The Coronavirus Disease 2019 pandemic initially presented in the United States in the greater Seattle area, and has rapidly progressed across the nation in the past 2 months, with the United States having the highest number of cases in the world. Radiology departments play a critical role in policy and guideline development both for the department and for the institutions, specifically in planning diagnostic screening, triage, and management of patients. In addition, radiology workflows, volumes and access must be optimized in preparation for the expected COVID-19 patient surges. This article discusses the processes that have been implemented at the University of Washington in managing the COVID-19 pandemic as well in preparing for patient surges, which may provide important guidance for other radiology departments who are in the early stages of preparation and management.
Essentials Radiology policy goals are to reduce COVID-19-related morbidity and mortality through early diagnosis, appropriate treatment and prevention of disease dissemination. Imaging currently is not routinely used to screen for COVID-19 unless access to RT-PCR results for COVID-19 is limited. Postponing elective imaging and procedures will preserve resources and hospital beds, while also limiting patient population exposures. Determination of time-sensitivity of procedures and imaging tests is by consensus with input from radiologists, patients, and/or ordering clinicians. Radiology departments must prepare for patient surges through streamlined approaches to imaging that will limit exposures to healthcare workers and patients.
The coronavirus disease 2019 (COVID-19) pandemic initially manifested in the United States in the greater Seattle area and has rapidly progressed across the nation in the past 2 months, with the United States having the highest number of cases in the world. Radiology departments play a critical role in policy and guideline development both for the department and for the institutions, specifically in planning diagnostic screening, triage, and management of patients. In addition, radiology workflows, volumes, and access must be optimized in preparation for the expected surges in the number of patients with COVID-19. In this article, the authors discuss the processes that have been implemented at the University of Washington in managing the COVID-19 pandemic as well in preparing for patient surges, which may provide important guidance for other radiology departments who are in the early stages of preparation and management.
Background
While animal study and cadaveric study have demonstrated an association between knee joint loading rate and joint degeneration, the relationship between knee joint loading rate during walking and osteoarthritis has not yet been sufficiently studied in humans.
Methods
Twenty-eight participants (14 transfemoral amputees and 14 age and body mass matched controls) underwent knee MRI with subsequent assessment using the semiquantitative Whole-Organ Magnetic Resonance Image Score. Each subject also underwent gait analysis in order to determine knee adduction moment loading rate, peak, and impulse and an exploratory measure, knee adduction moment rate*magnitude.
Findings
Significant correlations were found between medial tibiofemoral joint degeneration and knee adduction moment peak (slope = 0.42 [SE 0.20]; P=.037), loading rate (slope = 12.3 [SE 3.2]; P=.0004), and rate*magnitude (slope = 437 [SE 100]; P<.0001). These relationships continued to be significant after adjusting for body mass or subject type. The relationship between medial knee semiquantitative MRI score and knee adduction moment loading rate and rate*magnitude continued to be significant even after adjusting for peak moment (P<.0001), however, the relationship between medial knee semiquantitative MRI score and peak moment was no longer significant after adjusting for either loading rate or rate*magnitude (P>.2 in both cases).
Interpretation
This study suggests an independent relationship between knee adduction moment loading rate and medial tibiofemoral joint degeneration. Our results support the hypothesis that rate of loading, represented by the knee adduction moment loading rate, is strongly associated with medial tibiofemoral joint degeneration independent of knee adduction moment peak and impulse.
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