NIR-based sensing system for non-Invasive detection of Hemoglobin for point-of-care applications

2021 ◽  
Vol 17 ◽  
Author(s):  
Yogesh Kumar ◽  
Ayush Dogra ◽  
Vikash Shaw ◽  
Ajeet Kaushik ◽  
Sanjeev Kumar
Keyword(s):  
Linear Regression ◽  
Point Of Care ◽  
Principal Component ◽  
Hemoglobin Concentration ◽  
Multivariate Linear Regression ◽  
Bulbar Conjunctiva ◽  
Clinical Practices ◽  
Non Invasive ◽  
Sensing System ◽  
Sliding Mechanism

Background: Hemoglobin is essential biomolecule for the transportation of oxygen therefore; its assessment is also obligatory very frequently in innumerable clinical practices. Traditional invasive techniques have concomitant shortcomings e.g. time delay, onset of infections and discomfort, which necessitates a non-invasive hemoglobin estimating solution to get rid of these constraints in health informatics. Currently various techniques are underway in allied domain and scanty products are also feasible in the market but due to low satisfaction rate, invasive solutions are still assumed as gold standard. Recently introduced technologies are effectively evolved as optical spectroscopy and digital photographic concepts on different sensing spots e.g. fingertip, palpebral conjunctiva, bulbar conjunctiva and fingernail. Productive sensors utilize more than eight wavelengths to compute hemoglobin concentration and four wavelengths to display only Hb-index (trending of hemoglobin) either in disposable adhesive or reusable clip type sensor’s configuration. Objective: This study aims an optimistic optical spectroscopic technique to measure hemoglobin concentration and conditional usability of non-invasive blood parameters’ diagnostics at point-of-care. Methods: Two distinguishable light emitting sources (810nm & 1300nm) are utilized at isosbestic points with single photodetector (800-1700nm). With this purpose, reusable finger probe assembly is facilitated in transmittance mode based on newly offered sliding mechanism to block ambient light. Results: Investigation with proposed design presents correlation coefficients between reference hemoglobin and every individual feature, multivariate linear regression model for highly correlated independent features. Moreover, principal component analytical model with multivariate linear regression offers mean bias of 0.036 & -0.316 g/dL, precision of 0.878 & 0.838 and limits of agreement from -1.685 to 1.758 g/dL & -1.790 to 1.474 g/dL for 18 & 21 principle components respectively. Conclusion: The encouraging readouts emphasize favorable precision therefore proposed sensing system is amenable to assess hemoglobin in settings with limited resources and strengthening future routes for point of care applications.

Factors associated with erythrocyte count and hemoglobin concentration in men and women with type 2 diabetes

2019 ◽  
Vol 55 (3) ◽  
pp. 199-208
Author(s):  
Olga Martyna Koper-Lenkiewicz ◽  
Joanna Kamińska ◽  
Ewelina Wilińska ◽  
Anna Milewska ◽  
Sylwia Lewoniewska ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Linear Regression ◽  
Linear Regression Model ◽  
Cardiac Arrhythmias ◽  
Calcium Antagonists ◽  
Hemoglobin Concentration ◽  
Multivariate Linear Regression ◽  
Diabetic Patients ◽  
Multivariate Linear Regression Model

Introduction: The risk of developing anemia in diabetic patients is nearly 3-times higher than in non-diabetic patients. Aim: The aim was to assess factors that may affect both the erythrocyte count (RBC) and hemoglobin concentration (HGB) in type 2 diabetes patients. Material and methods: In type 2 diabetes patients (N = 80) and in control subjects with normal carbohydrate metabolism (N = 40) RBC and HGB were determined in whole blood collected in the EDTA-K3 tube. Results: The degree of metabolic compensation of diabetes, measured by the percentage of HbA1c, did not significantly affect RBC and HGB. In diabetic women, unlike men, there was no relationship between RBC and HGB and kidney function, measured with eGFR. Angiotensin-converting-enzyme inhibitors and angiotensin receptor blockers did not significantly affect RBC and HGB in these patients. Multivariate linear regression analysis showed that in type 2 diabetes women variables that affect the RBC included: systolic BP, arrhythmias, taking fibrates. In the multivariate linear regression model variables that influence the HGB in type 2 diabetes women included systolic BP and fibrate treatment. In type 2 diabetes men a statistically significant model of multivariate linear regression for RBC was not obtained. In the multivariate linear regression model the variables that influence the HGB in type 2 diabetes men included: white blood cell count, age, obesity, and taking statins. Conclusions: In women with type 2 diabetes, the RBC is influenced by other factors (systolic BP, cardiac arrhythmias, fibrates and calcium antagonists) than in men (obesity and the use of oral antidiabetic agents). In type 2 diabetes women also other factors influence HGB (systolic BP, cardiac arrhythmias presence, fibrates, calcium antagonists and ACE inhibitors) than in type 2 diabetes men (hypertension, obesity, leukocyte count, age, proton pump inhibitors and statins medication).

scholarly journals Comparison of the Accuracy of Noninvasive Hemoglobin Monitoring by Spectrophotometry (SpHb) and HemoCue® with Automated Laboratory Hemoglobin Measurement

2011 ◽  
Vol 115 (3) ◽  
pp. 548-554 ◽  
Author(s):  
Lionel Lamhaut ◽  
Roxana Apriotesei ◽  
Xavier Combes ◽  
Marc Lejay ◽  
Pierre Carli ◽  
...  
Keyword(s):  
Clinical Study ◽  
Linear Regression ◽  
Point Of Care ◽  
Reference Method ◽  
Hemoglobin Concentration ◽  
Automated Analysis ◽  
Laboratory Measurement ◽  
Altman Analysis ◽  
Simultaneous Measurements ◽  
Hemoglobin Measurement

Background The reference method for hemoglobin concentration measurement remains automated analysis in the laboratory. Although point-of-care devices such as the HemoCue® 201+ (HemoCue, Ängelholm, Sweden) provide immediate hemoglobin values, a noninvasive, spectrophotometry-based technology (Radical-7®; Masimo Corp., Irvine, CA) that provides continuous online hemoglobin (SpHb) measurements has been introduced. This clinical study aimed to test the hypothesis that SpHb monitoring was equivalent to that of HemoCue® (the automated hemoglobin measurement in the laboratory taken as a reference method) during acute surgical hemorrhage. Methods Blood for laboratory analysis was sampled after induction of anesthesia, during surgery according to the requirements of the anesthesiologist, and finally after the transfer of the patient to the recovery room. When each blood sample was taken, capillary samples were obtained for analysis with HemoCue®. SpHb monitoring was performed continuously during surgery. Using the automated hemoglobin measurement in the laboratory as a reference method, the authors tested the hypothesis that SpHb monitoring is equivalent to that of HemoCue®. The agreement between two methods was evaluated by linear regression and Bland and Altman analysis. Results Eighty-five simultaneous measurements from SpHb, HemoCue®, and the laboratory were obtained from 44 patients. Bland and Altman comparison of SpHb and HemoCue® with the laboratory measurement showed, respectively, bias of -0.02 ± 1.39 g · dl(-1) and -0.17 ± 1.05 g · dl(-1), and a precision of 1.11 ± 0.83 g · dl(-1) and 0.67 ± 0.83 g · dl(-1). Considering an acceptable difference of ± 1.0 g · dl(-1) with the laboratory measurement, the percentage of outliers was significantly higher for SpHb than for HemoCue® (46% vs. 16%, P < 0.05). Conclusions Taking automated laboratory hemoglobin measurement as a reference, the study shows that SpHb monitoring with Radical-7® gives lower readings than does the HemoCue® for assessment of hemoglobin concentration during hemorrhagic surgery.

Invasive and non-invasive point-of-care testing and point-of-care monitoring of the hemoglobin concentration in human blood – how accurate are the data?

2019 ◽  
Vol 64 (5) ◽  
pp. 495-506
Author(s):  
Frank Dietzel ◽  
Peter Dieterich ◽  
Frank Dörries ◽  
Hartmut Gehring ◽  
Philipp Wegerich
Keyword(s):  
Measurement Accuracy ◽  
Blood Donation ◽  
Point Of Care ◽  
Hemoglobin Concentration ◽  
Time Frame ◽  
Point Of Care Testing ◽  
Scientific Investigations ◽  
Non Invasive ◽  
Common Basis ◽  
Accuracy And Precision

Abstract In this review, scientific investigations of point-of-care testing (POCT) and point-of-care monitoring (POCM) devices are summarized with regard to the measurement accuracy of the hemoglobin concentration. As a common basis, information according to the Bland and Altman principle [bias, limits of agreement (LOA)] as well as the measurement accuracy and precision are considered, so that the comparability can be mapped. These collected data are subdivided according to the manufacturers, devices and procedures (invasive and non-invasive). A total of 31 devices were identified. A comparability of the scientific investigations in particular was given for 23 devices (18 invasive and five non-invasive measuring devices). In terms of measurement accuracy, there is a clear leap between invasive and non-invasive procedures, while no discernible improvement can be derived in the considered time frame from 2010 to 2018. According to the intended use, strict specifications result from the clinical standards, which are insufficiently met by the systems. More stringent requirements can be derived both in the area of blood donation and in the treatment of patients.

scholarly journals Breath analysis for detection and trajectory monitoring of acute respiratory distress syndrome in swine

2021 ◽  
pp. 00154-2021
Author(s):  
Ruchi Sharma ◽  
Menglian Zhou ◽  
Mohamad Hakam Tiba ◽  
Brendan M. McCracken ◽  
Robert P. Dickson ◽  
...  
Keyword(s):  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Distress Syndrome ◽  
Point Of Care ◽  
Principal Component ◽  
Breath Analysis ◽  
Non Invasive ◽  
Breath Sampling ◽  
Linear Discrimination

Despite the enormous impact on human health, acute respiratory distress syndrome (ARDS) is ill-defined, and its timely diagnosis is difficult, as is tracking the course of the syndrome. The objective of this pilot study was to explore the utility of breath collection and analysis methodologies to detect ARDS through changes in the volatile organic compound (VOC) profiles present in breath. Five male Yorkshire mix swine were studied and ARDS was induced utilising both direct and indirect lung injury. An automated portable gas chromatography device developed in-house was used for point of care breath analysis and to monitor swine breath hourly, starting from the initiation of the experiment until the development of ARDS, which was adjudicated based on the Berlin criteria at the breath sampling points and confirmed by lung biopsy at the end of the experiment. A total of 67 breath samples (chromatograms) were collected and analyzed. Through machine learning, principal component analysis, and linear discrimination analysis, seven VOCs biomarkers were identified that distinguished ARDS. These represent seven of the nine biomarkers found in our breath analysis study of human ARDS corroborating our findings. We also demonstrated that breath analysis detects changes 1–6 h earlier than the clinical adjudication based on the Berlin criteria. The findings provide proof of concept that breath analysis can be used for the identification of early changes associated with ARDS pathogenesis in swine. Its clinical application could provide intensive care clinicians with a non-invasive diagnostic tool for early detection and continuous monitoring of ARDS.

Glucose Calibration Modeling in Blood with Spline Regression Approaching to Non-Invasive Tools

2018 ◽  
pp. 144-149
Author(s):  
Ria Hayatun Nur ◽  
Indahwati A ◽  
Erfiani A
Keyword(s):  
Diabetes Mellitus ◽  
Linear Regression ◽  
Good Health ◽  
Cubic Spline ◽  
The Body ◽  
Spline Regression ◽  
Linear Quadratic ◽  
Important Thing ◽  
Non Invasive

In this globalization era, health is the most important thing to be able to run various activities. Without good health, this will hinder many activities. Diabetes mellitus is one of the diseases caused by unhealty lifestyle.There are many treatments that can be done to prevent the occurrence of diabetes. The treatments are giving the insulin and also checking the glucose rate to the patients.Checking the glucose rate needs the tools which is safety to the body. This research want to develop non invasive tool which is safety and do not injure the patient. The purpose of this research is also finding the best model which derived from Linear, Quadratic, and Cubic Spline Regression. Some respondents were taking to get the glucose measuring by invasive and non invasive tools. It could be seen clearly that Spline Linear Regression was the best model than Quadratic and Cubic Spline Regression. It had 70% and 33.939 for R2 and RMSEP respectively.

scholarly journals Association between triglyceride-glucose index and risk of arterial stiffness: a cohort study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Shouling Wu ◽  
Luli Xu ◽  
Mingyang Wu ◽  
Shuohua Chen ◽  
Youjie Wang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Linear Regression ◽  
Arterial Stiffness ◽  
Multivariate Linear Regression ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Cross Sectional ◽  
Tyg Index ◽  
Longitudinal Association ◽  
The Cross

Abstract Background Triglyceride–glucose (TyG) index, a simple surrogate marker of insulin resistance, has been reported to be associated with arterial stiffness. However, previous studies were limited by the cross-sectional design. The purpose of this study was to explore the longitudinal association between TyG index and progression of arterial stiffness. Methods A total of 6028 participants were derived from the Kailuan study. TyG index was calculated as ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Arterial stiffness was measured using brachial-ankle pulse wave velocity (baPWV). Arterial stiffness progression was assessed by the annual growth rate of repeatedly measured baPWV. Multivariate linear regression models were used to estimate the cross-sectional association of TyG index with baPWV, and Cox proportional hazard models were used to investigate the longitudinal association between TyG index and the risk of arterial stiffness. Results Multivariate linear regression analyses showed that each one unit increase in the TyG index was associated with a 39 cm/s increment (95%CI, 29–48 cm/s, P < 0.001) in baseline baPWV and a 0.29 percent/year increment (95%CI, 0.17–0.42 percent/year, P < 0.001) in the annual growth rate of baPWV. During 26,839 person-years of follow-up, there were 883 incident cases with arterial stiffness. Participants in the highest quartile of TyG index had a 58% higher risk of arterial stiffness (HR, 1.58; 95%CI, 1.25–2.01, P < 0.001), as compared with those in the lowest quartile of TyG index. Additionally, restricted cubic spline analysis showed a significant dose–response relationship between TyG index and the risk of arterial stiffness (P non-linearity = 0.005). Conclusion Participants with a higher TyG index were more likely to have a higher risk of arterial stiffness. Subjects with a higher TyG index should be aware of the following risk of arterial stiffness progression, so as to establish lifestyle changes at an early stage.

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