Feasibility and reliability of Doppler flow recordings in the fetal aortic isthmus: a multicenter evaluation
Bibliographic record
Abstract
OBJECTIVES: To evaluate the performance of three different centers with respect to their ability to identify the fetal aortic isthmus (AoI) adequately and place a Doppler sample volume in the AoI correctly, and to address the reproducibility of the isthmic flow index (IFI) calculated from Doppler waveforms recorded in the three centers. METHODS: The three collaborating centers sent several ultrasonographic recordings taken at random over a 6-week period to the Saint-Justine Fetal Cardiology Unit (StJ-FCU). A performance quotient ((number of total readings - number of unsatisfactory results)/number of total readings) was calculated for each center by each of three judges, who were experienced fetal cardiologists, to assess the ability of each center to identify the isthmus and to place the Doppler sample volume (DSV) adequately. Intraclass correlation coefficients (ICC) were computed to quantify the variability of IFI measurements ((systolic + diastolic)/systolic flow velocity integrals). RESULTS: Fifty-five recordings were available for this study. Concerning isthmus identification, there was 100% agreement between the three judges from StJ-FCU and the performance quotients of Centers A, B and C were: 0.90, 0.95 and 1.00, respectively. For DSV positioning, agreement between the judges varied; for Judge 1 vs. Judge 2, kappa = 0.836 (95% CI, 0.651-1.000); for Judge 1 vs. Judge 3, kappa = 0.773 (95% CI, 0.557-1.000); for Judge 2 vs. Judge 3, kappa = 0.941 (95% CI, 0.805-1.000). The performance quotients of the three centers for DSV positioning were consistently lower than were those for identification of the isthmus, being 0.85, 0.76 and 0.92, respectively. The ICC between the first and second measurements of the IFI by Rater 1 was 0.96 (95% CI, 0.93-0.98, P < 0.001) and that between Raters 1 and 2 was 0.97 (95% CI, 0.95-0.99, P < 0.001). CONCLUSION: Adequate imaging of the fetal AoI can be achieved easily by a trained sonographer, while DSV positioning is challenging. The intra- and interrater variability of the IFI are low.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".