8 resultados para reference range

em Deakin Research Online - Australia


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Background: Total immunoglobulin A in saliva (s-IgA) is normally assayed using an enzyme-linked immunosorbent assay. We have investigated methodological issues relating to the use of particle-enhanced nephelometric immunoassay (PENIA)
to measure s-IgA in whole unstimulated saliva and determine its reference range.

Methods: Whole unstimulated resting saliva was collected to determine sample stability (temperature, time, effect of a protease inhibitor), limit of quantitation (LOQ), assay precision and analytical variation. The reference range for 134 healthy adults was determined.

Results: Linearity was excellent (4–10.3 mg L21, P, 0.001; R2 ¼ 0.997) and without significant bias (mean of 20.7%). The lowest intra- and inter-analytical coefficients of variation were 1.8% and 7.5% and LOQ was 1.4 mg L21. The concentration of s-IgA is stable at room temperature for up to 6 h, at 48C for 48 h, at 248C for two weeks and at 2808C for up to 1.3 yr. There is no evidence that a protease inhibitor increases the stability or that repeated freeze–thawing cycles degrade sample quality. The reference ranges for s-IgA concentration, s-IgA secretion, s-IgA:albumin and s-IgA:osmolality were 15.9–414.5 mg L21, 7.2–234.9 mg min21, 0.4–19 and 0.6–8.9, respectively.

Conclusion:
Automated PENIA assay of s-IgA is precise and accurate. High stability of collected saliva samples and the ease and speed of the assay make this an ideal method for use in athletic and military training situations. The convenience of measuring albumin and IgA on the same analytical platform adds to the practicability of the test.

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Summary : A large population-based random sample of Australian white men was used to provide normative bone mineral density (BMD) data at multiple anatomical sites. The femoral neck BMD data are very similar to those obtained in USA non-Hispanic white males participating in the National Health and Nutrition Examination Survey III (NHANES III). The reference ranges will be suitable for similar populations.

Introduction : To provide normative BMD data for Australian men derived from a large population-based random sample.

Methods :
An age-stratified random sample of men was recruited from the Australian electoral rolls (n = 1,467 aged 20–97 years). BMD was quantified at multiple sites using Lunar densitometers.

Results : Age-related differences in BMD were best predicted by linear relationships at the spine and hip and by quadratic functions at the whole body and forearm. At the spine, a small age-related increase in mean BMD was observed. Although in the subset with no spinal abnormalities, there was a decrease of 0.003 g/cm2 per year from age 20. At the hip sites, mean BMD decreased at 0.001–0.006 g/cm2 per year from age 20. At the forearm and whole body, BMD peaked at 41–47 years. Apart from a small difference in men greater than or equal to 80 years, the Australian femoral neck BMD data are not different to those obtained in USA non-Hispanic white males participating in NHANES III and were generally similar to those of large studies from Canada (CaMos) and Spain.

Conclusions :
These data supply BMD reference ranges at multiple anatomical sites that will be applicable to white Australian men and similar populations such as USA non-Hispanic white men.

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Bone densitometry reports a measure of fracture risk in comparison with young adults (T-scores) and age-matched peers (Z-scores). To date, each manufacturer has provided its own reference range resulting in lack of uniformity. The Australia and New Zealand Bone and Mineral Society and Osteoporosis Australia have recognized the need to standardize the reference range and have recommended that data generated by the Geelong Osteoporosis Study (GOS) be used Australia-wide. The GOS recruited a random, population-based sample of adult women and measured bone mineral density (BMD) at the proximal femur and spine using a Lunar DPX-L. These data were used to establish reference ranges for Lunar machines and, using conversion equations, for Norland and Hologic machines. The new standardized Australian reference ranges for BMD will enable consistent diagnosis of osteoporosis and categorization of fracture risk across different types of densitometers.

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Objectives: To collect baseline data on the fat content of hot chips, quality (degradation) of cooking fat, deep-frying practices and related attitudes in fast food outlets in New Zealand. To identify the key determinants of the fat content of chips and quality of cooking fat. Methods: A nationally representative sample of fast food outlets (n=150, response rate 80%) was surveyed between September 1998 and March 1999. Data collected included a questionnaire, observation of cooking practices and analysis of cooked chips and frying fat. Results: Only 8% of independent operators had formal training in deep frying practices compared with 93% of chain operators. There was a wide range of fat content of chips (5%-20%, mean 11.5%). The use of thinner chips, crinkle cut chips and lower fryer fat temperature were associated with higher chip fat content. Eighty-nine per cent of chain outlets used 6–10 mm chips compared with 83% of independent outlets that used chips ≥12 mm. A wide range of frying temperatures was recorded (136–233°C) with 58% of outlets frying outside the reference range (175–190°C). As indices of fat degradation, fat acid and polar compound values above the recommended levels occurred in 54% and 5% of outlets respectively. Operators seemed willing to learn more about best practice techniques, with lack of knowledge being the main barrier to change. Conclusions and implications: Deep frying practices could be improved through operator training and certification options. Even a small decrease in the mean fat content of chips would reduce the obesogenic impact of this popular food.

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Fracture risk is determined by bone mineral density (BMD). The T-score, a measure of fracture risk, is the position of an individual's BMD in relation to a reference range. The aim of this study was to determine the magnitude of change in the T-score when different sampling techniques were used to produce the reference range. Reference ranges were derived from three samples, drawn from the same region: (1) an age-stratified population-based random sample, (2) unselected volunteers, and (3) a selected healthy subset of the population-based sample with no diseases or drugs known to affect bone. T-scores were calculated using the three reference ranges for a cohort of women who had sustained a fracture and as a group had a low mean BMD (ages 35-72 yr; n = 484). For most comparisons, the T-scores for the fracture cohort were more negative using the population reference range. The difference in T-scores reached 1.0 SD. The proportion of the fracture cohort classified as having osteoporosis at the spine was 26, 14, and 23% when the population, volunteer, and healthy reference ranges were applied, respectively. The use of inappropriate reference ranges results in substantial changes to T-scores and may lead to inappropriate management.

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Many children with autistic spectrum disorders (ASDs) suffer from gastrointestinal problems such as diarrhoea, constipation and abdominal pain. Such symptoms may be due to a disruption of the indigenous gut microbiota promoting the overgrowth of potentially pathogenic micro-organisms. These observations have stimulated investigations into possible abnormalities of intestinal microbiota in autistic patients. The purpose of the present study was to determine if a relationship exists between ASD severity (mild – severe) and GI microbial populations. The faecal microbiota of 22 male and 6 female participants with ASDs (aged 7 ± 6 years) were analyzed by standard microbial culture methods and compared within-group (based on ASD severity) and with a standard laboratory reference range. Comparisons between children with mild ASD and those with moderate to severe ASD, as well as comparisons to a neurotypical control group previously reported, revealed that no significant differences appear to exist in the composition of the gut microbiota. Nevertheless, examination of each individual’s gut microbial composition showed 10 cases of unusual findings witch means 1out of 3 cases have unusual microbiota. Our data do not support consistent GI microbial abnormalities in ASD children, but the findings do suggest that aberrations may be found in a minority subset of ASD children. Further studies are required to determine the possible association between the microbiota and gastrointestinal dysfunctions in a subset of children with both ASD and gastro-intestinal problems.

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Introduction

We aimed to make recommendations concerning the use of total IgA in saliva (s-IgA) as an aid for monitoring athletic and military training.

Methods:
Unstimulated whole saliva was collected from 16 subjects (11 women and 5 men ages 18–57) during nonconsecutive days of fasting and non-fasting. Seven samples were collected from each subject at 0700, 0900, 1200, 1400, 1600, 1800, and 2030 on each day and a further three samples were collected 30 min after three meals on the non-fasting day (at 0730, 1230, and 1830). Strenuous activity was avoided and subjects did not drink caffeine or alcohol-containing beverages. Albumin and s-IgA were measured by commercial nephelometric immunoassays with intra-analytical coefficient of variance (CVA) of 1.8% and 2.9%, respectively. Individual and group variations were determined. Diurnal variation was determined by use of repeated-measures analysis of variance.

Results:
CV-individual (CVI) was 48% for s-IgA concentration and 43% for s-IgA secretion and s-IgA:albumin. CV-group (CVG) for these same measures was 68%, 75%, and 68%, respectively. When measurements were adjusted for saliva flow rates there was no evidence that s-IgA is subject to diurnal variation. There was strong evidence for a postprandial decrease in s-IgA for all measures.

Conclusion:
The high degree of individuality in s-IgA precludes the use of population reference ranges for identifying individual abnormal results. For the purpose of monitoring individuals we recommend using the individual's calculated biological variance (determined from previous serial measurements over a period of days to weeks). Individual abnormal results can then be identified.

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Summary Heel ultrasound is a more portable modality for assessing fracture risk than dual-energy X-ray absorptiometry and does not use ionising radiation. Fracture risk assessment requires appropriate reference data to enable comparisons. This study reports the first heel ultrasound reference ranges for the Australian population.

Introduction This study aimed to develop calcaneal (heel) ultrasound reference ranges for the Australian adult population using a population-based random sample.

Methods Men and women aged ≥20 years were randomly selected from the Barwon Statistical Division in 2001–2006 and 1993–1997, respectively, using the electoral roll. Broadband ultrasound attenuation (BUA), speed of sound (SOS) and stiffness index (SI) were measured at the heel using a Lunar Achilles Ultrasonometer. Gender-specific means and standard deviations for BUA, SOS and SI were calculated for the entire sample (men 20–93 years, n = 1,104; women 20–92 years, n = 914) and for participants aged 20–29 years (men, n = 157; women, n = 151). Associations between ultrasound measures and age were examined using linear regression.

Results For men, mean ± standard deviation BUA, SOS and SI were 118.7 ± 15.8 dB/MHz, 1,577.0 ± 43.7 m/s and 100.5 ± 20.7, respectively; values for women were consistently lower (111.0 ± 16.4 dB/MHz, P < 0.001; 1,571.0 ± 39.0 m/s, P = 0.001; and 93.7 ± 20.3, P < 0.001, respectively). BUA was higher in young men compared with young women (124.5 ± 14.4 vs 121.0 ± 15.1 dB/MHz), but SOS (1,590.1 ± 43.1 vs 1,592.5 ± 35.0 m/s) and SI (108.0 ± 19.9 vs 106.3 ± 17.7) were not. The relationships between age and each ultrasound measure were linear and negative across the age range in men; associations were also negative in women but non-linear.

Conclusion These data provide reference standards to facilitate the assessment of fracture risk in an Australian population using heel ultrasound.