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Record W4408911067 · doi:10.1161/strokeaha.124.048215

Factors Associated With Stroke Recurrence After Initial Diagnosis of Cervical Artery Dissection

2025· article· en· W4408911067 on OpenAlexaff
Daniel Mandel, Liqi Shu, Christopher Chang, N JACK, Christopher R. Leon Guerrero, Nils Henninger, Jayachandra Muppa, Muhammad Affan, Omair ul haq Lodhi, Mirjam R. Heldner, Kateryna Antonenko, David Seiffge, Marcel Arnold, Setareh Salehi Omran, Ross Crandall, Evan Lester, Diego López-Mena, Antonio Araúz, Ahmad Nehme, Marion Boulanger, Emmanuel Touzé, João André Sousa, João Sargento‐Freitas, Vasco Barata, Paulo Castro‐Chaves, Maria Teresa Brito, Muhib Khan, Dania Mallick, Aaron Rothstein, Ossama Khazaal, Josefin E. Kaufmann, Stefan T. Engelter, Christopher Traenka, Diana Aguiar de Sousa, Mafalda Soares, Sara Rosa, Lily Zhou, Preet Gandhi, Thalia S. Field, Steven Mancini, Issa Metanis, Ronen R. Leker, Kelly Pan, Vishnu Dantu, Karl Baumgartner, Tina Burton, Regina von Rennenberg, Christian H. Nolte, Richard Choi, J Macdonald, Reza Bavarsad Shahripour, Xiaofan Guo, Malik Ghannam, Mohammad Almajali, Edgar A. Samaniego, Sebastian Sanchez, Bastien Rioux, Fayçal Zine-Eddine, Alexandre Y. Poppe, Ana Catarina Fonseca, Maria Fortuna Baptista, Diana Cruz, Michele Romoli, Giovanna De Marco, Marco Longoni, Zafer Keser, Kim J. Griffin, Lindsey Kuohn, Jennifer Frontera, Jordan Amar, James Giles, Marialuisa Zedde, Rosario Pascarella, Ilaria Grisendi, Hipólito Nzwalo, David S. Liebeskind, Amir Molaie, Annie Cavalier, Wayneho Kam, Brian Mac Grory, Sami Al Kasab, Mohammad Anadani, Kimberly Kicielinski, Ali Eltatawy, Lina Chervak, Roberto Chulluncuy Rivas, Yasmin Aziz, Ekaterina Bakradze, Thanh Lam Tran, Marc Rodrigo‐Gisbert, Manuel Requena, Faddi G. Saleh Velez, Jorge Ortiz-Garcia, Varsha Muddasani, Adam de Havenon, Venugopalan Y. Vishnu, Sridhara Yaddanapudi, L Adams, Abigail Browngoehl, Tamra Ranasinghe, Randy Dunston, Zachary Lynch, Mary Penckofer, James E. Siegler, Silvia Mayer, Joshua Z. Willey, Adeel Zubair, Yee Kuang Cheng, Richa Sharma, João Pedro Marto, Vítor Mendes Ferreira, Piers Klein, Thanh N. Nguyen, Syed Daniyal Asad, Zoha Sarwat, Anvesh Balabhadra, Shivam Patel, Thaís Secchi, Sheila Cristina Ouriques Martins, Gabriel Paulo Mantovani, Young Dae Kim, Balaji Krishnaiah, Cheran Elangovan, Sivani Lingam, Abid Qureshi, Sebastián Fridman, Alonso Alvarado‐Bolaños, Farid Khasiyev, Guillermo Linares, Marina Mannino, Valeria Terruso, Sofia Vassilopoulou, Vasileios Tentolouris-Piperas, Manuel Martínez-Marino, Victor Carrasco Wall, Fransisca Indraswari, Sleiman El Jamal, Shilin Liu, Muhammad Alvi, Farman Ali, Mohammed Sarvath, Rami Z. Morsi, Tareq Kass‐Hout, Feina Shi, Jinhua Zhang, Dilraj Sokhi, Jamil Said, Newnex Mongare, Alexis N. Simpkins, R. Ariel Gómez, Mohammad R Ghani, Marwa Elnazeir, Han Xiao, Narendra Kala, Farhan Khan, Christoph Stretz, Nahid Mohammadzadeh, Eric Goldstein, Karen L. Furie, Shadi Yaghi

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsWestern UniversityUniversité de MontréalPrecision Nanosystems (Canada)
Fundersnot available
KeywordsMedicineStroke (engine)Hazard ratioProportional hazards modelCervical ArteryInternal medicineAntithromboticRetrospective cohort studyVertebral artery dissectionSurgeryCardiologyDissection (medical)Confidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Patients presenting with cervical artery dissection (CAD) are at risk for subsequent ischemic events. We aimed to identify characteristics that are associated with increased risk of ischemic stroke after initial presentation of CAD and to evaluate the differential impact of anticoagulant versus antiplatelet therapy in these high-risk individuals. METHODS: This was a preplanned secondary analysis of the STOP-CAD study (Antithrombotic Treatment for Stroke Prevention in Cervical Artery Dissection), a multicenter international retrospective observational study (63 sites from 16 countries in North America, South America, Europe, Asia, and Africa) that included patients with CAD predominantly between January 2015 and June 2022. The primary outcome was subsequent ischemic stroke by day 180 after diagnosis. Clinical and imaging variables were compared between those with versus without subsequent ischemic stroke. Significant factors associated with subsequent stroke risk were identified using stepwise Cox regression. Associations between subsequent ischemic stroke risk and antithrombotic therapy type (anticoagulation versus antiplatelets) among patients with identified risk factors were explored using adjusted Cox regression. RESULTS: In all, 4023 patients (mean age was 47.4 years; 44.5% were women) were included. By day 180, subsequent ischemic stroke occurred in 5.3% of the cohort. In adjusted Cox regression, factors associated with increased risk of subsequent ischemic stroke were prior history of ischemic stroke (adjusted hazard ratio [aHR], 7.31 [95% CI, 1.61–33.13]; P =0.010), presentation within 7 days from first symptoms (aHR, 3.04 [95% CI, 1.04–8.91]; P =0.043), infarct on baseline imaging (aHR, 9.85 [95% CI, 3.65–26.58]; P <0.001), and occlusive dissection (aHR, 2.34 [95% CI, 1.03–5.34]; P =0.043). Only patients with occlusive dissection demonstrated a reduced risk of subsequent ischemic stroke when treated with anticoagulation versus antiplatelets (aHR, 0.36 [95% CI, 0.16–0.80]; P =0.01). CONCLUSIONS: In this post hoc analysis of the STOP-CAD study, several factors associated with subsequent ischemic stroke were identified among patients with CAD. Furthermore, we identified a potential benefit of anticoagulation in patients with CAD with occlusive dissection. These findings require validation by meta-analyses of prior studies to formulate optimal treatment strategies for specific high-risk CAD subgroups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.284
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2025
Admission routes1
Has abstractyes

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