ArticleClinical oral investigations2020
Clustering effects of oral conditions based on clinical and radiographic examinations.
Article in Clinical oral investigations, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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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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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Effectiveness of Endoscope-Assisted Subgingival Debridement Versus Repeated Root Surface Debridement or Access Flap Periodontal Surgery in Step 3 Periodontal Therapy: A Systematic Review and Meta-Analysis.Clinical and experimental dental research · 2025Pooled it
- Diagnostic Accuracy of Panoramic Radiography for Assessing Maxillary Posterior Root Protrusion into the Maxillary Sinus: A Cluster-Adjusted Prediction Model Using CBCT as Reference.Diagnostics (Basel, Switzerland) · 2026Article
- Unaccounted clustering assumptions still compromise inferences in cluster randomized trials in orthodontic research.Korean journal of orthodontics · 2024Article
- Detection of Proximal Caries Lesions on Bitewing Radiographs Using Deep Learning Method.Caries research · 2022Article
- Impact of Image Context on Deep Learning for Classification of Teeth on Radiographs.Journal of clinical medicine · 2021Article
- Generalizability of Deep Learning Models for Caries Detection in Near-Infrared Light Transillumination Images.Journal of clinical medicine · 2021Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe intra-class correlation coefficient (ICC) is a measure of intra-subject clustering effects. A priori estimates of the ICC and the associated design effect (DE) are required for sample size estimation in clustered studies, and should be considered during their analysis, too. We aimed to determine the clustering effects of carious lesions, apical lesions, periodontal bone loss, and periodontal pocketing, assessed in clinical or radiographic examinations.
methodsA subsample of patients (n = 175) enrolled in the fifth German Oral Health Study provided data on clinically determined carious teeth (i.e., with untreated carious lesions, WHO method) as well as teeth with periodontal pocketing (i.e., with maximum probing-pocket-depths ≥ 4 mm). A sample of panoramic radiographs (n = 85) from randomly chosen patients, examined from 2010 to 2017 at the Charité dental hospital, provided data on radiographically determined carious teeth (i.e., with lesions extending into dentine or enamel), teeth with apical lesions (determined by dentists via majority vote), and teeth with periodontal bone loss (≥ 20% of root-length). The ICC and its 95% confidence interval (95% CI) were determined.
resultsThere were 3839 and 1961 teeth assessed in clinical and radiographic evaluations, respectively. For clinically or radiographically determined carious lesions, the ICC (95% CI) was 0.20 (0.16-0.24) or 0.19 (0.14-0.25), respectively. For clinical pocketing or radiographic bone loss, the ICC was 0.40 (0.35-0.46) or 0.30 (0.24-0.38), respectively. The lowest ICC was found for apical lesions at 0.08 (0.06-0.13).
conclusionsThe ICC varied between assessment methods and conditions. Clustered trials should account for this during study planning and data analysis. CLINICAL RELEVANCE: Within the limitations of this study, and considering the risk of selection bias and the limited sample sizes of both datasets, clustering effects were substantial but varied between dental conditions. Studies not accounting for this during planning and analysis may yield misleading estimates if clustering is present.
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