Performance of panoramic radiography compared with computed tomography in the evaluation of pathological changes in the maxillary sinuses: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective: A systematic review was performed to evaluate the performance of panoramic radiography (PR) vs CT or cone beam CT (CBCT) in the diagnosis of pathological maxillary sinuses. Methods: This review was registered in the PROSPERO database under the number CRD42020211766. Observational studies that compared PR with CT/CBCT were used to evaluate pathological changes in the maxillary sinuses. A complete search of seven primary databases and gray literature was carried out. The risk of bias was assessed according to the Newcastle-Ottawa tool, and the GRADE tool was used to assess the quality of evidence. A binary meta-analysis was performed to assess the effectiveness of evaluating pathological alterations in the maxillary sinuses in PR and CT/CBCT. Results: Seven studies were included in our study, out of which four were included in a quantitative analysis. All studies were classified as low risk of bias. Five studies compared PR with CBCT and two studies compared PR to CT. The most common pathological alteration in maxillary sinuses reported was mucosal thickening. CT/CBCT was seen to be the most effective method for assessing pathological changes in the maxillary sinus when compared to PR (RR = 0.19, 95% confidence interval [CI] = 0.05 to 0.70, p = 0.01). Conclusion: CT/CBCT are the most appropriate imaging methods to evaluate pathological changes in the maxillary sinuses, while PR is still limited in the evaluation of these changes being considered only for initial diagnosis.
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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 | 0.026 | 0.072 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".