Abstract
Chronic renal failure (CRF) is a clinically serious kidney disease. If the patient is not treated in a timely manner, CRF will develop into uremia. However, current diagnostic methods, such as routine blood examinations and medical imaging, have low sensitivity. Therefore, it is important to explore new and effective diagnostic methods for CRF, such as serum spectroscopy. This study proposes a cost-effective and reliable method for detecting CRF based on Fourier transform infrared (FT-IR) spectroscopy and a support vector machine (SVM) algorithm. We measured and analyzed the FT-IR spectra of serum from 44 patients with CRF and 54 individuals with normal renal function. The partial least squares (PLS) algorithm was applied to reduce the dimensionality of the high-dimensional spectral data. The samples were input into the SVM after division by the Kennard–Stone (KS) algorithm. Compared with other models, the SVM optimized by a grid search (GS) algorithm performed the best. The sensitivity of our diagnostic model was 93.75%, the specificity was 100%, and the accuracy was 96.97%. The results demonstrate that FT-IR spectroscopy combined with a pattern recognition algorithm has great potential in screening patients with CRF.
Highlights
Chronic renal failure (CRF) refers to chronic and persistent renal impairment with various causes, resulting in renal sclerosis and nephron loss, and it is accompanied by many complications, such as cardiovascular disease [1,2,3,4]
Glomerular filtration function refers to the function of the kidneys whereby metabolites, poisons, and excessive water in the body are removed. e main methods for examining glomerular filtration function include detection of serum creatinine (Scr) concentration and creatinine clearance (Ccr), as well as radionuclide measurement of the glomerular filtration rate (GFR) [7, 8]
We can see the difference in Fourier transform infrared (FT-IR) spectra at the bottom of Figure 1, and this is the basis for differentiating the FT-IR spectra of the CRF patients from those of the control group
Summary
Chronic renal failure (CRF) refers to chronic and persistent renal impairment with various causes, resulting in renal sclerosis and nephron loss, and it is accompanied by many complications, such as cardiovascular disease [1,2,3,4]. Current routine examinations for the diagnosis of CRF include examination of blood, urine, and glomerular filtration function. Glomerular filtration function refers to the function of the kidneys whereby metabolites, poisons, and excessive water in the body are removed. E main methods for examining glomerular filtration function include detection of serum creatinine (Scr) concentration and creatinine clearance (Ccr), as well as radionuclide measurement of the glomerular filtration rate (GFR) [7, 8]. The Scr and Ccr values may be significantly different for different people, which may make it difficult for clinicians to make a correct diagnosis. According to a research by Sanchez, the sensitivity of Scr is only 46% by using a GFR of 90 mL/min as a cutoff value [9]. Erefore, it is important to find a rapid, objective, and accurate method for diagnosing CRF CRF can be diagnosed by medical imaging such as ultrasonography, but this process relies mainly on the doctor’s expertise and subjective experience. erefore, it is important to find a rapid, objective, and accurate method for diagnosing CRF
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