BACKGROUND: Detecting a benefit from closure of patent foramen ovale in patients with cryptogenic stroke is hampered by low rates of stroke recurrence and uncertainty about the causal role of patent foramen ovale in the index event. A method to predict patent foramen ovale-attributable recurrence risk is needed. However, individual databases generally have too few stroke recurrences to support risk modeling. Prior studies of this population have been limited by low statistical power for examining factors related to recurrence. AIMS: The aim of this study was to develop a database to support modeling of patent foramen ovale-attributable recurrence risk by combining extant data sets. METHODS: We identified investigators with extant databases including subjects with cryptogenic stroke investigated for patent foramen ovale, determined the availability and characteristics of data in each database, collaboratively specified the variables to be included in the Risk of Paradoxical Embolism database, harmonized the variables across databases, and collected new primary data when necessary and feasible. RESULTS: The Risk of Paradoxical Embolism database has individual clinical, radiologic, and echocardiographic data from 12 component databases, including subjects with cryptogenic stroke both with (n = 1925) and without (n = 1749) patent foramen ovale. In the patent foramen ovale subjects, a total of 381 outcomes (stroke, transient ischemic attack, death) occurred (median follow-up 2·2 years). While there were substantial variations in data collection between studies, there was sufficient overlap to define a common set of variables suitable for risk modeling. CONCLUSION: While individual studies are inadequate for modeling patent foramen ovale-attributable recurrence risk, collaboration between investigators has yielded a database with sufficient power to identify those patients at highest risk for a patent foramen ovale-related stroke recurrence who may have the greatest potential benefit from patent foramen ovale closure.
BACKGROUND: Detecting a benefit from closure of patent foramen ovale in patients with cryptogenic stroke is hampered by low rates of stroke recurrence and uncertainty about the causal role of patent foramen ovale in the index event. A method to predict patent foramen ovale-attributable recurrence risk is needed. However, individual databases generally have too few stroke recurrences to support risk modeling. Prior studies of this population have been limited by low statistical power for examining factors related to recurrence. AIMS: The aim of this study was to develop a database to support modeling of patent foramen ovale-attributable recurrence risk by combining extant data sets. METHODS: We identified investigators with extant databases including subjects with cryptogenic stroke investigated for patent foramen ovale, determined the availability and characteristics of data in each database, collaboratively specified the variables to be included in the Risk of Paradoxical Embolism database, harmonized the variables across databases, and collected new primary data when necessary and feasible. RESULTS: The Risk of Paradoxical Embolism database has individual clinical, radiologic, and echocardiographic data from 12 component databases, including subjects with cryptogenic stroke both with (n = 1925) and without (n = 1749) patent foramen ovale. In the patent foramen ovale subjects, a total of 381 outcomes (stroke, transient ischemic attack, death) occurred (median follow-up 2·2 years). While there were substantial variations in data collection between studies, there was sufficient overlap to define a common set of variables suitable for risk modeling. CONCLUSION: While individual studies are inadequate for modeling patent foramen ovale-attributable recurrence risk, collaboration between investigators has yielded a database with sufficient power to identify those patients at highest risk for a patent foramen ovale-related stroke recurrence who may have the greatest potential benefit from patent foramen ovale closure.
Authors: M M Steiner; M R Di Tullio; T Rundek; R Gan; X Chen; C Liguori; M Brainin; S Homma; R L Sacco Journal: Stroke Date: 1998-05 Impact factor: 7.914
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Authors: Benjamin S Wessler; David E Thaler; Robin Ruthazer; Christian Weimar; Marco R Di Tullio; Mitchell S V Elkind; Shunichi Homma; Jennifer S Lutz; Jean-Louis Mas; Heinrich P Mattle; Bernhard Meier; Krassen Nedeltchev; Federica Papetti; Emanuele Di Angelantonio; Mark Reisman; Joaquín Serena; David M Kent Journal: Circ Cardiovasc Imaging Date: 2014-05 Impact factor: 7.792
Authors: David E Thaler; Robin Ruthazer; Emanuele Di Angelantonio; Marco R Di Tullio; Jennifer S Donovan; Mitchell S V Elkind; John Griffith; Shunichi Homma; Cheryl Jaigobin; Jean-Louis Mas; Heinrich P Mattle; Patrik Michel; Marie-Luise Mono; Krassen Nedeltchev; Federica Papetti; Joaquín Serena; Christian Weimar; David M Kent Journal: Stroke Date: 2013-01-22 Impact factor: 7.914
Authors: David M Kent; Issa J Dahabreh; Robin Ruthazer; Anthony J Furlan; Christian Weimar; Joaquín Serena; Bernhard Meier; Heinrich P Mattle; Emanuele Di Angelantonio; Maurizio Paciaroni; Herwig Schuchlenz; Shunichi Homma; Jennifer S Lutz; David E Thaler Journal: Eur Heart J Date: 2015-07-03 Impact factor: 29.983
Authors: David E Thaler; Robin Ruthazer; Christian Weimar; Joaquín Serena; Heinrich P Mattle; Krassen Nedeltchev; Marie-Luise Mono; Emanuele Di Angelantonio; Mitchell S V Elkind; Marco R Di Tullio; Shunichi Homma; Patrik Michel; Bernhard Meier; Anthony J Furlan; Jennifer S Lutz; David M Kent Journal: Neurology Date: 2014-10-22 Impact factor: 9.910
Authors: Benjamin S Wessler; David E Thaler; Robin Ruthazer; Christian Weimar; Marco R Di Tullio; Mitchell S V Elkind; Shunichi Homma; Jennifer S Lutz; Jean-Louis Mas; Heinrich P Mattle; Bernhard Meier; Krassen Nedeltchev; Federica Papetti; Emanuele Di Angelantonio; Mark Reisman; Joaquín Serena; David M Kent Journal: Circ Cardiovasc Imaging Date: 2013-11-08 Impact factor: 7.792
Authors: David M Kent; Robin Ruthazer; Christian Weimar; Jean-Louis Mas; Joaquín Serena; Shunichi Homma; Emanuele Di Angelantonio; Marco R Di Tullio; Jennifer S Lutz; Mitchell S V Elkind; John Griffith; Cheryl Jaigobin; Heinrich P Mattle; Patrik Michel; Marie-Louise Mono; Krassen Nedeltchev; Federica Papetti; David E Thaler Journal: Neurology Date: 2013-07-17 Impact factor: 9.910