Originalartikel | erschienen - Druck | peer reviewed
Development and External Validation of a Multivariable Prediction Model to Identify Nondiabetic Hyperglycemia and Undiagnosed Type 2 Diabetes: Diabetes Risk Assessment in Dentistry Score (DDS)
JOURNAL OF DENTAL RESEARCH
2023 / Februar
;
102(2):
170 - 177
Bibliometrische Indikatoren
Impact Factor = 5,7
DOI = 10.1177/00220345221129807
PubMed-ID = 36254392
Autoren
Beteiligte Einrichtungen
Abstract
The aim of this study was to develop and externally validate a score for use in dental settings to identify those at risk of undiagnosed nondiabetic hyperglycemia (NDH) or type 2 diabetes (T2D). The Studies of Health in Pomerania (SHIP) project comprises 2 representative population-based cohort studies conducted in northeast Germany. SHIP-TREND-0, 2008 to 2012 (the development data set) had 3,339 eligible participants, with 329 having undiagnosed NDH or T2D. Missing data were replaced using multiple imputation. Potential covariates were selected for inclusion in the model using backward elimination. Heuristic shrinkage was used to reduce overfitting, and the final model was adjusted for optimism. We report the full model and a simplified paper-based point-score system. External validation of the model and score employed an independent data set comprising 2,359 participants with 357 events. Predictive performance, discrimination, calibration, and clinical utility were assessed. The final model included age, sex, body mass index, smoking status, first-degree relative with diabetes, presence of a dental prosthesis, presence of mobile teeth, history of periodontal treatment, and probing pocket depths ≥5 mm as well as prespecified interaction terms. In SHIP-TREND-0, the model area under the curve (AUC) was 0.72 (95% confidence interval [CI] 0.69, 0.75), calibration in the large was -0.025. The point score AUC was 0.69 (95% CI 0.65, 0.72), with sensitivity of 77.0 (95% CI 76.8, 77.2), specificity of 51.5 (95% CI 51.4, 51.7), negative predictive value of 94.5 (95% CI 94.5, 94.6), and positive predictive value of 17.0 (95% CI 17.0, 17.1). External validation of the point score gave an AUC of 0.69 (95% CI 0.66, 0.71), sensitivity of 79.2 (95% CI 79.0, 79.4), specificity of 49.9 (95% CI 49.8, 50.00), negative predictive value 91.5 (95% CI 91.5, 91.6), and positive predictive value of 25.9 (95% CI 25.8, 26.0). A validated prediction model involving dental variables can identify NDH or undiagnosed T2DM. Further studies are required to validate the model for different European populations.
Veröffentlicht in
JOURNAL OF DENTAL RESEARCH
Jahr | 2023 |
Monat/Hj. | Februar |
Impact Factor (2023) | 5,7 |
Volume | 102 |
Issue | 2 |
Seiten | 170 - 177 |
Open Access | nein |
Peer reviewed | ja |
Artikelart | Originalartikel |
Artikelstatus | erschienen - Druck |
DOI | 10.1177/00220345221129807 |
PubMed-ID | 36254392 |
Allgemeine Daten zur Fachzeitschrift
Kurzbezeichnung: J DENT RES
ISSN: 0022-0345
eISSN: 1544-0591
Land: USA
Sprache: English
Kategorie(n):
Impact Factor Entwicklung
ISSN: 0022-0345
eISSN: 1544-0591
Land: USA
Sprache: English
Kategorie(n):
- DENTISTRY, ORAL SURGERY & MEDICINE
Impact Factor Entwicklung
Jahr | Impact Factor |
---|---|
2008 | 3,142 |
2009 | 3,458 |
2010 | 3,773 |
2011 | 3,486 |
2012 | 3,826 |
2013 | 4,144 |
2014 | 4,139 |
2015 | 4,602 |
2016 | 4,755 |
2017 | 5,38 |
2018 | 5,125 |
2019 | 4,914 |
2020 | 6,116 |
2021 | 8,924 |
2022 | 7,6 |
2023 | 5,7 |
Forschungsschwerpunkt der Universität
Themenschwerpunkte
Beteiligte Departments
Community Medicine
Projekte
Development of a prediction rule for diagnosing previously unknown diabetes mellitus using information on the dental status
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