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15. Free Communications 5: Epidemiology, genetics, outcomes Inflammatory markers and extent and progression of early atherosclerosis: Pooled analysis of individual participant data from 20 prospective studies of the PROG-IMT collaboration: WSC-1521

Author

Willeit, P, Thompson, S G, Agewall, S, Bergström, G, Bickel, H, Catapano, A L, Chien, K L, de Groot, E, Empana, J P, Etgen, T, Franco, O H, Iglseder, B, Johnsen, S H, Kavousi, M, Lind, L, Liu, J, Mathiesen, E B, Norata, G D, Olsen, M H, Papagianni, A, Poppert, H, Price, J F, Sacco, R L, Yanez, D N, Zhao, D, Schminke, U, Bülbül, A, Polak, J F, Sitzer, M, Hofman, A, Grigore, L, Dörr, M, Su, T C, Ducimetière, P, Xie, W, Ronkainen, K, Kiechl, S, Rundek, T, Robertson, C, Fagerberg, B, Bokemark, L, Steinmetz, H, Ikram, M A, Völzke, H, Lin, H J, Plichart, M, Tuomainen, T P, Desvarieux, M, McLachlan, S, Schmidt, C, Kauhanen, J, Willeit, J, Lorenz, M W, and Sander, D

Published
2014

22. Schwindelabklärung im Alter

Author

Gosch, M., primary, Lanza, C., additional, Bonkowsky, V., additional, Koegler, O., additional, Waller, C., additional, and Iglseder, B., additional

Published
2020
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31. Correction: Predictive value for cardiovascular events of common carotid intima media thickness and its rate of change in individuals at high cardiovascular risk - Results from the PROG-IMT collaboration (PLoS One (2018) 13:4 (e0191172) DOI: 10.1371/journal.pone.0191172)

Author

Lorenz M. W., Gao L., Ziegelbauer K., Norata G. D., Empana J. P., Schmidtmann I., Lin H. -J., McLachlan S., Bokemark L., Ronkainen K., Amato M., Schminke U., Srinivasan S. R., Lind L., Okazaki S., Stehouwer C. D. A., Willeit P., Polak J. F., Steinmetz H., Sander D., Poppert H., Desvarieux M., Arfan Ikram M., Johnsen S. H., Staub D., Sirtori C. R., Iglseder B., Beloqui O., Engstrom G., Friera A., Rozza F., Xie W., Parraga G., Grigore L., Plichart M., Blankenberg S., Su T. -C., Schmidt C., Tuomainen T. -P., Veglia F., Volzke H., Nijpels G., Willeit J., Sacco R. L., Franco O. H., Uthoff H., Hedblad B., Suarez C., Izzo R., Zhao D., Wannarong T., Catapano A., Ducimetiere P., Espinola-Klein C., Chien K. -L., Price J. F., Bergstrom G., Kauhanen J., Tremoli E., Dorr M., Berenson G., Kitagawa K., Dekker J. M., Kiechl S., Sitzer M., Bickel H., Rundek T., Hofman A., Mathiesen E. B., Castelnuovo S., Landecho M. F., Rosvall M., Gabriel R., De Luca N., Liu J., Baldassarre D., Kavousi M., De Groot E., Bots M. L., Yanez D. N., Thompson S. G., Lorenz, M. W., Gao, L., Ziegelbauer, K., Norata, G. D., Empana, J. P., Schmidtmann, I., Lin, H. -J., Mclachlan, S., Bokemark, L., Ronkainen, K., Amato, M., Schminke, U., Srinivasan, S. R., Lind, L., Okazaki, S., Stehouwer, C. D. A., Willeit, P., Polak, J. F., Steinmetz, H., Sander, D., Poppert, H., Desvarieux, M., Arfan Ikram, M., Johnsen, S. H., Staub, D., Sirtori, C. R., Iglseder, B., Beloqui, O., Engstrom, G., Friera, A., Rozza, F., Xie, W., Parraga, G., Grigore, L., Plichart, M., Blankenberg, S., Su, T. -C., Schmidt, C., Tuomainen, T. -P., Veglia, F., Volzke, H., Nijpels, G., Willeit, J., Sacco, R. L., Franco, O. H., Uthoff, H., Hedblad, B., Suarez, C., Izzo, R., Zhao, D., Wannarong, T., Catapano, A., Ducimetiere, P., Espinola-Klein, C., Chien, K. -L., Price, J. F., Bergstrom, G., Kauhanen, J., Tremoli, E., Dorr, M., Berenson, G., Kitagawa, K., Dekker, J. M., Kiechl, S., Sitzer, M., Bickel, H., Rundek, T., Hofman, A., Mathiesen, E. B., Castelnuovo, S., Landecho, M. F., Rosvall, M., Gabriel, R., De Luca, N., Liu, J., Baldassarre, D., Kavousi, M., De Groot, E., Bots, M. L., Yanez, D. N., and Thompson, S. G.

Abstract

An affiliation for Moise Desvarieux is missing. In addition to affiliation #22, Moise Desvarieux is affiliated with: METHODS Core, Centre de Recherche Epidémiologie et Statistique Paris Sorbonne Cité (CRESS), Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1153, Paris France.

Published
2018

36. The EURO-FORTA (Fit fOR The Aged) List: International Consensus Validation of a Clinical Tool for Improved Drug Treatment in Older People

Author

Pazan, F., Weiss, C., Wehling, M., Burkhardt, H., Schwarz, S., Wedding, U., Johnell, K., Eriksson, T., Ruths, S., Husebo, B. S., Huupponen, R., Ranhoff, A. H., Onder, G., Incalzi, R. A., Marcucci, M., Cherubini, A., Volpato, S., Ruggiero, C., Mugelli, A., Laville, M., Annweiler, C., Mouchoux, C., Robert, P., Rhalimi, M., Jaurrieta, J. J. S., Manas, L. R., Nunez, J. F. M., Jentoft, A. J. C., Rexach, J. A. S., Agusti, A., Mateos, R., Laporte, A. S. -J., Gladman, J., Crome, P., Hughes, C., O'Mahony, D., Byrne, S., Ekpo, E., Ashton, C., Witham, M. D., Soiza, R. L., Wieczorowska-Tobis, K., Kostka, T., Slawek, J., Klich-Raczka, A., Grodzicki, T., Bien, B., Broncel, M., Mierzejewski, P., Jansen, R. W. M. M., van den Bemt, P. M. L. A., van der Cammen, T. J. M., Bauer, J., Berthold, H. K., Denkinger, M., Dovjak, P., Frohnhofen, H., Fruhwald, T., Gisinger, C., Gogol, M., Gosch, M., Gutzmann, H., Heuser, I., Hull, M., Iglseder, B., Kasper, S., Kwetkat, A., von Renteln-Kruse, W., Schindler, C., Schuler, M., Schulz, R. J., Sommeregger, U., and Zeyfang, A.

Subjects
medicine.medical_specialty, Consensus, Delphi Technique, Acknowledgement, Pharmacology toxicology, Delphi method, MEDLINE, 03 medical and health sciences, Drug treatment, 0302 clinical medicine, Drug Therapy, Geriatric Assessment/methods, Age Factors, Aged, Consensus, Delphi Technique, Drug Therapy/methods, Europe, Geriatric Assessment/methods, Humans, Polypharmacy, Prospective Studies, Reproducibility of Results, medicine, Humans, Pharmacology (medical), Drug Therapy/methods, 030212 general & internal medicine, Prospective Studies, Geriatric Assessment, Aged, Polypharmacy, Geriatrics gerontology, business.industry, Age Factors, Reproducibility of Results, Europe, Family medicine, Geriatrics and Gerontology, Older people, business, 030217 neurology & neurosurgery
Abstract

Drug treatment of older people is still potentially inappropriate in many cases as multimorbidity and related polypharmacy are highly prevalent. To increase the quality of drug treatment in older people, the FORTA (Fit fOR The Aged) List (first version 2012) was developed in a Delphi consensus procedure and updated (FORTA2015) by 21 experts from Germany and Austria. It has been validated in a randomized, controlled, prospective trial demonstrating significant improvement in the quality of drug treatment and clinical endpoints (VALFORTA).Based on these results, Delphi consensus validations (two rounds) of country/region-specific FORTA Lists were conducted in the UK/Ireland, France, Poland, Italy, Spain, the Nordic countries and The Netherlands. An algorithm based on geriatric/pharmacologic expertise, publications and professional position was used to find experts in the field.Forty-seven experts agreed to participate in the Delphi process (return rate of 97.9%). For each country/region, the overall mean consensus coefficient (deviation from the initiator proposal) was 0.9. FORTA Lists from six countries/regions with a minimum of four participating experts (excluding The Netherlands) plus the original FORTA List were collated into the EURO-FORTA List containing 264 items in 26 main indication groups. Two drugs had to be added to the proposed items, as proposed by at least four countries/regions; none had to be removed.This project produced seven new country/region-specific FORTA Lists, as well as the overarching EURO-FORTA List showing a high consensual level based on a broader expert base. EURO-FORTA should help to spread the FORTA approach and improve geriatric pharmacotherapy internationally.

Published
2018

38. Predictive value for cardiovascular events of common carotid intima media thickness and its rate of change in individuals at high cardiovascular risk – Results from the PROG-IMT collaboration

Author

Lorenz, M., Gao, L., Ziegelbauer, K., Norata, Giuseppe, Empana, J., Schmidtmann, I., Lin, H., McLachlan, S., Bokemark, L., Ronkainen, K., Amato, M., Schminke, U., Srinivasan, S., Lind, L., Okazaki, S., Stehouwer, C., Willeit, P., Polak, J., Steinmetz, H., Sander, D., Poppert, H., Desvarieux, M., Arfan Ikram, M., Johnsen, S., Staub, D., Sirtori, C., Iglseder, B., Beloqui, O., Engström, G., Friera, A., Rozza, F., Xie, W., Parraga, G., Grigore, L., Plichart, M., Blankenberg, S., Su, T., Schmidt, C., Tuomainen, T., Veglia, F., Völzke, H., Nijpels, G., Willeit, J., Sacco, R., Franco, O., Uthoff, H., Hedblad, B., Suarez, C., Izzo, R., Zhao, D., Wannarong, T., Catapano, A., Ducimetiere, P., Espinola-Klein, C., Chien, K., Price, J., Bergström, G., Kauhanen, J., Tremoli, E., Dörr, M., Berenson, G., Kitagawa, K., Dekker, J., Kiechl, S., Sitzer, M., Bickel, H., Rundek, T., Hofman, A., Mathiesen, E., Castelnuovo, S., Landecho, M., Rosvall, M., Gabriel, R., de Luca, N., Liu, J., Baldassarre, D., Kavousi, M., de Groot, E., Bots, M., Yanez, D., Thompson, S., Lorenz, M., Gao, L., Ziegelbauer, K., Norata, Giuseppe, Empana, J., Schmidtmann, I., Lin, H., McLachlan, S., Bokemark, L., Ronkainen, K., Amato, M., Schminke, U., Srinivasan, S., Lind, L., Okazaki, S., Stehouwer, C., Willeit, P., Polak, J., Steinmetz, H., Sander, D., Poppert, H., Desvarieux, M., Arfan Ikram, M., Johnsen, S., Staub, D., Sirtori, C., Iglseder, B., Beloqui, O., Engström, G., Friera, A., Rozza, F., Xie, W., Parraga, G., Grigore, L., Plichart, M., Blankenberg, S., Su, T., Schmidt, C., Tuomainen, T., Veglia, F., Völzke, H., Nijpels, G., Willeit, J., Sacco, R., Franco, O., Uthoff, H., Hedblad, B., Suarez, C., Izzo, R., Zhao, D., Wannarong, T., Catapano, A., Ducimetiere, P., Espinola-Klein, C., Chien, K., Price, J., Bergström, G., Kauhanen, J., Tremoli, E., Dörr, M., Berenson, G., Kitagawa, K., Dekker, J., Kiechl, S., Sitzer, M., Bickel, H., Rundek, T., Hofman, A., Mathiesen, E., Castelnuovo, S., Landecho, M., Rosvall, M., Gabriel, R., de Luca, N., Liu, J., Baldassarre, D., Kavousi, M., de Groot, E., Bots, M., Yanez, D., and Thompson, S.

Abstract

Aims: Carotid intima media thickness (CIMT) predicts cardiovascular (CVD) events, but the predictive value of CIMT change is debated. We assessed the relation between CIMT change and events in individuals at high cardiovascular risk. Methods and results: From 31 cohorts with two CIMT scans (total n = 89070) on average 3.6 years apart and clinical follow-up, subcohorts were drawn: (A) individuals with at least 3 cardiovascular risk factors without previous CVD events, (B) individuals with carotid plaques without previous CVD events, and (C) individuals with previous CVD events. Cox regression models were fit to estimate the hazard ratio (HR) of the combined endpoint (myocardial infarction, stroke or vascular death) per standard deviation (SD) of CIMT change, adjusted for CVD risk factors. These HRs were pooled across studies. In groups A, B and C we observed 3483, 2845 and 1165 endpoint events, respectively. Average common CIMT was 0.79mm (SD 0.16mm), and annual common CIMT change was 0.01mm (SD 0.07mm), both in group A. The pooled HR per SD of annual common CIMT change (0.02 to 0.43mm) was 0.99 (95% confidence interval: 0.95–1.02) in group A, 0.98 (0.93–1.04) in group B, and 0.95 (0.89–1.04) in group C. The HR per SD of common CIMT (average of the first and the second CIMT scan, 0.09 to 0.75mm) was 1.15 (1.07–1.23) in group A, 1.13 (1.05–1.22) in group B, and 1.12 (1.05–1.20) in group C. Conclusions: We confirm that common CIMT is associated with future CVD events in individuals at high risk. CIMT change does not relate to future event risk in high-risk individuals.

Published
2018

39. Automatic identification of variables in epidemiological datasets using logic regression

Author

Lorenz, M.W. (Matthias W.), Abdi, N.A. (Negin Ashtiani), Scheckenbach, F. (Frank), Pflug, A. (Anja), Bulbul, A. (Alpaslan), Catapano, A.L. (Alberico), Agewall, S. (Stefan), Ezhov, M. (Marat), Bots, M.L. (Michiel), Kiechl, S. (Stefan), Orth, A. (Andreas), Norata, G.D. (Giuseppe), Empana, J.P. (Jean Philippe), Lin, H.-J. (Hung-Ju), McLachlan, S. (Stela), Bokemark, L. (Lena), Ronkainen, K. (Kimmo), Amato, M. (Mauro), Schminke, U. (Ulf), Srinivasan, S.R. (Sathanur R.), Lind, L. (Lars), Kato, A. (Akihiko), Dimitriadis, C. (Chrystosomos), Przewlocki, T. (Tadeusz), Okazaki, S. (Shuhei), Stehouwer, C.D. (Coen), Lazarevic, T. (Tatjana), Willeit, J. (Johann), Yanez, D.N. (David N.), Steinmetz, H. (helmuth), Sander, D. (Dirk), Poppert, H. (Holger), Desvarieux, M. (Moise), Ikram, M.A. (Arfan), Bevc, S. (Sebastjan), Staub, D. (Daniel), Sirtori, C.R. (Cesare R.), Iglseder, B. (Bernhard), Engström, G., Tripepi, G.L. (Giovanni), Beloqui, O. (Oscar), Lee, M.-S. (Moo-Sik), Friera, A. (Alfonsa), Xie, W. (Wuxiang), Grigore, L. (Liliana), Plichart, M. (Matthieu), Su, T.-C. (Ta-Chen), Robertson, C.M. (Christine M), Schmidt, C. (Caroline), Tuomainen, T.-P. (Tomi-Pekka), Veglia, F. (Fabrizio), Völzke, H. (Henry), Nijpels, M.G.A.A.M. (Giel), Jovanovic, A. (Aleksandar), Sacco, R.L. (Ralph L.), Franco, O.H. (Oscar), Hojs, R. (Radovan), Uthoff, H. (Heiko), Hedblad, B. (Bo), Park, H.W. (Hyun Woong), Suarez, C. (Carmen), Zhao, D. (Dong), Catapano, A. (Alberico), Ducimetiere, P. (P.), Chien, K.-L. (Kuo-Liong), Price, J.F. (Jackie F.), Bergstrom, G. (Goran), Kauhanen, J. (Jussi), Tremoli, E. (Elena), Dörr, M. (Marcus), Berenson, G. (Gerald), Papagianni, A. (Aikaterini), Kablak-Ziembicka, A. (Anna), Kitagawa, K. (Kazuo), Dekker, J.M. (Jacqueline), Stolic, R. (Radojica), Polak, J.F. (Joseph F.), Sitzer, M. (Matthias), Bickel, H. (Horst), Rundek, T. (Tatjana), Hofman, A. (Albert), Ekart, R. (Robert), Frauchiger, B. (Beat), Castelnuovo, S. (Samuela), Rosvall, M. (Maria), Zoccali, C. (Carmine), Landecho, M.F. (Manuel F.), Bae, J.-H. (Jang-Ho), Gabriel, R. (Rafael), Liu, J. (Jing), Baldassarre, D. (Damiano), Kavousi, M. (Maryam), Lorenz, M.W. (Matthias W.), Abdi, N.A. (Negin Ashtiani), Scheckenbach, F. (Frank), Pflug, A. (Anja), Bulbul, A. (Alpaslan), Catapano, A.L. (Alberico), Agewall, S. (Stefan), Ezhov, M. (Marat), Bots, M.L. (Michiel), Kiechl, S. (Stefan), Orth, A. (Andreas), Norata, G.D. (Giuseppe), Empana, J.P. (Jean Philippe), Lin, H.-J. (Hung-Ju), McLachlan, S. (Stela), Bokemark, L. (Lena), Ronkainen, K. (Kimmo), Amato, M. (Mauro), Schminke, U. (Ulf), Srinivasan, S.R. (Sathanur R.), Lind, L. (Lars), Kato, A. (Akihiko), Dimitriadis, C. (Chrystosomos), Przewlocki, T. (Tadeusz), Okazaki, S. (Shuhei), Stehouwer, C.D. (Coen), Lazarevic, T. (Tatjana), Willeit, J. (Johann), Yanez, D.N. (David N.), Steinmetz, H. (helmuth), Sander, D. (Dirk), Poppert, H. (Holger), Desvarieux, M. (Moise), Ikram, M.A. (Arfan), Bevc, S. (Sebastjan), Staub, D. (Daniel), Sirtori, C.R. (Cesare R.), Iglseder, B. (Bernhard), Engström, G., Tripepi, G.L. (Giovanni), Beloqui, O. (Oscar), Lee, M.-S. (Moo-Sik), Friera, A. (Alfonsa), Xie, W. (Wuxiang), Grigore, L. (Liliana), Plichart, M. (Matthieu), Su, T.-C. (Ta-Chen), Robertson, C.M. (Christine M), Schmidt, C. (Caroline), Tuomainen, T.-P. (Tomi-Pekka), Veglia, F. (Fabrizio), Völzke, H. (Henry), Nijpels, M.G.A.A.M. (Giel), Jovanovic, A. (Aleksandar), Sacco, R.L. (Ralph L.), Franco, O.H. (Oscar), Hojs, R. (Radovan), Uthoff, H. (Heiko), Hedblad, B. (Bo), Park, H.W. (Hyun Woong), Suarez, C. (Carmen), Zhao, D. (Dong), Catapano, A. (Alberico), Ducimetiere, P. (P.), Chien, K.-L. (Kuo-Liong), Price, J.F. (Jackie F.), Bergstrom, G. (Goran), Kauhanen, J. (Jussi), Tremoli, E. (Elena), Dörr, M. (Marcus), Berenson, G. (Gerald), Papagianni, A. (Aikaterini), Kablak-Ziembicka, A. (Anna), Kitagawa, K. (Kazuo), Dekker, J.M. (Jacqueline), Stolic, R. (Radojica), Polak, J.F. (Joseph F.), Sitzer, M. (Matthias), Bickel, H. (Horst), Rundek, T. (Tatjana), Hofman, A. (Albert), Ekart, R. (Robert), Frauchiger, B. (Beat), Castelnuovo, S. (Samuela), Rosvall, M. (Maria), Zoccali, C. (Carmine), Landecho, M.F. (Manuel F.), Bae, J.-H. (Jang-Ho), Gabriel, R. (Rafael), Liu, J. (Jing), Baldassarre, D. (Damiano), and Kavousi, M. (Maryam)

Abstract

Background: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.

Published
2017
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40. Automatic identification of variables in epidemiological datasets using logic regression

Author

Lorenz, M., Abdi, N., Scheckenbach, F., Pflug, A., Bülbül, A., Catapano, A., Agewall, S., Ezhov, M., Bots, M., Kiechl, S., Orth, A., Norata, Giuseppe, Empana, J., Lin, H., McLachlan, S., Bokemark, L., Ronkainen, K., Amato, M., Schminke, U., Srinivasan, S., Lind, L., Kato, A., Dimitriadis, C., Przewlocki, T., Okazaki, S., Stehouwer, C., Lazarevic, T., Willeit, P., Yanez, D., Steinmetz, H., Sander, D., Poppert, H., Desvarieux, M., Ikram, M., Bevc, S., Staub, D., Sirtori, C., Iglseder, B., Engström, G., Tripepi, G., Beloqui, O., Lee, M., Friera, A., Xie, W., Grigore, L., Plichart, M., Su, T., Robertson, C., Schmidt, C., Tuomainen, T., Veglia, F., Völzke, H., Nijpels, G., Jovanovic, A., Willeit, J., Sacco, R., Franco, O., Hojs, R., Uthoff, H., Hedblad, B., Park, H., Suarez, C., Zhao, D., Ducimetiere, P., Chien, K., Price, J., Bergström, G., Kauhanen, J., Tremoli, E., Dörr, M., Berenson, G., Papagianni, A., Kablak-Ziembicka, A., Kitagawa, K., Dekker, J., Stolic, R., Polak, J., Sitzer, M., Bickel, H., Rundek, T., Hofman, A., Ekart, R., Frauchiger, B., Castelnuovo, S., Rosvall, M., Zoccali, C., Landecho, M., Bae, J., Gabriel, R., Liu, J., Baldassarre, D., Kavousi, M., Lorenz, M., Abdi, N., Scheckenbach, F., Pflug, A., Bülbül, A., Catapano, A., Agewall, S., Ezhov, M., Bots, M., Kiechl, S., Orth, A., Norata, Giuseppe, Empana, J., Lin, H., McLachlan, S., Bokemark, L., Ronkainen, K., Amato, M., Schminke, U., Srinivasan, S., Lind, L., Kato, A., Dimitriadis, C., Przewlocki, T., Okazaki, S., Stehouwer, C., Lazarevic, T., Willeit, P., Yanez, D., Steinmetz, H., Sander, D., Poppert, H., Desvarieux, M., Ikram, M., Bevc, S., Staub, D., Sirtori, C., Iglseder, B., Engström, G., Tripepi, G., Beloqui, O., Lee, M., Friera, A., Xie, W., Grigore, L., Plichart, M., Su, T., Robertson, C., Schmidt, C., Tuomainen, T., Veglia, F., Völzke, H., Nijpels, G., Jovanovic, A., Willeit, J., Sacco, R., Franco, O., Hojs, R., Uthoff, H., Hedblad, B., Park, H., Suarez, C., Zhao, D., Ducimetiere, P., Chien, K., Price, J., Bergström, G., Kauhanen, J., Tremoli, E., Dörr, M., Berenson, G., Papagianni, A., Kablak-Ziembicka, A., Kitagawa, K., Dekker, J., Stolic, R., Polak, J., Sitzer, M., Bickel, H., Rundek, T., Hofman, A., Ekart, R., Frauchiger, B., Castelnuovo, S., Rosvall, M., Zoccali, C., Landecho, M., Bae, J., Gabriel, R., Liu, J., Baldassarre, D., and Kavousi, M.

Abstract

Background: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.

Published
2017

41. Research update for articles published in EJCI in 2008

Author

Anderwald, C., Ankersmit, H. J., Badaoui, A., Beneduce, L., Buko, V. U., Calo, L. A., Carrero, J. J., Chang, C. Y., Chang, K. C., Chen, Y. J., Cnotliwy, M., Costelli, Paola, Crujeiras, A. B., Cuocolo, A., Davis, P. A., de Boer, O. J., Ebenbichler, C. F., Erridge, C., Fassina, G., Felix, S. B., García Gómez, M. C., Guerrero Romero, F., Haider, D. G., Heinemann, A., Herda, L. R., Hoogeveen, E. K., Hörl, W. H., Iglseder, B., Huang, K. C., Kaser, S., Kastrati, A., Kuzniatsova, N., Latella, G., Lichtenauer, M., Lin, Y. K., Lip, G. Y., N. H., Lu, Lukivskaya, O., Luschnig, P., Maniscalco, M., Martinez, J. A., Müller Krebs, S., Ndrepepa, G., Nicolaou, G., Peck Radosavljevic, M., Penna, Fabio, Pintó, X., Reiberger, T., Rodriguez Moran, M., Schmidt, A., Schwenger, V., Spinelli, L., Starkel, P., Stehouwer, C. D., Stenvinkel, P., Strasser, P., Suzuki, H., Tschoner, A., van der Wal, A. C., Vesely, D. L., Wen, C. J., Wiernicki, I., Zanninelli, G., Zhu, Y., Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), RS: CARIM School for Cardiovascular Diseases, Anderwald, C, Ankersmit, Hj, Badaoui, A, Beneduce, L, Buko, Vu, Calo, La, Carrero, Jj, Chang, C, Chang, K, Chen, Y, Cnotliwy, M, Costelli, P, Crujeiras, Ab, Cuocolo, Alberto, Davis, Pa, De Boer, Oj, Ebenbichler, Cf, Erridge, C, Fassina, G, Felix, Sb, García Gómez, Mc, Guerrero Romero, F, Haider, Dg, Heinemann, A, Herda, Lr, Hoogeveen, Ek, Hörl, Wh, Iglseder, B, Huang, K, Kaser, S, Kastrati, A, Kuzniatsova, N, Latella, G, Lichtenauer, M, Lin, Y, Lip, Gyh, Lu, N, Lukivskaya, O, Luschnig, P, Maniscalco, M, Martinez, Ja, Müller Krebs, S, Ndrepepa, G, Nicolaou, G, Peck Radosavljevic, M, Penna, F, Pintó, X, Reiberger, T, Rodriguez Moran, M, Schmidt, A, Schwenger, V, Spinelli, Letizia, Starkel, P, Stehouwer, Cda, Stenvinkel, P, Strasser, P, Suzuki, H, Tschoner, A, Van Der Wal, Ac, Vesely, Dl, Wen, C, Wiernicki, I, Zanninelli, G, and Zhu, Y.

Abstract

Eur J Clin Invest 2010; 40 (9): 770-789.

Published
2010

42. Normative values for carotid intima media thickness and its progression: Are they transferrable outside of their cohort of origin?

Author

Liao, X., Norata, Giuseppe, Polak, J., Stehouwer, C., Catapano, A., Rundek, T., Ezhov, M., Sander, D., Thompson, S., Lorenz, M., Balakhonova, T., Safarova, M., Grigore, L., Empana, J., Lin, H., McLachlan, S., Bokemark, L., Ronkainen, K., Schminke, U., Lind, L., Willeit, P., Yanez, D., Steinmetz, H., Poppert, H., Desvarieux, M., Ikram, M., Johnsen, S., Iglseder, B., Friera, A., Xie, W., Plichart, M., Su, T., Srinivasan, S., Schmidt, C., Tuomainen, T., Völzke, H., Nijpels, G., Willeit, J., Franco, O., Suarez, C., Zhao, D., Ducimetiere, P., Chien, K., Robertson, C., Bergström, G., Kauhanen, J., Dörr, M., Dekker, J., Kiechl, S., Sitzer, M., Bickel, H., Sacco, R., Hofman, A., Mathiesen, E., Gabriel, R., Liu, J., Berenson, G., Kavousi, M., Price, J., Liao, X., Norata, Giuseppe, Polak, J., Stehouwer, C., Catapano, A., Rundek, T., Ezhov, M., Sander, D., Thompson, S., Lorenz, M., Balakhonova, T., Safarova, M., Grigore, L., Empana, J., Lin, H., McLachlan, S., Bokemark, L., Ronkainen, K., Schminke, U., Lind, L., Willeit, P., Yanez, D., Steinmetz, H., Poppert, H., Desvarieux, M., Ikram, M., Johnsen, S., Iglseder, B., Friera, A., Xie, W., Plichart, M., Su, T., Srinivasan, S., Schmidt, C., Tuomainen, T., Völzke, H., Nijpels, G., Willeit, J., Franco, O., Suarez, C., Zhao, D., Ducimetiere, P., Chien, K., Robertson, C., Bergström, G., Kauhanen, J., Dörr, M., Dekker, J., Kiechl, S., Sitzer, M., Bickel, H., Sacco, R., Hofman, A., Mathiesen, E., Gabriel, R., Liu, J., Berenson, G., Kavousi, M., and Price, J.

Abstract

© 2016 European Society of Cardiology. Background The clinical use of carotid intima media thickness (cIMT) requires normal values, which may be subject to variation of geographical factors, ethnicity or measurement details. The influence of these factors has rarely been studied. The aim of this study was to determine whether normative cIMT values and their association with event risk are generalizable across populations. Design Meta-analysis of individual participant data. Method From 22 general population cohorts from Europe, North America and Asia we selected subjects free of cardiovascular disease. Percentiles of cIMT and cIMT progression were assessed separately for every cohort. Cox proportional hazards models for vascular events were used to estimate hazard ratios for cIMT in each cohort. The estimates were pooled across Europe, North America and Asia, with random effects meta-analysis. The influence of geography, ethnicity and ultrasound protocols on cIMT values and on the hazard ratios was examined by meta-regression. Results Geographical factors, ethnicity and the ultrasound protocol had influence neither on the percentiles of cIMT and its progression, nor on the hazard ratios of cIMT for vascular events. Heterogeneity for percentiles of cIMT and cIMT progression was too large to create meaningful normative values. Conclusions The distribution of cIMT values is too heterogeneous to define universal or regional population reference values. CIMT values vary widely between different studies regardless of ethnicity, geographic location and ultrasound protocol. Prediction of vascular events with cIMT values was more consistent across all cohorts, ethnicities and regions.

Published
2016

43. Inflammatory markers and extent and progression of early atherosclerosis: Meta-analysis of individual-participant-data from 20 prospective studies of the PROG-IMT collaboration

Author

Willeit, P., Thompson, S., Agewall, S., Bergström, G., Bickel, H., Catapano, A., Chien, K., De Groot, E., Empana, J., Etgen, T., Franco, O., Iglseder, B., Johnsen, S., Kavousi, M., Lind, L., Liu, J., Mathiesen, E., Norata, Giuseppe, Olsen, M., Papagianni, A., Poppert, H., Price, J., Sacco, R., Yanez, D., Zhao, D., Schminke, U., Bülbül, A., Polak, J., Sitzer, M., Hofman, A., Grigore, L., Dörr, M., Su, T., Ducimetière, P., Xie, W., Ronkainen, K., Kiechl, S., Rundek, T., Robertson, C., Fagerberg, B., Bokemark, L., Steinmetz, H., Ikram, M., Völzke, H., Lin, H., Plichart, M., Tuomainen, T., Desvarieux, M., McLachlan, S., Schmidt, C., Kauhanen, J., Willeit, J., Lorenz, M., Sander, D., Willeit, P., Thompson, S., Agewall, S., Bergström, G., Bickel, H., Catapano, A., Chien, K., De Groot, E., Empana, J., Etgen, T., Franco, O., Iglseder, B., Johnsen, S., Kavousi, M., Lind, L., Liu, J., Mathiesen, E., Norata, Giuseppe, Olsen, M., Papagianni, A., Poppert, H., Price, J., Sacco, R., Yanez, D., Zhao, D., Schminke, U., Bülbül, A., Polak, J., Sitzer, M., Hofman, A., Grigore, L., Dörr, M., Su, T., Ducimetière, P., Xie, W., Ronkainen, K., Kiechl, S., Rundek, T., Robertson, C., Fagerberg, B., Bokemark, L., Steinmetz, H., Ikram, M., Völzke, H., Lin, H., Plichart, M., Tuomainen, T., Desvarieux, M., McLachlan, S., Schmidt, C., Kauhanen, J., Willeit, J., Lorenz, M., and Sander, D.

Abstract

© 2014 European Society of Cardiology. Background Large-scale epidemiological evidence on the role of inflammation in early atherosclerosis, assessed by carotid ultrasound, is lacking. We aimed to quantify cross-sectional and longitudinal associations of inflammatory markers with common-carotid-artery intima-media thickness (CCA-IMT) in the general population. Methods Information on high-sensitivity C-reactive protein, fibrinogen, leucocyte count and CCA-IMT was available in 20 prospective cohort studies of the PROG-IMT collaboration involving 49,097 participants free of pre-existing cardiovascular disease. Estimates of associations were calculated within each study and then combined using random-effects meta-analyses. Results Mean baseline CCA-IMT amounted to 0.74 mm (SD = 0.18) and mean CCA-IMT progression over a mean of 3.9 years to 0.011 mm/year (SD = 0.039). Cross-sectional analyses showed positive linear associations between inflammatory markers and baseline CCA-IMT. After adjustment for traditional cardiovascular risk factors, mean differences in baseline CCA-IMT per one-SD higher inflammatory marker were: 0.0082 mm for high-sensitivity C-reactive protein (p < 0.001); 0.0072 mm for fibrinogen (p < 0.001); and 0.0025 mm for leucocyte count (p = 0.033). 'Inflammatory load', defined as the number of elevated inflammatory markers (i.e. in upper two quintiles), showed a positive linear association with baseline CCA-IMT (p < 0.001). Longitudinal associations of baseline inflammatory markers and changes therein with CCA-IMT progression were null or at most weak. Participants with the highest 'inflammatory load' had a greater CCA-IMT progression (p = 0.015). Conclusion Inflammation was independently associated with CCA-IMT cross-sectionally. The lack of clear associations with CCA-IMT progression may be explained by imprecision in its assessment within a limited time period. Our findings for 'inflammatory load' suggest important combined effects of the three

Published
2016

49. Delir

Author

Frühwald, T., primary, Weissenberger-Leduc, M., additional, Jagsch, C., additional, Singler, K., additional, Gurlit, S., additional, Hofmann, W., additional, Böhmdorfer, B., additional, and Iglseder, B., additional

Published
2015
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50. Inflammatory markers and extent and progression of early atherosclerosis : Pooled analysis of individual participant data from 20 prospective studies of the PROG-IMT collaboration

Author

Willeit, P., Thompson, S. G., Agewall, S., Bergstrom, G., Bickel, H., Catapano, A. L., Chien, K. L., de Groot, E., Empana, J. P., Etgen, T., Franco, O. H., Iglseder, B., Johnsen, S. H., Kavousi, M., Lind, Lars, Liu, J., Mathiesen, E. B., Norata, G. D., Olsen, M. H., Papagianni, A., Poppert, H., Price, J. F., Sacco, R. L., Yanez, D. N., Zhao, D., Schminke, U., Buelbuel, A., Polak, J. F., Sitzer, M., Hofman, A., Grigore, L., Doerr, M., Su, T. C., Ducimetiere, P., Xie, W., Ronkainen, K., Kiechl, S., Rundek, T., Robertson, C., Fagerberg, B., Bokemark, L., Steinmetz, H., Ikram, M. A., Voelzke, H., Lin, H. J., Plichart, M., Tuomainen, T. P., Desvarieux, M., McLachlan, S., Schmidt, C., Kauhanen, J., Willeit, J., Lorenz, M. W., Sander, D., Willeit, P., Thompson, S. G., Agewall, S., Bergstrom, G., Bickel, H., Catapano, A. L., Chien, K. L., de Groot, E., Empana, J. P., Etgen, T., Franco, O. H., Iglseder, B., Johnsen, S. H., Kavousi, M., Lind, Lars, Liu, J., Mathiesen, E. B., Norata, G. D., Olsen, M. H., Papagianni, A., Poppert, H., Price, J. F., Sacco, R. L., Yanez, D. N., Zhao, D., Schminke, U., Buelbuel, A., Polak, J. F., Sitzer, M., Hofman, A., Grigore, L., Doerr, M., Su, T. C., Ducimetiere, P., Xie, W., Ronkainen, K., Kiechl, S., Rundek, T., Robertson, C., Fagerberg, B., Bokemark, L., Steinmetz, H., Ikram, M. A., Voelzke, H., Lin, H. J., Plichart, M., Tuomainen, T. P., Desvarieux, M., McLachlan, S., Schmidt, C., Kauhanen, J., Willeit, J., Lorenz, M. W., and Sander, D.

Published
2014

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