Measurement Of Blood Glucose Concentration Research Articles

A Novel Method for Blood Glucose Measurement by Noninvasive Technique Using Laser

A method and apparatus for noninvasive measurement of blood glucose concentration based on transilluminated laser beam via the Index Finger has been reported in this paper. This method depends on atomic gas (He-Ne) laser operating at 632.8nm wavelength. During measurement, the index finger is inserted into the glucose sensing unit, the transilluminated optical signal is converted into an electrical signal, compared with the reference electrical signal, and the obtained difference signal is processed by signal processing unit which presents the results in the form of blood glucose concentration. This method would enable the monitoring blood glucose level of the diabetic patient continuously, safely and

Noninvasive Polarimetric-Based Glucose Monitoring: An in Vivo Study

Since 1990, there has been significant research devoted toward development of a noninvasive physiological glucose sensor. In this article, we report on the use of optical polarimetry for the noninvasive measurement of physiological glucose concentration in the anterior chamber of the eye of New Zealand white (NZW) rabbits. Measurements were acquired using a custom-designed laser-based optical polarimetry system in a total of seven NZW rabbits anesthetized using an isoflurane-only anesthesia protocol. Aqueous humor-based polarimetric measurements were obtained by coupling light through the anterior chamber of the eye. Blood glucose levels were first stabilized and then altered with intravenous dextrose and insulin administration and measured every 3-5 min with a standard glucometer and intermittently with a YSI 2300 glucose analyzer. Acquired polarimetric glucose signals are calibrated to measured blood glucose concentration. Based on a total of 41 data points, Clarke error grid analysis indicated 93% in zone A, 7% in zone B, and 0% in zones C and D, with reference concentrations between 93 and 521 mg/dl. Errors in prediction are shown to be related to gross movement of the rabbit during the procedures, incurring time-varying corneal birefringence effects that directly affect the measured polarimetric signal. These effects can be compensated for with appropriate design modifications. An optical polarimetry technique was used for in vivo physiological glucose monitoring. The technique demonstrated provides a basis for the development of a noninvasive polarimetric glucose monitor for home, personal, or hospital use.

Direct measurements of blood glucose concentration in the presence of saccharide interferences using slope and bias orthogonal signal correction and Fourier transform near-infrared spectroscopy

Saccharide interferences such as Dextran, Galactose, etc. have a great potential to interfere with near infrared (NIR) glucose analysis since they have a similar spectroscopic fingerprint and are present physiologically at large relative concentrations. These can lead to grossly inappropriate interpretation of patient glucose levels and resultant treatment in critical care and hospital settings. This study describes a methodology to reduce this effect on glucose analysis using an NIR Fourier transform spectroscopy method combined with a multivariate calibration technique (PLS) using preprocessing by orthogonal signal correction (OSC). A mathematical approach based on the use of a single calibration based bias and slope correction was applied in addition to a standard OSC was investigated. This approach is combined with a factorial interferent calibration design to accommodate for interference effects. We named this approach as a slope and bias OSC (sbOSC). sbOSC differs from OSC in the way it handles the prediction. In sbOSC, statistics on slope and bias obtained from a set of calibration samples are then used as a validation parameter in the prediction set. Healthy human volunteer blood with different glucose (80 to 200 mg/dL) and hematocrit (24 to 48 vol.%) levels containing high expected levels of inteferents have been measured with a transmittance near-infrared Fourier transform spectrometer operates in the broadband spectral range of 1.25-2.5 μm (4000-8000 cm(-1)). The effect of six interferents compounds used in intensive care and operating rooms, namely Dextran, Fructose, Galactose, Maltose, Mannitol, and Xylose, were tested on blood glucose. A maximum interference effect (MIE) parameter was used to rank the significance for the individual interferent type on measurement error relative to the total NIR whole blood glucose measurement error. For comparison, a YSI (Yellow Springs Instrument) laboratory reference glucose analyzer and NIR data were collected at the same time as paired samples. MIE results obtained by sbOSC were compared with several standard spectral preprocessing approaches and show a substantial reduced effect of saccharide interferences. NIR glucose measurement results are substantially improved when comparing standard error of prediction from validation samples; and resulting MIE values are small.

Estimating Interval Process Models for Type 1 Diabetes for Robust Control Design

AbstractA linear transfer function model comprising 4 parameters is used to describe the post-prandial breakfast excursions of a group of 10 type 1 diabetes patients who are treated with multiple daily insulin injections. The model is able to simulate the glucose concentration in blood and uses the information of carbohydrate content of the breakfast and the administered insulin injections as inputs. Additionally, a measurement of the actual blood glucose concentration at the time when the breakfast occurs is required. No additional information, in particular the use of a continuous glucose monitoring system is necessary. Based on a 3 day observational period, parameter intervals are calculated such that the measured glucose responses are inside the bounds given by the output of the model. The model together with the parameter intervals can be used for robust control design.

Glucose variability and survival in critically ill children: Allostasis or harm?*

To assess whether individual blood glucose variability in critically ill children is associated with increased mortality and to define the temporal patterns of blood glucose variability during critical illness in children. Retrospective cohort study. A 20-bed pediatric intensive care unit in a children's hospital. Patients aged 0-20 yrs and with at least 12 blood glucose measurements taken within the first 72 hrs of pediatric intensive care unit admission. None. A total of 101 eligible patients had 3,144 measured blood glucose concentrations with 16% mortality. Nonsurvivors had higher median blood glucose concentrations (129 mg/dL vs. 118 mg/dL, p < .01), more hyperglycemia (blood glucose >200 mg/dL) (88% vs. 59%, p < .05), and more hypoglycemia (blood glucose <60 mg/dL) (56% vs. 15%, p < .01) than survivors. The mean blood glucose range (257 mg/dL vs. 185 mg/dL, p < .01) and the blood glucose variability (63 mg/dL vs. 45 mg/dL, p = .02) were greater in nonsurvivors compared with survivors. Blood glucose variability tertiles were proportionately associated with increasing mortality: 6% vs. 15% vs. 27% (p = .07). Compared with survivors, daily blood glucose variability was significantly higher in nonsurvivors during the first 48 hrs of admission and after 1 wk of admission. After controlling for confounders, individual blood glucose variability was associated with higher pediatric intensive care unit mortality for each mg/dL of blood glucose concentration (adjusted odds ratio, 1.03; 95% confidence interval, 1.01-1.05). Glucose variability is common in critically ill children and is associated with increased mortality. Whereas early alterations in blood glucose may represent allostasis, later fluctuations in blood glucose may represent an alteration of autoregulation with resulting higher mortality. Control of variability may need to be incorporated into glycemic control regimens.

A two-level partial least squares system for non-invasive blood glucose concentration prediction

In this study, we propose and demonstrate a novel two-Level Partial Least Squares (2L-PLS) architecture for non-invasive blood glucose concentration measurement. A total of 290 Near-Infrared (NIR) spectroscopy readings from six laser diodes with discrete wavelengths of between 1500 nm and 1800 nm are obtained together with blood glucose concentration readings collected via Oral Glucose Tolerance Test (OGTT) experiments from a healthy volunteer over 4 days. While the conventional approach to predicting the blood glucose concentrations is to use a single Partial Least Squares (PLS) or non-linear PLS model, these systems do not achieve a high level of accuracy. As such, a 2L-PLS system consisting of one PLS model at the first level and three at the second level is proposed to enhance the prediction accuracy. A non-linear 2L-PLS system based on the same structure is also investigated in this study. The proposed 2L-PLS systems show improvements of 10 to 12% in the number of predictions that fall below a 5% error margin as compared to single-level PLS systems.

Determination of blood glucose concentration by back propagation neural network

This paper presents a supervised backpropagation neural (BPN) network for the determination of blood glucose in diabetic patients. Non- invasive measurement of blood glucose concentration based on reflected laser beam from the index finger has been reported in this paper. This method depends on Helium-Neon (He-Ne) gas laser operating at 632.8 nm wave length. During measurement the index finger is placed in the laser beam transceiver unit, the reflected optical signal is converted into its corresponding electrical signal and the obtained signal is processed by the neural network which presents the results in the form of blood glucose concentration. Diabetes database used for empirical comparisons and the results are shown that BPN network performs better. Keywords: Artificial neural network, diabetes mellitus, non-invasive measurement, supervised learning.

Determination of blood glucose concentration by back propagation neural network

This paper presents a supervised backpropagation neural (BPN) network for the determination of blood glucose in diabetic patients. Non- invasive measurement of blood glucose concentration based on reflected laser beam from the index finger has been reported in this paper. This method depends on Helium-Neon (He-Ne) gas laser operating at 632.8 nm wave length. During measurement the index finger is placed in the laser beam transceiver unit, the reflected optical signal is converted into its corresponding electrical signal and the obtained signal is processed by the neural network which presents the results in the form of blood glucose concentration. Diabetes database used for empirical comparisons and the results are shown that BPN network performs better.

Relationship Between Obesity and Incident Diabetes in Middle-Aged and Older Japanese Adults: The Ibaraki Prefectural Health Study

To investigate the age-specific relationship between body mass index (BMI) and risk of diabetes in a Japanese general population. A cohort of Japanese men (N=19,926) and women (N=41,489) (aged 40-79 years) who under went community-based health checkups in 1993 and were free of diabetes was followed up by annual examinations with measurement of blood glucose concentrations until the end of 2006. Incident diabetes mellitus was defined as a blood glucose concentration of 126 mg/dL or greater under fasting conditions, 200 mg/dL or greater under nonfasting conditions, or diabetic medication use at baseline. Hazard ratios (HRs) for diabetes according to BMI were estimated using a Cox proportional hazard model. The model was adjusted for possible confounding variables. A total of 4429 participants (7.2%) developed diabetes (2065 men and 2364 women) during a mean follow-up of 5.5 years. Compared with those with a BMI of less than 25.0, the multivariate HRs for diabetes among participants with a BMI of 30.0 or greater were 1.40 (95% confidence interval [CI], 0.89-2.20) for men aged 40 to 59 years and 1.26 (95% CI, 0.81-1.96) for men aged 60 to 79 years (P=.002 for interaction). The HRs were 2.50 (95% CI, 2.01-3.11) for women aged 40 to 59 years and 1.80 (95% CI, 1.41-2.30) for women aged 60 to 79 years (P=.04 for interaction). The effect of obesity on the risk of diabetes is greater for middle-aged than for older adults.

Comparison of a human portable blood glucose meter, veterinary portable blood glucose meter, and automated chemistry analyzer for measurement of blood glucose concentrations in dogs

To compare blood glucose concentrations measured with 2 portable blood glucose meters (PBGMs) validated for use in dogs (PBGM-D) and humans (PBGM-H) and an automated chemistry analyzer. Validation study. 92 samples of fresh whole blood and plasma from 83 dogs with various diseases. Each PBGM was used to measure whole blood glucose concentration, and the automated analyzer was used to measure plasma glucose concentration. Passing-Bablok linear regression and Bland-Altman plots were used to determine correlations and bias between the PBGMs and the automated analyzer. Calculated acceptability limits based on combined inherent instrument imprecision were used with Bland-Altman plots to determine agreement. Clinical relevance was assessed via error grid analysis. Although correlation between results of both PBGMs and the standard analyzer was > 0.90, disagreement was greater than could be explained by instrument imprecision alone. Mean difference between PBGM-H and chemistry-analyzer values was -15.8 mg/dL. Mean difference between PBGM-D and chemistry-analyzer values was 2.4 mg/dL. Linear regression analysis revealed proportional bias of PBGM-H (greater disagreement at higher glucose concentrations); no proportional bias was detected for PBGM-D. No constant bias was detected for either PBGM. Error grid analysis revealed all measurements from both PBGMs were within zones without an anticipated effect on clinical outcome. Neither PBGM had exact agreement with the automated analyzer; however, the disagreement detected did not have serious clinical consequences. Our findings stressed the importance of using the same device for monitoring trends in dogs and using instrument-specific reference ranges.

Effectiveness of Sodium Fluoride as a Glycolysis Inhibitor on Blood Glucose Measurement: Comparison of Blood Glucose using Specimens from the Korea National Health and Nutrition Examination Surve

Accurate measurement of blood glucose concentrations is essential for defining diabetes, and the minimization of ex vivo glycolysis has been recommended. Recent guidelines advocate two kinds of methods for sample collection and processing: either the sodium fluoride (NaF) method or immediate refrigeration using a serum separation tube (SST). We investigated the difference between the two methods in measuring subsequent glucose concentrations using blood specimens from participants recruited for the fourth Korean National Health and Nutrition Examination Survey. Paired venous blood samples were collected in an SST and a NaF tube from 1,103 men and women. SST serum was separated within 30 min, including standing for 15 min, and then refrigerated. The NaF samples were refrigerated, but not separated until immediately before analysis. We compared the blood glucose concentrations between the SST (SST glucose) and NaF (NaF glucose) methods. The mean SST glucose was significantly higher than NaF glucose (99.0 mg/dL vs 96.5 mg/dL, P<0.05). NaF glucose showed a negative mean bias of 2.6 mg/dL vs SST glucose but showed high correlation (R=0.9899). There was no significant correlation between the bias of blood glucose concentrations by two methods and the storage time of NaF glucose. The negative bias associated with the use of NaF tubes may significantly affect the prevalence of diabetes. Serum separation and refrigeration within 30 min after venous sampling is recommended over NaF method, not only to minimize the preanalytical impact on detecting diabetes but also to reduce sample volume and number of tubes.

All Glucose Measurements Are Not Equal

Dr. Rice et al. have raised a very interesting question about our article published in the March 2009 issue of Anesthesiology,1that concerns the accuracy of the glycemic measurements on capillary blood samples. We agree that the most reliable measurement for blood glucose concentration is on blood samples obtained by arterial line. Generally, the measurement of blood glucose concentration through the HemoCue B-Glucose analyzer (HemoCue, Angelhom, Sweden) with peripheral capillary blood is considered to be reliable in noncritical patients.2,3Thus, previous studies even in critical care patients have used this approach, including the one by Van den Berghe et al. that specified: “The dose of insulin was adjusted according to whole-blood glucose levels, measured at 1- to 4-h intervals in arterial blood or, when an arterial catheter was not available, in capillary blood, with the use of a point-of-care glucometer (HemoCue B-glucose analyzer, HemoCue).”4Our protocol is similar to that of Van den Berghe et al. , but we hypothesized that in our patients population, which is relatively younger than in previous studies, the risk of hypotension, hypoxia, and acidosis is lower.Nevertheless, as we have mentioned in our article, to overcome the risks of this bias we have performed the measurements of blood glucose concentration exclusively on capillary blood samples only in few cases (i.e. , patient in which was difficult to get arterial blood sample: &lt;5% of the measurements). Thus, “in all patients, glucose concentrations were measured in whole blood or on undiluted arterial blood rather than capillary blood samples.” Furthermore, as we reported in the paper, we have made systematic cross controls between blood glucose concentration obtained by arterial and capillary samples and found in our study group nonsignificant differences between the values obtained with the two approaches.*University of Rome, Rome, Italy. bilotta@tiscali.it

전완 부위 혈당검사의 정확도 분석

통증이 거의 없는 새로운 모세혈액 채혈기법인 진공자동채혈법(vacuum assisted auto-lancing)의 정확도를 분석하고자 전형적인 대체부위인 전완(팔) 부위에서 채혈하여 측정한 혈당값을 표준 채혈부위인 정맥 및 손가락에서 채혈하여 측정한 혈당값과 비교, 분석하는 연구를 수행하였다. C대학교병원을 내원한 531명의 환자들을 대상으로 왼손 집게손가락 끝과 왼쪽 전완 부위에서 말초혈액의 혈당을 측정하였고, 곧바로 정맥 채혈하여 혈당을 측정하였다. 전완 부위 혈당 평균값이 손가락보다 정맥 혈당값에 더욱 가까웠으나 이들 간의 차이는 약 10 mg/dL 범위에 불과하여 임상적으로는 동일한 값들로 볼 수 있었다. 측정값들 간에 상관분석을 수행한 결과 손가락과 정맥 채혈의 혈당값 간의 상관계수는 0.94, 전완 부위와 정맥 혈당값 간의 상관계수는 0.92, 또한 전완 부위와 손가락 채혈 간의 상관계수는 0.94로 모두 매우 유의한 상관관계를 보였다(p<0.001). 따라서 대체부위인 전완 부위 혈당검사의 정확도가 실험적으로 입증되었다. 손가락 혈당검사는 상당한 채혈 통증이 수반되어 당뇨 환자들이 자가 검사를 기피하는 주요 원인이 되지만, 전완 부위에서 진공자동채혈하면 통증이 거의 없으므로 만성 당뇨환자들의 자가 질환관리를 위해 매우 유용하리라 기대된다. The present study aimed to evaluate the accuracy of the blood glucose test with almost painless vacuum assisted auto-lancing technique. The blood glucose concentration measurements in the capillary blood sampled from the alternative (forearm) site were compared with the standard venous or finger sampling techniques. Capillary blood was sampled from both the left index finger and the forearm, followed by the venous blood sampling in 531 patients who visited the C University Hospital. Blood sugar test was performed for each blood samples for comparative analysis. Mean blood glucose concentration measured on the forearm was closer to the venous glucose level than that of the finger, but the difference was approximately 10 mg/dL small enough to ignore from the clinical point of view. The correlation coefficients of the measured blood glucose levels between finger and vein and between forearm and vein were 0.94 and 0.92, respectively (p<0.001). The blood glucose measurement on the forearm also well correlated with the finger, showing a correlation coefficient of 0.94, and both data were very much close to each other. Therefore, the blood sugar test on the alternative capillary blood sampling site such as forearm was accurate enough for clinical practice. The vacuum assisted auto-lancing technique on the alternative site would be of particular interest for the disease management of the chronic diabetes, since it induces almost no pain when sampling blood from the capillaries.

Multivariate Regression and Classification Models for Estimation of Blood Glucose Levels Using a New Non-invasive Optical Measurement Technique Named “Pulse-Glucometry

An optical method recently proposed for non-invasive in vivo blood glucose concentration (BGL) measurement, named pulse glucometry, was implemented with three multivariate regression methods, Principal Component Regression (PCR), Partial Least Squares Regression (PLS) and Support Vector Machines Regression (SVMsR), as well as with a classification method, Support Vector Machines Classification (SVMsC), for carrying out calibration. A very fast spectrophotometer provided instantaneously and simultaneously the total transmitted radiation spectrum (I � ) and the cardiac-related pulsatile component (� I � ) superimposed on Iin human fingertips over a wavelength range from 900 to 1700 nm with resolution of 8 nm in 100 Hz sampling. From a family of Is including information relating to various BGL values, differential optical densities (� ODs (=log(1+� I � /I � )) were calculated and normalized by theODvalues at 1100 nm. Finally, the 2nd derivatives of the normalizedODs served as regressors. Subsequently, calibration models from regressors and regressands (the corresponding measured BGL or classified BGL values) were constructed with PCR, PLS, SVMsR and SVMsC. Each regression model showed a relatively good result by evaluating a 5-fold cross validation using total 100 data-sets: Clarke error grid analysis indicated a good correlation in each model compared with the measured BGL values, and the SVMsR calibration provided the best plot distributions. Good regression models were obtained by these three methods. This study suggests that pulse glucometry can produce clinically acceptable results when implemented with regression and classification type calibrations, and, through rapid BGL assessment, promises to offer a more practical, easier and more convenient way for diabetes screening and health care in normal subjects than is possible with existing methods.

Tight Glucose Control in Critically Ill Patients: Should Glucose Meters Be Used?

Measurement of blood glucose concentrations using portable, hand-held meters is used widely in patients with diabetes. Clinical settings include self-monitoring of blood glucose by patients, in doctors’ offices, in chronic care facilities, and in hospitals. More recently, evidence has emerged suggesting that tight glycemic control of nondiabetic patients in hospital intensive care units (ICUs)1 improves clinical outcomes. Based on this evidence, lowering blood glucose concentrations with insulin has become the standard of care in many ICUs and other hospital settings. In the vast majority of these patients, frequent measurements of blood glucose are performed with portable glucose meters, and the values are used to determine the dose of insulin. In this Q&A article, 5 experts in the field are asked to comment on the use of glucose meters in tight glycemic control. Greet Van den Berghe2 : This depends on the definition of “tight” and what is meant by “hospitalized.” Although there are numerous studies showing a strong association of both hyperglycemia and hypoglycemia with mortality in hospitalized patients (the nadir of the risk being associated with the “normal for age” fasting blood glucose range), the evidence from randomized controlled studies currently comes from those performed in ICU patients. The 3 studies that we performed in Leuven compared a “normal (fasting) for age” target for blood glucose [80–110 mg/dL (4.4–6.1 mmol/L) for adults, 70–100 mg/dL (3.9–5.6 mmol/L) for children, and 50–80 mg/dL (2.8–4.4 mmol/L) for infants] with a control group in which we assumed hyperglycemia to be a potentially beneficial adaptation. In the control group, we therefore used a “do not touch” approach unless glucose exceeded the renal threshold of 215 mg/dL (11.9 mmol/L). Blood glucose was measured with only 1 device, namely an ABL blood gas analyzer in the surgical and pediatric ICU studies and the HemoCue …

Evaluation of six portable blood glucose meters for measuring blood glucose concentration in dogs

To evaluate accuracy of 6 portable blood glucose meters (PBGMs) by comparing results of these meters with results obtained with a reference chemistry analyzer. Evaluation study. 49 dogs (158 blood samples). Procedures-Venous blood samples were tested with the 6 PBGMs, and results were compared with results of a commercially available analyzer that used a reference method based on the hexokinase reaction. Plasma glucose concentrations obtained with the reference analyzer ranged from 41 to 639 mg/dL. There were significant correlations between blood glucose concentrations obtained with the 6 PBGMs and plasma glucose concentrations obtained with the reference analyzer (r > or = 0.96). However, for all 6 PBGMs, results differed from results for the reference analyzer, with the difference increasing as plasma glucose concentration increased. Significant differences in bias were found among meters. For 142 samples classified as hypoglycemic, euglycemic, or hyperglycemic on the basis of results of the reference analyzer, the percentage of samples that were misclassified on the basis of results of the PBGMs ranged from 2.1% to 38.7%. Results of the present study suggested that there were substantial differences in the accuracy of currently available PBGMs when used to determine blood glucose concentration in dogs.

Rapid blood separation is superior to fluoride for preventing in vitro reductions in measured blood glucose concentration

Aims:To determine whether tubes containing sodium fluoride negatively bias blood glucose concentration by directly comparing glucose concentrations in paired blood samples collected in tubes containing lithium heparin (Li-Heparin) and tubes...

Evaluation of the agreement among three handheld blood glucose meters and a laboratory blood analyzer for measurement of blood glucose concentration in Hispaniolan Amazon parrots (Amazona ventralis)

To determine the degree of agreement between 3 commercially available point-of-care blood glucose meters and a laboratory analyzer for measurement of blood glucose concentrations in Hispaniolan Amazon parrots (Amazona ventralis). 20 healthy adult Hispaniolan Amazon parrots. A 26-gauge needle and 3-mL syringe were used to obtain a blood sample (approx 0.5 mL) from a jugular vein of each parrot. Small volumes of blood (0.6 to 1.5 microL) were used to operate each of the blood glucose meters, and the remainder was placed into lithium heparin microtubes and centrifuged. Plasma was harvested and frozen at -30 degrees C. Within 5 days after collection, plasma samples were thawed and plasma glucose concentrations were measured by means of the laboratory analyzer. Agreement between pairs of blood glucose meters and between each blood glucose meter and the laboratory analyzer was evaluated by means of the Bland-Altman method, and limits of agreement (LOA) were calculated. None of the results of the 3 blood glucose meters agreed with results of the laboratory analyzer. Each point-of-care blood glucose meter underestimated the blood glucose concentration, and the degree of negative bias was not consistent (meter A bias, -94.9 mg/dL [LOA, -148.0 to -41.7 mg/dL]; meter B bias, -52 mg/dL [LOA, -107.5 to 3.5 mg/dL]; and meter C bias, -78.9 mg/dL [LOA, -137.2 to -20.6 mg/dL]). On the basis of these results, use of handheld blood glucose meters in the diagnosis or treatment of Hispaniolan Amazon parrots and other psittacines cannot be recommended.

Evaluation of the agreement among three handheld blood glucose meters and a laboratory blood analyzer for measurement of blood glucose concentration in Hispaniolan Amazon parrots (Amazona ventralis)

Evaluation of the agreement among three handheld blood glucose meters and a laboratory blood analyzer for measurement of blood glucose concentration in Hispaniolan Amazon parrots (<i>Amazona ventralis</i>)

The Physiology of Seven Consecutive Days of Competitive Cross Country Mountain Biking

Many lab based studies investigating methodologies to enhance recovery from competition or training use test-strategy/placebo-re-test designs. However, in the field competitive events (e.g. Track Cycling) and training programmes often feature many repetitions of the desired activity: yet little is known about the physiological effects of multiple days of competition. PURPOSE: To determine the effect of seven consecutive days of cross-country mountain bike racing on selected physiological variables. METHODS: Forty four participants in the TransScotland 7 day mountain bike stage race were recruited. Prior to competition (day 0) VO2peak was predicted (submaximal cycle ergometery) and basic anthropological measurements were made. Fasted measurements of blood glucose concentration, urine osmolality, rating of muscle soreness and body mass were made before each stage and again in the post-prandial state after each stage. RESULTS: Fasted blood glucose concentration was lower than pre-competition (day 1: 4.63 ± 0.91 mmol·L−1) on days 2 to 6 (all p < 0.01) but returned to baseline levels on the 7th day of competition (day 7: 4.76 ± 0.78 mmol·L−1) (p = 0.32). Post exercise rating of muscle soreness increased from day 1 (3.81 ± 1.5) to day 7 (4.71 ± 1.64) of competition (p < 0.01). Pre- and post-exercise urine osmolality increased from day 1 (pre: 550.7 ± 180.6 post: 435.5 ± 245.8 mOsmol·kg−1) to day 7 (pre: 631.2 ± 184.1 post: 600.0 ± 247 mOsmol·kg−1) of competition (pre: p = 0.03 post: p < 0.01). There was a significant reduction in body mass from pre-competition on day 1 (81.2 ± 8.41 kg) to pre- (78.3 ± 8.14 kg) (p < 0.01) and post-competition on day 7 (78.8 ± 7.74 kg) (p < 0.01). The reduction in body mass was accompanied by a reduction in the sum of four site skin-fold thickness from pre-competition on day 0 (36.6 ± 10.7 mm) to postcompetition on day 7 (35.3 ± 9.9 mm) (p = 0.01). Subjects consumed an average of 570 ± 92 ml·hr−1 of CHO-electrolyte drink during competition. CONCLUSIONS: Seven consecutive days of cross-country mountain bike racing has a substantial, additive, deleterious impact on the measured physiological variables. This should be taken into account when designing investigations aimed at improving recovery in real-world situations. Supported in part by the Andrews Fund, University of Glasgow and by High5 Ltd, Leicester, UK.