Background: This prospective cohort study aimed to assess the predictability and survival rates of dental implant treatment in edentulous patients while identifying potential factors contributing to implant failure.
Material And Methods: A total of 80 outpatients, receiving 166 dental implants between September 2015 and November 2017 in two private dental clinics, were included in this study. Patient and implant characteristics, surgical procedures, primary stability, prosthetic rehabilitation, failure analysis, and survival rates were analyzed.
Results: The majority of patients (53.75%) received a single implant for treating single-gap edentulism, with 6.25% requiring implants for fully edentulous jaws. Most implants (66.87%) were Avinent Ocean IC implants with specific design features. Surgical placement primarily occurred in healed pristine bone (78.31%), immediate implants in fresh extraction sockets (19.88%), and bone regeneration was simultaneous in 15.66% of cases. While 54.82% of implants achieved primary stability over 35Ncm, none exceeded 45Ncm, and only 4.82% failed to attain primary stability. Prosthetic rehabilitation revealed that 13.25% received immediate loading prostheses. During follow-up, four implants failed, resulting in a 2.41% failure rate, with bruxism (HR: 96.62; < 0.001) and absence of primary stability (HR: 23.54; < 0.001) significantly associated with implant failure. The cumulative survival rate at 24 months was 97.44%.
Conclusions: This study demonstrates the high predictability and survival rates of dental implant treatment in edentulous patients, consistent with established standards. Factors such as bruxism and primary stability may impact early implant failure. Dental implants remain a reliable treatment option, boasting a 97.44% cumulative survival rate at 24 months. Further research is required to explore implant failure indicators and multifactorial influences. Dental implants, survival, edentulous patients.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11231890 | PMC |
| http://dx.doi.org/10.4317/jced.61457 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
High-Throughput Chemotherapeutic Drug Screening System for Gastric Cancer (Cure-GA).
Ann Surg Oncol
January 2025
Department of Surgery, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Background: Three dimensional (3D) cell cultures can be effectively used for drug discovery and development but there are still challenges in their general application to high-throughput screening. In this study, we developed a novel high-throughput chemotherapeutic 3D drug screening system for gastric cancer, named 'Cure-GA', to discover clinically applicable anticancer drugs and predict therapeutic responses.
Methods: Primary cancer cells were isolated from 143 fresh surgical specimens by enzymatic treatment.
Evaluation of bioaccessibility, metabolic clearance and interaction with xenobiotic receptors (PXR and AhR) of cinnamaldehyde.
Food Chem (Oxf)
June 2025
National Center for Natural Products Research, School of Pharmacy, The University of Mississippi, MS 38677, United States.
Cinnamon is one of the oldest known spices used in various food delicacies and herbal formulations. Cinnamaldehyde is a primary active constituent of cinnamon and substantially contributes to the food additive and medicinal properties of cinnamon. This report deals with cinnamaldehyde bioaccessibility, metabolic clearance, and interaction with human xenobiotic receptors (PXR and AhR).
View Article and Find Full Text PDFOptimal Machine Learning Models for Developing Prognostic Predictions in Patients With Advanced Cancer.
Cureus
December 2024
Mathematics, Keio University, Yokohama, JPN.
Context: Accurate prognosis prediction for cancer patients in palliative care is critical for clinical decision-making and personalized care. Traditional statistical models have been complemented by machine learning approaches; however, their comparative effectiveness remains underexplored.
Objectives: To assess the prognostic accuracy of statistical and machine learning models in predicting 30-day survival in patients with advanced cancer using objective data, such as the result of the blood test.
Microbial communities in the phyllosphere and endosphere of Norway spruce under attack by .
Front Microbiol
January 2025
Department of Forest Sciences, Faculty of Agriculture and Forestry, University of Helsinki, Helsinki, Finland.
species complex has been regarded as the most destructive disease agent of conifer trees in boreal forests. Tree microbiome can regulate the plant-pathogen interactions by influencing both host resistance and pathogen virulence. Such information would help to improve the future health of forests and explore strategies to enhance ecosystem stability.
View Article and Find Full Text PDFChemical Dissipation from Outdoor Plastics: The Significant Impact of Transformation Processes Revealed by Adjusted Mass Transfer Modeling.
Environ Sci Technol
January 2025
Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), Dalian Key Laboratory on Chemicals Risk Control and Pollution Prevention Technology, School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China.
Chemicals in plastics raise significant concerns for potential adverse environmental and health impacts. However, dissipation kinetics and fluxes of chemicals from outdoor plastic products remain largely uncharacterized, hindering the accurate assessment of their environmental exposure. This study quantified outdoor dissipation profiles for 20 "priority" chemicals, including sunscreens (benzophenone, benzophenone-3, octyl salicylate, etc.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!