Use of the HAVOC Score to Identify Patients at Highest Risk of Developing Atrial Fibrillation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Recent studies using insertable cardiac monitors (ICMs) show a high incidence of atrial fibrillation (AF). Further identifying subsets of patients who could benefit most from ICMs is desirable. We evaluated whether the HAVOC risk score which predicts AF in patients with cryptogenic stroke also predicts AF detection by ICMs in those without recent stroke. METHODS: Participants were included from the prospective, industry-sponsored REVEAL AF study assessing AF incidence in patients with CHADS2 scores ≥3 or =2 with 1 or more additional AF risk factors, who had ICM data and were not receiving anti-arrhythmic drugs. Ischemic stroke occurring less than 1 year prior to enrollment or documented AF were exclusion criteria. AF was defined as an adjudicated ICM-detected episode ≥6 min in duration. HAVOC scores were calculated by assigning 4 points for congestive heart failure, 2 points for each of hypertension, age ≥75 years, valvular disease, and coronary artery disease, and 1 point for each of peripheral vascular disease and obesity (body mass index >30). Scores classified risk as low (0-4), intermediate (5-9), or high (10-14); corresponding AF detection rates were compared using the log-rank test. AF incidence rates in patients with and without a history of remote stroke at baseline were also compared. RESULTS: Among 391 participants, the mean age was 71.5 ± 9.8 years and 186 (47.6%) were women. In total, 130 (33.2%) developed AF over 18 months. Stratification by HAVOC risk score was: 95 (24%) low, 241 (62%) intermediate, and 55 (14%) high. At 18 months, AF incidence in patients with low HAVOC scores (19.5%) was lower than in those with intermediate (32.1%) or high (34.2%) scores. AF incidence was similar among those with (n = 78) versus without (n = 313) remote stroke (27.3% vs. 29.8%; median time from stroke to ICM insertion was 4.2 [2.2-8.2] years). CONCLUSIONS: The HAVOC risk score identified a subset of individuals at greatest risk of developing AF, while AF incidence rates were similar among those with and without remote stroke. The use of the HAVOC score could help identify those at greatest likelihood of manifesting AF during long-term monitoring.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it