Comprehensive orthodontic treatment using miniscrews and digital rehabilitation in a patient with severe recessive dystrophic epidermolysis bullosa.

INTRODUCTION: Epidermolysis bullosa (EB) is a rare genetic disorder characterized by skin fragility and blister formation. The phenotypic presentation is broad with four major types, being Recessive Dystrophic EB (RDEB) the most severe, including oral anomalies such as severe microstomia, ankyloglossia, vestibule obliteration and occlusal anomalies, turning orthodontic treatment into a challenge. AIM: This case report aims to present the comprehensive treatment of a patient with severe RDEB, including periodontal surgery, orthodontic fixed braces with mini-screws and oral rehabilitation with anterior veneers. CASE REPORT: A 27-year-old female patient with severe RDEB received orthodontic treatment in the upper jaw to improve malalignment and anterior crossbite. After 13 months of treatment with fixed appliances, miniscrews were placed in the anterior segment to intrude and procline the upper incisors. Oral surgery was performed to increase the vestibule depth of the upper lip. Once edge-to-edge occlusion was obtained, anterior veneers were placed to improve aesthetic and stabilize occlusion, especially with the lack of posterior support. DISCUSSION: The multidisciplinary treatment approach, involving orthodontic treatment, periodontal surgery and oral rehabilitation, played a crucial role in achieving favorable results. This case highlights the successful use of miniscrews as a viable orthodontic approach for patients with severe RDEB.

Evaluation of Urine and Vaginal Self-Sampling versus Clinician-Based Sampling for Cervical Cancer Screening: A Field Comparison of the Acceptability of Three Sampling Tests in a Rural Community of Cuenca, Ecuador.

Self-sampling methods for HPV testing have been demonstrated to be highly sensitive and specific. The implementation of these methods in settings with a lack of infrastructure or medical attention has been shown to increase the coverage of cervical cancer screening and detect cervical abnormalities in the early stages. The aim of this study is to compare the acceptability of urine and vaginal self-sampling methods versus clinician sampling among rural women. A total of 120 women participated. Each participant self-collected urine and vaginal samples and underwent clinician sampling for Pap smear and HPV testing. After the sample collection, a questionnaire to qualify the device, technique, and individual acceptability was applied, and the additional overall preference of three sample tests was evaluated. Results: The characteristics of the participants were as follows: median age of 35 years; 40.8% were married; 46.7% had a primary level of education; median age of sexual onset of 17.6 years. Compared with clinician sampling, both vaginal self-sampling, OR 20.12 (7.67-52.8), and urine sampling, OR 16.63 (6.79-40.72), were more comfortable; granted more privacy: vaginal self-sampling, OR 8.07 (3.44-18.93), and urine sampling, OR 19.5 (5.83-65.21); were less painful: vaginal self-sampling, OR 0.07 (0.03-0.16), and urine sampling, OR 0.01 (0-0.06); were less difficult to apply: vaginal self-sampling, OR 0.16 (0.07-0.34), and urine sampling, OR 0.05 (0.01-0.17). The overall preference has shown an advantage for vaginal self-sampling, OR 4.97 (2.71-9.12). No statistically significant preference was demonstrated with urine self-sampling versus clinician sampling. Conclusions: Self-sampling methods have a high acceptance in rural communities. Doubts on the reliability of self-sampling often appear to be a limitation on its acceptability. However, the training and education of the community could increase the uptake of these methods.

Radiomics Diagnostic Tool Based on Deep Learning for Colposcopy Image Classification.

BACKGROUND: Colposcopy imaging is widely used to diagnose, treat and follow-up on premalignant and malignant lesions in the vulva, vagina, and cervix. Thus, deep learning algorithms are being used widely in cervical cancer diagnosis tools. In this study, we developed and preliminarily validated a model based on the Unet network plus SVM to classify cervical lesions on colposcopy images. Methodology: Two sets of images were used: the Intel & Mobile ODT Cervical Cancer Screening public dataset, and a private dataset from a public hospital in Ecuador during a routine colposcopy, after the application of acetic acid and lugol. For the latter, the corresponding clinical information was collected, specifically cytology on the PAP smear and the screening of human papillomavirus testing, prior to colposcopy. The lesions of the cervix or regions of interest were segmented and classified by the Unet and the SVM model, respectively. Results: The CAD system was evaluated for the ability to predict the risk of cervical cancer. The lesion segmentation metric results indicate a DICE of 50%, a precision of 65%, and an accuracy of 80%. The classification results' sensitivity, specificity, and accuracy were 70%, 48.8%, and 58%, respectively. Randomly, 20 images were selected and sent to 13 expert colposcopists for a statistical comparison between visual evaluation experts and the CAD tool (p-value of 0.597). Conclusion: The CAD system needs to improve but could be acceptable in an environment where women have limited access to clinicians for the diagnosis, follow-up, and treatment of cervical cancer; better performance is possible through the exploration of other deep learning methods with larger datasets.

Role of Self-Sampling for Cervical Cancer Screening: Diagnostic Test Properties of Three Tests for the Diagnosis of HPV in Rural Communities of Cuenca, Ecuador.

BACKGROUND: HPV primary screening has shown effectiveness for cancer prevention; however, gynaecological examination is considered uncomfortable. Self-sampling methods increase the acceptance of screening. The aim of this study is to compare the sensitivity and specificity of clinician sampling versus vaginal and urine self-sampling for HPV diagnosis. METHODS: A diagnostic test study was conducted in a rural parish of Cuenca, Ecuador. A total of 120 women participated. Each participant self-collected urine and vaginal samples and underwent clinician sampling for HPV testing. The latter was considered as the golden standard. All three samples were processed with the same amplification and hybridization protocol for HPV detection (Hybribio) following the manufacturer's instructions. RESULTS: Characteristics of the participants were: median age 35 years; 40.8% married; 46.7% had a primary level of education; and median age of sexual onset, 17.6 years. The prevalence of any type of HPV with clinician sampling was 15.0%, 17.5% with urine sampling and 18.3% with vaginal self-sampling. Self-sampling sensitivity reached 94.4% (IC 74.2-99.9), and specificity 92.1% (IC 85.2-95.9). Urine sampling had a sensitivity of 88.8% (IC 67.2, 96.9), and specificity 94.1% (IC 67.2-96.9). The negative predictive value was 98.9% (IC 94.2-99.8) for vaginal self-sampling and 97.6% (IC 92.6-99.4) for urine sampling. CONCLUSIONS: This study shows that vaginal and urine self-sampling methods have similar sensitivity and specificity compared with clinician sampling for the diagnosis of HPV. The correlation between HPV genotypes among the three tests is satisfactory.