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BACKGROUD: Hyaluronic acid (HA) is proposed as a marker of functional liver capacity. The aim of the present study was to compare a new turbidimetric assay for measuring HA with the current standard method.METHODS: HA was measured by a particle-enhanced turbidimetric immunoassay (PETIA) and enzyme-linked immunosorbent assay (ELISA) in a 40-sample dilution series and 39 intensive care unit (ICU) patients. Agreement was assessed with Bland-Altman's method.RESULTS: In the ICU patients, the median HA concentration was 159.0 ng/ml (interquartile range (IQR) 117.5-362.5 ng/ml) with ELISA and 157.5 ng/ml (IQR 92.5-359.6 ng/ml) with PETIA. The mean difference was 12.88 ng/ml (95% CI, -4.3 to 30.1 ng/ml, P = 0.14) and the 95% limits of agreement were -91.17 to 116.9 ng/ml. In the dilution series, the mean difference was -59.26 ng/ml (95% CI, -74.68 to 43.84 ng/ml, P < 0.0001) and the 95% limits of agreement were 35.23 to -153.8 ng/ml.CONCLUSION: We found random variation between the PETIA and ELISA test that could affect performance in a clinical context, but only to a lesser extent in a research context. The new clinical biochemistry assay for HA determination will allow for large studies of the clinical utility of HA.

The aim of our study was to describe the occurrence of Acute Intermittent Porphyria (AIP) in Denmark demographically, genetically and biochemically.The study was based on a database of porphobilinogen deaminase (PBGD) mutations detected in the period of 2000-2010. A total of 148 individuals were registered (90 (61%) women, 58 (39%) men). 14 of these had died during the period, and three had emigrated (the latter were excluded from further analysis). The geographical distribution of PBGD mutation carriers was based on their addresses (five Danish regions, Greenland and Faroe Islands) at the end of the study period. PBGD mutations were detected by standard exon and splice site sequencing procedures.The biochemical diagnosis of an acute porphyria attack was based on a PBG/creatinine ratio of ≥5.0 mmol/mol (reference interval 0.0–0.8 mmol/mol).Demographic distribution and prevalence:Region of Denmark Populations number Number of different mutations Number of carriers identified Approximate prevalenceCapital 1.662.285 7 16 1:104.000Zealand 821.252 7 17 1:48.000South 1.194.659 12 36 1:33.000Central 1.247.732 5 27 1:46.000North 580.515 6 18 1:32.000Greenland 56.061 2 2 1:28.000FaroeIsl. 48.644 1 15 1:3.000Total 5.611.148 22 131 1:43.000 The average age of the 131 PBGD mutation carriers still alive at the end of the observation period was 47 years (2-97) (men; 44 years (2-97), women; 49 years (5-94)). Of these individuals 25 (19%) had obtained a biochemical diagnosis of AIP (6 (11%) men, 19 (26%) women). The total amount of measurements of biochemistry significant for acute porphyria attack in the registration period was 366, which corresponds to an average of 15 (1-83) per individual (32 (2-83) among the men, 9 (1-41) among the women) The 14 individuals who died during the registration period showed a higher prevalence of biochemical diagnosis of AIP (43%). Interestingly, they were all women showing a shorter mean lifespan (68 years, range 44-93) than the general female population (80.78 years). In total, 22 different PBGD mutations were discovered, the mutations were widely distributed across regions, with the striking exception of the Faroe Islands, where all 15 individuals carried the same mutation (c.498+1G>A, p.splicedefect). The prevalence of PBGD mutation was very high in the Faroe Islands (1:3000).However, for the rest of the country the prevalence was comparable to or lower than the prevalence reported in several other countries (Sweden (10:100.000),Finland (3:100.000),USA (4:100.000), and Western Australia (3:100.000)).[1]1. Bylesjö I. Epidemiological, clinical and pathogenetic studies of Acute Intermittent Porphyria. Dissertation, Umeå University. 2008.

AIM: To derive an accurate prediction model for estimating glomerular filtration rate (GFR) in children based primarily on the endogenous renal function marker cystatin C (CysC) and body cell mass (BCM).THEORY: Cystatin C is produced at a constant rate in all cells of the body and is excreted by glomerular filtration followed by catabolization in the tubular cells. We hypothesized that production rate is proportional to body cell mass (BCM) and inferred GFR (mL/min) to be proportional to BCM/CysC.MATERIAL AND METHODS: GFR was determined with 51Cr-EDTA-clearance in 131 children (52 girls, 79 boys) aged 2-14 years (mean 8.8 years). GFR was 14-147 mL/min/1.73m2 (mean 97 mL/min/1.73m2). BCM was estimated using bioimpedance spectroscopy (Xitron Hydra 4200). Log-transformed data on BCM/CysC, serum creatinine (SCr), body-surface-area (BSA), height x BSA/SCr, serum CysC, weight, sex, age, height, serum urea and albumin were considered possible explanatory variables using robust regression in a forward, stepwise procedure. GFR (mL/min) was the dependent variable. The accuracy and precision of the prediction model were compared to other prediction models from the literature, using leave-one-out cross validation. Local constants and coefficients were calculated for all models. RESULTS: New prediction equation GFR (mL/min) = (BCM/CysC)^0.40 x (heightxBSA/SCr)^0.65 x 10.2 could predict 130/131 within 30% of reference GFR, and 87/131 within 10%. This was higher than all other equations, see Table I. The present equation also had the highest R2 and the narrowest 95% limits of agreement.CONCLUSION: The new equation predicts GFR with higher accuracy than other equations. Endogenous methods are, however, still not accurate enough to replace exogenous markers when GFR must be determined with high accuracy. Table I. Bias, 95% limits of agreement (LOA), R2, root mean squared error (RMSE) and percentages of estimates within 10% and 30% of measured GFR of log-transformed data.Reference Bias(%)95% LOA(%)R2RMSEWithin 30%(%)Within 10%(%)Schwartz, 1976-1.1*-29.9; 26.8*0.6814.2*95.450.4Bökenkamp, 1998 0.07*-32.6; 32.8*0.5716.61*89.441.7Filler, 2003 0.12-29.9; 43.10.700.18190.142.4Bouvet, 2006 0.10-23.1; 30.10.930.13396.257.2Zappitelli, 2006 0.03-20.3; 25.50.880.11597.761.8Schwartz, 2008 0.01-20.4; 25.70.880.15696.964.1Present work, 20100.02-18.5; 22.80.960.10499.266.4*Not log-transformed

AIM: To derive an accurate prediction model for estimating glomerular filtration rate (GFR) in children based primarily on the endogenous renal function marker cystatin C (CysC) and body cell mass (BCM).THEORY: Cystatin C is produced at a constant rate in all cells of the body and is excreted by glomerular filtration followed by catabolization in the tubular cells. We hypothesized that production rate is proportional to body cell mass (BCM) and inferred GFR (mL/min) to be proportional to BCM/CysC.MATERIAL AND METHODS: GFR was determined with 51Cr-EDTA-clearance in 131 children (52 girls, 79 boys) aged 2-14 years (mean 8.8 years). GFR was 14-147 mL/min/1.73m2 (mean 97 mL/min/1.73m2). BCM was estimated using bioimpedance spectroscopy (Xitron Hydra 4200). Log-transformed data on BCM/CysC, serum creatinine (SCr), body-surface-area (BSA), height x BSA/SCr, serum CysC, weight, sex, age, height, serum urea and albumin were considered possible explanatory variables using robust regression in a forward, stepwise procedure. GFR (mL/min) was the dependent variable. The accuracy and precision of the prediction model were compared to other prediction models from the literature, using leave-one-out cross validation. Local constants and coefficients were calculated for all models. RESULTS: New prediction equation GFR (mL/min) = (BCM/CysC)^0.40 x (heightxBSA/SCr)^0.65 x 10.2 could predict 130/131 within 30% of reference GFR, and 87/131 within 10%. This was higher than all other equations, see Table I. The present equation also had the highest R2 and the narrowest 95% limits of agreement.CONCLUSION: The new equation predicts GFR with higher accuracy than other equations. Endogenous methods are, however, still not accurate enough to replace exogenous markers when GFR must be determined with high accuracy. Table I. Bias, 95% limits of agreement (LOA), R2, root mean squared error (RMSE) and percentages of estimates within 10% and 30% of measured GFR of log-transformed data.Reference Bias(%)95% LOA(%)R2RMSEWithin 30%(%)Within 10%(%)Schwartz, 1976-1.1*-29.9; 26.8*0.6814.2*95.450.4Bökenkamp, 1998 0.07*-32.6; 32.8*0.5716.61*89.441.7Filler, 2003 0.12-29.9; 43.10.700.18190.142.4Bouvet, 2006 0.10-23.1; 30.10.930.13396.257.2Zappitelli, 2006 0.03-20.3; 25.50.880.11597.761.8Schwartz, 2008 0.01-20.4; 25.70.880.15696.964.1Present work, 20100.02-18.5; 22.80.960.10499.266.4*Not log-transformed