ArticleJournal of clinical medicine2019
A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year.
Article in Journal of clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction models for the complication incidence and survival rate of dental implants-a systematic review and critical appraisal.International journal of implant dentistry · 2025Pooled it
- Residual bone level as a prognostic factor in the surgical treatment of peri-implantitis.Frontiers in dental medicine · 2024Review
- Peri-Implant Diseases: Diagnosis, Clinical, Histological, Microbiological Characteristics and Treatment Strategies. A Narrative Review.Antibiotics (Basel, Switzerland) · 2020Review
- Science, Innovation and Education as Pillars of High-Quality Implant Dentistry: Overcoming Challenges through Innovation Dictates Trends.Journal of clinical medicine · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis investigation, based on a 1-year retrospective cohort study, aimed to estimate and validate a prognostic model for ailing and failing implants due to peri-implant disease.
methodsA total of 240 patients (male: 97; female: 143; average age of 57.3 years) with at least one ailing or failing implant were included: 120 patients for model derivation and 120 patients for model validation. The primary outcome measure was the implant status: success, defined as the arrest of the disease, or failure defined as implant extraction, prevalence or re-incidence of peri-implant disease). Potential prognostic risk indicators were collected at the baseline evaluation. The relative risk (RR) was estimated for the predictors through logistic regression and the c-statistic (95% confidence interval) was calculated for both derivation and validation sets. The significance level was set at 5%.
resultsThe risk model retrieved the prognostic factors age (RR = 1.04), history of Periodontitis (RR = 3.13), severe peri-implant disease status (RR = 3.26), implant length (RR = 3.52), early disease development (RR = 3.99), with good discrimination in both the derivation set (0.763 [0.679; 0.847]) and validation set (0.709 [0.616; 0.803]).
conclusionsA prognostic risk model for estimating the outcome of implants with peri-implant disease is available, with a good performance considering the c-statistic evaluation.
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