Issa, Julien OR 0000000264987989 Dotaz Zobrazit nápovědu
This retrospective study aims to investigate the impact of cone-beam computed tomography (CBCT) viewing parameters such as contrast, slice thickness, and sharpness on the identification of the inferior alveolar nerve (IAC). A total of 25 CBCT scans, resulting in 50 IACs, were assessed by two investigators using a three-score system (good, average, and poor) on cross-sectional images. Slice thicknesses of 0.25 mm, 0.5 mm, and 1 mm were tested, along with varying sharpness (0, 6, 8, and 10) and contrast (0, 400, 800, and 1200) settings. The results were statistically analyzed to determine the optimal slice thickness for improved visibility of IAC, followed by evaluating the influence of sharpness and contrast using the optimal thickness. The identified parameters were then validated by performing semi-automated segmentation of the IACs and structure overlapping to evaluate the mean distance. Inter-rater and intra-rater reliability were assessed using Kappa statistics, and inferential statistics used Pearson's Chi-square test. Inter-rater and intra-rater reliability for all parameters were significant, ranging from 69% to 83%. A slice thickness of 0.25 mm showed consistently "good" visibility (80%). Sharpness values of zero and contrast values of 1200 also demonstrated high frequencies of "good" visibility. Overlap analysis resulted in an average mean distance of 0.295 mm and a standard deviation of 0.307 mm across all patients' sides. The study revealed that a slice thickness of 0.25 mm, zero sharpness value, and higher contrast value of 1200 improved the visibility and accuracy of IAC segmentation in CBCT scans. The individual patient's characteristics, such as anatomical variations, decreased bone density, and absence of canal walls cortication, should be considered when using these parameters.
- Publikační typ
- časopisecké články MeSH
Vaccine hesitancy, spurred by misinterpretation of Adverse Events (AEs), threatens public health. Despite sporadic reports of oral AEs post-COVID-19 vaccination, systematic analysis is scarce. This study evaluates these AEs using the Australian Database of Adverse Event Notifications (DAEN). A secondary analysis of DAEN data was conducted, with the analysis period commencing from the start of the COVID-19 vaccination rollout in February 2021 and the inception of the influenza vaccine database in 1971, both through until December 2022. The focus of the analysis was on oral AEs related to COVID-19 and influenza vaccines. Reports were extracted according to a predefined schema and then stratified by vaccine type, sex, and age. Oral paresthesia was the most common oral AE after COVID-19 vaccination (75.28 per 10,000 reports), followed by dysgeusia (73.96), swollen tongue (51.55), lip swelling (49.43), taste disorder (27.32), ageusia (25.85), dry mouth (24.75), mouth ulceration (18.97), oral hypoaesthesia (15.60), and oral herpes (12.74). While COVID-19 and influenza vaccines shared most oral AEs, taste-related AEs, dry mouth, and oral herpes were significantly more common after COVID-19 vaccination. mRNA vaccines yielded more oral AEs than other types. Females had higher oral AE incidence. Most oral AEs did not differ significantly between COVID-19 and influenza vaccination. However, specific oral AEs, particularly taste-related, dry mouth, and oral herpes, were more prevalent after COVID-19 vaccination compared with seasonal influenza, especially in females and mRNA vaccine recipients.
- MeSH
- chřipka lidská * epidemiologie prevence a kontrola MeSH
- COVID-19 * prevence a kontrola MeSH
- lidé MeSH
- vakcinace škodlivé účinky MeSH
- vakcíny proti chřipce * škodlivé účinky MeSH
- vakcíny proti COVID-19 * škodlivé účinky MeSH
- xerostomie * MeSH
- Check Tag
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Austrálie MeSH
This study aims to evaluate the diagnostic accuracy of artificial intelligence in detecting apical pathosis on periapical radiographs. A total of twenty anonymized periapical radiographs were retrieved from the database of Poznan University of Medical Sciences. These radiographs displayed a sequence of 60 visible teeth. The evaluation of the radiographs was conducted using two methods (manual and automatic), and the results obtained from each technique were afterward compared. For the ground-truth method, one oral and maxillofacial radiology expert with more than ten years of experience and one trainee in oral and maxillofacial radiology evaluated the radiographs by classifying teeth as healthy and unhealthy. A tooth was considered unhealthy when periapical periodontitis related to this tooth had been detected on the radiograph. At the same time, a tooth was classified as healthy when no periapical radiolucency was detected on the periapical radiographs. Then, the same radiographs were evaluated by artificial intelligence, Diagnocat (Diagnocat Ltd., San Francisco, CA, USA). Diagnocat (Diagnocat Ltd., San Francisco, CA, USA) correctly identified periapical lesions on periapical radiographs with a sensitivity of 92.30% and identified healthy teeth with a specificity of 97.87%. The recorded accuracy and F1 score were 96.66% and 0.92, respectively. The artificial intelligence algorithm misdiagnosed one unhealthy tooth (false negative) and over-diagnosed one healthy tooth (false positive) compared to the ground-truth results. Diagnocat (Diagnocat Ltd., San Francisco, CA, USA) showed an optimum accuracy for detecting periapical periodontitis on periapical radiographs. However, more research is needed to assess the diagnostic accuracy of artificial intelligence-based algorithms in dentistry.
Dental students are the future leaders of oral health in their respective communities; therefore, their oral health-related attitudes and behaviours are of practical value for primary disease prevention. The present study aimed to evaluate oral health-related knowledge, attitudes, and behaviours of dental students in Arab countries and explore the potential sociodemographic predictors of their oral health outcomes. A multi-centre, cross-sectional study was conducted during the academic year 2019/2020 in three Arab countries: Lebanon, Syria, and Tunisia. The study used a validated Arabic version of the Hiroshima University Dental Behavioural Inventory (HU-DBI) composed of original twenty items that assess the level of oral health-related knowledge, attitudes, and behaviours, and four additional dichotomous items related to tobacco smoking, alcohol drinking, problematic internet use, and regular dental check-up The HU-DBI score ranges between 0 and 12. A total of 1430 students took part in this study, out of which 60.8% were females, 57.8% were enrolled in clinical years, 24.5% were tobacco smokers, 7.2% were alcohol drinkers, and 87% reported internet addiction. The mean HU-DBI score was 6.31 ± 1.84, with Lebanon having the highest score (6.67 ± 1.83), followed by Syria (6.38 ± 1.83) and Tunisia (6.05 ± 1.83). Clinical students (6.78 ± 1.70) had higher HU-DBI scores than their preclinical peers (5.97 ± 1.86). The year-over-year analysis revealed that dental public health and preventive dentistry courses had significantly and positively impacted the undergraduate students' knowledge, attitudes, and behaviours. The gender-based differences were not statistically significant, with a modest trend favouring males, especially oral health behaviours. Tobacco smoking, alcohol drinking, and problematic internet use were associated with lower HU-DBI scores. In the Arab world, the economic rank of the country where the dental students live/study was weakly correlated with the students' mean HU-DBI score.
- MeSH
- Arabové MeSH
- lidé MeSH
- orální hygiena MeSH
- orální zdraví * MeSH
- průřezové studie MeSH
- průzkumy a dotazníky MeSH
- studenti stomatologie * MeSH
- zdravé chování MeSH
- zdraví - znalosti, postoje, praxe MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Libanon MeSH
Since healthcare professionals (HCPs) play a critical role in shaping their local communities' attitudes toward vaccines, HCPs' beliefs and attitudes toward vaccination are of vital importance for primary prevention strategies. The present study was designed as a cross-sectional survey-based study utilizing a self-administered questionnaire to collect data about COVID-19 vaccine booster hesitancy (VBH) among Polish HCPs and students of medical universities (MUSs). Out of the 443 included participants, 76.3% were females, 52.6% were HCPs, 31.8% were previously infected by SARS-CoV-2, and 69.3% had already received COVID-19 vaccine booster doses (VBD). Overall, 74.5% of the participants were willing to receive COVID-19 VBD, while 7.9 and 17.6% exhibited their hesitance and rejection, respectively. The most commonly found promoter for acceptance was protection of one's health (95.2%), followed by protection of family's health (81.8%) and protection of community's health (63.3%). Inferential statistics did not show a significant association between COVID-19 VBH and demographic variables, e.g., age and gender; however, the participants who had been previously infected by SARS-CoV-2 were significantly more inclined to reject the VBD. Protection from severe infection, community transmission, good safety profile, and favorable risk-benefit ratio were the significant determinants of the COVID-19 VBD acceptance and uptake. Fear of post-vaccination side effects was one of the key barriers for accepting COVID-19 VBD, which is consistent with the pre-existing literature. Public health campaigns need to highlight the postulated benefits of vaccines and the expected harms of skipping VBD.
- MeSH
- COVID-19 * epidemiologie prevence a kontrola MeSH
- lidé MeSH
- průřezové studie MeSH
- průzkumy a dotazníky MeSH
- SARS-CoV-2 MeSH
- sekundární imunizace MeSH
- studenti MeSH
- vakcíny proti COVID-19 MeSH
- vakcíny * MeSH
- zdraví - znalosti, postoje, praxe MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Polsko MeSH
