The use of knowledge-based systems to improve medical knowledge about urine analysis.

Urine protein diagnostics has developed into a routine method for screening and monitoring kidney diseases. It is based on the quantitative measurement of total protein, albumin, alpha(1)-microglobulin, immunoglobulin G and alpha(2)-macroglobulin (all related to urine creatinine), as well as a dipstick screening. The excretion pattern of the marker proteins allows differentiation of haematuria, leukocyturia and proteinuria and to assign them to prerenal, renal and postrenal causes. In order to provide the clinical partner not only with pure analytical results, but to support clinical decision making by an interpretative report, a urine protein expert system (UPES) has been developed. Based on a database containing more than 500 excretion patterns of patients with known diagnoses, a knowledge base was extracted. In its modules plausibility control, glomerular filtration rate, hematuria, leukocyturia and proteinuria, IF-THEN-rules interpret the given patterns and select matching text elements. The knowledge base has been integrated in the modern expert system shell WILAS, and the resulting interpretation system has been thoroughly verified and validated. An internal acceptance study revealed that urine protein differentiation is widely accepted as a diagnostic option and that its interpretation, provided with the help of UPES, is appreciated as a service. In an external study, the usability of UPES in routine and its knowledge representation was evaluated in 11 centres consisting of laboratories and nephrological partners. Over seven months, more than 500 cases were interpreted using UPES and documented by questionnaires. The discussion of the results at a user conference revealed that the problem of analytical standardisation as well as the common definition of diagnostic terms by laboratory staff and clinicians play a crucial role for the use of knowledge-based systems in laboratory medicine. Whereas the user interface of UPES was judged very heterogeneously, the correctness of the proposed interpretations was unanimously rated as "good". As a result of the evaluation, the user interface has been modernised. The knowledge base has been extended to address paediatric issues as well, and to take clinical information and previous findings into consideration.

From a urinalysis strategy to an evaluated urine protein expert system.

Urine single protein analysis has developed into a routine method for the screening and monitoring of kidney diseases. In order to support clinical decision making by an interpretative report, a urine protein expert system (UPES) has been developed. Based on a database containing more than 500 excretion patterns, a modular knowledge base was extracted in production rules and implemented in a modern expert system shell. The resulting interpretation system has been thoroughly verified and validated. After the need of interpretation of the complex findings had been documented in a survey, its usability in routine and its knowledge representation was evaluated in 11 hospitals. A user conference confirmed a high quality level of the reports proposed by UPES. It revealed that the problem of automatic data transfer as well as the common definition of diagnostic terms by laboratorians and clinicians play a crucial role for the use of knowledge-based systems in laboratory medicine.

Evaluation of pediatric nephropathies by a computerized Urine Protein Expert System (UPES).

A computerized Urine Protein Expert System (UPES) measuring creatinine, total protein, albumin, IgG, alpha(1)-microglobulin, alpha(2)-macroglobulin, and N-acetyl-beta-D-glucosaminidase, together with urine dipstick testing for granulocyte esterase and hemoglobin pseudoperoxidase, and measurement of serum creatinine had been found to be useful in adults for differentiating between renal disorders. The objective of this study was to investigate UPES for identifying the different types of proteinuria and their underlying prerenal, glomerular, tubular, and postrenal causes in 146 children characterized by routine and invasive nephrological investigations. UPES proved to be a useful tool in pediatric renal patients after refinements were implemented in the program. Comparing UPES with the pediatric nephrologist's interpretation of all available clinical and laboratory data, UPES diagnosed glomerulopathies in 46 (75%) of 61 patients. In a further 23% it suggested glomerular involvement by indicating either a disturbed glomerular permeability or increased excretion of albumin. Tubular proteinuria was correctly described by UPES in 23 (100%) patients with different tubulopathies. UPES revealed normal kidney function in all healthy children and all children with remission of renal disorders. Therefore, UPES can be regarded as a useful tool in the automated differentiation of renal diseases in children.

Physiopathology of proteinuria and laboratory diagnostic strategy based on single protein analysis.

A quantification of proteins of different molecular size has been shown to be useful in characterizing the mechanism and medical causes of proteinuria. By analyzing urine albumin, alpha1-microglobulin, immunoglobulin G and alpha2-macroglobulin together with total protein, prerenal, glomerular, tubular and postrenal causes of proteinuria can be detected and differentiated by their specific urine protein patterns. Using automated turbidimetric procedures, prerenal proteinurias are characterized by an albumin/total protein ratio below 0.4. Tubulo-interstitial diseases which are negative in the protein test strip procedure are detected and clearly differentiated from other causes of proteinuria by their high alpha1-microglobulin/albumin ratios. In post-renal proteinuria, alpha2-macroglobulin proved to be a useful marker, when albumin excretion exceeds 100 mg/l urine. This protein exhibits plasma-like ratios to albumin in postrenal causes, whereas it is much lower in renal proteinurias. The new strategy, which has been evaluated in more than 500 clinically and partly histologically proven cases of renal diseases, more sensitively detects glomerular and tubulo-interstitial diseases when applied in urine screening and allows us to distinguish all clinically important causes from analysis of a morning spot urine sample.

Development and evaluation of a urine protein expert system.

Based on the quantitative determination of creatinine, total protein, albumin, alpha 1-microglobulin, IgG, alpha 2-macroglobulin, and N-acetyl-beta, D-glucosaminidase in urine in combination with a test strip screening, the findings of hematuria, leukocyturia, and proteinuria can be assigned to prerenal, renal, or postrenal causes. Using this graded diagnostic strategy as a knowledge base, we developed a computerbased expert system for urine protein differentiation ("UPES") as a decision-supporting tool. The knowledge base was implemented as a combination of "if/then" rules and two-step bivariate distance classification of marker proteins. The knowledge for this form of pattern recognition was derived from the results for a set of 267 patients with clinically and histologically documented nephropathies. To determine the diagnostic value of UPES, we tested another set of data: results for 129 urine analyses from 94 patients. Using these data, the system reached 98% concordance with the clinical diagnoses for the patients and was superior to the diagnostic interpretations of four human experts. UPES has been successfully integrated into the laboratory routine process, including automated data import.