Prospective evaluation of the negative predictive value of V/Q SPECT using 99mTc-Technegas
Bibliographic record
Abstract
OBJECTIVE: To verify the negative predictive value of pulmonary ventilation/perfusion scintigraphy with single photon emission computed tomography (V/Q SPECT) in ruling out pulmonary thromboembolism. METHODS: V/Q SPECT using 99mTc-Technegas was performed on 584 patients to rule out pulmonary thromboembolism between October 2004 and July 2005. Pulmonary thromboembolism was defined as any clear-cut vascular mismatch, regardless of size. Indeterminate scans were defined as cases having matching vascular type defects with a corresponding X-ray abnormality, or cases with equivocal mismatches. Other patterns were considered negative for pulmonary thromboembolism. Outcome data was gathered >3 months after the scan. Absence of pulmonary thromboembolism was defined as any patient still alive at least 3 months after the scan, with no anticoagulation treatment and no proof of pulmonary thromboembolism by other techniques, either at the time of the scan or during follow-up, or death by other causes. RESULTS: One hundred and eight patients (19%) had a positive pulmonary thromboembolism reading, 18 (3%) an indeterminate study, and 458 (78%) patients had a negative reading for pulmonary thromboembolism. There were 189 patients with an abnormal chest X-ray. The mean follow-up time was 165 days. Of the 458 patients classified as negative for pulmonary thromboembolism, patients receiving chronic anticoagulation for other causes were excluded from follow-up (n=53), which left 405 patients for final analysis. There were no pulmonary thromboembolism-related deaths in the negative group. Six patients were identified as false negatives. The negative predictive value is estimated at 98.5%. CONCLUSION: SPECT pulmonary scintigraphy using 99mTc-Technegas demonstrates a high negative predictive value and a low indeterminate rate.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".