Mark A. Arnold

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially. APPROACH An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence Based Laboratory Medicine Committee of the AACC jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association. CONTENT In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A(1c) (Hb A(1c)) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of Hb A(1c). The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. SUMMARY The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.

Temperature-Insensitive Near-Infrared Spectroscopic Measurement of Glucose in Aqueous Solutions

A digital Fourier filter is combined with partial least-squares (PLS) regression to generate a calibration model for glucose that is insensitive to sample temperature. This model is initially created by using spectra collected over the 5000 to 4000 cm−1 spectral range with samples maintained at 37°C. The analytical utility of the model is evaluated by judging the ability to determine glucose concentrations from a set of prediction spectra. Absorption spectra in this prediction set are obtained by ratioing single-beam spectra collected from solutions at temperatures ranging from 32 to 41°C to reference spectra collected at 37°C. The temperature sensitivity of the underlying water absorption bands creates large baseline variations in prediction spectra that are effectively eliminated by the Fourier filtering step. The best model provides a mean standard error of prediction across temperatures of 0.14 mM (2.52 mg/dL). The benefits of the Fourier filtering step are established, and critical experimental parameters, such as number of PLS factors, mean and standard deviation for the Gaussian shaped Fourier filter, and spectral range, are considered.

Simultaneous Measurements of Glucose, Glutamine, Ammonia, Lactate, and Glutamate in Aqueous Solutions by Near-Infrared Spectroscopy

Calibration models are generated and evaluated for the measurement of five different components in synthetic mixtures prepared in aqueous solutions. Mixtures of glucose, glutamine, ammonia, lactate, and glutamate were prepared to simulate concentration levels expected during routine bioreactor fermentation processes. Near-IR spectra were collected from these solutions over the spectral range from 5000 to 4000 cm−1. This spectral information was used to build individual multivariate calibration models for each analyte. Models were constructed on the basis of partial least-squares regression of raw and Fourier filtered absorbance spectra. Each analyte could be detected selectively with mean percent errors of prediction ranging from 4 to 8%.

Position Statement Executive Summary: Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND Multiple laboratory tests are used in the diagnosis and management of patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially. APPROACH An expert committee compiled evidence-based recommendations for the use of laboratory analysis in patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. A draft of the guidelines was posted on the Internet, and the document was modified in response to comments. The guidelines were reviewed by the joint Evidence-Based Laboratory Medicine Committee of the AACC and the National Academy of Clinical Biochemistry and were accepted after revisions by the Professional Practice Committee and subsequent approval by the Executive Committee of the American Diabetes Association. CONTENT In addition to the long-standing criteria based on measurement of venous plasma glucose, diabetes can be diagnosed by demonstrating increased hemoglobin A1c (HbA1c) concentrations in the blood. Monitoring of glycemic control is performed by the patients measuring their own plasma or blood glucose with meters and by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. SUMMARY The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Recent Advances in the Development and Analytical Applications of Biosensing Probes

Abstract The term “biosensor” has become a fashionable buzzword in recent analytical literature. While scientists have used the word to describe any number of innovative devices and instrumental systems, we believe that the two most widely accepted definitions are as follows:

Measurement of Glucose in Water with First-Overtone Near-Infrared Spectra

Partial least-squares (PLS) regression analysis was used to build calibration models for three unique spectral data sets of glucose in water. Spectra in the first data set were collected with a 2.0 mm optical pathlength. For these data, the measured root-mean-square (rms) noise of 100% lines over the 5975-5850 cm−1 spectral range was 4.5 micro-absorbance units (μAU). Spectrometer upgrades permitted a 5.2 mm optical pathlength for the second data set, and the resulting spectra had an rms noise of 5.9 μAU. Further spectrometer adjustments allowed the use of a 10.0 mm optical pathlength for the third data set, and the resulting spectral rms noise was 8.4 μAU. In each case, the instrumentation was modified individually in order to provide high radiant powers at the detector while avoiding detector saturation. Poor calibration models for the first data set indicate that a 2.0 mm optical pathlength is insufficient for adequate glucose measurements at clinically relevant concentrations. Calibration and prediction errors for the data collected at 5.2 and 10.0 mm pathlengths ranged from 0.40–0.50 and 0.35–0.40 mM, respectively. Digital Fourier filtering significantly improved model performance by reducing the required number of latent variables (factors) in the PLS models and by reducing the wavelength dependency of these models. For the best calibration model, spectra in the data set corresponding to a 10.0 mm pathlength were Fourier filtered with a Gaussian-shaped filter defined in digital frequency units (f) by a mean position of 0.0206 f and a standard deviation width of 0.0031 f. These filtered spectra were then submitted to a one-factor PLS model that is limited to the 5975-5850 cm−1 spectral range. Consideration of different spectral ranges and an analysis of spectral loading vectors indicate that the 5920 cm−1 absorption band for glucose is critical for useful analytical measurements.

Noninvasive Blood Glucose Measurements by Near-Infrared Transmission Spectroscopy Across Human Tongues

Noninvasive blood glucose measurements are characterized in human subjects. A series of first overtone transmission spectra are collected across the tongues of five human subjects with type 1 diabetes. The noninvasive human spectra are collected by an experimental protocol that is designed to minimize chance correlations with blood glucose levels. In one treatment of the data, every fifth sample is used as a blind prediction point to validate model performance. In another rearrangement of the data, the spectra collected over the first 29 days are used to build calibration models that are then used to predict in vivo glycemia from spectra collected over the next 10 days. Of the five data sets (one for each subject), one demonstrates a complete inability to predict blood glucose levels and is deemed void of glucose-specific information. Glucose-specific information is evident in the remaining four data sets, albeit to varying degrees. For all data sets, the ability to measure glucose from spectra collected noninvasively from human subjects depends on spectral quality and reproducibility of the tongue-to-spectrometer interface. The standard error of prediction is 3.4 mM for the best calibration model. The significance of this magnitude of prediction error is discussed relative to the situations where: (1) the model is completely void of glucose-specific information and (2) glucose predictions are limited by spectral signal-to-noise and sample thickness. Overall, glucose-specific information is available from noninvasive first-overtone spectra collected across human tongues. Significant improvements are necessary, however, before clinically useful measurements are possible.

Molar Absorptivities of Glucose and other Biological Molecules in Aqueous Solutions over the First Overtone and Combination Regions of the Near-Infrared Spectrum:

Molar absorptivities are measured for water, glucose, alanine, ascorbate, lactate, triacetin, and urea in the near-infrared spectral region at 37 °C. Values are based on the Beer–Lambert law and cover the first overtone (1550–1850 nm; 6450–5400 cm−1) and combination (2000–2500 nm; 4000–5000 cm−1) spectral windows through aqueous media. Accurate calculations demand accounting for the impact of water displacement upon dissolution of solute. In this regard, water displacement coefficients are measured and reported for each solute. First overtone absorptivities range from 2 to 7 × 10−5 mM−1mm−1 for all solutes except urea, for which absorptivity values are below 0.5 × 10−5 mM−1mm−1 across this spectral range. Molar absorptivities over the combination spectral region range from 0.8 to 3.2 × 10−4 mM−1mm−1, which is a factor of four to five greater than the first overtone absorptivities. Accuracy of the measured values is assessed by comparing calculated or modeled spectra with spectra measured from standard solutions. This comparison reveals accurately modeled spectra in terms of magnitude and position of solute absorption bands. Both actual and modeled spectra from glucose solutions reveal positive and negative absorbance values depending on the measurement wavelength. It is shown that the net absorbance of light is controlled by the magnitude of the absorptivity of glucose compared to the product of the absorptivity of water and the water displacement coefficient for glucose.

Non-invasive glucose monitoring

Several recent reports claim success in measuring blood glucose non-invasively in human subjects with near-infrared spectroscopy. A critical examination of these published results suggests more fundamental research is needed to verify the validity of these claims. In addition, progress continues in assessing the utility of near-infrared spectroscopy as a non-invasive probe for continuous bioreactor monitoring during fermentation processes. Recent work demonstrates that five critical fermentation components, including glucose, may be measured simultaneously.

Tunable Laser Diode System for Noninvasive Blood Glucose Measurements

Optical sensing of glucose would allow more frequent monitoring and tighter glucose control for people with diabetes. The key to a successful optical noninvasive measurement of glucose is the collection of an optical spectrum with a very high signal-to-noise ratio in a spectral region with significant glucose absorption. Unfortunately, the optical throughput of skin is low due to absorption and scattering. To overcome these difficulties, we have developed a high-brightness tunable laser system for measurements in the 2.0–2.5 μm wavelength range. The system is based on a 2.3 μm wavelength, strained quantum-well laser diode incorporating GaInAsSb wells and AlGaAsSb barrier and cladding layers. Wavelength control is provided by coupling the laser diode to an external cavity that includes an acousto-optic tunable filter. Tuning ranges of greater than 110 nm have been obtained. Because the tunable filter has no moving parts, scans can be completed very quickly, typically in less than 10 ms. We describe the performance of the present laser system and avenues for extending the tuning range beyond 400 nm.