Associations between Periodontitis and COPD: An Artificial Intelligence-Based Analysis of NHANES III
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Data Handling and Statistical Analysis
- CPU: AMD Ryzen 9 5950X 16-Core Processor (Santa Clara, CA, USA);
- RAM: 64 GB;
- GPU: NVIDIA Geforce RTX 3090 (Santa Clara, CA, USA);
- Python version: 3.10.4 (64-bit) (Wilmington, DE, USA);
- OS: Windows 10 (Redmond, WA, USA).
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Low-Risk Cluster | High-Risk Cluster | ||||||||
---|---|---|---|---|---|---|---|---|---|
Count | Row N % | Mean | Standard Deviation | Count | Row N % | Mean | Standard Deviation | ||
COPD diagnosis | no | 7187 | 65.5% | 3780 | 34.5% | ||||
yes | 161 | 15.0% | 915 | 85.0% | |||||
Race/ethnicity | Non-Hispanic white | 1946 | 44.0% | 2477 | 56.0% | ||||
Non-Hispanic black | 2295 | 66.4% | 1163 | 33.6% | |||||
Mexican-American | 2786 | 76.3% | 867 | 23.7% | |||||
Other | 321 | 63.1% | 188 | 36.9% | |||||
Sex | Male | 3525 | 61.1% | 2242 | 38.9% | ||||
Female | 3823 | 60.9% | 2453 | 39.1% | |||||
Upper-quadrant periodontal assessments | 1 | 3694 | 60.7% | 2389 | 39.3% | ||||
2 | 3654 | 61.3% | 2306 | 38.7% | |||||
Lower-quadrant periodontal assessments | 3 | 3659 | 61.5% | 2291 | 38.5% | ||||
4 | 3689 | 60.5% | 2404 | 39.5% | |||||
Dentate status | Completely edentulous | 0 | 0.0% | 0 | 0.0% | ||||
Edentulous in one arch | 0 | 0.0% | 177 | 100.0% | |||||
Teeth present | 7348 | 61.9% | 4518 | 38.1% | |||||
Age at interview (Screener) | 28 | 11 | 53 | 16 | |||||
Poverty income ratio (unimputed income) | 3 | 2 | 2 | 2 | |||||
Pulse rate (beats/min) (age 5+ years) | 74 | 12 | 75 | 12 | |||||
Overall average K1, systolic, BP (age 5+) | 114 | 12 | 129 | 19 | |||||
Overall average K5, diastolic, BP (age 5+) | 69 | 11 | 76 | 10 | |||||
Body mass index | 25.6 | 5.9 | 27.5 | 5.7 | |||||
Sum of permanent DMFS due to disease | 12 | 11 | 56 | 23 | |||||
Sum of permanent DFMS due to any cause | 13 | 11 | 58 | 23 | |||||
Sum of permanent DFS | 8 | 7 | 30 | 19 | |||||
Sum of permanent DMFT due to disease | 5 | 4 | 16 | 5 | |||||
Sum of permanent DMFT due to any cause | 5 | 4 | 17 | 5 | |||||
Bleeding_Percentage | 10.43 | 14.37 | 7.88 | 11.26 | |||||
Furcation_SUM | 0.05 | 0.30 | 0.57 | 1.40 | |||||
MAL | 0.58 | 0.53 | 1.51 | 1.16 |
Algorithm | Accuracy | AUC |
---|---|---|
Logistic regression | 0.884 | 0.835 |
Random forest classifier | 0.883 | 0.819 |
SGD classifier | 0.879 | 0.804 |
K-nearest neighbors | 0.872 | 0.723 |
Decision tree classifier | 0.823 | 0.608 |
GaussianNB | 0.803 | 0.807 |
SVM | 0.884 | 0.685 |
Custom CNN | 0.887 | 0.953 |
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Vollmer, A.; Vollmer, M.; Lang, G.; Straub, A.; Shavlokhova, V.; Kübler, A.; Gubik, S.; Brands, R.; Hartmann, S.; Saravi, B. Associations between Periodontitis and COPD: An Artificial Intelligence-Based Analysis of NHANES III. J. Clin. Med. 2022, 11, 7210. https://doi.org/10.3390/jcm11237210
Vollmer A, Vollmer M, Lang G, Straub A, Shavlokhova V, Kübler A, Gubik S, Brands R, Hartmann S, Saravi B. Associations between Periodontitis and COPD: An Artificial Intelligence-Based Analysis of NHANES III. Journal of Clinical Medicine. 2022; 11(23):7210. https://doi.org/10.3390/jcm11237210
Chicago/Turabian StyleVollmer, Andreas, Michael Vollmer, Gernot Lang, Anton Straub, Veronika Shavlokhova, Alexander Kübler, Sebastian Gubik, Roman Brands, Stefan Hartmann, and Babak Saravi. 2022. "Associations between Periodontitis and COPD: An Artificial Intelligence-Based Analysis of NHANES III" Journal of Clinical Medicine 11, no. 23: 7210. https://doi.org/10.3390/jcm11237210