The above-stated requirement for POCT systems, i.e. that the confidence limits should lie close to 5 g/l cHb, held true for the dry heparinized samples of the blood gas analyzer (1st measurement and mean of 2), the HemoCue system (mean of 3) and the automated hematology analyzer.

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.

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The interest of this paper is the determination of the optical properties of oxygenated (saturation above 97 %) hemoglobin in clinical relevant concentrations (ranging from 5 to 15 g/dl), dependent on the layer thickness. Furthermore the generation of a high rate data set for training with machine learning approaches was intended. With a double integrating sphere setup (laser diodes from 780 to 1310 nm) - as a well referenced method - and flow through optical cuvettes ranging from 1 to 3 mm layer thickness, the transmission (𝑀𝑇) and reflection (𝑀𝑅) values of the samples were acquired. From those the layer thickness independent absorption (𝜇𝑎) and reduced scattering coefficients (𝜇𝑠’) were calculated by the means of the Inverse Adding Doubling (IAD) algorithm. For each sample the same coefficients should result correspondingly for all cuvette thicknesses in test. This relationship serves as an internal standard in the evaluation of the collected data sets. In parallel a spectrophotometer in the range from 690 to 1000 nm recorded transmission spectra for all samples as a second reference. First, the IAD algorithm provided optical coefficients (𝜇𝑎, 𝜇𝑠’) in all measurements, with few exceptions at low hemoglobin concentrations. The resulting coefficients match independently of the layer thickness. As a main second result, a high rate data set was generated which serves for further analysis - for example with machine learning approaches.