Effects of Diagnostic Work-Up on Medical Decision-Making for Canine Urinary Tract Infection: An Observational Study in Danish Small Animal Practices

BACKGROUND

Clinical signs of urinary tract disease in dogs often lead to prescription of antibiotics. Appropriate diagnostic work-up could optimize treatment and reduce the risk of inappropriate use of antibiotics.

HYPOTHESIS/OBJECTIVES

To describe and evaluate the impact of diagnostic work-up on decision to treat (DTT) and choice of antibiotic treatment (COT) for dogs presenting with clinical signs of urinary tract disease.

ANIMALS

One hundred and fifty-one dogs presenting to 52 Danish veterinary practices.

METHODS

Prospective, observational study. Clinical signs, diagnostic work-up, and prescriptions were recorded. Urine samples were submitted to a reference laboratory for quantitative bacterial culture (QBC) and susceptibility testing. The laboratory results were used as reference for assessing the appropriateness of DTT and COT.

RESULTS

In the majority of dogs, veterinarians performed dipstick (99%), microscopic examination of urine (80%) and bacterial culture (56%). Fifty-one percent of dogs had urinary tract infection (UTI) based on reference QBC. Appropriate DTT was made for 62% of the dogs, while 36% were over-prescribed and 2% under-prescribed. Inappropriate use of second-line agents was found in 57% of the UTI cases. Performing microscopy-but not culture-significantly impacted DTT (P = 0.039) while no difference was seen in COT (P = 0.67). The accuracy of in-house microscopy and culture were 64.5 and 77%, respectively.

CONCLUSIONS AND CLINICAL IMPORTANCE

Over-prescription of antibiotics was common among dogs with suspected UTI, regardless of the diagnostic work-up performed. Test inaccuracy under practice conditions and incoherence between diagnostic test results and decision-making both explained inappropriate and unnecessary use of antibiotics.

Digital elevation model uncertainty and hazard analysis using a geophysical flow model

This paper describes a new methodology to quantify the variation in the output of a computational fluid dynamics model for block and ash flows, when the digital elevation model (DEM) of the terrain and other inputs are given as a range of possible values with a prescribed uncertainty. Integrating these variations in the possible flows as a function of input uncertainties provides well-defined hazard probabilities at specific locations, i.e. a hazard map. Earlier work provided a methodology for assessing hazards based on variations in flow initiation and friction parameters. This paper extends this approach to include the effect of terrain error and uncertainty. The results are based on potential flows at Mammoth Mountain, CA, and Galeras Volcano, Colombia. The analysis establishes the soundness of the approach and the effect of including the uncertainty in DEMs in the construction of probabilistic hazard maps.