularity assumptions that are often too strong to adequately describe the distribution of beta values. Results: We develop a statistical model for the analysis of beta values that is derived from a bivariate gamma distribution for the signal intensities M and U. By allowing for possible correlations between M and U, the proposed model explicitly takes into account the data-generating process underlying the calculation of beta values. Conclusion: The proposed model can be used to improve the identification of associations between beta values and covariates such as clinical variables and lifestyle factors in epigenome-wide association studies. It is as easy to apply to a sample of beta values as beta regression and M-value regression.

Published
2016

27. Cardiac troponin T as a serum biomarker of respiratory impairment in amyotrophic lateral sclerosis.

Author

Koch, Teresa, Fabian, Rachel, Weinhold, Leonie, Koch, Franz‐W., Barakat, Saman, Castro‐Gomez, Sergio, Grehl, Torsten, Bernsen, Sarah, and Weydt, Patrick

Subjects
AMYOTROPHIC lateral sclerosis, PHYSIOLOGY, VITAL capacity (Respiration), TROPONIN, CYTOPLASMIC filaments
Abstract

Objective: Informative biomarkers are an urgent need in the management of amyotrophic lateral sclerosis. Serum cardiac troponin T is elevated in the majority of amyotrophic lateral sclerosis patients and increases with disease progression. We sought to establish the informative value of cardiac troponin T with regard to respiratory function, a major prognostic factor in amyotrophic lateral sclerosis. Methods: In this retrospective observation, we analyzed two independent hospital‐based cohorts (d = discovery cohort; v = validation cohort) regarding serum cardiac troponin T (nd = 298; nv = 49), serum neurofilament light chain (nd = 117; nv = 17), and respiratory tests (nd = 93; nv = 49). Results: Serum cardiac troponin T, in contrast to serum neurofilament levels, was associated with the respiratory domain of the revised amyotrophic lateral sclerosis functional rating scale and with pulmonary function parameters, namely forced vital capacity % (r = −0.45, p = 0.001) and slow vital capacity % (r = −0.50, p = 0.001). Serum cardiac troponin T reliably discriminated benchmarks of slow vital capacity <80% (AUC 0.73, 95% CI 0.62–0.84) and <50% (AUC 0.80, 95% CI 0.68–0.93), forced vital capacity <80% (AUC 0.72, 95% CI 0.61–0.83) and <50% (AUC 0.79, 95% CI 0.67–0.91). Interpretation: Our findings position cardiac Troponin T as a valuable serum biomarker in amyotrophic lateral sclerosis, complementing neurofilaments and expanding the understanding of underlying physiological mechanisms. In clinical practice, serum cardiac troponin T can flag benchmarks of compromised respiratory function. [ABSTRACT FROM AUTHOR]

Published
2024
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32. P‐tau217 is the earliest plasma marker of dementia of the Alzheimer’s type in older primary care patients

Author

Kleineidam, Luca, primary, Oezdemir, Selçuk, additional, Martino‐Adami, Pamela, additional, Weinhold, Leonie, additional, Koehler, David, additional, Chatterjee, Madhurima, additional, Pentzek, Michael, additional, Weyerer, Siegfried, additional, Bickel, Horst, additional, Wiese, Birgitt, additional, Riedel‐Heller, Steffi G., additional, Scherer, Martin, additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, Schmid, Matthias, additional, Ruiz, Agustin, additional, Peters, Oliver, additional, Jeromin, Andreas, additional, Wagner, Michael, additional, Ramirez, Alfredo, additional, and Schneider, Anja, additional

Published
2023
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34. Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Author

de Rojas, Itziar, Moreno-Grau, Sonia, Tesi, Niccolo, Grenier-Boley, Benjamin, Andrade, Victor, Jansen, Iris E., Pedersen, Nancy L., Stringa, Najada, Zettergren, Anna, Hernández, Isabel, Montrreal, Laura, Antúnez, Carmen, Antonell, Anna, Tankard, Rick M., Bis, Joshua C., Sims, Rebecca, Bellenguez, Céline, Quintela, Inés, González-Perez, Antonio, Calero, Miguel, Franco-Macías, Emilio, Macías, Juan, Blesa, Rafael, Cervera-Carles, Laura, Menéndez-González, Manuel, Frank-García, Ana, Royo, Jose Luís, Moreno, Fermin, Huerto Vilas, Raquel, Baquero, Miquel, Diez-Fairen, Mónica, Lage, Carmen, García-Madrona, Sebastián, García-González, Pablo, Alarcón-Martín, Emilio, Valero, Sergi, Sotolongo-Grau, Oscar, Ullgren, Abbe, Naj, Adam C., Lemstra, Afina W., Benaque, Alba, Pérez-Cordón, Alba, Benussi, Alberto, Rábano, Alberto, Padovani, Alessandro, Squassina, Alessio, de Mendonça, Alexandre, Arias Pastor, Alfonso, Kok, Almar A. L., Meggy, Alun, Pastor, Ana Belén, Espinosa, Ana, Corma-Gómez, Anaïs, Martín Montes, Angel, Sanabria, Ángela, DeStefano, Anita L., Schneider, Anja, Haapasalo, Annakaisa, Kinhult Ståhlbom, Anne, Tybjærg-Hansen, Anne, Hartmann, Annette M., Spottke, Annika, Corbatón-Anchuelo, Arturo, Rongve, Arvid, Borroni, Barbara, Arosio, Beatrice, Nacmias, Benedetta, Nordestgaard, Børge G., Kunkle, Brian W., Charbonnier, Camille, Abdelnour, Carla, Masullo, Carlo, Martínez Rodríguez, Carmen, Muñoz-Fernandez, Carmen, Dufouil, Carole, Graff, Caroline, Ferreira, Catarina B., Chillotti, Caterina, Reynolds, Chandra A., Fenoglio, Chiara, Van Broeckhoven, Christine, Clark, Christopher, Pisanu, Claudia, Satizabal, Claudia L., Holmes, Clive, Buiza-Rueda, Dolores, Aarsland, Dag, Rujescu, Dan, Alcolea, Daniel, Galimberti, Daniela, Wallon, David, Seripa, Davide, Grünblatt, Edna, Dardiotis, Efthimios, Düzel, Emrah, Scarpini, Elio, Conti, Elisa, Rubino, Elisa, Gelpi, Ellen, Rodriguez-Rodriguez, Eloy, Duron, Emmanuelle, Boerwinkle, Eric, Ferri, Evelyn, Tagliavini, Fabrizio, Küçükali, Fahri, Pasquier, Florence, Sanchez-Garcia, Florentino, Mangialasche, Francesca, Jessen, Frank, Nicolas, Gaël, Selbæk, Geir, Ortega, Gemma, Chêne, Geneviève, Hadjigeorgiou, Georgios, Rossi, Giacomina, Spalletta, Gianfranco, Giaccone, Giorgio, Grande, Giulia, Binetti, Giuliano, Papenberg, Goran, Hampel, Harald, Bailly, Henri, Zetterberg, Henrik, Soininen, Hilkka, Karlsson, Ida K., Alvarez, Ignacio, Appollonio, Ildebrando, Giegling, Ina, Skoog, Ingmar, Saltvedt, Ingvild, Rainero, Innocenzo, Rosas Allende, Irene, Hort, Jakub, Diehl-Schmid, Janine, Van Dongen, Jasper, Vidal, Jean-Sebastien, Lehtisalo, Jenni, Wiltfang, Jens, Thomassen, Jesper Qvist, Kornhuber, Johannes, Haines, Jonathan L., Vogelgsang, Jonathan, Pineda, Juan A., Fortea, Juan, Popp, Julius, Deckert, Jürgen, Buerger, Katharina, Morgan, Kevin, Fließbach, Klaus, Sleegers, Kristel, Molina-Porcel, Laura, Kilander, Lena, Weinhold, Leonie, Farrer, Lindsay A., Wang, Li-San, Kleineidam, Luca, Farotti, Lucia, Parnetti, Lucilla, Tremolizzo, Lucio, Hausner, Lucrezia, Benussi, Luisa, Froelich, Lutz, Ikram, M. Arfan, Deniz-Naranjo, M. Candida, Tsolaki, Magda, Rosende-Roca, Maitée, Löwenmark, Malin, Hulsman, Marc, Spallazzi, Marco, Pericak-Vance, Margaret A., Esiri, Margaret, Bernal Sánchez-Arjona, María, Dalmasso, Maria Carolina, Martínez-Larrad, María Teresa, Arcaro, Marina, Nöthen, Markus M., Fernández-Fuertes, Marta, Dichgans, Martin, Ingelsson, Martin, Herrmann, Martin J., Scherer, Martin, Vyhnalek, Martin, Kosmidis, Mary H., Yannakoulia, Mary, Schmid, Matthias, Ewers, Michael, Heneka, Michael T., Wagner, Michael, Scamosci, Michela, Kivipelto, Miia, Hiltunen, Mikko, Zulaica, Miren, Alegret, Montserrat, Fornage, Myriam, Roberto, Natalia, van Schoor, Natasja M., Seidu, Nazib M., Banaj, Nerisa, Armstrong, Nicola J., Scarmeas, Nikolaos, Scherbaum, Norbert, Goldhardt, Oliver, Hanon, Oliver, Peters, Oliver, Skrobot, Olivia Anna, Quenez, Olivier, Lerch, Ondrej, Bossù, Paola, Caffarra, Paolo, Dionigi Rossi, Paolo, Sakka, Paraskevi, Mecocci, Patrizia, Hoffmann, Per, Holmans, Peter A., Fischer, Peter, Riederer, Peter, Yang, Qiong, Marshall, Rachel, Kalaria, Rajesh N., Mayeux, Richard, Vandenberghe, Rik, Cecchetti, Roberta, Ghidoni, Roberta, Frikke-Schmidt, Ruth, Sorbi, Sandro, Hägg, Sara, Engelborghs, Sebastiaan, Helisalmi, Seppo, Botne Sando, Sigrid, Kern, Silke, Archetti, Silvana, Boschi, Silvia, Fostinelli, Silvia, Gil, Silvia, Mendoza, Silvia, Mead, Simon, Ciccone, Simona, Djurovic, Srdjan, Heilmann-Heimbach, Stefanie, Riedel-Heller, Steffi, Kuulasmaa, Teemu, del Ser, Teodoro, Lebouvier, Thibaud, Polak, Thomas, Ngandu, Tiia, Grimmer, Timo, Bessi, Valentina, Escott-Price, Valentina, Giedraitis, Vilmantas, Deramecourt, Vincent, Maier, Wolfgang, Jian, Xueqiu, Pijnenburg, Yolande A. L., Kehoe, Patrick Gavin, Garcia-Ribas, Guillermo, Sánchez-Juan, Pascual, Pastor, Pau, Pérez-Tur, Jordi, Piñol-Ripoll, Gerard, Lopez de Munain, Adolfo, García-Alberca, Jose María, Bullido, María J., Álvarez, Victoria, Lleó, Alberto, Real, Luis M., Mir, Pablo, Medina, Miguel, Scheltens, Philip, Holstege, Henne, Marquié, Marta, Sáez, María Eugenia, Carracedo, Ángel, Amouyel, Philippe, Schellenberg, Gerard D., Williams, Julie, Seshadri, Sudha, van Duijn, Cornelia M., Mather, Karen A., Sánchez-Valle, Raquel, Serrano-Ríos, Manuel, Orellana, Adelina, Tárraga, Lluís, Blennow, Kaj, Huisman, Martijn, Andreassen, Ole A., Posthuma, Danielle, Clarimón, Jordi, Boada, Mercè, van der Flier, Wiesje M., Ramirez, Alfredo, Lambert, Jean-Charles, van der Lee, Sven J., and Ruiz, Agustín

Published
2021
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37. A transgenerational mutational signature from ionizing radiation exposure.

Author

Brand, Fabian, primary, Klinkhammer, Hannah, additional, Knaus, Alexej, additional, Holtgrewe, Manuel, additional, Weinhold, Leonie, additional, Beule, Dieter, additional, Ludwig, Kerstin, additional, Kothiyal, Prachi, additional, Maxwell, George, additional, Noethen, Markus, additional, Schmid, Matthias, additional, Sperling, Karl, additional, and Krawitz, Peter, additional

Published
2023
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38. Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI

Author

Bischoff, Leon M., primary, Peeters, Johannes M., additional, Weinhold, Leonie, additional, Krausewitz, Philipp, additional, Ellinger, Jörg, additional, Katemann, Christoph, additional, Isaak, Alexander, additional, Weber, Oliver M., additional, Kuetting, Daniel, additional, Attenberger, Ulrike, additional, Pieper, Claus C., additional, Sprinkart, Alois M., additional, and Luetkens, Julian A., additional

Published
2023
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39. Circulating metabolites and general cognitive ability and dementia: Evidence from 11 cohort studies

Author

van der Lee, Sven J., Teunissen, Charlotte E., Pool, René, Shipley, Martin J., Teumer, Alexander, Chouraki, Vincent, Melo van Lent, Debora, Tynkkynen, Juho, Fischer, Krista, Hernesniemi, Jussi, Haller, Toomas, Singh-Manoux, Archana, Verhoeven, Aswin, Willemsen, Gonneke, de Leeuw, Francisca A., Wagner, Holger, van Dongen, Jenny, Hertel, Johannes, Budde, Kathrin, Willems van Dijk, Ko, Weinhold, Leonie, Ikram, M. Arfan, Pietzner, Maik, Perola, Markus, Wagner, Michael, Friedrich, Nele, Slagboom, P. Eline, Scheltens, Philip, Yang, Qiong, Gertzen, Robert E., Egert, Sarah, Li, Shuo, Hankemeier, Thomas, van Beijsterveldt, Catharina E.M., Vasan, Ramachandran S., Maier, Wolfgang, Peeters, Carel F.W., Jörgen Grabe, Hans, Ramirez, Alfredo, Seshadri, Sudha, Metspalu, Andres, Kivimäki, Mika, Salomaa, Veikko, Demirkan, Ayşe, Boomsma, Dorret I., van der Flier, Wiesje M., Amin, Najaf, and van Duijn, Cornelia M.

Published
2018
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42. Levels of Alzheimer's disease blood biomarkers are altered after food intake—A pilot intervention study in healthy adults.

Author

Huber, Hanna, Ashton, Nicholas J., Schieren, Alina, Montoliu‐Gaya, Laia, Molfetta, Guglielmo Di, Brum, Wagner S., Lantero‐Rodriguez, Juan, Grötschel, Lana, Stoffel‐Wagner, Birgit, Coenen, Martin, Weinhold, Leonie, Schmid, Matthias, Blennow, Kaj, Stehle, Peter, Zetterberg, Henrik, and Simon, Marie‐Christine

Abstract

INTRODUCTION: Blood biomarkers accurately identify Alzheimer's disease (AD) pathophysiology and axonal injury. We investigated the influence of food intake on AD‐related biomarkers in cognitively healthy, obese adults at high metabolic risk. METHODS: One‐hundred eleven participants underwent repeated blood sampling during 3 h after a standardized meal (postprandial group, PG). For comparison, blood was sampled from a fasting subgroup over 3 h (fasting group, FG). Plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), amyloid‐beta (Aβ) 42/40, phosphorylated tau (p‐tau) 181 and 231, and total‐tau were measured via single molecule array assays. RESULTS: Significant differences were found for NfL, GFAP, Aβ42/40, p‐tau181, and p‐tau231 between FG and PG. The greatest change to baseline occurred for GFAP and p‐tau181 (120 min postprandially, p < 0.0001). CONCLUSION: Our data suggest that AD‐related biomarkers are altered by food intake. Further studies are needed to verify whether blood biomarker sampling should be performed in the fasting state. Highlights: Acute food intake alters plasma biomarkers of Alzheimer's disease in obese, otherwise healthy adults.We also found dynamic fluctuations in plasma biomarkers concentration in the fasting state suggesting physiological diurnal variations.Further investigations are highly needed to verify if biomarker measurements should be performed in the fasting state and at a standardized time of day to improve the diagnostic accuracy. [ABSTRACT FROM AUTHOR]

Published
2023
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43. High prevalence of peripheral and carotid artery disease in patients with interstitial lung diseases

Author

Stumpf, Max Jonathan, primary, Fleddermann, Max Fabian, additional, Wirtz, Marina Michaela Luise, additional, Biener, Leonie, additional, Weinhold, Leonie, additional, Schahab, Nadjib, additional, Weber, Marcel, additional, Nickenig, Georg, additional, Skowasch, Dirk, additional, Schaefer, Christian Alexander, additional, and Pizarro, Carmen, additional

Published
2023
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44. Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Author

Davies, Gail, Lam, Max, Harris, Sarah E., Trampush, Joey W., Luciano, Michelle, Hill, W. David, Hagenaars, Saskia P., Ritchie, Stuart J., Marioni, Riccardo E., Fawns-Ritchie, Chloe, Liewald, David C. M., Okely, Judith A., Ahola-Olli, Ari V., Barnes, Catriona L. K., Bertram, Lars, Bis, Joshua C., Burdick, Katherine E., Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E., Hayward, Caroline, Hofer, Edith, Ikram, M. Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A., Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A., Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A., Smith, Albert V., Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J., Ware, Erin B., Windham, B. Gwen, Wright, Margaret J., Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A., Armstrong, Nicola J., Assareh, Amelia A., Attia, John R., Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A., Böhmer, Anne C., Boyle, Patricia A., Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D., Cirulli, Elizabeth T., Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R., Dale, Anders M., Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G., Evangelou, Evangelos, Faul, Jessica D., Ford, Ian, Freimer, Nelson A., Gao, He, Giegling, Ina, Gillespie, Nathan A., Gordon, Scott D., Gottesman, Rebecca F., Griswold, Michael E., Gudnason, Vilmundur, Harris, Tamara B., Hartmann, Annette M., Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G., Joshi, Peter K., Kähönen, Mika, Kardia, Sharon L. R., Karlsson, Ida, Kleineidam, Luca, Knopman, David S., Kochan, Nicole A., Konte, Bettina, Kwok, John B., Le Hellard, Stephanie, Lee, Teresa, Lehtimäki, Terho, Li, Shu-Chen, Lill, Christina M., Liu, Tian, Koini, Marisa, London, Edythe, Longstreth, Jr, Will T., Lopez, Oscar L., Loukola, Anu, Luck, Tobias, Lundervold, Astri J., Lundquist, Anders, Lyytikäinen, Leo-Pekka, Martin, Nicholas G., Montgomery, Grant W., Murray, Alison D., Need, Anna C., Noordam, Raymond, Nyberg, Lars, Ollier, William, Papenberg, Goran, Pattie, Alison, Polasek, Ozren, Poldrack, Russell A., Psaty, Bruce M., Reppermund, Simone, Riedel-Heller, Steffi G., Rose, Richard J., Rotter, Jerome I., Roussos, Panos, Rovio, Suvi P., Saba, Yasaman, Sabb, Fred W., Sachdev, Perminder S., Satizabal, Claudia L., Schmid, Matthias, Scott, Rodney J., Scult, Matthew A., Simino, Jeannette, Slagboom, P. Eline, Smyrnis, Nikolaos, Soumaré, Aïcha, Stefanis, Nikos C., Stott, David J., Straub, Richard E., Sundet, Kjetil, Taylor, Adele M., Taylor, Kent D., Tzoulaki, Ioanna, Tzourio, Christophe, Uitterlinden, André, Vitart, Veronique, Voineskos, Aristotle N., Kaprio, Jaakko, Wagner, Michael, Wagner, Holger, Weinhold, Leonie, Wen, K. Hoyan, Widen, Elisabeth, Yang, Qiong, Zhao, Wei, Adams, Hieab H. H., Arking, Dan E., Bilder, Robert M., Bitsios, Panos, Boerwinkle, Eric, Chiba-Falek, Ornit, Corvin, Aiden, De Jager, Philip L., Debette, Stéphanie, Donohoe, Gary, Elliott, Paul, Fitzpatrick, Annette L., Gill, Michael, Glahn, David C., Hägg, Sara, Hansell, Narelle K., Hariri, Ahmad R., Ikram, M. Kamran, Jukema, J. Wouter, Vuoksimaa, Eero, Keller, Matthew C., Kremen, William S., Launer, Lenore, Lindenberger, Ulman, Palotie, Aarno, Pedersen, Nancy L., Pendleton, Neil, Porteous, David J., Räikkönen, Katri, Raitakari, Olli T., Ramirez, Alfredo, Reinvang, Ivar, Rudan, Igor, Dan Rujescu, Schmidt, Reinhold, Schmidt, Helena, Schofield, Peter W., Schofield, Peter R., Starr, John M., Steen, Vidar M., Trollor, Julian N., Turner, Steven T., Van Duijn, Cornelia M., Villringer, Arno, Weinberger, Daniel R., Weir, David R., Wilson, James F., Malhotra, Anil, McIntosh, Andrew M., Gale, Catharine R., Seshadri, Sudha, Mosley, Jr, Thomas H., Bressler, Jan, Lencz, Todd, and Deary, Ian J.

Published
2019
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46. Low Serum Vitamin D Status Is Associated with Incident Alzheimer’s Dementia in the Oldest Old

Author

Melo van Lent, Debora, primary, Egert, Sarah, additional, Wolfsgruber, Steffen, additional, Kleineidam, Luca, additional, Weinhold, Leonie, additional, Wagner-Thelen, Holger, additional, Stoffel-Wagner, Birgit, additional, Bickel, Horst, additional, Wiese, Birgitt, additional, Weyerer, Siegfried, additional, Pentzek, Michael, additional, Jessen, Frank, additional, Schmid, Matthias, additional, Maier, Wolfgang, additional, Scherer, Martin, additional, Riedel-Heller, Steffi G., additional, Ramirez, Alfredo, additional, and Wagner, Michael, additional

Published
2022
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47. Erratum to ‘Linking EORTC QLQ-C-30 and PedsQL/PEDQOL physical functioning scores in patients with osteosarcoma’ [Eur J Cancer 170 (2022) 209-235]

Author

Budde, Axel, primary, Baust, Katja, additional, Weinhold, Leonie, additional, Bernstein, Mark, additional, Bielack, Stefan, additional, Dhooge, Catharina, additional, Hjorth, Lars, additional, Janeway, Katherine A., additional, Jenney, Meriel, additional, Krailo, Mark D., additional, Marina, Neyssa, additional, Nagarajan, Rajaram, additional, Smeland, Sigbjørn, additional, Sydes, Matthew R., additional, De Vos, Patricia, additional, Whelan, Jeremy, additional, Wiener, Andreas, additional, Calaminus, Gabriele, additional, and Schmid, Matthias, additional

Published
2022
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49. A novel and simple cardiac magnetic resonance score (PE2RT) predicts outcome in takotsubo syndrome.

Author

Isaak, Alexander, Bratz, Johanna, Kravchenko, Dmitrij, Mesropyan, Narine, Eckardt, Irina, Bischoff, Leon M., Weinhold, Leonie, Kuetting, Daniel, Pieper, Claus Christian, Attenberger, Ulrike, Zimmer, Sebastian, and Luetkens, Julian A.

Subjects
HEART failure, CARDIAC magnetic resonance imaging, MAJOR adverse cardiovascular events, HEALTH outcome assessment, PERICARDIAL effusion, KAPLAN-Meier estimator
Abstract

Objectives: To find simple imaging-based features on cardiac magnetic resonance (CMR) that are associated with major adverse cardiovascular events (MACE) in takotsubo syndrome (TTS). Methods: Patients with TTS referred for CMR between 2007 and 2021 were retrospectively evaluated. Besides standard CMR analysis, commonly known complications of TTS based on expert knowledge were assessed and summarised via a newly developed PE2RT score (one point each for pleural effusion, pericardial effusion, right ventricular involvement, and ventricular thrombus). Clinical follow-up data was reviewed up to three years after discharge. The relationship between PE2RT features and the occurrence of MACE (cardiovascular death or new hospitalisation due to acute myocardial injury, arrhythmia, or chronic heart failure) was examined using Cox regression analysis and Kaplan–Meier estimator. Results: Seventy-nine patients (mean age, 68 ± 14 years; 72 women) with TTS were included. CMR was performed in a median of 4 days (IQR, 2–6) after symptom onset. Over a median follow-up of 13.3 months (IQR, 0.4–36.0), MACE occurred in 14/79 (18%) patients: re-hospitalisation due to acute symptoms (9/79, 11%) or chronic heart failure symptoms (4/79, 5%), and cardiac death (1/79, 1%). Patients with MACE had a higher PE2RT score (median [IQR], 2 [2–3] vs 1 [0–1]; p < 0.001). PE2RT score was associated with MACE on Cox regression analysis (hazard ratio per PE2RT feature, 2.44; 95%CI: 1.62–3.68; p < 0.001). Two or more PE2RT complications were strongly associated with the occurrence of MACE (log-rank p < 0.001). Conclusions: The introduced PE2RT complication score might enable an easy-to-assess outcome evaluation of TTS patients by CMR. Key Points: • Complications like pericardial effusion, pleural effusion, right ventricular involvement, and ventricular thrombus (summarised as PE2RT features) are relatively common in takotsubo syndrome. • The proposed PE2RT score (one point per complication) was associated with the occurrence of major adverse cardiac events on follow-up. • Complications easily detected by cardiac magnetic resonance imaging can help clinicians derive long-term prognostic information on patients with takotsubo syndrome. [ABSTRACT FROM AUTHOR]

Published
2023
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50. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Author

Davies, Gail, Lam, Max, Harris, Sarah E., Trampush, Joey W., Luciano, Michelle, Hill, W. David, Hagenaars, Saskia P., Ritchie, Stuart J., Marioni, Riccardo E., Fawns-Ritchie, Chloe, Liewald, David C. M., Okely, Judith A., Ahola-Olli, Ari V., Barnes, Catriona L. K., Bertram, Lars, Bis, Joshua C., Burdick, Katherine E., Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E., Hayward, Caroline, Hofer, Edith, Ikram, M. Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A., Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A., Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A., Smith, Albert V., Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J., Ware, Erin B., Windham, B. Gwen, Wright, Margaret J., Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A., Armstrong, Nicola J., Assareh, Amelia A., Attia, John R., Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A., Böhmer, Anne C., Boyle, Patricia A., Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D., Cirulli, Elizabeth T., Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R., Dale, Anders M., Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G., Evangelou, Evangelos, Faul, Jessica D., Ford, Ian, Freimer, Nelson A., Gao, He, Giegling, Ina, Gillespie, Nathan A., Gordon, Scott D., Gottesman, Rebecca F., Griswold, Michael E., Gudnason, Vilmundur, Harris, Tamara B., Hartmann, Annette M., Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G., Joshi, Peter K., Kähönen, Mika, Kardia, Sharon L. R., Karlsson, Ida, Kleineidam, Luca, Knopman, David S., Kochan, Nicole A., Konte, Bettina, Kwok, John B., Le Hellard, Stephanie, Lee, Teresa, Lehtimäki, Terho, Li, Shu-Chen, Lill, Christina M., Liu, Tian, Koini, Marisa, London, Edythe, Longstreth, Jr, Will T., Lopez, Oscar L., Loukola, Anu, Luck, Tobias, Lundervold, Astri J., Lundquist, Anders, Lyytikäinen, Leo-Pekka, Martin, Nicholas G., Montgomery, Grant W., Murray, Alison D., Need, Anna C., Noordam, Raymond, Nyberg, Lars, Ollier, William, Papenberg, Goran, Pattie, Alison, Polasek, Ozren, Poldrack, Russell A., Psaty, Bruce M., Reppermund, Simone, Riedel-Heller, Steffi G., Rose, Richard J., Rotter, Jerome I., Roussos, Panos, Rovio, Suvi P., Saba, Yasaman, Sabb, Fred W., Sachdev, Perminder S., Satizabal, Claudia L., Schmid, Matthias, Scott, Rodney J., Scult, Matthew A., Simino, Jeannette, Slagboom, P. Eline, Smyrnis, Nikolaos, Soumaré, Aïcha, Stefanis, Nikos C., Stott, David J., Straub, Richard E., Sundet, Kjetil, Taylor, Adele M., Taylor, Kent D., Tzoulaki, Ioanna, Tzourio, Christophe, Uitterlinden, André, Vitart, Veronique, Voineskos, Aristotle N., Kaprio, Jaakko, Wagner, Michael, Wagner, Holger, Weinhold, Leonie, Wen, K. Hoyan, Widen, Elisabeth, Yang, Qiong, Zhao, Wei, Adams, Hieab H. H., Arking, Dan E., Bilder, Robert M., Bitsios, Panos, Boerwinkle, Eric, Chiba-Falek, Ornit, Corvin, Aiden, De Jager, Philip L., Debette, Stéphanie, Donohoe, Gary, Elliott, Paul, Fitzpatrick, Annette L., Gill, Michael, Glahn, David C., Hägg, Sara, Hansell, Narelle K., Hariri, Ahmad R., Ikram, M. Kamran, Jukema, J. Wouter, Vuoksimaa, Eero, Keller, Matthew C., Kremen, William S., Launer, Lenore, Lindenberger, Ulman, Palotie, Aarno, Pedersen, Nancy L., Pendleton, Neil, Porteous, David J., Räikkönen, Katri, Raitakari, Olli T., Ramirez, Alfredo, Reinvang, Ivar, Rudan, Igor, Dan Rujescu, Schmidt, Reinhold, Schmidt, Helena, Schofield, Peter W., Schofield, Peter R., Starr, John M., Steen, Vidar M., Trollor, Julian N., Turner, Steven T., Van Duijn, Cornelia M., Villringer, Arno, Weinberger, Daniel R., Weir, David R., Wilson, James F., Malhotra, Anil, McIntosh, Andrew M., Gale, Catharine R., Seshadri, Sudha, Mosley, Jr, Thomas H., Bressler, Jan, Lencz, Todd, and Deary, Ian J.

Published
2018
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