Characterization of glycated hemoglobin based on Raman spectroscopy and artificial neural networks

González-Viveros, N.; Castro‐Ramos, J.; Gómez-Gil, Pilar; Cerecedo-Núñez, Héctor H.

doi:10.1016/j.saa.2020.119077

Cited by 22 publications

(9 citation statements)

References 53 publications

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“…In a variety of visceral heart disease, about 20%~40% are pulmonary heart disease [ 21 – 24 ]. Pulmonary heart disease is mostly induced by chronic obstructive pulmonary disease, and it is a slow occurrence and development process [ 25 ]. If the condition is not controlled in time, it may lead to right heart failure, leading to the death of end-stage patients.…”

Section: Discussionmentioning

confidence: 99%

The Combination Clinical Value of Plasma Brain Natriuretic Peptide and Serum HbAlc in the Diagnosis of Chronic Pulmonary Heart Disease

Jia¹

2022

Computational and Mathematical Methods in Medicine

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Objective. To analyze the combination clinical value of plasma brain natriuretic peptide and serum glycated hemoglobin (HbAlc) in chronic pulmonary heart disease. Methods. A total of 200 patients with chronic pulmonary heart disease admitted to our hospital from January 2021 to January 2022 were selected as the observation group, and 200 healthy subjects were selected as the control group during the same period. All subjects were examined by an ECG vector map and plasma BNP, and HbAlc levels were detected to analyze the value and clinical significance of each index in single diagnosis and combined diagnosis. Results. Plasma BNP and HbAlc levels in the observation group were significantly higher than those in the control group ( P < 0.05 ). There were 154 BNP positive, 146 HbAlc positive, 164 parallel combined diagnosis positive, and 132 serial combined diagnosis positive. Sensitivity of series combination diagnosis was significantly higher than other indexes ( P < 0.05 ); especially, parallel combination diagnosis was significantly higher than other indexes ( P < 0.05 ). Besides, area under the ROC curve of parallel combination diagnosis and series combination diagnosis was significantly higher than that of each index alone diagnosis ( P < 0.05 ). Conclusion. In the diagnosis of chronic pulmonary heart disease, the combination of plasma BNP and HbAlc can effectively improve the diagnostic specificity and sensitivity, as well as improve the area under the ROC curve.

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Section: Discussionmentioning

confidence: 99%

The Combination Clinical Value of Plasma Brain Natriuretic Peptide and Serum HbAlc in the Diagnosis of Chronic Pulmonary Heart Disease

Jia¹

2022

Computational and Mathematical Methods in Medicine

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“…Raman spectroscopy‐based detection of HbA1c has been demonstrated in vitro, under well‐controlled conditions, and at high concentrations [17]. However, it is unclear whether Raman spectroscopy can be sensitive to HbA1c concentrations in vivo in conditions akin to a clinical setting.…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Raman spectroscopy as a potential in vivo tool to screen for pre‐diabetes and diabetes

Guevara

Torres‐Galván

González

et al. 2022

Journal of Biophotonics

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In this article, we investigated the feasibility of using Raman spectroscopy and multivariate analysis method to noninvasively screen for prediabetes and diabetes in vivo. Raman measurements were performed on the skin from 56 patients with diabetes, 19 prediabetic patients and 32 healthy volunteers. These spectra were collected along with reference values provided by the standard glycated hemoglobin (HbA1c) assay. A multiclass principal component analysis and support vector machine (PCA‐SVM) model was created from the labeled Raman spectra and was validated through a two‐layer cross‐validation scheme. Classification accuracy of the model was 94.3% with an area under the receiver operating characteristic curve AUC of 0.76 (0.65–0.84) for the prediabetic group, 0.86 (0.71–0.93) for the diabetic group and 0.97(0.93–0.99) for the control group. Our results suggest the feasibility of using Raman spectroscopy for the classification of prediabetes and diabetes in vivo.

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“…A nonlinear regression model based on a feed-forward neural network was then built to predict the unknown concentration of HbA1c in different solutions, which resulted in a low root mean square error of 0.08% AE 0.04 after fivefold cross-validation (CV). 37 While this work does not directly investigate diagnosing diabetes, the successful results indicate that future work could extend toward monitoring the levels of HbA1c in blood samples for both detecting and monitoring the progression of the disease.…”

Section: Monitoring Glycated Hemoglobin Levels For Indicating Diabetesmentioning

confidence: 99%

Vibrational Spectroscopy for Detection of Diabetes: A Review

Ralbovsky

Lednev

2021

Appl Spectrosc

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Type II diabetes mellitus (T2DM) is a metabolic disorder that is characterized by chronically elevated glucose caused by insulin resistance. Although T2DM is manageable through insulin therapy, the disorder itself is a risk factor for much more dangerous diseases including cardiovascular disease, kidney disease, retinopathy, Alzheimerâs disease, and more. T2DM affects 450 million people worldwide and is attributed to causing over 4 million deaths each year. Current methods for detecting diabetes typically involve testing a personâs glycated hemoglobin levels as well as blood sugar levels randomly or after fasting. However, these methods can be problematic due to an individualâs levels differing on a day-to-day basis or being affected by diet or environment, and due to the lack of sensitivity and reliability within the tests themselves. Vibrational spectroscopic methods have been pursued as a novel method for detecting diabetes accurately and early-on in a minimally invasive manner. This review summarizes recent research, since 2015, which has used infrared or Raman spectroscopy for the purpose of developing a fast and accurate method for diagnosing diabetes. Based on critical evaluation of the reviewed work, vibrational spectroscopy has the potential to improve and revolutionize the way diabetes is diagnosed, thereby allowing for faster and more effective treatment of the disorder.

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Characterization of glycated hemoglobin based on Raman spectroscopy and artificial neural networks

Cited by 22 publications

References 53 publications

The Combination Clinical Value of Plasma Brain Natriuretic Peptide and Serum HbAlc in the Diagnosis of Chronic Pulmonary Heart Disease

The Combination Clinical Value of Plasma Brain Natriuretic Peptide and Serum HbAlc in the Diagnosis of Chronic Pulmonary Heart Disease

Feasibility of Raman spectroscopy as a potential in vivo tool to screen for pre‐diabetes and diabetes

Vibrational Spectroscopy for Detection of Diabetes: A Review

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