[How to validate the symptoms of pulmonary thromboembolism: how diagnostic scales help].
Bibliographic record
Abstract
AIM: To detect the most important clinical symptoms suggesting pulmonary thromboembolism (PTE) and to determine the diagnostic value of the scales used to estimate the likelihood of its occurrence. MATERIALS AND METHODS: The prospective study included 130 patients admitted to hospital with a diagnosis of PTE and a referral for a surgery clinic. Scores of the likelihood of PTE were estimated using the Canada and Geneva scales in all the patients on admission. RESULTS: In all the patients with suspected PTE, the Canadian and revised Geneva scores averaged 4.2 +/- 0.48 and 6.21 +/- 0.5, respectively. These scores correspond to the intermediate clinical probability of PTE. In 96 patients whose diagnosis was verified by instrumental studies, the Canadian and Geneva scores were 4.41 +/- 0.57 and 6.17 +/- 0.63, respectively, which was also consistent with the intermediate clinical probability of PTE. In 34 patients, whose diagnosis of PTE was ruled out, the average scores did not virtually differ from those in the patients with the verified diagnosis and were 6.14 +/- 1.3 and 4.18 +/- 0.87, respectively. The area under characteristic curve for the Canadian scale was 0.428 and that for the Geneva scale was 0.512. With the use of a two-level interpretation system, a total of more than 6 Canadian scores and 10 Geneva scores suggested that there was a high probability of PTE. CONCLUSION: The investigation indicated the low value of integral systems for estimating the likelihood of PTE in the total population of patients with this disease. The authors recommend the two-level interpretation system, in which a total of more than 6 Canadian scores and 10 Geneva scores were identified with a high probability (up to 80%) of PTE.
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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 | 0.022 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".