Diagnostic Value of Computed Tomography Imaging Features in Malignant Pleural Mesothelioma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Medical history, thoracentesis, and imaging features are usually the first steps in the investigation of a possible malignant pleural effusion (MPE). Unfortunately, the diagnostic yield of thoracentesis in this situation is suboptimal even if the procedure is repeated, especially in the context of malignant pleural mesothelioma (MPM). The next step for confirming the diagnosis, if clinically appropriate, is thoracoscopy, but not all patients are fit to undergo this procedure, so the diagnosis is then based on the medical history and imaging features only. OBJECTIVES: Our objective was to evaluate the diagnostic value of the medical history and imaging features in MPM. METHODS: We reviewed the imaging and medical charts of 92 patients with a final diagnosis of MPE included in our prospective medical thoracoscopy database. The clinical characteristics and imaging features of patients with primary MPE were compared with those of patients with secondary MPE. RESULTS: Male sex (82 vs. 59%, p = 0.02), asbestos exposure (58 vs. 10%, p < 0.001), and mediastinal (68 vs. 33%, p = 0.04), diaphragmatic (75 vs. 31%, p = 0.001) and circumferential pleural thickening (55 vs. 19% p = 0.001) were significantly more frequent in MPM patients. In a multivariate linear regression model, only asbestos exposure (OR 11.2; 95% CI 3.4-36.9) and circumferential pleural thickening (OR 4.7; 95% CI 1.6-13.9) were significantly associated with a diagnosis of MPM. CONCLUSION: In situations where it is impossible to obtain adequate pleural samples to differentiate MPM from a secondary pleural malignancy, the combination of circumferential pleural thickening and a history of asbestos exposure may be sufficient to make a clinical diagnosis.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it