Results 131 to 140 of about 14,465 (253)

Restoring the dental aesthetic

Journal of Clinical and Experimental Dentistry, 2017
P Gallart Manchon, C Bastus Bachs, J Espona Roig, L Jane Noblom   +3 more
openaire   +1 more source

Histogram‐Corrected Intraoral Photographs for Early Gingivitis Screening in Orthodontic Patients

International Journal of Dental Hygiene, EarlyView.
ABSTRACT Objectives Gingivitis has a significant impact on periodontal health, both during and after orthodontic treatment. Early detection and management are essential for minimizing tissue damage. This study investigated an early gingivitis detection method using intraoral photographs (IOPs) taken before, at the midpoint (MO), and three‐quarters of ...
Ji‐Youn Kim, Kyuseok Kim, Han‐Na Kim
wiley   +1 more source

The influence of obstructive sleep apnea on self-perceived dental aesthetics and need for orthodontic treatment among the general population in Makkah, Saudi Arabia. [PDF]

J Orthod Sci, 2022
Alotaibi SD, Alotaibi AS, Barashi MA, Khojah MZ, Rajeh MT.   +4 more
europepmc   +1 more source

Comprehensive Clinical Evaluation and Risk Indicators for Furcation Involvement in Molars: A Study in a Population With Limited Access to Dental Care

International Journal of Dental Hygiene, EarlyView.
ABSTRACT Aims To describe the occurrence, extent and severity of furcation involvement (FI) in molars and to evaluate the risk indicators associated with FI. Material and Methods This cross‐sectional study is nested within a representative sample of individuals living in a rural area.
Flávia Letícia Bueno Menk, Ticiane de Góes Mário Ferreira, Fabrício Batistin Zanatta, Karen Finger Tatsch, Leandro Machado Oliveira, Carlos Heitor Cunha Moreira   +5 more
wiley   +1 more source

Is Psychosocial Impact of Dental Aesthetics Questionnaire (PIDAQ) Valid for the Indian Population?-A Psychometric Study. [PDF]

J Int Soc Prev Community Dent, 2021
Monisha J, Peter E, Ani GS.
europepmc   +1 more source

Machine Learning‐Based Prediction of Dental Caries in 12‐Year‐Old Adolescents: A Nationwide Cross‐Sectional Study in Korea

International Journal of Dental Hygiene, EarlyView.
ABSTRACT Objective We aimed to develop and evaluate machine learning models to support population‐level risk stratification for dental caries in the permanent dentition of 12‐year‐old Korean children and to visualise the relative importance of key predictors.
Gahyun Cho, Hae‐Young Kim, Ki‐Bong Choi, Sunmi Song, Junesun Kim   +4 more
wiley   +1 more source

Short Versions of the Arabic Psychosocial Impact of Dental Aesthetics Questionnaire for Yemeni Adolescents: Cross-Sectional Derivation and Validation. [PDF]

Children (Basel), 2022
Alsanabani AAM, Yusof ZYM, Wan Hassan WN, Aldhorae K, Alyamani HA.   +4 more
europepmc   +1 more source

Validity and Reliability of the Arabic Version of the Psychosocial Impact of Dental Aesthetics Questionnaire for Yemeni Adolescents. [PDF]

Children (Basel), 2021
Alsanabani AAM, Yusof ZYM, Wan Hassan WN, Aldhorae K, Alyamani HA.   +4 more
europepmc   +1 more source

Multicenter RCT 6‐Year Survival of Zirconia‐Reinforced Lithium Silicate Endocrowns: 90° Shoulder Versus Butt‐Joint Margins

International Endodontic Journal, EarlyView.
ABSTRACT Objectives Margin design significantly influences endocrown biomechanical performance. Nevertheless, long‐term clinical data comparing margin designs within a singular zirconia‐reinforced lithium silicate (ZLS) system remain scarce. This study reports the 6‐year follow‐up results of a multicenter, prospective, randomized, assessor‐blinded ...
Ping Xiao, Ziting Zheng, Yuting Zeng, Xiaoyu Lin, Jiayao Mo, Liya Chen, Jilei Wang, Yuan Wu, Zhongchun Tong, Wenjuan Yan   +9 more
wiley   +1 more source

Risk Factors and Management of Gingival Enlargement: A Systematic Review and Meta‐Analysis

Journal of Clinical Periodontology, EarlyView.
ABSTRACT Objective To identify risk factors/indicators of gingival enlargement (GE) and to summarise evidence for its management. Methods A systematic review was undertaken following PRISMA guidelines and divided into PECOTS and PICOTS questions, related to risk factors/indicators and treatment studies, respectively.
Luigi Nibali, Emily Ming‐Chieh Lu, Helvis E. S. Paz, Jing Kang, Nagihan Bostanci, Georgios N. Belibasakis   +5 more
wiley   +1 more source