MétaCan
Menu
Back to cohort
Record W3164177772 · doi:10.1093/europace/euab116.292

Assessing atrial fibrillation ablation priority during COVID-19 -does use of patient questionnaires help in stratification above physician assessment?

2021· article· en· W3164177772 on OpenAlexaboutno aff
Charlene Pius, Hamaad Ahmad, Richard Snowdon, Reza Ashrafi, Johan Waktare, Zoltan Borbas, Vishal Luther, Saagar Mahida, Simon Modi, Mark Hall, Dhiraj Gupta, Derick Todd

Bibliographic record

VenueEP Europace · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAtrial fibrillationQuality of life (healthcare)Catheter ablationCoronavirus disease 2019 (COVID-19)Emergency medicineCanadian Cardiovascular SocietyPediatricsPhysical therapyInternal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Catheter ablation for atrial fibrillation (AF) is largely offered for symptomatic relief. The ORBIT registry has shown that patients with a higher EHRA class and lower quality of life (QoL) scores (AFEQT score <65.7) are more likely to suffer emergency hospital admissions. To help prevent unplanned AF admissions and to best utilise the reduced capacity for elective work during the COVID-19 pandemic, it has become even more important to prioritise the most symptomatic AF patients for ablation. Purpose: To evaluate the accuracy of a subjective symptom-based clinician prioritisation schema compared to objective patient-completed quality of life (QoL) scores. Methods: In July 2020, all elective cases awaiting AF ablation at our institution were categorised by their cardiologist as either category 1 (C1-urgent), category 2 (C2–priority, procedure to be done during the ongoing COVID-19 pandemic) or category 3 (C3–routine, procedure may be delayed until post pandemic). This categorisation was based on review of clinic letters where EHRA AF symptom class or PROMS are not routinely recorded. All patients in C2 and C3 were then posted an AF specific (AFEQT) and a generic (EQ5D) QoL questionnaire to complete. Physicians were blinded to patient responses on the QoL questionnaires. Results: Details of physician prioritisation and completed questionnaires were available for 85 patients (62 ± 10 years, PAF in 61%, males 66%). The 18 patients that had been categorised in C2 (priority) group were found to have a significantly lower AFEQT score (30.4, IQR 17.2-51.9) compared to the 67 patients classed in C3 (routine) group (56.5, IQR 32.1-74.1; p < 0.01)(Figure 1a). EQ5D scores also tended to be lower in the C2 patients (0.7, IQR 0.4-0.8) compared to C3 (0.8, IQR 0.6-0.9; p = 0.056) (Figure 1c). 16 (89%) patients in C2 had significant AF-related impact on QoL (as defined as AFEQT score <65.7) compared to 42 (63%) of patients in C3. However, there was significant overlap between groups (Figure 1b). 4 patients in C3 had unplanned AF related hospital admissions while awaiting ablation, as compared to none in C2. The median AFEQT score of these 4 patients was 23.3, indicating that they were highly symptomatic despite being classified in C3 by their cardiologist. Conclusion : Physician assessments are moderately accurate in prioritising patients awaiting AF ablation. The addition of formal patient-completed QoL assessment such as with AFEQT, helps to identify the most symptomatic patients at risk of emergency hospital admission, and physicians should consider using these as part of routine assessment, especially during the COVID pandemic. Abstract Figure 1

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.099
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.242
GPT teacher head0.442
Teacher spread0.200 · 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 teacher head, 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEP EuropaceSame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207