Observer variation in spirometry.
The intra-observer and inter-observer variation associated with clinical spirometry was statistically analyzed. The technical errors for the MEFR and MMF measurements were large enough to question their clinical reliability, especially in borderline instances. Measurement differences between two observers, as in this study, are statistically significant. This observation has special meaning for groups engaged in epidemiologic studies. Significant inter-individual variation will diminish the quality of pooled results.
Variability of routine pulmonary function tests1
Hruby, J. and Butler, J. (1975). Thorax, 30, 548-553. Variability of routine pulmonary functon tests. Pulmonary function tests sometimes indicate a progressive deterioration and at other times a 'stepwise' worsening which may be followed by improvement. Interpretation depends on the extent of random or diurnal variations in function. Routine pulmonary function tests (VC, FEV,, FRC, and airway resistance (Raw)) were repeatedly measured in normal subjects, patients with stable irreversible airways obstruction, and patients with stable restrictive disease. In all groups there was a significant (P<0 001) diurnal variation in Raw, with high values in the morning, low values at noon, and rising values in the evening. The midday Raw values were about 80% of the highest daily values. The considerable random and diurnal variability seen in all tests is reflected in the range of high and low values (% of mean individual response) in individuals. The largest variation in an individual between measurements taken at two different times was 81% in Raw (range: 40% above to 41% below the mean). There was less variation in FEV, (29%), FRC (62%), and VC (30%). Thus the finding of a stepwise change in function could reflect its natural variability. When repeated studies are done to assess progress or the effects of therapy on disease, there are many factors, including the time of day at which the tests are performed, which should be standardized as far as possible.
An automated retinal image quality grading algorithm
This paper introduces an algorithm for the automated assessment of retinal fundus image quality grade. Retinal image quality grading assesses whether the quality of the image is sufficient to allow diagnostic procedures to be applied. Automated quality analysis is an important preprocessing step in algorithmic diagnosis, as it is necessary to ensure that images are sufficiently clear to allow pathologies to be visible. The algorithm is based on standard recommendations for quality analysis by human screeners, examining the clarity of retinal vessels within the macula region. An evaluation against a reference standard data-set is given; it is shown that the algorithm's performance correlates closely with that of clinicians manually grading image quality.