Preliminary accuracy, inter- and intra-rater reliability of a 4-point cervical artery dissection diagnostic decision support tool in an ambulatory setting using real and simulated cases: a quality improvement project
Oct 2026· Chiropractic & Manual Therapies· 43 references
Cerebrovascular and Carotid Artery Diseases
Abstract
Abstract Background Cervical artery dissection (CeAD) is a rare but life-threatening condition that commonly presents with non-specific symptoms such as neck and head pain, complicating early recognition in ambulatory care settings. The CeAD diagnostic decision support tool (DDST) is a 4-item assessment designed to identify patients that should be referred for advanced diagnostic work-up to rule out CeAD; however, its utility in ambulatory settings has not been established. Methods This quality improvement project aimed to evaluate the accuracy, inter-rater reliability, and intra-rater reliability of chiropractors applying the CeAD DDST using clinical vignettes simulating a typical ambulatory encounter before deploying the DDST broadly as part of the clinical workflow. Five experienced chiropractors assessed 40 standardized clinical vignettes. CeAD-positive cases ( n = 10) were derived from published imaging-confirmed ambulatory care case reports. CeAD-negative cases ( n = 30) were developed using generative artificial intelligence and refined by senior authors to reflect common conditions encountered in chiropractic practice. Raters independently assessed cases with the DDST (score 0–4), with a cutoff score of ≥ 3 recommending referral for advanced diagnostic work-up in two rounds, beginning November 11, 2025 and January 07, 2026, with a two-week capture period. Accuracy, inter-rater reliability, and intra-rater reliability were assessed. Results Accuracy in identification ranged from 72.5% to 95.0% across raters and rounds. False positives and negatives were present across raters in both rounds, with false positives being more prevalent. Inter-rater reliability was moderate to substantial in both rounds (Round 1: κ = 0.609, 95% CI 0.432–0.806, Round 2: κ = 0.540, 95% CI 0.365–0.735). Intra-rater reliability ranged from moderate to almost perfect agreement (range 0.457–0.931). Conclusions The CeAD DDST demonstrated moderate to good accuracy and reliability among chiropractors in a simulated ambulatory setting. The presence of false negatives and inter-rater reliability falling below recommended benchmarks preclude recommendation for implementation at this time. Iterative refinement informed by end-user input and prospective ambulatory testing is warranted prior to clinical adoption of the CeAD DDST. Future evaluations should include prospective studies using real clinical data to better represent real-world settings.
This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.
F. Xia, Amir Zamir, Zhi-Yang He et al.· 2018 IEEE/CVF Conference on...· 1,069 citations· ⚡112
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
An algorithm is proposed which leverages disentangled semantic factors to generate adversarial perturbation by altering controlled semantic attributes to fool the learner towards various "adversarial" targets.
Haonan Qiu, Chaowei Xiao, Lei Yang et al.· arXiv.org· 208 citations· ⚡17
This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9