Clinical utility of abnormal opacity overlying the vertebral column on lateral chest radiography
Bibliographic record
Abstract
BACKGROUND: Chest radiography is an important component of the evaluation of patients with complaints referable to the chest. We sought to investigate the clinical utility of one particular finding on the lateral chest radiograph (CXR), namely, radioopacity obscuring the normal superior to inferior progression of vertebral radiolucency. A review of the literature yielded little published evidence to characterize the clinical utility of this finding to date. METHODS: We retrospectively identified 370 patients from a hospital database who underwent both computed tomography (CT) imaging of the chest and lateral chest radiography within 24 hours. We calculated the sensitivity, specificity, and likelihood ratios (LRs) associated with the presence or absence of an abnormal opacity overlying the vertebral column on lateral chest radiography using CT imaging of the chest as the reference standard. We also estimated interobserver and intraobserver reliability of this finding. RESULTS: Abnormal opacity overlying the vertebral column had a sensitivity of 86.9% (95% confidence interval [CI], 82.5%-90.3%) and specificity of 70.4% (95% CI, 59.7%-79.2%) for relevant CT-documented lower lobe and associated structural pathology. The associated summary positive LR (LR+) was 2.9 (95% CI, 2.1-4.1) and summary negative LR (LR-) was 0.19 (95% CI, 0.13-0.26). Kappa statistics were indicative of moderate intraobserver and interobserver agreement. CONCLUSIONS: The presence of abnormal opacity overlying the vertebral column on lateral chest radiography increases the probability of lower lobe and associated structural pathology somewhat. The absence of this finding decreased the probability of such pathology to a greater degree. Thus, this finding is useful in differentiating those patients with pathology from those without.
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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 | 0.004 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".