Reliability of Electric Pulp Test, Cold Pulp Test or Tooth Transillumination to Assess Pulpal Health in Permanent Dog Teeth
Bibliographic record
Abstract
The aim of this study was to evaluate the reliability of electric pulp test (EPT), cold pulp test (CPT) and tooth transillumination (TTI) in the assessment of pulpal health in dog teeth. Forty-five client-owned dogs requiring tooth extraction or pulpectomy were included. For each patient, one affected and two control healthy teeth were evaluated with EPT, followed by CPT and TTI. Direct pulp inspection was used as a gold standard. The real pulpal health (vital or necrotic) was determined by the presence or absence of bleeding after creating access to the pulp chamber. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of EPT, CPT and TTI were obtained for each pulp test using the binomial Clopper-Pearson exact method to establish confidence intervals. Forty-five affected teeth were tested. Forty-three were tested with EPT, CPT, and TTI, and two were tested solely with EPT and CPT. All dogs tested with EPT and TTI were included in the study whereas 21 out of 45 (47%) dogs tested with CPT were excluded. The sensitivity, specificity, PPV, NPV and accuracy were respectively 0.96, 1.00, 1.00, 0.96 and 0.98 for EPT; 1.00, 0.89, 0.92, 1.00 and 0.95 for CPT; and 0.59, 0.95, 0.94, 0.67 and 0.76 for TTI. This study concluded that EPT is a highly reliable diagnostic test to evaluate pulpal health in dogs. The high accuracy of CPT is conditional on the patient's responsiveness to stimulation applied to its control healthy teeth. TTI was the least reliable test in the study.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".