Geriatric oral lesions: A multicentric study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: To carry out an oral biopsy survey in geriatric patients from the participating institutions. METHODS: The biopsy records of the participating institutions were reviewed for oral lesions from patients aged 65 years and older diagnosed from 2003 to 2012. Demographic data and the site of the lesions were collected. Histopathological diagnoses were categorized into two categories: non-neoplastic lesions (reactive/inflammatory lesion, cyst, allergic/immunologic disorders, potentially malignant disorders, infection and others) and neoplastic lesions (benign and malignant tumors). Data were analyzed by appropriate statistics using stata11. RESULTS: Of the 76,045 accessioned cases, 11,346 cases (14.92%) were in geriatric patients. The mean age of the patients was 72.98 ± 6.25 years. A total of 5010 cases (44.16%) were diagnosed in males, whereas 6336 cases (55.84%) were diagnosed in females. The male-to-female ratio was 0.79:1. Non-neoplastic lesions outnumbered the neoplastic counterpart. The five most prevalent oral lesions in the geriatric population in the present study in descending order of frequency were squamous cell carcinoma, focal fibrous hyperplasia (irritation fibroma), radicular cyst, osteomyelitis and epithelial dysplasia, respectively. The site of predilection was labial/buccal mucosa, followed by gingiva, mandibular bone, tongue and maxillary bone, respectively. CONCLUSIONS: The geriatric oral lesions from the present study showed a similar trend with studies based on histopathological data, but different from the studies based on clinical data. This study also shed more light on potentially malignant disorders, as well as benign and malignant tumors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it