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Record W4401554217 · doi:10.2147/vhrm.s431612

Interobserver Variability of Coronary Stenosis Characterized by Coronary Angiography: A Single-Center (Toronto General Hospital) Retrospective Chart Review by Staff Cardiologists

2024· article· en· W4401554217 on OpenAlexaffabout
Seyedmohammadshahab Shivaie, Hadi Tohidi, Pragash Loganathan, Manish Kar, Habiba Hashemy, Mohammad A. Shafiee

Bibliographic record

VenueVascular Health and Risk Management · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineCoronary angiographyRetrospective cohort studyStenosisSingle CenterChartGeneral hospitalCardiologyRadiologyInternal medicineEmergency medicineMyocardial infarction

Abstract

fetched live from OpenAlex

Introduction: The reliability of interpretation of coronary angiography as a diagnostic tool was investigated. Furthermore, the impact of interobserver variability of coronary lesions on clinical decision-making was assessed. One of our motivations to do this research was the research gaps and our aim to have up-to-date information regarding interobserver variability among different cardiologists. Methods: Our objective was to quantify interobserver variability among cardiologists who have seen angiograms independently. Disagreement among cardiologists in the visual assessment of invasive coronary angiography of coronary artery stenosis is not uncommon in previous studies. Three cardiologists with extensive experience in coronary angiography, including the primary cardiologist of each patient, read the angiograms of 200 patients from Toronto General Hospital independently. Results: Our research showed the mean agreement among all participating observers was 77.4%; therefore, the interobserver variability of coronary angiography interpretation was 22.6%. Discussion: Coronary angiography is still the gold-standard technique for guidance regarding coronary lesions. Sometimes, coronary angiography results in underestimation or overestimation of a lesion’s functional severity. Interobserver variability should also be considered when interpreting the severity of coronary stenoses via invasive coronary angiography. This research shows that interobserver variability regarding coronary angiograms is still present (22.6%). Plain language summary : The gold-standard method for diagnosing coronary stenosis, invasive coronary angiography has some challenges too. One of these challenges has been the difference among various cardiologists regarding determination of severity of each coronary stenosis. In this study, we focused on differences in interobserver variability in coronary angiography interpretation. Three cardiologists who were experienced in coronary angiography read each patient’s coronary angiogram separately. Overall, 200 patients with a history of angiography at Toronto General Hospital were selected randomly. The research showed that overall agreement among all participating cardiologists with regard to the reading of coronary angiograms was 77.4%. In other words, interobserver variability of 22.6% was seen among the readers. Keywords: coronary angiography, ICA, PCI, fractional flow reserve, interobserver variability

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.253
Teacher spread0.245 · 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.

Study designObservational
DomainMethods
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

Citations8
Published2024
Admission routes2
Has abstractyes

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