Point-of-care estimation of haemoglobin concentration in all age groups in clinical practice

Schapkaitz, Elise; Mahlangu, Johnny

doi:10.1080/20786204.2011.10874098

Cited by 4 publications

(8 citation statements)

References 14 publications

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“…Effective and low-cost point-of-care medical diagnostic tests provide the obvious solution to these problems, by enabling analysis to be performed at the point of need. For the vast majority of patient visits, the first point of diagnostic inquiry is often a full blood count [2]. However, these blood cell counting based tests require blood to be transported from clinics to laboratories for analysis using large, costly laboratory equipment.…”

Section: Introductionmentioning

confidence: 99%

“…Effective and low-cost point-of-care medical diagnostic tests provide developing countries and rural communities with accessible healthcare solutions [1], and can be particularly beneficial for blood cell count tests, which are often the starting point in the process of diagnosing a patient [2].The initial focus of this work is on total white and red blood cell counts, using a microfluidic cartridge [3] for sample processing. Analysis of the processed samples has been implemented by means of two main optical visualization systems developed in-house: 1) a fluidic operation analysis system using high speed video data to determine volumes, mixing efficiency and flow rates, and 2) a microscopy analysis system to investigate homogeneity and concentration of blood cells.…”

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Sample to answer visualization pipeline for low-cost point-of-care blood cell counting

et al. 2015

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We present a visualization pipeline from sample to answer for point-of-care blood cell counting applications. Effective and low-cost point-of-care medical diagnostic tests provide developing countries and rural communities with accessible healthcare solutions [1], and can be particularly beneficial for blood cell count tests, which are often the starting point in the process of diagnosing a patient [2].The initial focus of this work is on total white and red blood cell counts, using a microfluidic cartridge [3] for sample processing. Analysis of the processed samples has been implemented by means of two main optical visualization systems developed in-house: 1) a fluidic operation analysis system using high speed video data to determine volumes, mixing efficiency and flow rates, and 2) a microscopy analysis system to investigate homogeneity and concentration of blood cells. Fluidic parameters were derived from the optical flow [4] as well as color-based segmentation of the different fluids using a hue-saturation-value (HSV) color space. Cell count estimates were obtained using automated microscopy analysis and were compared to a widely accepted manual method for cell counting using a hemocytometer [5].The results using the first iteration microfluidic device [3] showed that the most simple -and thus low-cost -approach for microfluidic component implementation was not adequate as compared to techniques based on manual cell counting principles. An improved microfluidic design has been developed to incorporate enhanced mixing and metering components, which together with this work provides the foundation on which to successfully implement automated, rapid and low-cost blood cell counting tests.

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Section: Introductionmentioning

confidence: 99%

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Sample to answer visualization pipeline for low-cost point-of-care blood cell counting

et al. 2015

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“…The economic realities in developing nations makes it cost-prohibitive to setup and run standard laboratory facilities at all levels of the health care system [8,10,11]. The use of point-of-care (POC) haemoglobin meters is potentially economically advantageous and time-saving and may also be of tremendous help in critical care units where rapid and frequent testing are required [11,12]. These devices are much cheaper than automated analysers and do not require sophisticated expertise training to be able to operate them [13].…”

Section: Introductionmentioning

confidence: 99%

“…These devices are much cheaper than automated analysers and do not require sophisticated expertise training to be able to operate them [13]. As such they are usually operated by a non-laboratory staff such as a physician who is directly involved in patient care [12]. They are battery-powered and will be highly beneficial in settings with inconsistent electric power supply.…”

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confidence: 99%

Evaluation of the accuracy of two point-of-care haemoglobin meters used in sub-Saharan African population: a cross-sectional study

Choukem

Sih

Ntumsi

et al. 2020

BMC Cardiovasc Disord

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Background: Point-of-care haemoglobin meters are attractive solutions to improve timely diagnosis of anaemia in resource-limited settings. However, concerns regarding the accuracy of these meters may affect their adoption. The accuracy of two hand-held point-of-care haemoglobin meters was evaluated against reference full blood count analyser. Methods: This was a hospital-based cross-sectional study conducted at the Douala General hospital, Cameroon. Two handheld haemoglobin meters were assessed: Urit12® (URIT Medical Electronics Co.,Ltd. Guangxi, China) and MissionHb®(ACON Laboratories, Inc., San Diego, USA); against a reference standard CELL-DYN RUBY® (ABBOTT DIAGNOSTICS, Illinois, USA). The Pearson's correlation and Bland-Altman agreement were used to assess the technical accuracy of the meters. Clinical accuracy was evaluated using total error allowable and area under the Receiver Operating Curve. Finally, their agreement with the reference in diagnosing anaemia was assessed using the kappa statistic. Results: A total of 228 participants were included in the study. The mean haemoglobin values of both haemoglobin meters (MissionHb®: 11.6 ± 2.5 g/dl; Urit12®: 10.9 ± 2.7 g/dl) were significantly higher than the reference value (10.5 ± 2.5 g/dl), p < 0.001 for both meters. Both haemoglobin meters had good correlation with the reference analyser (r = 0.89 and r = 0.90 for Urit12® and MissionHb® respectively) and good agreement on the Bland-Altman plots. However, the MissionHb® meter did not meet the clinical accuracy requirements (p < 0.001). Even though both meters were excellent at identifying the presence of anemia (MissionHb®-AUC = 0.9161, Urit 12®-AUC = 0.9009), they, however, both had weak agreement with the reference analyser in diagnosing the severity of anaemia (K = 0.39 for MissionHb®, p < 0.001 and K = 0.54 for Urit12®, p < 0.001). Conclusion: Although both devices showed technical accuracy with a positive correlation with the reference analyser and were able to accurately diagnose the presence of anemia, both meters however, had sub-optimal agreement with the reference analyser in diagnosing the degree of severity of anaemia among our participants.

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Microfluidic Cartridges for Automated, Point-of-Care Blood Cell Counting

et al. 2017

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Disposable, low-cost microfluidic cartridges for automated blood cell counting applications are presented in this article. The need for point-of-care medical diagnostic tools is evident, particularly in low-resource and rural settings, and a full blood count is often the first step in patient diagnosis. Total white and red blood cell counts have been implemented toward a full blood count, using microfluidic cartridges with automated sample introduction and processing steps for visual microscopy cell counting to be performed. The functional steps within the microfluidic cartridge as well as the surrounding instrumentation required to control and test the cartridges in an automated fashion are described. The results recorded from 10 white blood cell and 10 red blood cell counting cartridges are presented and compare well with the results obtained from the accepted gold-standard flow cytometry method performed at pathology laboratories. Comparisons were also made using manual methods of blood cell counting using a hemocytometer, as well as a commercially available point-of-care white blood cell counting system. The functionality of the blood cell counting microfluidic cartridges can be extended to platelet counting and potential hemoglobin analysis, toward the implementation of an automated, point-of-care full blood count.

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Point-of-care estimation of haemoglobin concentration in all age groups in clinical practice

Cited by 4 publications

References 14 publications

Sample to answer visualization pipeline for low-cost point-of-care blood cell counting

Sample to answer visualization pipeline for low-cost point-of-care blood cell counting

Evaluation of the accuracy of two point-of-care haemoglobin meters used in sub-Saharan African population: a cross-sectional study

Microfluidic Cartridges for Automated, Point-of-Care Blood Cell Counting

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