Multidetector Computed Tomography for Detection and Characterization of Pulmonary Hypertension in Consideration of WHO Classification
Bibliographic record
Abstract
OBJECTIVE: We evaluated the reliability of various multidetector computed tomography (MDCT) parameters for diagnosis and severity assessment of pulmonary hypertension (PH) with consideration of World Health Organization (WHO) classification. METHODS: A total of 172 patients were included in this retrospective study. One hundred fourteen patients had a diagnosis of PH (mean pulmonary artery pressure ≥25 mm Hg), and 58 patients without PH (mean pulmonary artery pressure <20 mm Hg) served as control subjects. The patients with PH were grouped according to the WHO classification based on PH etiology. RESULTS: The patients with PH had significantly greater main, left, and right pulmonary artery diameters than the control subjects (P < 0.001). No significant differences within the PH subgroups were found. Receiver operating characteristic analysis showed reasonable sensitivity and specificity for selected MDCT parameters. The severity of PH did not correlate with MDCT parameters. CONCLUSIONS: Easy-to-determine MDCT parameters allow detection of PH independent of the WHO group. In patients with dilated aorta, the vertebra can be an alternative internal standard. Severity of PH cannot be estimated by MDCT parameters.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".