It would be helpful to be able to identify respiratory effort-related arousal (RERA) without needing to measure oesophageal pressure. Thoracoabdominal movements yield an indirect flow measurement from which reduction of amplitude and alteration of the inspiratory flow curve can be detected. The aim of this study was to evaluate the accuracy of using the shape and amplitude of signals from thoracoabdominal bands (inductance plethysmography) to detect RERAs.Altogether, 94 subjects suspected of having sleep apnoea but with an apnoea/ hypopnoea index f10 in full polysomnography with oesophageal pressure were studied. A routine polysomnographical analysis was carried out. The polysomnographies were then reanalysed at random to determine which of the identified arousals were due to RERA, as determined either by oesophageal pressure or by induction bands without an oesophageal pressure signal. Altogether, 14,617 arousals were analysed.The sensitivity and specificity to find RERA (arousal by arousal) from bands versus oesophageal pressure were both 94%. The average difference of RERA index between oesophageal pressure and bands was -0.6. The correlation between RERA index determined by oesophageal pressure and bands was 0.98. To evaluate the intra and interobserver agreement, 1183 arousals were additionally analysed. The intraobserver agreement was 91% for RERAs by oesophageal pressure and 80% by bands. The interobserver agreement was 89% by oesophageal pressure and 85% by bands.The thoracoabdominal bands can be used to identify respiratory effort-related arousal (obstructive events not detected by thermistor) with similar efficacy to oesophageal pressure measurement. Since bands are routinely used in most polysomnographies, they can be used as the usual method to detect respiratory effort-related arousal, using a thermistor to evaluate apnoeas and hypopnoeas or as a complement to other methods, such as nasal cannula, which can detect apnoeas, hypopnoeas and respiratory effort-related arousal. Eur Respir J 2003; 22: 661-667.

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SUMMARYStatistical methods for carrying out asymptotic inferences (tests or confidence intervals) relative to one or two independent binomial proportions are very frequent. However inferences about a linear combination of K independent proportions L=β i p i (in which the first two are special cases) have had very little attention paid to them (focused exclusively on the classic Wald method). In this paper the authors approach the problem from the more efficient viewpoint of the score method, which can be solved using a free program which is available from the webpage quoted in the article. In addition the paper offers approximate formulas that are easy to calculate, gives a general proof of Agresti's heuristic method (consisting of adding a certain number of successes and failures to the original results before applying Wald's method) and, finally, it proves that the score method (which verifies the desirable properties of spatial and parametric convexity) is the best option in comparison with other methods.

Asymptotic inferences about a linear combination of K independent binomial proportions are very frequent in applied research. Nevertheless, until quite recently research had been focused almost exclusively on cases of K2 (particularly on cases of one proportion and the difference of two proportions). This article focuses on cases of K>2, which have recently begun to receive more attention due to their great practical interest.In order to make this inference, there are several procedures which have not been (which is a generalization of the Newcombe method). The article describes a new procedure (P0) based on the classic Peskun method, modifies the previous methods giving them continuity correction (methods S0c, W3c, N0c and P0c respectively) and, finally, a simulation is made to compare the eight aforementioned procedures (which are selected from a total of 32 possible methods). The conclusion reached is that S0c method is the best, although for very small samples (n i  10, i) the W3 method is better. The P0 method would be the optimal method if one needs a method which is almost never too liberal, but this entails using a method which is too conservative and which provides excessively wide confidence intervals. The W3 and P0 methods have the additional advantage of being very easy to apply.A free programme which allows the application of the S0 and S0c methods (which are the most complex) can be obtained at

There is a frequent need to measure the degree of agreement among R observers who independently classify n subjects within K nominal or ordinal categories. The most popular methods are usually kappa-type measurements. When R = 2, Cohen's kappa coefficient (weighted or not) is well known. When defined in the ordinal case while assuming quadratic weights, Cohen's kappa has the advantage of coinciding with the intraclass and concordance correlation coefficients. When R > 2, there are more discrepancies because the definition of the kappa coefficient depends on how the phrase 'an agreement has occurred' is interpreted. In this paper, Hubert's interpretation, that 'an agreement occurs if and only if all raters agree on the categorization of an object', is used, which leads to Hubert's (nominal) and Schuster and Smith's (ordinal) kappa coefficients. Formulae for the large-sample variances for the estimators of all these coefficients are given, allowing the latter to illustrate the different ways of carrying out inference and, with the use of simulation, to select the optimal procedure. In addition, it is shown that Schuster and Smith's kappa coefficient coincides with the intraclass and concordance correlation coefficients if the first coefficient is also defined assuming quadratic weights.