Negative predictive value of multiplane transesophageal echocardiography in the diagnosis of infective endocarditis
Bibliographic record
Abstract
BACKGROUND: The clinical implications of a negative multiplane transesophageal echocardiography (TEE) have not yet been reported. We aim to determine the negative predictive value (NPV) of a negative multiplane TEE in patients with suspected infective endocarditis (IE). METHODS AND RESULTS: We identified 83 consecutive patients with suspected IE and negative multiplane TEE from our echocardiographic database. Of 74 patients with a minimum of 1-month follow-up, only 1 patient developed "definite IE". Eight patients had "possible IE". The calculated NPV of multiplane TEE in IE was 98.6% if we only considered the case of "definite IE". If we assumed that all patients with "possible IE" had the disease, then the NPV of multiplane TEE was 87.8%. CONCLUSIONS: Multiplane TEE is a highly accurate diagnostic tool with excellent NPV in IE. However, in a highly suspicious clinical setting for IE, a repeat TEE is still recommended to assess evolving echocardiographic features.
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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 | 0.002 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".