The relative area score for sublingual varices reliability measurement: a diagnostic study.

BACKGROUND: Sublingual varices (SV) and their predictive potential for other clinical parameters is a much studied topic in oral medicine. SVs have been well studied as predictive markers for many common diseases such as arterial hypertension, cardiovascular disease, smoking, type 2 diabetes mellitus and age. Despite many prevalence studies, it is still unclear how the reliability of SV inspection affects its predictive power. The aim of this study was to quantify the inspection reliability of SV. METHODS: In a diagnostic study, the clinical inspection of 78 patients by 23 clinicians was examined for the diagnosis of SV. Digital images of the underside of the tongue were taken from each patient. The physicians were then asked to rate them for the presence of sublingual varices (0/1) in an online inspection experiment. Statistical analysis for inter-item and inter-rater reliability was performed in a τ-equivalent measurement model with Cronbach's [Formula: see text] and Fleiss κ. RESULTS: The interrater reliability for sublingual varices was relatively low with κ = 0.397. The internal consistency of image findings for SV was relatively high with α≈ 0.937. This shows that although SV inspection is possible in principle, it has a low reliability R. This means that the inspection finding (0/1) of individual images often cannot be reproduced stably. Therefore, SV inspection is a difficult task of clinical investigation. The reliability R of SV inspection also limits the maximum linear correlation [Formula: see text] of SV with an arbitrary other parameter Y. The reliability of SV inspection R = 0.847 limits the maximum correlation to [Formula: see text] (SV, Y) = 0,920-a 100% correlation was a priori not achievable in our sample. To overcome the problem of low reliability in SV inspection, we propose the RA (relative area) score as a continuous classification system for SV, which normalises the area of visible sublingual veins to the square of the length of the tongue, providing a dimensionless measure of SV. CONCLUSIONS: The reliability of the SV inspection is relatively low. This limits the maximum possible correlation of SV with other (clinical) parameters. SV inspection reliability is an important indicator for the quality of SV as a predictive marker. This should be taken into account when interpreting previous studies on SV and has implications for future studies. The RA score could help to objectify the SV examination and thus increase its reliability.

Influence of soft tissue grafting, orofacial implant position, and angulation on facial hard and soft tissue thickness at immediately inserted and provisionalized implants in the anterior maxilla.

BACKGROUND: Resorption of hard and soft tissues following immediate implant insertion is frequently reported. Data regarding the influencing factors on facial tissue thickness are rare. PURPOSE: This retrospective study investigated the impact of connective tissue grafting, the orofacial angulation and position of immediately inserted and provisionalized implants on the facial hard and soft tissue thickness in the anterior maxilla within a 1- to 5-year follow-up. MATERIAL AND METHODS: Implants with the prerequisite of having preoperative and postoperative cone beam computed tomography (CBCT) and a follow-up of 1 to 5 years were included. Facial bone deficiencies were grafted flaplessly with autogenous bone in all sites. In a subgroup of implants additional connective tissue grafting was performed, whereas the remaining implants were not grafted with soft tissue. The orofacial tooth and implant angulation, the change of horizontal position and the facial bone thickness were measured by CBCT, the facial mucosa thickness by an ultrasonic device. RESULTS: In total, 76 implants were placed in 55 patients. Sixty-nine sites showed a facial bone defect. Thirty-eight received a connective tissue graft additionally. All implants were still in function after a mean follow-up of 36 months. The mean thickness of the facial mucosa was 1.72 mm at 1 mm, 1.63 mm at 4 mm, 1.52 mm at 6 mm, and 1.66 mm at 9 mm apically to mucosal margin. The bone thickness was 0.02, 0.25, and 0.36 mm initially and 1.32, 1.26, and 1.11 mm finally at 1, 3, and 6 mm apically to implant shoulder level. Mixed model analysis revealed an impact of the preoperative bone status on the facial bone increase. The facial soft tissue thickness was significantly influenced by the gingival biotype. CONCLUSIONS: The results indicate that an initial severe hard tissue defect allows for significant bone regeneration. The facial soft tissue thickness is primarily influenced by the gingival biotype.