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Fibromuscular Dysplasia and Spontaneous Cervical Artery Dissection

2025· article· en· W4415966042 on OpenAlexaff
Ahmad Nehme, Liqi Shu, Marion Boulanger, Junpeng Ma, Salter Arms, Daniel Mandel, Christopher R. Leon Guerrero, Esther S.H. Kim, Nils Henninger, Jayachandra Muppa, Mirjam R. Heldner, Kateryna Antonenko, Valentin K. Steinsiepe, Marcel Arnold, Setareh Salehi Omran, Ross Crandall, Evan Lester, Aaron Rothstein, Ossama Khazaal, Malik Ghannam, Mohammad Almajali, Edgar A. Samaniego, Bastien Rioux, Alexandre Y. Poppe, Ana Catarina Fonseca, Michele Romoli, Marialuisa Zedde, David S. Liebeskind, Brian Mac Grory, Wayneho Kam, Sami Al Kasab, Mary Penckofer, Adeel Zubair, Richa Sharma, João Pedro Marto, Balaji Krishnaiah, Cheran Elangovan, Marwa Elnazeir, Farhan Khan, Shadi Yaghi, Emmanuel Touzé, Muhammad Affan, Omair ul haq Lodhi, David Seiffge, Diego López Mena, Antonio Araúz, João André Sousa, João Sargento‐Freitas, Vasco Barata, Paulo Castro‐Chaves, Maria Teresa Brito, Muhib Khan, Dania Mallick, 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, Richard Choi, Jason MacDonald, Reza Bavarsad Shahripour, Xiaofan Guo, Sebastian Sanchez, Fayçal Zine-Eddine, Maria Fortuna Baptista, Diana Cruz, Giovanna De Marco, Marco Longoni, Kim J. Griffin, Lindsey Kuohn, Jennifer Frontera, Jordan Amar, James Giles, Rosario Pascarella, Ilaria Grisendi, Hipólito Nzwalo, Amir Molaie, Annie Cavalier, Mohammad Anadani, Kimberly Kicielinski, Ali Eltatawy, Lina Chervak, Roberto Chulluncuy‐Rivas, Yasmin Aziz, Ekaterina Bakradze, Thanh Lam Tran, Marc Rodrigo‐Gisbert, Manuel Requena, Faddi Saleh Velez, Jorge Ortiz Garcia, Varsha Mudassani, Adam de Havenon, Venugopalan Y. Vishnu, Sridhara Yaddanapudi, L Adams, Abigail Browngoehl, Tamra Ranasinghe, Randy Dunston, Zachary Lynch, James E. Siegler, Mayer Se, Joshua Z. Willey, Yee Kuang Cheng, Vítor Mendes Ferreira, Piers Klein, Thanh N. Nguyen, Syed Daniyal Asad, Zoha Sarwat, Anvesh Balabhadra, Shivam Patel, Thaís Secchi, Sheila Cristina Ouriques Martins, Gabriel Mantovani, Young Dae Kim, Sivani Lingam, Abid Quereshi, Sebastián Fridman, Alonso Alvarado, Farid Khasiyev, Guillermo Linares, Marina Mannino, Valeria Terruso, Sofia Vassilopoulou, Vasilis Tentolouris, Manuel Martínez-Marino, Victor Carrasci Wall, Francisca 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, Alexis N. Simpkins, Mohammad R Ghani, Han Xiao, Narendra Kala, Nahid Mohammadzadeh, Eric Goldstein, Karen L. Furie

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldMedicine
TopicGynecological conditions and treatments
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsFibromuscular dysplasiaCervical ArteryCohortArterial diseaseDysplasiaDissection (medical)Disease

Abstract

fetched live from OpenAlex

Importance: Fibromuscular dysplasia (FMD) is found in 6 to 14% of patients with spontaneous cervical artery dissection (SCEAD) and may be associated with recurrent SCEAD. Objective: To evaluate the correlates of FMD in patients with SCEAD and to determine whether FMD is associated with recurrent SCEAD. Design, Setting, and Participants: This cohort study included patients from the Stroke Prevention in Cervical Artery Dissection (STOP-CAD) retrospective cohort study who presented from January 2015 to December 2022. This multicenter and international cohort included consecutive adult patients presenting at acute care hospitals and diagnosed with SCEAD in 63 sites in 16 countries. Data were analyzed from April to November 2024. Exposure: Fibromuscular dysplasia was defined as either a history of FMD or presence of FMD on cervical or renal artery imaging. Main Outcomes and Measures: Clinical and radiological correlates were compared between patients with and without FMD using logistic regression models. Rates of recurrent SCEAD by 24 months were compared using a Cox proportional hazards model. Results: This study included 3714 patients with SCEAD (median [IQR] age, 47 [38-56] years; 1637 [44.1%] females), of whom 196 (5.3%) had FMD. Patients with FMD were older (aOR per 10 years, 1.28; 95% CI, 1.14-1.43) and more often female (aOR, 2.00; 95% CI, 1.45-2.75). They more often had a history of dissection involving a noncervical artery (aOR, 8.10; 95% CI, 2.64-24.83), a history of SCEAD (aOR, 2.05; 95% CI, 1.07-3.93), a recent upper respiratory tract infection (aOR, 2.40; 95% CI, 1.52-3.78), a cerebral aneurysm (aOR, 2.22; 95% CI, 1.22-4.06), or a history of migraines (aOR, 2.44; 95% CI, 1.75-3.40). On imaging, they were less likely to have a single vertebral artery dissection (aOR, 0.37; 95% CI, 0.25-0.55) or an occlusive dissection (aOR, 0.55; 95% CI, 0.38-0.78). Eighty-one patients experienced a recurrent SCEAD, of which 46 (56.8%) occurred in the first 3 months of follow-up. The 24-month risk of recurrent SCEAD was 7.7% (95% CI, 3.1%-12.2%) and 2.8% (95% CI, 2.1%-3.5%) in patients with and without FMD, respectively (aHR, 2.75; 95% CI, 1.46-5.18; P = .002). Conclusions and relevance: In this cohort study of patients with SCEAD, FMD was associated with distinct correlates and a higher rate of recurrent SCEAD. These findings may help physicians in identifying and counseling patients with FMD and SCEAD.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.282
Teacher spread0.271 · 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 designCase report
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".

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Citations4
Published2025
Admission routes1
Has abstractyes

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