Determination of total fat in foods and feeds by the caviezel method, based on a gas chromatographic technique.

This peer-verified method specifies a fast, easy, and reliable quantitative method to determine total fat in foods and feeds in compliance with the new definition of fat from the U.S. Food and Drug Administration. The method takes into consideration all fatty acids, from C4 to C24, and when fat is present at 0.3-100%. The validation study included 9 matrixes, with fat levels ranging from 1 to 79%. Sample and internal standard (IS; tridecanoic acid) are added to solvent (n-butyl alcohol). Fat is extracted and simultaneously saponified by potassium hydroxide. The fatty acid potassium salts are converted to fatty acids by adding an acidic aqueous salt solution, which produces a 2-phase system. The upper phase, containing the fatty acids and IS, is injected into the fat determination system. After gas chromatographic separation, the fat content is calculated from IS and fatty acid peak areas. The fat content is automatically converted to triglyceride content with a pre-determined factor. Ten replicates of 9 different food samples, which cover the whole range of different contents in fat, proteins, and carbohydrates, were analyzed by the submitting and the peer laboratories. Repeatability relative standard deviation (RSDr) values ranged from 0.47 to 4.62%. Reproducibility relative standard deviation (RSDR) values ranged from 0.85 to 9.52%. These estimates include between-run variability. The method shows good accuracy. Values for standard reference materials (SRMs) are in agreement with certified values. Regression analysis of the correlation between observed fat and certified value over all matrixes and fat levels indicated good precision and absence of method bias (5 SRMs; 1-30% fat; correlation coefficient, R2 = 99.98%).

[Computer alert and quality of care: application to the surveillance of hospital infections]. / Alertes informatiques et qualité des soins: application à la surveillance des infections hospitalières.

The Centre Informatique of Geneva University Hospital is developing, in the environment of its hospital information system, DIOGENE, a computerized alert system for surveillance of hospital infections. This hospital information system is based on an open distributed architecture and a relational database system, and covers many medical applications. This environment allows the development of alerts useful for detecting patients at risk. The alerts offer to clinicians a mean to control their efficacy in patient care. They are a new application of telematics for surveillance in clinical epidemiology, and are a tool for quality assurance. Two examples of alerts established for hospital infection control activities are presented. The first alert systematically detects all cases of patients colonized by or infected with methicillin-resistant Staphylococcus aureus (MRSA). The second alert helps to organize prospective surveillance of bloodstream infections in order to identify some risk factors for infection and propose preventive measures.