Lower risk of cardiovascular events and death associated with initiation of sodium‐glucose cotransporter‐2 inhibitors versus sulphonylureas: Analysis from the <scp>CVD‐REAL</scp> 2 study
Notice bibliographique
Résumé
Su-Yen Goh has received institutional grants from AstraZeneca, Medtronic and Sanofi. She has participated in advisory boards for Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Novo Nordisk, Medtronic, MSD and Sanofi, and has received honoraria/speaker fees. Mikhail N. Kosiborod has received research grants from AstraZeneca and Boehringer Ingelheim, other research support from AstraZeneca, and has received honoraria from AstraZeneca, Boehringer Ingelheim and Novo Nordisk. He has acted as a consultant or participated on advisory boards for 35Pharma, Alnylam, Amgen, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Cytokinetics, Dexcom, Eli Lilly, Esperion Therapeutics, Janssen, Lexicon, Merck (Diabetes and Cardiovascular), Novo Nordisk, Pharmacosmos, Pfizer, Sanofi, Structure Therapeutics, Vifor Pharma and Youngene Therapeutics. Carolyn S. P. Lam has received research support from Boston Scientific, Bayer, Roche Diagnositics, AstraZeneca, Medtronic and Vifor Pharma, and has served as a consultant or on an Advisory Board/Steering Committee/Executive Committee for Boston Scientific, Bayer, Roche Diagnostics, AstraZeneca, Medtronic, Vifor Pharma, Novartis, Amgen, Merck, Janssen Research & Development LLC, Menarini, Boehringer Ingelheim, Novo Nordisk, Abbott Diagnostics, Corvia, Stealth BioTherapeutics, JanaCare, Biofourmis, Darma, Applied Therapeutics, MyoKardia, WebMD Global LLC, Radcliffe Group Ltd and Corpus. Matthew A. Cavender has received personal fees from AstraZeneca, Merck, Sanofi-Aventis, Chiesi and research support (non-salary) from Abbott Laboratories, AstraZeneca, GlaxoSmithKline, The Medicines Company, Merck and Takeda. Shun Kohsaka has received grants from Bayer Yakuhin and Daiichi Sankyo and consulting fees from Bayer Yakuhin, Bristol-Myers Squibb, and Pfizer. Anna Norhammar has received honoraria for lectures and advisory board meetings for AstraZeneca, Novo Nordisk, Boehringer Ingelheim and Lilly. Kåre I. Birkeland has received grants to his institution from AstraZeneca for this study and has given lectures and consulted for Novo Nordisk, Sanofi, Lilly, Boehringer Ingelheim and Merck Sharp & Dohme. Reinhard W. Holl reports grants to the University Hospital, Ulm, from AstraZeneca. Dídac Mauricio has received honoraria for lectures or consulting from AB-Biotics, Almirall, Amgen, Eli Lilly, Esteve, Ferrer, Janssen, Menarini, Merck Sharp & Dohme, Novo Nordisk and Sanofi. Navdeep Tangri has received consulting fees from Otsuka, Tricida and AstraZeneca. He has received research support from AstraZeneca, including for this work. His research programme is supported by the Canadian Institute for Health Research and Research Manitoba. Jonathan E. Shaw has received honoraria for advisory boards and lectures from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Merck Sharp & Dohme, Mylan, Novartis, Novo Nordisk and Sanofi. Marcus Thuresson is an employee at Statisticon AB, for which AstraZeneca is a client. Peter Fenici is an AstraZeneca employee and holds stock options. Dae Jung Kim has received grant support from Boehringer Ingelheim, LG Chem, Sanofi and AstraZeneca, has been a consultant for AstraZeneca, Novo Nordisk and Sanofi, has received speaker fees from Novo Nordisk, Boehringer Ingelheim, Handok, LG Chem, Novartis Korea, Hanmi, DongWha Pharm, Lilly Korea and AstraZeneca. The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/dom.15092. Data underlying the findings described in this manuscript may be obtained in accordance with AstraZeneca's data sharing policy described at https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure. Data for studies directly listed on Vivli can be requested through Vivli at www.vivli.org. Data for studies not listed on Vivli could be requested through Vivli at https://vivli.org/members/enquiries-about-studies-not-listed-on-the-vivli-platform/. AstraZeneca Vivli member page is also available outlining further details: https://vivli.org/ourmember/astrazeneca/. Data S1.Supporting Information Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».