Citations

The purpose of this study was to examine the validity of a Garmin device for estimating heart rate, energy expenditure, and step count during incremental treadmill exercise. Eighteen physically active males (n = 12; mean ± SD age = 22.8 ± 4.7 years; body mass = 83.8 ± 13.4 kg) and females (n = 6; 24.2 ± 5.6 years; 65.2 ± 9.6 kg) completed an incremental treadmill test with the Garmin Vivoactive 4 and criterion methods measuring heart rate, energy expenditure, and step count. Mean absolute percent error (MAPE) and Bland–Altman plots were used to assess accuracy. Acceptable accuracy was defined as MAPE < 5% for heart rate and <10% for energy expenditure and step count. MAPE (±SD) values were 13.0 (±10.1), 19.1 (±15.0), and 4.6 (±5.3)% for heart rate, energy expenditure, and step count, respectively. The Bland–Altman regression analyses illustrated proportional bias was present for heart rate (r = 0.591, p < 0.001) and step count (r = 0.516, p = 0.028), but not energy expenditure (r = 0.351, p = 0.153). These findings indicated that the Garmin Vivoactive 4 provided acceptable accuracy for step count but unacceptable accuracy for heart rate and energy expenditure during incremental treadmill exercise.

Abstract Background Computed tomography (CT) is an essential imaging modality for disease diagnosis, treatment efficacy, and image‐based guidance of various medical procedures. The locally deposited radiation dose in tissues, as estimated by the computed tomography dose index (CTDI), can vary considerably across exposures delivered by CT scanners from different vendors, even if the scans are performed using similar technique factors, such as tube potential and tube current. The volumetric CTDI (CTDI vol ) is a common dose metric that reports an average radiation dose (in mGy) delivered to a specific volume within a test phantom. The CTDI vol is important in dosimetry applications as the organ absorbed dose within the patient has been shown to scale in near‐linear proportion, creating a basis for comparing organ doses across different scan protocols and scanner models. Purpose To develop a database of tube current‐time product (mAs) normalized CTDI vol values for currently utilized CT scanner models for each of the four primary CT vendors for use in the MIRDct organ dosimetry software available at MIRDsoft.org. This data forms the basis of the MIRDct code, which reports organ doses across a range of computational phantoms based upon axial organ dose coefficient libraries generated through Monte Carlo radiation transport for a reference CT scanner. Organ doses delivered by alternate CT scanner vendors and models may then be reported using ratios of normalized CTDI vol values under similar technique factors. Methods Scanners were selected from four major CT manufacturers: Philips Healthcare, GE Healthcare, Canon Medical Systems, and Siemens Healthineers. Technique parameters were also selected for each scanner that closely matched values used in the generation of an equivalent CT source term (small to large bowtie filters; 80–140‐kVp tube voltage; and 10‐mm to 40‐mm beam collimation). For each scanner chosen, the appropriate technique factors and protocols were selected, and the console‐reported CTDI vol values were recorded and normalized to a set value of 100 mAs. The normalized CTDI vol data collected for use within the MIRDct code were analyzed for noticeable patterns, features, and trends, and were compared to similar normalized CTDI vol datasets used within the National Cancer Institute NCICT software and the Virtual Phantoms, Inc. VirtualDose software. Results For all given CT scanner and technique factor combinations, there was strong agreement in normalized CTDI vol values across all three codes: between 0% and 12% difference for the compared scanners. Ratios of CTDI vol values for various CT scanner vendors and models to the corresponding CTDI vol values for the MIRDct reference scanner (Cannon Aquilion One Genesis) were also compared on the basis of either the 16‐cm head PMMA phantom or the 32‐cm body PMMA phantom. The mean quotient of these normalized CTDI vol ratios (head ratios to body ratios) was found to be approximately 1.06, and thus either ratio may be applied in reporting patient organ dose by MIRDct. Conclusions A database of normalized CTDI vol (mGy/100 mAs) was created for 17 models of CT scanners from four manufacturers at varying tube potentials, collimations, x‐ray bowtie filters, and phantom sizes for use in the MIRDct software.

PURPOSE There is growing scientific interest in incorporating patient-reported outcomes (PROs) in early phase dose-finding oncology trials (DFOTs) to assess tolerability, inform dose selection, and guide later stage trial design. However, research indicates that PRO objectives in DFOTs are often unclear. The Incorporating Patient-Reported Outcomes in Dose-Finding Trials-Research Objectives Recommendations (OPTIMISE-ROR) project was established to support trialists to effectively incorporate PROs into DFOTs. METHODS Using the Enhancing Quality and Transparency of Health Research (EQUATOR) Network's methodological framework, guideline development included the following: (1) a methodological review of published DFOTs incorporating PROs; (2) candidate item generation, refined through expert consultation; (3) a two-round international multistakeholder Delphi survey (N = 109 in Round 1 [October 2024]; N = 96 in Round 2 [December 2024]); and (4) an independently chaired virtual consensus meeting (N = 31; January 2025) where multidisciplinary, international experts reviewed and voted to finalize items for inclusion. RESULTS Consensus was reached on six recommendations emphasizing three core PRO tolerability concepts: overall side effect impact, symptomatic adverse events, and overall health-related quality of life. The integration of PROs to inform final dose recommendations in dose escalation and optimization trials should be considered, regardless of trial design. The recommendations highlight the importance of PRO data analysis over time and across dose levels, defining PRO research objectives as descriptive or statistically powered, and assessing PRO-related end points to guide end point selection for subsequent studies. CONCLUSION This foundational guidance outlines key PRO research objectives in DFOTs. By facilitating the systematic integration of PROs, this guidance supports the utilization of patient-centered evidence for the tolerability and efficacy assessment of therapies to inform dose escalation, optimization, and regulatory evaluation—ultimately contributing to the development of safer, more effective therapies.

Abstract Aims Left ventricular hypertrophy (LVH) is a strong predictor of cardiovascular disease. We previously compared supervised machine learning techniques to classify cardiac magnetic resonance (CMR)-derived LVH using electrocardiogram (ECG) and clinical variables in 37 534 UK Biobank participants, obtaining an area under the receiving operating curve (AUROC) of 0.85, but with limited specificity and requiring external validation. In this study, we develop a deep learning (DL) model to improve classification with external evaluation in the Study of Health in Pomerania (SHIP). Methods and results We analysed 12-lead ECGs of 48 835 participants from the UK Biobank imaging study. The dataset was split into a training set (70%), validation set (15%), and test set (15%) for performance evaluation. The model architecture was a fully convolutional network, for which the input was the participants’ median ECG and clinical variables and the predicted indexed left ventricular mass (iLVM) as the output. A subsequent logistic regression model was used to recalibrate iLVM predictions. In UK Biobank, 717 (1.5%) participants had CMR-derived LVH and the AUROC for the DL model was 0.97. The ECG components most predictive of LVH were the QRS complex and ventricular rate. The DL model outperformed our supervised algorithms, previous DL modelling efforts and clinical ECG benchmarks. There was modest generalizability of the DL model to 1423 participants in SHIP (AUROC 0.78), with differences in clinical profile, ECG acquisition, and CMR labelling as important factors. Conclusion Our findings support the feasibility of scalable DL-based screening tools for the prediction of LVH from the ECG, whilst highlighting the need for model development using larger datasets with greater diversity to ensure generalizability.

Abstract Background Inflammatory bowel disease (IBD) is associated with increased risk of major adverse cardiovascular events (MACE), likely driven by systemic inflammation. Treating inflammation may reduce this risk. We aimed to investigate MACE across different therapies in patients with IBD. Methods We used Swedish nationwide registers (2007–2023) to describe MACE rates (ischemic heart disease, stroke, heart failure, and cardiovascular mortality) in patients with IBD receiving different therapies. For contextualization, we compared MACE rates during therapy exposure periods in patients with IBD with matched (by age, sex, and residence) general population comparators without IBD. Comparisons included exposure periods naïve to immunomodulators/advanced therapies and periods of different treatments (immunomodulators, TNF-α inhibitors (TNFi), vedolizumab, ustekinumab, and Janus kinase inhibitors). Each patient could contribute with multiple periods, with a new period starting upon switch of therapy. Incidence rates (IRs) and adjusted hazard ratios (aHRs) were estimated by using Cox regression (Model 1: conditioned on matching variables; Model 2: additional adjustment for Charlson Comorbidity Index). Among patients with IBD, we performed 1:1 propensity score (PS)-matched analysis, with exposure periods of TNFi or vedolizumab as the reference, to compare MACE rates between advanced therapies. In these comparisons, we adjusted for demographics, disease characteristics, healthcare utilization, prior treatment, and cardiovascular risk factors. Results We included 106,894 patients with IBD with 99,661 exposure periods naïve to immunomodulators/advanced therapy, 60,573 exposure periods of immunomodulators, and 71,551 of advanced therapies. Distribution of age, sex and disease duration differed substantially across therapy exposures (data not shown). Compared with the general population, MACE rates in patients with IBD were similar across therapies (IRs=3.0-13.0/1,000 person-years; aHRs=1.02-1.49) (Table 1), and significantly increased only for exposure periods naïve to immunomodulators/advanced therapy, immunomodulators, or ustekinumab. In PS-matched comparisons, no significant differences were found between periods of TNFi, vedolizumab and other advanced therapies (Table 2). Conclusion Therapy exposure periods in patients with IBD showed only slightly increased MACE rates compared to corresponding periods in the general population, and significantly so only for periods naïve to immunomodulators/advanced therapy and exposure to immunomodulators or ustekinumab. In PS-matched analyses of patients with IBD, no significant differences in MACE rates were observed when comparing exposure periods of different advanced therapies. Conflict of interest: Eriksson, Carl: Served as speaker/advisory board member for Janssen Cilag AB and Tillotts Pharma. Forss, Anders: Served as speaker/advisory board member for Janssen Cilag AB and Tillotts Pharma. Singh, Siddharth: Dr. Singh has research grants from Pfizer. Halfvarson, Jonas: Grant support: Swedish Foundation for Strategic Research (RB13-0160 to J.H.), the Swedish Research Council (2020-02021 to J.H.), the Örebro University Hospital research foundation (OLL-890291 to J.H.), NordForsk (90569 to J.H.) and Vinnova ( 2019-01185 to JH and 2024-01155 co-applicant), IHI, EU, INTERCEPT (Grant agreement number 101194780, co-applicant), miGut-Health, HORIZON-HLTH-2022, EU (Grant Agreement 101095470, Co-applicant), 3TR, IMI 2, EU, (Grant agreement number 831434, Co-applicant), Janssen, MSD, and Takeda. Consulting and/or advisory board fees from: AbbVie, Alfasigma, Aqilion, Bristol Myers Squibb, Celgene, Celltrion, Eli Lilly, Ferring, Galapagos, Gilead Sciences, Hospira, Index Pharmaceuticals, Janssen, Johnson &amp Johnson, MEDA, Medivir, Medtronic, Merck, Merck Sharp &amp Dohme, Novartis, Pfizer, Prometheus Laboratories Inc., Sandoz, Shire, STADA, Takeda, Thermo Fisher Scientific, Tillotts Pharma, Vifor Pharma, UCB and speaker’s fees from: AbbVie, Alfasigma, Bristol Myers Squibb, Celgene, Eli Lilly, Ferring, Galapagos, Gilead, Hospira, Janssen, Johnson &amp Johnson, Merck Sharp &amp Dohme, Novartis, Pfizer, Shire, Takeda, Thermo Fisher Scientific, Tillotts Pharma and research grant support from Janssen, Merck Sharp &amp Dohme and Takeda. Sun, Jiangwei: No conflicts Söderling, Jonas: Dr. Söderling has worked on projects at Karolinska Institutet and SWIBREG partly financed by grants from Ferring and Janssen. Everhov, Åsa H: Dr Everhov has worked on projects at Karolinska Institutet and SWIBREG, partly financed by grants from Ferring and Janssen. Bröms, Gabriella: Dr. Bröms has served as a speaker for Takeda and Janssen and worked on projects at Karolinska Institutet, partly financed by Janssen, UCB and Pfizer. James, Stefan: Dr. James reports institutional research grants from Novo Nordisk, Astra Zeneca, Amgen, Jansen, Alnylam and proctor fees from Medtronic. Ludvigsson, Jonas: Dr. Ludvigsson has coordinated an unrelated study for the Swedish IBD Quality Register (SWIBREG). That study received funding from Jansen Corporation. Ludvigsson has also received financial support from MSD/Merck for unrelated research on inflammatory bowel disease, and for developing a paper reviewing national healthcare registers in China. Ludvigsson has an ongoing research collaboration with Takeda about celiac disease and is discussing additional collaboration on chronic liver disease with this company. Olen, Ola: Karolinska Institutet has received research grants from Pfizer, Janssen, AbbVie, Takeda, Ferring, Bristol Myers Squibb, and Alfasigma for projects led by Olén. Ola Olén has also received fees for lectures from Pfizer, Janssen, Bristol Myers Squibb, and Takeda.

Abstract Background Global data demonstrate an inverse relationship between hospital ileoanal pouch volume and adverse outcomes, highlighting the need for quality metrics for this technically demanding procedure.1-4 Currently, there are no standardised quality indicators to define high-quality pouch surgery. This study aimed to establish international consensus on key performance indicators (KPIs) in pouch surgery. Methods A modified Delphi process was conducted among an international, multidisciplinary panel of experts. Participants were identified through professional networks, literature review, and direct email invitation; additional participants recruited via a snowball sampling approach over one month. Candidate KPIs were generated from literature review and expert input across 5 domains. Each item was rated on a 9-point Likert scale (1 = not important, 9 = critically important); consensus was predefined as ≥ 80% of respondents rating an item 7–9. Items not reaching consensus were re-rated in a second round following anonymized group feedback. Results Round 1 included 312 participants from 37 countries. Demographics (Table 1): 53% were age 45 years, 35.2% were female, and included surgeons (68.6%) and gastroenterologists (31.1%). Most (76.6%) practice at academic or university hospitals, with a median of 11 (5–17) years in practise; 78.9% perform &gt;1 pouchoscopy per month, and 39.5% of surgeons perform 5 pouches/year. Respondents’ regions included North America (51%), Europe (26%), Oceania (9%), Asia (6%), Latin America (4%), and the Middle East/Africa (4%). Seven (18%) countries (Denmark, Lithuania, Malaysia, Norway, United Arab Emirates, Sweden, and Switzerland) reported pouch surgery is already centralised, while 70.6% agreed pouch centralisation should be implemented. Cost/logistics and professional autonomy were the most important barriers to centralisation, whereas capacity and training exposure were least important. Overall, 37/59 (62.7%) candidate KPIs reached consensus after Round 1. The Round 2 response rate was 61%, and 2 additional KPIs reached consensus (preop ileitis and long-term risk of pouchitis). Additionally, 14 of 25 (56%) informed consent items reached consensus, and 64% of respondents felt informed consent for pouch surgery requires 2 or more office visits. Consensus items were used to populate a KPIPS Checklist (Figure 1). Conclusion Through an international Delphi process, the KPIPS study identified a consensus-derived set of key performance indicators to measure quality in pouch surgery. These quality metrics provide a foundation for benchmarking outcomes and represent a critical step towards centralization and the development of designated pouch centres of excellence to improve global standards of care for pouch patients. References: 1. Worley GHT, Fearnhead NS, Brown SR, et al. Review of current practice and outcomes following ileoanal pouch surgery: Lessons learned from the ileoanal pouch registry and the 2017 ileoanal pouch report. Colorectal Dis 2018;20:913–22. 2. Giddings HL, Yang PF, Steffens D, Solomon MJ, Ng KS. Influence of hospital-level and surgeon factors on the outcomes after ileo-anal pouch surgery for inflammatory bowel disease: Systematic review. Br J Surg 2024;111. 3. Hoang CM, Maykel JA, Davids JS, et al. Distribution of elective ileal pouch-anal anastomosis cases for ulcerative colitis: A study utilizing the university health system consortium database. J Gastrointest Surg 2020;24:2613–9. 4. Moojen TB, Visser E, Reijntjes MA, et al. One-year stoma-free survival of ileoanal pouches for uc in european centers: The miracle project. Ann Surg Open 2025;6:e596. Conflict of interest: Prof. Holubar, Stefan: No conflict of interest Soop, Mattias: No conflict of interest Poskus, Tomas: No conflict of interest Neary, Peter: No conflict of interest Uchino, Tairin: No conflict of interest Yang, Song-soo: No conflict of interest Adamina, Michel: No conflict of interest Avellaneda, Nicolas Luis: No conflict of interest Barnes, Edward: No conflict of interest Brouquet, Antoine: No conflict of interest Brown, Steven Ross: No conflict of interest De Buck Van Overstraeten, Anthony: No conflict of interest Buskens, Christianne J.: No conflict of interest Chiorean, Michael: No conflict of interest Clark, David: No conflict of interest Cohen, Benjamin: No conflict of interest El Ouali, Sara: No conflict of interest Faiz, Omar Darius: No conflict of interest Fichera, Alessandro: No conflict of interest Hahnloser, Dieter: No conflict of interest Hancock, Laura: No conflict of interest Herfarth, Hans: No conflict of interest Johnston, Michael: No conflict of interest Kayal, Maia: No conflict of interest Laharie, David: No conflict of interest Liberman, Sender: No conflict of interest Loftus, Jr, Edward: No conflict of interest Moeslein, Gabriela: No conflict of interest Myrelid, Pär: No conflict of interest Poylin, Vitaliy: No conflict of interest Qazi, Taha: No conflict of interest Raffals, Laura: No conflict of interest Rubin, David T.: No conflict of interest Spinelli, Antonino: No conflict of interest Steinhagen, Emily: No conflict of interest Tozer, Philip: No conflict of interest Verstockt, Bram: No conflict of interest Warusavitarne, Janindra: No conflict of interest Wexner, Steven: No conflict of interest Winter, Desmond: No conflict of interest

Abstract Objective To measure the relative levels of signal and noise in expert diagnosis of epilepsy. Methods Twenty multinational epileptologists independently reviewed 50 vignettes of adult and pediatric patients presenting with suspected seizure(s) on two separate occasions with a ≥30‐day washout period. Experts provided a diagnosis of epilepsy or non‐epilepsy based on clinical information and, if requested, routine EEG and neuroimaging data. Cases had an established clinical diagnosis of epilepsy or non‐epilepsy based on capture of habitual paroxysmal events on video‐EEG or long‐term clinical follow‐up. Experts' judgments were analyzed to decompose variability into different sources: signal (objective differences between cases), level noise (experts' bias toward over/under‐diagnosis), pattern noise (experts' idiosyncratic reactions to specific case features), and occasion noise (inconsistency across occasions). Results The probability of an expert making a different diagnosis for a given case on two different occasions was 16%. The probability of two different experts making a different diagnosis for the same case was 26%. Signal (case “difficulty”) accounted for 66–69% of total variation, with 31–34% attributable to noise. Level noise was the largest contributor in the absence of EEG/neuroimaging results (23%), while pattern noise dominated when test results were available (24%). Occasion noise contributed relatively little (1%) but was still sufficient to cause diagnostic reversals in 16–22% between occasions. Significance The degree of noise in expert diagnosis of epilepsy is substantial, stemming primarily from physicians' idiosyncratic interpretations of case features and variable dispositions toward over‐ or under‐diagnosis. Strategies to improve reliability are needed, including standardized data collection protocols and structured decision algorithms. For “difficult cases,” where expert reliability and accuracy are lowest, our findings support current clinical practice which favors early referral for video‐EEG monitoring over reliance on diagnostic anchoring. This diagnostic pathway may become more accessible with advances in EEG technology (e.g., wearable devices) and artificial intelligence.

Abstract Introduction Cervical arterial dissections (CeAD) can involve either single (sCeAD) or multiple (mCeAD) arteries. Whether the involvement of a single versus multiple arteries is associated with outcomes remains unclear. We aimed to study associations between the number of affected arteries and clinical, imaging and outcome parameters. Patients and methods Patients with CeAD from the STOP-CAD multicenter registry study were included. Clinical, imaging, treatment and outcome parameters were compared between patients with sCeAD and mCeAD. Regression analyses were performed to identify associations with multi-arteries involvement. Results Overall, 3858 STOP-CAD patients were included in this analysis and 443 (11.5%) had mCeAD. The presence of mCeAD was associated with age (adjusted odds ratio [aOR] 95% confidence intervals [95% CI] 0.99; (0.98–1.00)), female sex (aOR 1.5; 95% CI 1.17–1.91), recent upper respiratory infection (aOR 2.25; 95% CI 1.55–3.27), presence of connective tissue disease (aOR 3.11; 95% CI 2.32–4.17), severe arterial stenosis (aOR 1.95; 95% CI 1.95–2.58), intracranial extension (aOR 1.47; 95% CI 1.04–2.09), vertebral artery involvement (aOR 2.50; 95% CI 1.94–3.22) and presence of dissecting aneurysm (aOR 2.59; 95% CI 1.95–3.42). In adjusted analyses, mCeAD was not associated with clinical outcomes (ischemic stroke, mortality, and sICH; all p &gt; 0.05). Conclusions mCeAD does not appear to increase risk of subsequent stroke as compared to sCAD despite baseline risk factors suggestive of vasculopathy. mCeAD patients who did develop a stroke presented with milder strokes and less often had vessel occlusions compared to those with sCeAD. The presence of mCeAD did not impact outcomes.

Abstract Aims Cardiogenic shock (CS) is often treated with catecholamines titrated to an adequate target mean arterial pressure (MAP) while minimizing adverse effects. We aim to assess the optimal catecholamine dose/MAP balance in heart failure-associated CS (HF-CS). Methods Patients with HF-CS were retrospectively enrolled from 16 tertiary centres in 5 European countries (2016–2021; NCT03313687). Dosage was quantified by inotropic scores (epinephrine, norepinephrine, and dobutamine). Associations of baseline and seven-day summarized dosage with intensive care unit (ICU) discharge (mixed-effects logistic regression) and 30-day mortality (Cox regression) were analysed. Potential catecholamine/MAP target ratios for optimized outcomes were assessed in models adjusted for age, sex, pH, lactate and prior resuscitation, stratified by centre. Results N = 704 patients: median age 63 years, 74% male, 34% post-resuscitation, median lactate 5.2 mmol/l. Of these, 53% were discharged from ICU, 48% died within 30 days. Higher inotropic scores independently predicted a lower probability of ICU discharge (baseline score: OR 0.78 [95%-CI 0.69–0.88]; summarized score: OR 0.46 [0.38–0.56]; both P &lt; .001) and higher risk of 30-day mortality (baseline score: HR 1.27 [1.15–1.40], summarized score HR 1.83 [1.60–2.09]; both P &lt; .001). A score/MAP ratio &lt;0.403 µg/kg/min/mmHg was associated with higher ICU discharge odds (ceiling effect); a &lt; 0.426 µg/kg/min/mmHg with lower 30-day mortality hazards (no ceiling effect). Lowering catecholamine doses by accepting reduced MAP targets was linked to better outcomes. Conclusion In HF-CS, higher catecholamine support independently associates with worse outcomes. Accepting lower blood pressure targets to reduce catecholamine dosage may improve outcomes. Validation in randomized controlled trials is urgently needed.

BACKGROUND: Patients with cervical artery dissection (CeAD) may experience a recurrent dissection, but its frequency, risk factors, and clinical implications are not well defined. We aimed to determine the risk, associated factors, and clinical impact of recurrent CeAD. METHODS: The STOP-CAD study (Antithrombotic Treatment for Stroke Prevention in Cervical Artery Dissection) was a multicenter international retrospective observational study of patients with CeAD treated between January 2015 and June 2022. Recurrent dissection was defined as a CeAD occurring at least 7 days after the diagnosis of the index event that affects a different artery or a different segment of the same artery. Patients were followed from day 7 up to 2 years. The absolute risk of recurrent CeAD over time was calculated using Kaplan-Meier survival estimates. Multivariable logistic and Cox regression models were used to assess predictors of CeAD recurrence. RESULTS: Of the 4023 patients included in STOP-CAD, 3836 (median age 46 years, 45% women) were eligible for this analysis. During a median (interquartile range) follow-up of 295 (97–720) days, 88 (2.29%) patients had a CeAD recurrence. Median time-to-recurrent CeAD was 53 (interquartile range, 18–157) days. The estimated risk of recurrent CeAD at 2 years was 3.22% (95% CI, 2.59%–4.00%). In multivariable analyses, younger age (adjusted odds ratios, 0.98 [95% CI, 0.96–0.99]), migraine (adjusted odds ratio, 1.88 [95% CI, 1.14–3.07]), and fibromuscular dysplasia (adjusted odds ratio, 2.90 [95% CI, 1.66–5.06]) were associated with CeAD recurrence, while presenting with an ischemic stroke was associated with a lower likelihood of recurrence (adjusted odds ratio, 0.47 [95% CI, 0.29–0.75]). These associations with CeAD recurrence over time were confirmed by Cox regression analyses. Among the 88 patients with recurrent CeAD, only 5 had accompanying ischemic events (3 strokes, 2 transient ischemic attacks). CONCLUSIONS: In this retrospective study, recurrent CeAD was uncommon, approximately half of the events were diagnosed within the first 2 months of the index event, and recurrent events rarely caused new ischemic events. Younger age, migraine, absence of ischemic stroke at presentation, and signs of fibromuscular dysplasia may help identify high-risk patients.