Quantitative grading of testing has research and clinical relevance. QASAT (quantitative scale for grading of cardiovascular reflex tests, transcranial Doppler, sudomotor testing, and small fiber densities from skin biopsies) is an objective instrument for grading dysautonomia, related small fiber neuropathy and cerebral blood flow. QASAT uses established autonomic tests (deep breathing, Valsalva maneuver, tilt test, sudomotor test) and skin biopsies for assessment of small fibers. Calculations of scores are complex. This paper presents a qpack-an open source software package that implements QASAT in a Python programming language. The qpack automatically generates reproducible scores of each test and reduces calculation errors. Datasets for verifying the correct qpack implementation are provided. The goal of qpack is to facilitate availability, reproducibility, and quality of autonomic studies and skin biopsies for assessment of small fibers. Qpack is easy to use with standard Python distributions, can be incorporated into routine clinical or research autonomic testing and it is freely available.
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http://dx.doi.org/10.1007/s10072-022-06007-w | DOI Listing |
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