Practical sources of error in measuring pulmonary artery occlusion pressure: a study in participants of a special intensivist training program of The Scandinavian Society of Anaesthesiology and Intensive Care Medicine (SSAI)

BACKGROUND: Physiological data obtained with the pulmonary artery catheter (PAC) are susceptible to errors in measurement and interpretation. Little attention has been paid to the relevance of errors in hemodynamic measurements performed in the intensive care unit (ICU). The aim of this study was to assess the errors related to the technical aspects (zeroing and reference level) and actual measurement (curve interpretation) of the pulmonary artery occlusion pressure (PAOP). METHODS: Forty-seven participants in a special ICU training program and 22 ICU nurses were tested without pre-announcement. All participants had previously been exposed to the clinical use of the method. The first task was to set up a pressure measurement system for PAC (zeroing and reference level) and the second to measure the PAOP. RESULTS: The median difference from the reference mid-axillary zero level was - 3 cm (-8 to + 9 cm) for physicians and -1 cm (-5 to + 1 cm) for nurses. The median difference from the reference PAOP was 0 mmHg (-3 to 5 mmHg) for physicians and 1 mmHg (-1 to 15 mmHg) for nurses. When PAOP values were adjusted for the differences from the reference transducer level, the median differences from the reference PAOP values were 2 mmHg (-6 to 9 mmHg) for physicians and 2 mmHg (-6 to 16 mmHg) for nurses. CONCLUSIONS: Measurement of the PAOP is susceptible to substantial error as a result of practical mistakes. Comparison of results between ICUs or practitioners is therefore not possible.

Extrinsic causes of erosion. Oral hygiene products and acidic medicines

Acidic or EDTA-containing oral hygiene products and acidic medicines have the potential to soften dental hard tissues. The low pH of oral care products increases the chemical stability of some fluoride compounds, favors the incorporation of fluoride ions in the lattice of hydroxyapatite and the precipitation of calcium fluoride on the tooth surface. This layer has some protective effect against an erosive attack. However, when the pH is too low or when no fluoride is present these protecting effects are replaced by direct softening of the tooth surface. Xerostomia or oral dryness can occur as a consequence of medication such as tranquilizers, anti-histamines, anti-emetics and anti-parkinsonian medicaments or of salivary gland dysfunction e.g. due to radiotherapy of the oral cavity and the head and neck region. Above all, these patients should be aware of the potential demineralization effects of oral hygiene products with low pH and high titratable acids. Acetyl salicylic acid taken regularly in the form of multiple chewable tablets or in the form of headache powder as well chewing hydrochloric acids tablets for treatment of stomach disorders can cause erosion. There is most probably no direct association between asthmatic drugs and erosion on the population level. Consumers, patients and health professionals should be aware of the potential of tooth damage not only by oral hygiene products and salivary substitutes but also by chewable and effervescent tablets. Additionally, it can be assumed that patients suffering from xerostomia should be aware of the potential effects of oral hygiene products with low pH and high titratable acids.

Error models for microarray intensities

We derive the additive-multiplicative error model for microarray intensities, and describe two applications. For the detection of differentially expressed genes, we obtain a statistic whose variance is approximately independent of the mean intensity. For the post hoc calibration (normalization) of data with respect to experimental factors, we describe a method for parameter estimation.

Model Evaluation Based on the Distribution of Estimated Absolute Prediction Error

The construction of a reliable, practically useful prediction rule for future response is heavily dependent on the "adequacy" of the fitted regression model. In this article, we consider the absolute prediction error, the expected value of the absolute difference between the future and predicted responses, as the model evaluation criterion. This prediction error is easier to interpret than the average squared error and is equivalent to the mis-classification error for the binary outcome. We show that the distributions of the apparent error and its cross-validation counterparts are approximately normal even under a misspecified fitted model. When the prediction rule is "unsmooth", the variance of the above normal distribution can be estimated well via a perturbation-resampling method. We also show how to approximate the distribution of the difference of the estimated prediction errors from two competing models. With two real examples, we demonstrate that the resulting interval estimates for prediction errors provide much more information about model adequacy than the point estimates alone.

Inference on Survival Data with Covariate Measurement Error - An Imputation-based Approach

We propose a new method for fitting proportional hazards models with error-prone covariates. Regression coefficients are estimated by solving an estimating equation that is the average of the partial likelihood scores based on imputed true covariates. For the purpose of imputation, a linear spline model is assumed on the baseline hazard. We discuss consistency and asymptotic normality of the resulting estimators, and propose a stochastic approximation scheme to obtain the estimates. The algorithm is easy to implement, and reduces to the ordinary Cox partial likelihood approach when the measurement error has a degenerative distribution. Simulations indicate high efficiency and robustness. We consider the special case where error-prone replicates are available on the unobserved true covariates. As expected, increasing the number of replicate for the unobserved covariates increases efficiency and reduces bias. We illustrate the practical utility of the proposed method with an Eastern Cooperative Oncology Group clinical trial where a genetic marker, c-myc expression level, is subject to measurement error.