m+Medelevator.RU
← Поиск публикаций
Scientific reports · 2025

Development of a novel method to evaluate gingivitis in children by combining rapid saliva test systems.

СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Iwamoto Yuko, Mitsuhata Chieko, Ikeda Shunya, Ito Yuya, Hamaguchi Shuma, Tabata Eimi, Tsuge Yasuko, Kaneki Ami, Ogawa Masashi, Nishimura Taku, Kametani Mariko, Kusaka Satoru, Asao Yuria, Akitomo Tatsuya, Kozai Katsuyuki, Nomura Ryota

Аннотация

Few tools can objectively assess the risk of gingivitis in children. We developed a novel method to evaluate gingivitis by combining rapid saliva test systems. Seventy-six subjects (aged 3-19 years) were included in the study. Gingival condition was evaluated using the papillary marginal attached (PMA) index. Liquid gargled by the subjects was examined using Perioscreen to measure the amount of hemoglobin, and the Salivary Multi Test (SMT) to quantify six factors related to oral health. PMA values were significantly higher in subjects with positive hemoglobin than in those with negative hemoglobin (P < 0.001). Of the six SMT items, buffering capacity and protein showed correlations with PMA value (R2 > 0.25). Next, a multivariate receiver operating characteristic (ROC) analysis for the diagnosis of gingivitis was performed using PMA value as the outcome and hemoglobin, buffering capacity, and protein as variables. The results showed that the area under the curve (AUC) for the combination of the three variables, including hemoglobin, buffering capacity, and protein, was significantly higher than when any single variable was used (P < 0.05). Our findings suggest that this new method could identify children at risk of gingivitis by complementing hemoglobin detection with protein and buffering capacity detection.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты