A mathematical model for breath gas analysis of volatile organic compounds with special emphasis on acetone

Recommended standardized procedures for determining exhaled lower respiratory nitric oxide and nasal nitric oxide have been developed by task forces of the European Respiratory Society and the American Thoracic Society. These recommendations have paved the way for the measurement of nitric oxide to become a diagnostic tool for specific clinical applications. It would be desirable to develop similar guidelines for the sampling of other trace gases in exhaled breath, especially volatile organic compounds (VOCs) which reflect ongoing metabolism. The concentrations of water-soluble, blood-borne substances in exhaled breath are influenced by: (i) breathing patterns affecting gas exchange in the conducting airways; (ii) the concentrations in the tracheo-bronchial lining fluid; (iii) the alveolar and systemic concentrations of the compound. The classical Farhi equation takes only the alveolar concentrations into account. Real-time measurements of acetone in end-tidal breath under an ergometer challenge show characteristics which cannot be explained within the Farhi setting. Here we develop a compartment model that reliably captures these profiles and is capable of relating breath to the systemic concentrations of acetone. By comparison with experimental data it is inferred that the major part of variability in breath acetone concentrations (e.g., in response to moderate exercise or altered breathing patterns) can be attributed to airway gas exchange, with minimal changes of the underlying blood and tissue concentrations. Moreover, it is deduced that measured end-tidal breath concentrations of acetone determined during resting conditions and free breathing will be rather poor indicators for endogenous levels. Particularly, the current formulation includes the classical Farhi and the Scheid series inhomogeneity model as special limiting cases.Comment: 38 page

Use of information on disease diagnoses from databases for animal health economic, welfare and food safety purposes: strengths and limitations of recordings

Many animal health, welfare and food safety databases include data on clinical and test-based disease diagnoses. However, the circumstances and constraints for establishing the diagnoses vary considerably among databases. Therefore results based on different databases are difficult to compare and compilation of data in order to perform meta-analysis is almost impossible. Nevertheless, diagnostic information collected either routinely or in research projects is valuable in cross comparisons between databases, but there is a need for improved transparency and documentation of the data and the performance characteristics of tests used to establish diagnoses. The objective of this paper is to outline the circumstances and constraints for recording of disease diagnoses in different types of databases, and to discuss these in the context of disease diagnoses when using them for additional purposes, including research. Finally some limitations and recommendations for use of data and for recording of diagnostic information in the future are given. It is concluded that many research questions have such a specific objective that investigators need to collect their own data. However, there are also examples, where a minimal amount of extra information or continued validation could make sufficient improvement of secondary data to be used for other purposes. Regardless, researchers should always carefully evaluate the opportunities and constraints when they decide to use secondary data. If the data in the existing databases are not sufficiently valid, researchers may have to collect their own data, but improved recording of diagnostic data may improve the usefulness of secondary diagnostic data in the future

Validation of computerized diagnostic information in a clinical database from a national equine clinic network

BACKGROUND: Computerized diagnostic information offers potential for epidemiological research; however data accuracy must be addressed. The principal aim of this study was to evaluate the completeness and correctness of diagnostic information in a computerized equine clinical database compared to corresponding hand written veterinary clinical records, used as gold standard, and to assess factors related to correctness. Further, the aim was to investigate completeness (epidemiologic sensitivity), correctness (positive predictive value), specificity and prevalence for diagnoses for four body systems and correctness for affected limb information for four joint diseases. METHODS: A random sample of 450 visits over the year 2002 (nvisits=49,591) was taken from 18 nation wide clinics headed under one company. Computerized information for the visits selected and copies of the corresponding veterinary clinical records were retrieved. Completeness and correctness were determined using semi-subjective criteria. Logistic regression was used to examine factors associated with correctness for diagnosis. RESULTS: Three hundred and ninety six visits had veterinary clinical notes that were retrievable. The overall completeness and correctness were 91% and 92%, respectively; both values considered high. Descriptive analyses showed significantly higher degree of correctness for first visits compared to follow up visits and for cases with a diagnostic code recorded in the veterinary records compared to those with no code noted. The correctness was similar regardless of usage category (leisure/sport horse, racing trotter and racing thoroughbred) or gender.For the four body systems selected (joints, skin and hooves, respiratory, skeletal) the completeness varied between 71% (respiration) and 91% (joints) and the correctness ranged from 87% (skin and hooves) to 96% (respiration), whereas the specificity was >95% for all systems. Logistic regression showed that correctness was associated with type of visit, whether an explicit diagnostic code was present in the veterinary clinical record, and body system. Correctness for information on affected limb was 95% and varied with joint. CONCLUSION: Based on the overall high level of correctness and completeness the database was considered useful for research purposes. For the body systems investigated the highest level of completeness and correctness was seen for joints and respiration, respectively