Application of a Novel Biosensor for Salivary Conductivity in Detecting Chronic Kidney Disease.
Chen-Wei LinYuan-Hsiung TsaiYen-Pei LuJen-Tsung YangMei-Yen ChenTung-Jung HuangRui-Cian WengChun-Liang LinPublished in: Biosensors (2022)
The prevalence of chronic kidney disease (CKD) is increasing, and it brings an enormous healthcare burden. The traditional measurement of kidney function needs invasive blood tests, which hinders the early detection and causes low awareness of CKD. We recently designed a device with miniaturized coplanar biosensing probes for measuring salivary conductivity at an extremely low volume (50 μL). Our preliminary data discovered that the salivary conductivity was significantly higher in the CKD patients. This cross-sectional study aims to validate the relationship between salivary conductivity and kidney function, represented by the estimated glomerular filtration rate (eGFR). We enrolled 214 adult participants with a mean age of 63.96 ± 13.53 years, of whom 33.2% were male. The prevalence rate of CKD, defined as eGFR < 60 mL/min/1.73 m 2 , is 11.2% in our study. By multivariate linear regression analyses, we found that salivary conductivity was positively related to age and fasting glucose but negatively associated with eGFR. We further divided subjects into low, medium, and high groups according to the tertials of salivary conductivity levels. There was a significant trend for an increment of CKD patients from low to high salivary conductivity groups (4.2% vs. 12.5% vs. 16.9%, p for trend: 0.016). The receiver operating characteristic (ROC) curves disclosed an excellent performance by using salivary conductivity combined with age, gender, and body weight to diagnose CKD (AUC equal to 0.8). The adjusted odds ratio of CKD is 2.66 (95% CI, 1.10-6.46) in subjects with high salivary conductivity levels. Overall, salivary conductivity can serve as a good surrogate marker of kidney function; this real-time, non-invasive, and easy-to-use portable biosensing device may be a reliable tool for screening CKD.
Keyphrases
- chronic kidney disease
- end stage renal disease
- healthcare
- small cell lung cancer
- epidermal growth factor receptor
- peritoneal dialysis
- newly diagnosed
- body weight
- ejection fraction
- risk factors
- type diabetes
- mental health
- adipose tissue
- weight loss
- machine learning
- big data
- patient reported outcomes
- prognostic factors
- blood glucose
- insulin resistance
- living cells
- social media
- health information