scholarly journals Differential Molecular Signature of Human Saliva Using ATR-FTIR Spectroscopy for Chronic Kidney Disease Diagnosis

2019 ◽  
Vol 30 (5) ◽  
pp. 437-445 ◽  
Author(s):  
Renata PCB Rodrigues ◽  
Emilia MG Aguiar ◽  
Leia Cardoso-Sousa ◽  
Douglas C Caixeta ◽  
Cizilene CFV Guedes ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Ftir Spectroscopy ◽  
Disease Diagnosis ◽  
Molecular Signature ◽  
Second Derivative ◽  
Vibrational Modes ◽  
Derivative Spectra ◽  
Control Subjects ◽  
Second Derivative Spectra

Abstract The symptoms of chronic kidney disease (CKD) are often not specific or absent in the early stages of this illness. Therefore, there is a demand for developing low cost, non-invasive and highly accurate platforms for CKD diagnostics. We hypothesized that the level of specifics salivary components changes when CKD is emplace, which could be clinically used to discriminate CKD patients from healthy subjects. The present study aimed to compare salivary components between CKD patients and matched control subjects by using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The predictive power of salivary components was evaluated by receiver operating characteristic (ROC) curves. Several components were identified, and 4 of them showed different expression (p<0.05) between CKD and control subjects. Thiocyanate (SCN-, 2052 cm-1) and phospholipids/carbohydrates (924 cm-1) vibrational modes using original and second-derivative spectra by ATR-FTIR could potentially be used as salivary biomarkers to differentiate CKD than control subjects. The combination of original and second-derivative spectra by ATR-FTIR of 924 cm-1 vibrational modes could reach 92.8% sensitivity and 85.7% specificity for CKD detection. Despite, the limitation of our investigation, the acquired data indicates that salivary vibrational modes by ATR-FTIR platform should be further explored as an auxiliary diagnostic tool for CKD.

Exploring Patients' Experiences After Chronic Kidney Disease Diagnosis: A Qualitative Study

2020 ◽  
Vol 47 (1) ◽  
pp. 67
Author(s):  
Areti Stavropoulou ◽  
Michael Rovithis ◽  
Maria G. Grammatikopoulou ◽  
Konstantina Kyriakidi ◽  
Andriani Pylarinou ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Qualitative Study ◽  
Disease Diagnosis

Second‐Derivative Spectra for Estimating Crop Residue Cover

1994 ◽  
Vol 86 (2) ◽  
pp. 349-354 ◽  
Author(s):  
Haiping Su ◽  
Michel D. Ransom ◽  
Edward T. Kanemasu ◽  
Tanvir H. Demetriades‐Shah
Keyword(s):  
Crop Residue ◽  
Second Derivative ◽  
Derivative Spectra ◽  
Second Derivative Spectra

Risk Factor Identification, Classification and Prediction Summary of Chronic Kidney Disease

2020 ◽  
Vol 13 ◽  
Author(s):  
Pramila Arulanthu ◽  
Eswaran Perumal
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Disease Diagnosis ◽  
Medical Data ◽  
Machine Learning Algorithms ◽  
World Health ◽  
Medical Field ◽  
Data Set ◽  
Medical Issues ◽  
Health Organization

: The medical data has an enormous quantity of information. This data set requires effective classification for accurate prediction. Predicting medical issues is an extremely difficult task in which Chronic Kidney Disease (CKD) is one of the major unpredictable diseases in medical field. Perhaps certain medical experts do not have identical awareness and skill to solve the issues of their patients. Most of the medical experts may have underprivileged results on disease diagnosis of their patients. Sometimes patients may lose their life in nature. As per the Global Burden of Disease (GBD-2015) study, death by CKD was ranked 17th place and GBD-2010 report 27th among the causes of death globally. Death by CKD is constituted 2·9% of all death between the year 2010 and 2013 among people from 15 to 69 age. As per World Health Organization (WHO-2005) report, 58 million people expired by CKD. Hence, this article presents the state of art review on Chronic Kidney Disease (CKD) classification and prediction. Normally, advanced data mining techniques, fuzzy and machine learning algorithms are used to classify medical data and disease diagnosis. This study reviews and summarizes many classification techniques and disease diagnosis methods presented earlier. The main intention of this review is to point out and address some of the issues and complications of the existing methods. It is also attempts to discuss the limitations and accuracy level of the existing CKD classification and disease diagnosis methods.

scholarly journals Guidelines adherence in the prevention and management of chronic kidney disease in patients with diabetes mellitus on the background of recent European recommendations – a registry-based analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Peter Bramlage ◽  
Stefanie Lanzinger ◽  
Sascha R. Tittel ◽  
Eva Hess ◽  
Simon Fahrner ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Clinical Practice ◽  
Kidney Disease ◽  
Analysis Data ◽  
Disease Diagnosis ◽  
Diabetic Patients ◽  
European Society Of Cardiology

Abstract Background Recent European Society of Cardiology (ESC)/European Association for the Study of Diabetes (EASD) guidelines provide recommendations for detecting and treating chronic kidney disease (CKD) in diabetic patients. We compared clinical practice with guidelines to determine areas for improvement. Methods German database analysis of 675,628 patients with type 1 or type 2 diabetes, with 134,395 included in this analysis. Data were compared with ESC/EASD recommendations. Results This analysis included 17,649 and 116,747 patients with type 1 and type 2 diabetes, respectively. The analysis showed that 44.1 and 49.1 % patients with type 1 and type 2 diabetes, respectively, were annually screened for CKD. Despite anti-diabetic treatment, only 27.2 % patients with type 1 and 43.5 % patients with type 2 achieved a target HbA1c of < 7.0 %. Use of sodium-glucose transport protein 2 inhibitors (1.5 % type 1/8.7 % type 2 diabetes) and glucagon-like peptide-1 receptor agonists (0.6 % type 1/5.2 % type 2 diabetes) was limited. Hypertension was controlled according to guidelines in 41.1 and 67.7 % patients aged 18–65 years with type 1 and 2 diabetes, respectively, (62.4 vs. 68.4 % in patients > 65 years). Renin angiotensin aldosterone inhibitors were used in 24.0 and 40.9 % patients with type 1 diabetes (micro- vs. macroalbuminuria) and 39.9 and 47.7 %, respectively, in type 2 diabetes. Conclusions Data indicate there is room for improvement in caring for diabetic patients with respect to renal disease diagnosis and treatment. While specific and potentially clinically justified reasons for non-compliance exist, the data may serve well for a critical appraisal of clinical practice decisions.

scholarly journals Provider perspectives on chronic kidney disease diagnosis delivery

2018 ◽  
Vol 89 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Hannah Tiu ◽  
Angela Fagerlin ◽  
Meghan Roney ◽  
Ev Kerr ◽  
Akinlolu Ojo ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Disease Diagnosis ◽  
Provider Perspectives

Pathophysiology and Treatment of Cystinuria

2018 ◽  
Author(s):  
Jacob Britt ◽  
Ava Saidian ◽  
Dustin Whitaker ◽  
Carter Boyd ◽  
Kyle Wood ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Autosomal Recessive Disorder ◽  
Disease Diagnosis ◽  
Urine Ph ◽  
Binding Agents ◽  
Stone Prevention ◽  
Thiol Binding ◽  
Dietary Modifications ◽  
Dibasic Amino Acids

Cystinuria is a relatively rare autosomal recessive disorder that manifests early in life and is associated with the development of kidney stones composed of cystine. It is due to mutations in two genes that are involved in the transport of cystine, neutral, and dibasic amino acids in the proximal tubule of the kidney. Patients are at risk for developing chronic kidney disease. Diagnosis is typically established with stone analysis and quantitative urinary cystine excretion. These patients may form extremely large stones requiring percutaneous nephrolithotomy. Stone-prevention strategies include dietary modifications (increased fluid intake and limitation of sodium and animal protein consumption), urine pH manipulation, and thiol-binding agents. These patients should be followed closely, and preemptive stone removal with ureteroscopy should be considered to limit the necessity for more invasive procedures.   This review contains 2 figures and 38 references. Key Words: a-mercaptopropionyl glycine, amino acid transport, chronic kidney disease, cystinuria, SLC3A1, SLC7A9, thiol-binding agent, urinary pH manipulation

Multi-wavelength analyses of second-derivative spectra for rapid determination of acetaminophen in serum.

1988 ◽  
Vol 34 (6) ◽  
pp. 1119-1121 ◽  
Author(s):  
B Dingeon ◽  
M A Charvin ◽  
M T Quenard ◽  
H Thome
Keyword(s):  
Phosphate Buffer ◽  
Rapid Determination ◽  
Turnaround Time ◽  
Second Derivative ◽  
Derivative Spectra ◽  
Multi Wavelength ◽  
Precision And Accuracy ◽  
Second Derivative Spectra ◽  
Method Of Extraction

Abstract Measurement of acetaminophen by analysis of the second derivative of its spectrum is specific and sensitive. The method of extraction and the use of just one phosphate buffer as reagent makes this method very convenient. Readings are reliable from 10 to 1500 mg/L. A turnaround time of 20 min makes this method well suited for emergency cases. Precision and accuracy of the method are presented. Results are not biased by interferences, not even from N-acetylcysteine.

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