Standerd cervical mediastinoscopy in the diagnosis of mediastinal mass in Ghazi Al-Hariri Hospital
Bibliographic record
Abstract
Background: Mediastinoscopy is an integral part in the diagnosis of mediastinal mass. The most common indications for mediastinoscopy is for tissue sampling and determining the extent of lung cancer.Objectives: To validate our experience with standard cervical mediastinoscopy and to evaluate the usefulness of cervical mediastinoscopy in the assessing the mediastinal diseases when imaging modalities are none diagnostic.Material and Methods: A retrospective study of 16 patients between January 2012 and July 2014. Mediastinoscopy was indicated for diagnostic staging of nodal disease related to lung cancer in 8 patients (group I) and for isolated mediastinal lymphadenopathy in 8 patients (group II)Results: There were 11 males and 5 females, with a mean age of 47 years. The mean operative time was 30 minutes and the mean hospital stay was 8 hours. In lung cancer (group I) there was positive results in 3 patients and negative results in 5 patients. In patients with isolated mediastinal lymphadenopathy (group II), TB was the commonest diagnosis. There was no surgical related morbidity or mortality in our study. The sensitivity and specificity of standard cervical mediastinoscopy in this study was 100%Conclusion: Standard cervical mediastinoscopy is safe in the hands of well trained persons and needs a good knowledge of the anatomy of the region, cost effective, highly specific and still the first investigation of choice in the diagnosis of mediastinal nodal involvement.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".