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PubMed1990

Increased hepatic efficacy of urea synthesis from alanine in insulin-dependent diabetes mellitus.

The relation of urea synthesis rate to blood alanine concentration was assessed in seven healthy controls and in 18 patients with insulin-dependent diabetes mellitus (HbAlc = 8.4 +/- 1.0% (mean +/- SD)). Following an overnight fast alanine was infused at 2 mmol h-1 kg-1 body weight. The hourly rate of urea synthesis was determined as the urinary excretion of urea corrected for accumulation of urea in total body water and intestinal hydrolysis. The functional hepatic nitrogen clearance, i.e. the relation of urea synthesis rate to blood alanine concentration, was calculated as the slope of linear regression of urea synthesis rates on blood alanine concentrations. Fasting glucagon concentrations were 85 +/- 26 ng l-1 in controls and 161 +/- 35 ng l-1 (P less than 0.01) in patients. The functional hepatic nitrogen clearances were 21.8 +/- 4.4 l h-1 in controls and 44.7 +/- 12.4 l h-1 (P less than 0.001) in patients. By multiple step-wise linear regression analysis the functional hepatic nitrogen clearance was found to correlate independently to fasting glucagon concentration, duration of diabetes, change in blood glucose and insulin following alanine infusion (r2 = 0.74). In a simple linear regression analysis the functional hepatic nitrogen clearance correlated strongly to fasting glucagon concentration (r2 = 0.54). In conclusion the kinetics of urea synthesis in insulin-dependent diabetes is changed in favour of increased conversion of alanine-N to urea-N at any blood amino acid concentration. The increased FHNC correlates strongly with hyperglucagonaemia.

Adult↗
PubMed2005

A new statistical approach for quantifying change in series of retinal and optic nerve head topography images.

PURPOSE: To describe and evaluate new statistical techniques for detecting topographic changes in series of retinal and optic nerve head images acquired by scanning laser tomography (Heidelberg Retinal Tomograph [HRT]; Heidelberg Engineering, Heidelberg, Germany). METHODS: Proven quantitative techniques, collectively referred to as statistic image mapping (SIM), are widely used in neuroimaging. These techniques are applied to HRT images. A pixel-by-pixel analysis of topographic height over time yields a statistic image that is generated by using permutation testing, derives significance limits for change wholly from the patient's own data, and removes the need for reference data sets. These novel techniques were compared to the Topographic Change Analysis (TCA super-pixel analysis) available in the current HRT software, by means of an extensive series of computer experiments. The SIM and TCA techniques were further tested and compared to linear regression of rim area (RA) against time, in real longitudinal HRT series of eyes of 20 normal subjects and 30 ocular hypertensive (OHT) patients that were known to have converted to glaucoma, on the basis of visual field criteria. RESULTS: Computer simulation indicated that SIM has better diagnostic precision at detecting change. In the real longitudinal series, SIM flagged false-positive structural progression in two (10%) of normal subjects, whereas TCA identified three (15%), and linear regression of RA against time identified two (10%). SIM identified 22 (73%) of the OHT converters as having structural progression, whereas the TCA and linear regression of RA against time each identified 16 (53%) over the course of the follow-up. CONCLUSIONS: SIM has better diagnostic precision in detecting change in series of HRT images when compared to current quantitative techniques. The clinical utility of these techniques will be established on further longitudinal data sets.

Adult↗
PubMed2004

Aerobic composting of chips from clear-cut trees with various co-materials.

Swollen chips made from trees felled during clear-cutting were composted with various organic and inorganic materials in an aerobic composting reactor for 5 months and then piled for 5 months. The organic materials included chicken feces, urea, nitrogenous lime (calcium cyanamide, manure), and material rapidly composted from food garbage in 24-h bacterial fermentation, while the inorganic materials were coal ash and volcanic ash. In this paper, we first attempt to estimate the quality and degree of maturity of each compost from its chemical properties. Furthermore, we try to calculate the maturity of the fermented wood chip composts from their mixture ratio of the initial materials by multiple linear regression analysis. We measured changes in the C/N ratio, nitrate nitrogen (NO3-N) content, percentage of humic acid in the alkali soluble fraction (PQ), cation exchange capacity, pH, and EC during the composting period. The degrees of maturity of the composts were estimated via a plant growth test using Chinese cabbage. We found that the CN ratio, NO3-N concentration, and PQ were suitable for estimating the degree of maturity of wood chip composts. For maturity, the CN ratio should be less than 14, the PQ more than 66.2, and the NO3-N concentration more than 853 mgkg-1. We devised an equation to estimate the degree of maturity after 10 months by a multiple linear regression analysis from the mixing ratio of wood chips and the co-composted materials. From the multiple linear regression analysis, the above three indices of compost maturity could be estimated from the mixing ratio of the initial materials. This equation should enable us to determine the degree of compost maturity after 10 months based on the initial mixing ratio.

Brassica↗
PubMed1998

Comparative binding energy analysis of HIV-1 protease inhibitors: incorporation of solvent effects and validation as a powerful tool in receptor-based drug design.

A comparative binding energy (COMBINE) analysis (Ortiz et al. J. Med. Chem. 1995, 38, 2681-2691) has been performed on a training set of 33 HIV-1 protease inhibitors, and the resulting regression models have been validated using an additional external set of 16 inhibitors. This data set was originally reported by Holloway et al. (J. Med. Chem. 1995, 38, 305-317), who showed the usefulness of molecular mechanics interaction energies for predicting the activity of novel HIV-1 protease inhibitors within the framework of the MM2X force field and linear regression techniques. We first used the AMBER force field on the same set of three-dimensional structures to check up on any possible force-field dependencies. In agreement with the previous findings, the calculated raw ligand-receptor interaction energies were highly correlated with the inhibitory activities (r2 = 0.81), and the linear regression model relating both magnitudes had an acceptable predictive ability both in internal validation tests (q2 = 0.79, SDEPcv = 0.61) and when applied to the external set of 16 different inhibitors (SDEPex = 1.08). When the interaction energies were further analyzed using the COMBINE formalism, the resulting PLS model showed improved fitting properties (r2 = 0.89) and provided better estimations for the activity of the compounds in the external data set (SDEPex = 0.83). Computation of the electrostatic part of the ligand-receptor interactions by numerically solving the Poisson-Boltzmann equation did not improve the quality of the linear regression model. On the contrary, incorporation of the solvent-screened residue-based electrostatic interactions and two additional descriptors representing the electrostatic energy contributions to the partial desolvation of both the ligands and the receptor resulted in a COMBINE model that achieved a remarkable predictive ability, as assessed by both internal (q2 = 0.73, SDEPcv = 0.69) and external validation tests (SDEPex = 0.59). Finally, when all the inhibitors studied were merged into a single expanded set, a new model was obtained that explained 91% of the variance in biological activity (r2 = 0.91), with very high predictive ability (q2 = 0.81, SDEPcv = 0.66). In addition, the COMBINE analysis provided valuable information about the relative importance of the contributions to the activity of individual residues that can be fruitfully used to design better inhibitors. All in all, COMBINE analysis is validated as a powerful methodology for predicting binding affinities and pharmacological activities of congeneric ligands that bind to a common receptor.

Drug Design↗
PubMed1991

Implantable glucose sensors: comparison between in vitro and in vivo kinetics.

This study was aimed at validating the in vitro estimated response characteristics of implanted glucose oxidase/H2O2 electrodes with respect to their in vivo function. Monoexponential non-linear regression analysis of sensor current vs. time curves in response to square alterations in glucose concentration gave response times T95 of between 1 and 5 min. Non-primed glucose infusions were applied to dogs with these electrodes implanted subcutaneously. The simultaneously monitored in vivo data were subjected to non-linear regression analysis. The time constants T of increases or decreases after starting or ending the glucose load were (mean +/- SEM) 53 +/- 10 and 26 +/- 4 min (significant difference, p less than 0.05) in sensor current, 28 +/- 8 and 15 +/- 2 min (NS) in whole blood, and 26 +/- 5 and 18 +/- 2 min (NS) in plasma. The in vivo kinetic patterns of sensors were not related to their in vitro response times. Non-linear regression analysis of in vitro responses of glucose sensors under clearly defined conditions is recommended as a basis for further studies. The physiological delay in the subcutaneous glucose system needs more attention in this field of research.

Animals↗
PubMed2006

Prediction of ozone concentrations in Oporto city with statistical approaches.

The performance of three statistical methods: time-series, multiple linear regression and feedforward artificial neural networks models were compared to predict the daily mean ozone concentrations. The study here reported was based on data from one urban site with traffic influences and one rural background site. The studies were performed for the year 2002 and the respective four trimesters separately. In the multiple linear regression and feedforward artificial neural network models, the concentrations of ozone, the concentrations of its precursors (nitrogen oxides) and some meteorological variables for one and two days before the prediction day were used as predictors. For the application of these models in the validation step, the inputs of ozone concentration for one and two days before were replaced by the ozone concentrations predicted by the models. The results showed that time-series modelling was not profitable. In the development step, similar performances were obtained with multiple linear regression and feedforward artificial neural network. Better performance indexes were achieved with feedforward artificial neural network models in validation step. Concluding, feedforward artificial neural network models were more efficient to predict ozone concentrations.

Air Pollutants↗
PubMed1975

Optimal statistical design of radioimmunoassays and competitive protein-binding assays.

The statistical analysis of radioimmunoassay and competitive protein binding assay data is complex. Because the response variable (percent counts) is not lineraly related to log dose, a logit transformation of the response variable usually is performed to permit linear regression analysis. This transformation induces marked heterogeneity of variance, so that iterative weighted regression programs have been used to achieve the best standard curve and the most precise dose estimates of unknowns. In this study several parameters of assay design are investigated in order to establish those designs yielding antigen concentration estimates of highest precision as well as estimates of comparable precision by either simple linear regression analysis or by the more complex weighted regression technique. Unknown estimates of highest precision are obtained when 1) the present counts of the standard doses covers a range of approximately 80 percent to 20 percent, 2) the number of standard dose levels is eight or more, 3) the number of replicates at each dose level is two or more, and 4) the percent counts of the unknowns also are within the range 80 percent ot 20 percent. Under these conditions, also, simple linear regression yields unknown estimates of comparable precision to weighted regression and therefore may be safely used.

Antigens↗
PubMed1984

Quantitative evaluation of anti-HBs in sera--II.

We have investigated about the most correct way to express the anti-HBs titration in serum. The following linear regression has been elaborated on the basis of the results (converted into logarithms) obtained by 33 titrations of the International Reference Standard (the dilutions prepared were the following: 150, 100, 75, 37.5, 18.75, 9.375 mUI/ml) by as many kit lots AUSAB EIA (Abbott): y = 0.8590732x - 1.6936435. The correlation between the couples: optical density log. mUI/ml has been highly significative (r = 0.991091; P less than 0.01). In order to limit the variability effects in the same laboratory, the use of the correction factor "F" is suggested. The variation of the optical density corrected by the "F" variation is illustrated. A linear regression on the Author's data has been elaborated by the inverse application of the Hollinger formula. The adaptability of this linear regression has been tested on 196 dilutions out of the 33 standard tests studied. The average values obtained, the 95% confidence limits and the mean values +/- 2s limits are compared with the same values obtained by applying the Hollinger original formula.

Hepatitis B Antibodies↗
PubMed2024

An epigenome-wide study of selenium status and DNA methylation in the Strong Heart Study.

BACKGROUND: Selenium (Se) is an essential nutrient linked to adverse health endpoints at low and high levels. The mechanisms behind these relationships remain unclear and there is a need to further understand the epigenetic impacts of Se and their relationship to disease. We investigated the association between urinary Se levels and DNA methylation (DNAm) in the Strong Heart Study (SHS), a prospective study of cardiovascular disease (CVD) among American Indians adults. METHODS: Selenium concentrations were measured in urine (collected in 1989-1991) using inductively coupled plasma mass spectrometry among 1,357 participants free of CVD and diabetes. DNAm in whole blood was measured cross-sectionally using the Illumina MethylationEPIC BeadChip (850 K) Array. We used epigenome-wide robust linear regressions and elastic net to identify differentially methylated cytosine-guanine dinucleotide (CpG) sites associated with urinary Se levels. RESULTS: The mean (standard deviation) urinary Se concentration was 51.8 (25.1) μg/g creatinine. Across 788,368 CpG sites, five differentially methylated positions (DMP) (hypermethylated: cg00163554, cg18212762, cg11270656, and hypomethylated: cg25194720, cg00886293) were significantly associated with Se in linear regressions after accounting for multiple comparisons (false discovery rate p-value: 0.10). The top hypermethylated DMP (cg00163554) was annotated to the Disco Interacting Protein 2 Homolog C (DIP2C) gene, which relates to transcription factor binding. Elastic net models selected 425 hypo- and hyper-methylated DMPs associated with urinary Se, including three sites (cg00163554 [DIP2C], cg18212762 [MAP4K2], cg11270656 [GPIHBP1]) identified in linear regressions. CONCLUSIONS: Urinary Se was associated with minimal changes in DNAm in adults from American Indian communities across the Southwest and the Great Plains in the United States, suggesting that other mechanisms may be driving health impacts. Future analyses should explore other mechanistic biomarkers in human populations, determine these relationships prospectively, and investigate the potential role of differentially methylated sites with disease endpoints.

Humans↗
PubMed1997

Influence of regional cardiovascular mortality on the use of angiography after acute myocardial infarction.

Utilization of angiography after acute myocardial infarction (AMI) treated with thrombolytics has been shown in large clinical trials to be related primarily to the availability of the procedure and not individual clinical circumstances. This study evaluated the regional influence of overall population cardiovascular mortality on utilization of angiography in the United States participants of the Global Utilization of Streptokinase and t-PA for Occluded Arteries (GUSTO-1) trial. Published summary statistics from GUSTO-1 and U.S. Census Bureau 1991 data were evaluated using simple and multiple linear regression with analysis for outliers. Region predictor variables (age adjusted) included mean total cardiovascular deaths/100,000/year (ICD/9 codes 390 to 459), mean coronary artery disease deaths/ 100,000/year (ICD/9 codes 410 to 414), and mean stroke deaths/100,000/year (ICD/9 codes 430 to 438), with the major outcome being regional proportion of GUSTO-1 patients undergoing angiography during the hospital stay after treatment with thrombolysis. All 3 cardiovascular death rates varied significantly by region (p < 0.00002) with no significant difference in GUSTO-1 mortality by region (p = 0.25). Simple linear regression analysis revealed associations between regional death rates and angiography use (r = 0.60, p = 0.12; r = 0.39, p = 0.33; r = 0.81, and p = 0.015). Multiple stepwise linear regression analysis found regional death rate due to stroke as the strongest predictor of angiography use with 65.86% of the variation explained by the model. New England was found to be a consistent outlier with reduced angiography use because of its background regional disease burden. This study confirms regional bias in the use of angiography in GUSTO-1. This form of operator bias appears to be due to more aggressive practice patterns in regions, except New England, where the overall cardiovascular disease burden is greater in terms of lives lost per 100,000 per year.

Age Factors↗
PubMed2006

Scanning microarrays at multiple intensities enhances discovery of differentially expressed genes.

MOTIVATION: Scanning parameters are often overlooked when optimizing microarray experiments. A scanning approach that extends the dynamic data range by acquiring multiple scans of different intensities has been developed. RESULTS: Data from each of three scan intensities (low, medium, high) were analyzed separately using multiple scan and linear regression approaches to identify and compare the sets of genes that exhibit statistically significant differential expression. In the multiple scan approach only one-third of the differentially expressed genes were shared among the three intensities, and each scan intensity identified unique sets of differentially expressed genes. The set of differentially expressed genes from any one scan amounted to < 70% of the total number of genes identified in at least one scan. The average signal intensity of genes that exhibited statistically significant changes in expression was highest for the low-intensity scan and lowest for the high-intensity scan, suggesting that low-intensity scans may be best for detecting expression differences in high-signal genes, while high-intensity scans may be best for detecting expression differences in low-signal genes. Comparison of the differentially expressed genes identified in the multiple scan and linear regression approaches revealed that the multiple scan approach effectively identifies a subset of statistically significant genes that linear regression approach is unable to identify. Quantitative RT-PCR (qRT-PCR) tests demonstrated that statistically significant differences identified at all three scan intensities can be verified. AVAILABILITY: The data presented can be viewed at http://www.ncbi.nlm.nih.gov/geo/ under GEO accession no. GSE3017.

Gene Expression Profiling↗
PubMed1997

Prediction equations do not eliminate systematic error in self-reported body mass index.

Epidemiological studies of the risks of obesity often use body mass index (BMI) calculated from self-reported height and weight. The purpose of this study was to examine the pattern of reporting error associated with self-reported values of BMI and to evaluate the extent to which linear regression models predict measured BMI from self-reported data and whether these models could compensate for this reporting error. We examined measured and self-reported weight and height on 5079 adults aged 30 years to 64 years from the second National Health and Nutrition Examination Survey. Measured and self-reported BMI (kg/m2) was calculated, and multiple linear regression techniques were used to predict measured BMI from self-reported BMI. The error in self-reported BMI (self-reported BMI minus measured BMI) was not constant but varied systematically with BMI. The correlation between measured BMI and the error in self-reported BMI was -0.37 for men and -0.38 for women. The pattern of reporting error was only weakly associated with self-reported BMI, with the correlation being 0.05 for men and -0.001 for women. Error in predicted BMI (predicted BMI minus measured BMI) also varied systematically with measured BMI, but less consistently with self-reported BMI. More complex models only slightly improved the ability to predict measured BMI compared with self-reported BMI alone. None of the equations were able to eliminate the systematic reporting error in determining measured BMI values from self-reported data. The characteristic pattern of error associated with self-reported BMI is difficult or impossible to correct by the use of linear regression models.

Adult↗
PubMed2004

Transcutaneous carbon dioxide monitoring during diabetic ketoacidosis in children and adolescents.

OBJECTIVE: Our aim was to evaluate the utility of transcutaneous CO2 (TC-CO2) monitoring in following the response to therapy in children and adolescents in diabetic ketoacidosis (DKA) requiring ICU admission. METHODS: During therapy for DKA, TC-CO2 was monitored and compared with the serum bicarbonate values (HCO3-). As clinically indicated, serum electrolytes including serum HCO3- were drawn and at the same time, the TC-CO2 value was recorded. Using the TC-CO2 value and the equation (PaCO2=1.5xHCO3-+8), a calculated HCO3- value was determined. The measured serum HCO3- value was subtracted from the calculated HCO3- value and the absolute difference was recorded. The difference between the measured serum HCO3- and the calculated HCO3- was analysed using analysis of variance after stratification for serum HCO3- values and patient age ranges. Calculated to serum HCO3- values were compared using linear regression analysis. In addition, serum HCO3- values were plotted against TC-CO2 values to derive an equation from these data which would relate the TC-CO2 values to the measured serum HCO3-. RESULTS: The cohort included 28 patients ranging in age from 1.6 to 21 years (9.4 +/- 4.7 years) and in weight from 13 to 96 kg (35.6 +/- 18.2 kg). Two additional patients were not included as the initial TC-CO2 values were inaccurate because of tissue hypoperfusion. In the remaining 28 patients, the absolute difference between the calculated bicarbonate and serum bicarbonate values was 1.5 +/- 1.2 mmol.l-1. The difference was < or =2 mol.l in 74.4% of samples and < or=5 mmol.l(-1) in 99.2%. No difference in the value between the calculated and measured serum HCO3- was present according to serum HCO3- value or patient's age. Linear regression analysis of calculated HCO3- against serum HCO3- revealed a slope of 0.95 and an r2 value of 0.88. Linear regression analysis using serum HCO3- against TC-CO2 resulted in the following equations: TC-CO2=(1.64xHCO3-)+3.9 or HCO3-=0.61x(TC-CO2-3.9). CONCLUSIONS: TC-CO2 correlates with serum HCO3- and can be used to follow therapy in children and adolescents in DKA.

Adolescent↗
PubMed2006

A Process Analytical Technology approach to near-infrared process control of pharmaceutical powder blending. Part III: Quantitative near-infrared calibration for prediction of blend homogeneity and characterization of powder mixing kinetics.

The Process Analytical Technology (PAT) initiative, undertaken by the Food and Drug Administration (FDA), paves the way for improvement of drug manufacturing through real-time measurements that allow better process understanding. This study is the third and final Part in a series of studies that represent an integrated approach for real-time blend uniformity assessment using near-infrared (NIR) technology. In this study, the development of a quantitative NIR model for prediction of blending end point is presented. Process signature was built into NIR calibration models by using blend samples that were collected from actual blend experiments under different processing conditions. Evaluation of various calibration algorithms including principal component regression (PCR), partial least squares (PLS), and multi-term linear regression (MLR) was performed. It was found that linear regression, using a single wavelength, yielded optimum calibration and prediction results. The blending profiles predicted by the NIR quantitative model correlated well to those determined by the UV reference analytical method. Characterization of intra-shell versus inter-shell powder mixing kinetics and its implication in sensor positioning was also performed and will be discussed.

Calibration↗
PubMed2004

Measures of abdominal obesity assessed for visceral adiposity and relation to coronary risk.

AIMS: We aimed to identify by computed tomography (CT) the best suited of three anthropometric indices that reflect the visceral adipose tissue (VAT), and to discern the relationship between VAT and certain atherogenic risk factors and coronary heart disease (CHD) diagnosis in a population sample which had a high (34%) prevalence of the metabolic syndrome (MS). METHODS: A single-scan CT was performed between the fourth and fifth lumbar vertebrae in 157 unselected men and women aged 34-69 y. Total adipose tissue area, abdominal VAT area and the abdominal sagittal diameter were determined. Diagnosis of CHD was based on clinical findings and Minnesota coding of resting electrocardiograms. RESULTS: Men had significantly higher VAT than women. Linear regression analysis for correlates of abdominal VAT area, in a model comprising age, sex, waist circumference, waist-to-hip ratio (WHR) and body mass index (BMI) identified waist circumference as the only independent variable (P<0.001). Waist circumference in men and BMI in women were the independently associated parameters of sagittal diameter (P<0.001). By stepwise linear regression, it was elicited that VAT area rose significantly by a mean of 6.8 cm2 in men and 3 cm2 in women for every 1 cm increment in waist circumference, independent of WHR. Age in women and (inversely) BMI in men were further independent variables, indicating in men that a lower BMI at a given waist girth suggests the existence of a higher VAT. Apo B and HDL-cholesterol (HDL-C) in men, and the latter in women were independently associated with VAT area in linear regression models that also comprised triglycerides, fasting insulin and C-reactive protein concentrations. In the study sample comprising 13 individuals with a CHD diagnosis, the age-adjusted odds ratio of cutpoints of VAT area > vs <140 cm2 in men and > vs <120 cm2 in women was 11.3 (95% CI (1.37, 93)). CONCLUSIONS: The best surrogate of visceral adiposity across a wide age range is waist circumference, in a population in which MS prevails. Apo B and HDL-C in men, and the latter in women were independently associated with VAT area, which proved to be closely related to CHD risk. A lower BMI at a given waist girth in men suggests the existence of a higher VAT.

Abdomen↗
PubMed2003

The influence of serum leptin concentration on bone mass assessed by quantitative ultrasonometry in pre and postmenopausal women.

OBJECTIVE: the aim of this study was to evaluate the influence of serum leptin concentration on bone mass assessed by quantitative ultrasound (QUS) in a large sample of healthy pre and postmenopausal women. DESIGN: 555 healthy pre and postmenopausal (n=261 and n=294) women (mean age, 49.5+/-17.2 years) not on hormone replacement therapy were recruited on the occasion of a routine gynecological visit. Before entry to the study, all women had answered a detailed questionnaire on important risk factors and gave written informed consent. Speed of sound (SOS), broadband ultrasound attenuation (BUA) and stiffness index (SI) of the os Calcis were measured using the Achilles ultrasonometer (GE/lunar). We systematically investigated the relation of menopause, BMI and leptin on bone mass by allocating women into the following groups: (a) premenopausal women BMI<25 kg/m(2) (N=178); (b) premenopausal women BMI>25 kg/m(2) (N=83); (c) postmenopausal women BMI<25 kg/m(2) (N=125); and (d) postmenopausal women BMI>25 kg/m(2) (N=169). Additionally we investigated the relation of serum leptin concentrations, age and BMI on ultrasonometry variables by performing a multiple linear regression analyses. RESULTS: in the initial analyses premenopausal women showed a significantly (P<0.001) lower mean age, weight, BMI, follicle stimulating hormone (FSH) and leptin concentration, a higher mean height, serum estradiol and ultrasonometry variables in comparison to postmenopausal women. Irrespective of the menopausal status, women with a BMI>25 kg/m(2) had significantly higher leptin concentrations (P<0.001) and BUA (P<0.05) whereas SOS and SI was not significant different, compared to women with a BMI<25 kg/m(2). The multiple linear regression analyses showed that only BMI but not Leptin was related to higher ultrasonometry variables, whereas increasing age was associated with a decrease in ultrasonometry variables. Furthermore, the multiple linear regression analyses confirmed that age and BMI were the only statistically significant independent predictor for ultrasonometry variables. There was no significant influence of leptin on ultrasonometry variables even after controlling for BMI or age, or BMI and age. CONCLUSIONS: serum leptin concentrations are significantly higher in pre and postmenopausal obese women, compared with normal weight controls. Ultrasonometry variables are influenced by age and BMI but not by serum leptin concentrations.

Adult↗
PubMedDate not supplied

Calculation of knemometric growth rates in group studies of children treated with exogenous glucocorticoids.

Calculation of growth rates in short-term knemometry studies is often based on linear regression analysis. The method, however, has not been compared to the conventional method for calculation of growth rates (increase in length divided by the time interval) in glucocorticoid-treated populations. The aim of the present study was to assess whether the conventional method for calculation of growth rates is as sensitive as the linear regression method in the assessment of short-term lower leg growth in group studies of children treated with exogenous glucocorticoids. Three different studies were conducted during which knemometry was performed once or twice weekly. Six boys and six girls aged 5-12 years, with atopic dermatitis, participated in an open longitudinal study with three periods of 2 weeks duration. Ten boys and four girls aged 12-16 years, with asthma, were studied in a randomized double-blind, placebo-controlled two-period crossover trial, with treatment periods of 4 weeks. Thirteen boys and 11 girls aged 5-12 years, with asthma, were enrolled in a randomized double-blind two-period crossover trial with treatment periods of 4 weeks. During active treatment periods topical budesonide was given. Mean lower leg growth rates and the results of significance tests based on the two methods for calculation of growth rates were similar in all studies. Significant correlations between the growth rates based on the two methods were found in the non-glucocorticoid and glucocorticoid treatment periods in all studies (Pearson correlation r coefficient varied from 0.81 to 0.97, p from < 0.001 to < 0.0001). The conventional method for calculation of lower leg growth rates is as reliable as linear regression analysis. By using the conventional method the number of visits required for knemometric growth rate assessment in group studies of systemic activity of exogenous glucocorticoids can be reduced.

Administration, Cutaneous↗
PubMed2003

Effect of lesion size, visual acuity, and lesion composition on visual acuity change with and without verteporfin therapy for choroidal neovascularization secondary to age-related macular degeneration: TAP and VIP report no. 1.

PURPOSE: To determine whether differences in baseline lesion size and visual acuity might explain differing results found in three different lesion compositions (predominantly classic, minimally classic, and occult with no classic) among three placebo-controlled, randomized clinical trials evaluating photodynamic therapy with verteporfin (Visudyne, Novartis AG), also termed verteporfin therapy, in patients with subfoveal choroidal neovascularization (CNV) due to age-related macular degeneration (AMD). METHODS: Exploratory analyses were conducted in patients with predominantly classic or minimally classic lesions at enrollment in the Treatment of AMD with Photodynamic Therapy (TAP) Investigation and in AMD patients with occult with no classic CNV in the Verteporfin In Photodynamic Therapy (VIP) Trial. Baseline characteristics of patients among these three lesion compositions were compared. In addition, multiple linear regression modeling was used to explore the effect of baseline lesion size, visual acuity, and lesion composition on mean change in visual acuity from baseline to 24 months. RESULTS: At baseline, the mean size of predominantly classic lesions (3.4 disk areas) was smaller than that of minimally classic (4.7 disk areas) and occult with no classic lesions (4.3 disk areas). In the multiple linear regression model of individual lesion compositions, there was a significant treatment-by-lesion-size interaction for minimally classic and occult with no classic lesions, but not for predominantly classic lesions. Interaction between treatment and baseline visual acuity was not significant for any lesion composition. Small verteporfin-treated lesions lost less vision than large verteporfin-treated lesions in each lesion composition. In the multiple linear regression model that included all lesion compositions, lesion size was a more significant predictive factor for the magnitude of treatment benefit than either lesion composition or visual acuity. Smaller (4.0 disk areas or less) minimally classic and occult with no classic lesions had similar visual acuity outcomes to those observed in predominantly classic lesions. CONCLUSIONS: Based on exploratory analyses, lesion size in the TAP Investigation and VIP Trial was an important predictor of the magnitude of treatment benefit with verteporfin therapy in occult with no classic and minimally classic lesion compositions. In patients with AMD, treating smaller rather than larger neovascular lesions, regardless of lesion composition, likely will result in a better level of visual acuity.

Aged↗