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Background: Periodontal diseases are chronic inflammatory conditions that require early screening for effective long‐term management. Oral neutrophil counts (ONCs) correlate with periodontal inflammation. This study investigates a point‐of‐care test using a neutrophil enzyme activity (NEA) colorimetric strip for measuring periodontal inflammation. Methods: This prospective study had two phases. Phase 1 validated the relationship between ONCs and periodontal inflammation with 90 participants. Phase 2 examined the test's applicability in a real‐world setting through a multicentre clinical trial with 375 participants at four sites. ONCs were quantified in oral rinses using laboratory‐based methods, and the NEA strip was used for ONC stratification. Clinical measures included bleeding on probing (BoP), probing depth (PD) and clinical attachment loss (CAL). Results: ONCs were significantly elevated in patients with Grade B periodontitis and deep periodontal pockets (PD ≥ 5 mm, CAL ≥ 5 mm). The NEA strip accurately classified patients into high or low ONC categories, showing 80% sensitivity, 82.5% specificity and an AUC of 0.89. It also assessed the effectiveness of periodontal therapy in reducing ONC and inflammation. The test was user‐friendly, with no reported discomfort among patients. Conclusion: The NEA strip is a user‐friendly and rapid screening tool for detecting high ONCs associated with periodontal inflammation and for evaluating the effectiveness of periodontal therapy. [ABSTRACT FROM AUTHOR]

Background: This systematic review aimed to evaluate the performance of machine learning (ML) models in predicting post-treatment survival and disease progression outcomes, including recurrence and metastasis, in head and neck cancer (HNC) using clinicopathological structured data. Methods: A systematic search was conducted across the Medline, Scopus, Embase, Web of Science, and Google Scholar databases. The methodological characteristics and performance metrics of studies that developed and validated ML models were assessed. The risk of bias was evaluated using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Results: Out of 5,560 unique records, 34 articles were included. For survival outcome, the ML model outperformed the Cox proportional hazards model in time-to-event analyses for HNC, with a concordance index of 0.70–0.79 vs. 0.66–0.76, and for all sub-sites including oral cavity (0.73–0.89 vs. 0.69–0.77) and larynx (0.71–0.85 vs. 0.57–0.74). In binary classification analysis, the area under the receiver operating characteristics (AUROC) of ML models ranged from 0.75–0.97, with an F1-score of 0.65–0.89 for HNC; AUROC of 0.61–0.91 and F1-score of 0.58–0.86 for the oral cavity; and AUROC of 0.76–0.97 and F1-score of 0.63–0.92 for the larynx. Disease-specific survival outcomes showed higher performance than overall survival outcomes, but the performance of ML models did not differ between three- and five-year follow-up durations. For disease progression outcomes, no time-to-event metrics were reported for ML models. For binary classification of the oral cavity, the only evaluated subsite, the AUROC ranged from 0.67 to 0.97, with F1-scores between 0.53 and 0.89. Conclusions: ML models have demonstrated considerable potential in predicting post-treatment survival and disease progression, consistently outperforming traditional linear models and their derived nomograms. Future research should incorporate more comprehensive treatment features, emphasize disease progression outcomes, and establish model generalizability through external validations and the use of multicenter datasets. [ABSTRACT FROM AUTHOR]

Objectives: This systematic review aimed at evaluating the performance of artificial intelligence (AI) models in detecting dental caries on oral photographs. Methods: Methodological characteristics and performance metrics of clinical studies reporting on deep learning and other machine learning algorithms were assessed. The risk of bias was evaluated using the quality assessment of diagnostic accuracy studies 2 (QUADAS‐2) tool. A systematic search was conducted in EMBASE, Medline, and Scopus. Results: Out of 3410 identified records, 19 studies were included with six and seven studies having low risk of biases and applicability concerns for all the domains, respectively. Metrics varied widely and were assessed on multiple levels. F1‐scores for classification and detection tasks were 68.3%–94.3% and 42.8%–95.4%, respectively. Irrespective of the task, F1‐scores were 68.3%–95.4% for professional cameras, 78.8%–87.6%, for intraoral cameras, and 42.8%–80% for smartphone cameras. Limited studies allowed assessing AI performance for lesions of different severity. Conclusion: Automatic detection of dental caries using AI may provide objective verification of clinicians' diagnoses and facilitate patient‐clinician communication and teledentistry. Future studies should consider more robust study designs, employ comparable and standardized metrics, and focus on the severity of caries lesions. [ABSTRACT FROM AUTHOR]

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OBJECTIVE: Canada's national system of health insurance facilitates equitable access to health care; however, since dental care is generally privately financed and delivered, access to oral health care remains uneven and inequitable. To avoid the upfront costs, many argue that socially marginalized groups should seek oral health care from medical providers. This study therefore explored the rates and numbers of visits to physicians for oral health-related diagnoses in Ontario, Canada's most populated province. METHODS: A retrospective secondary data analysis of health system utilization in Ontario was conducted for visits to physicians for oral health-related diagnoses. Data for all Ontario Health Insurance Plan (OHIP) approved billing claims were accessed over 11 fiscal years (2001-2011). Age- and sex-adjusted rates were calculated. RESULTS: Approximately 208,375 visits per year, with an average of 1,298/100,000 persons, were made to physicians for oral health-related diagnoses. Women, irrespective of the year, made more visits, and there was an increasing trend in visits made by elderly people. CONCLUSION: The number of people visiting physicians for oral health reasons is arguably high. The public health system is being billed for services for oral health issues that the provider is not appropriately trained to treat. Provision of timely and accessible oral health care for socially marginalized populations needs to be prioritized in health care policy. KEY WORDS: Medical billing; health services; health policy; access to oral health care OBJECTIF: Le systeme national d'assurance-sante du Canada facilite l'acces equitable aux soins de sante; toutefois, comme les soins dentaires sont generalement finances et offerts a titre prive, l'acces aux soins buccodentaires demeure inegal et inequitable. Pour eviter les couts initiaux, beaucoup sont d'avis que les groupes socialement marginalises devraient obtenir des soins buccodentaires aupres de dispensateurs de soins medicaux. Notre etude explore donc les taux et le nombre des visites medicales pour obtenir des diagnostics de sante buccodentaire en Ontario, la province la plus peuplee du Canada. METHODE: Nous avons mene une analyse retrospective de donnees secondaires sur l'utilisation du systeme de sante en Ontario pour ce qui est des visites medicales pour obtenir des diagnostics de sante buccodentaire. Nous avons consulte les donnees de toutes les demandes de paiement des medecins approuvees par le Regime d'assurance-maladie de l'Ontario (RAMO) au cours de 11 exercices (2001-2011). Les taux rajustes selon l'age et le sexe ont ete calcules. RESULTATS: Il y a eu environ 208 375 visites medicales par annee (1 298 p. 100 000 personnes en moyenne) pour obtenir des diagnostics de sante buccodentaire. Les femmes, peu importe l'annee, ont fait davantage de ces visites, et le nombre de visites effectuees par les personnes agees affiche une tendance croissante. CONCLUSION: Le nombre de personnes consultant des medecins pour des raisons de sante buccodentaire est probablement eleve. Le systeme de sante publique est facture pour des services lies a des problemes de sante buccodentaire que les dispensateurs n'ont pas la formation necessaire pour traiter. La politique de soins de sante devrait offrir en priorite des soins buccodentaires rapides et accessibles aux populations socialement marginalisees. MOTS CLES: facturation des services medicaux; services de sante; politique de sante; acces aux soins buccodentaires La traduction du resume se trouve a la fin de l'article. Can J Public Health 2015;106(3):e127-e131 doi: 10.17269/CJPH.106.4866, Canada's national system of health insurance, Medicare, has become associated with the values of equity and solidarity. In general, universal access to health care has become a reality, specifically for [...]