Continuity of care for patients with de novo metastatic cancer during the COVID-19 pandemic:A population-based observational study

During the COVID-19 pandemic recommendations were made to adapt cancer care. This population-based study aimed to investigate possible differences between the treatment of patients with metastatic cancer before and during the pandemic by comparing the initial treatments in five COVID-19 periods (weeks 1–12 2020: pre-COVID-19, weeks 12–20 2020: 1st peak, weeks 21–41 2020: recovery, weeks 42–53 2020: 2nd peak, weeks 1–20 2021: prolonged 2nd peak) with reference data from 2017 to 2019. The proportion of patients receiving different treatment modalities (chemotherapy, hormonal therapy, immunotherapy or targeted therapy, radiotherapy primary tumor, resection primary tumor, resection metastases) within 6 weeks of diagnosis and the time between diagnosis and first treatment were compared by period. In total, 74,208 patients were included. Overall, patients were more likely to receive treatments in the COVID-19 periods than in previous years. This mainly holds for hormone therapy, immunotherapy or targeted therapy and resection of metastases. Lower odds were observed for resection of the primary tumor during the recovery period (OR 0.87; 95% CI 0.77–0.99) and for radiotherapy on the primary tumor during the prolonged 2nd peak (OR 0.84; 95% CI 0.72–0.98). The time from diagnosis to the start of first treatment was shorter, mainly during the 1st peak (average 5 days, p &lt;.001). These findings show that during the first 1.5 years of the COVID-19 pandemic, there were only minor changes in the initial treatment of metastatic cancer. Remarkably, time from diagnosis to first treatment was shorter. Overall, the results suggest continuity of care for patients with metastatic cancer during the pandemic.</p

Assessment of Walking Ability in Patients with Intermittent Claudication Using a Smartphone Accelerometer

Objectives: It is challenging to accurately monitor the progress of intermittent claudication patients during or after treatment. Furthermore, diagnostic tools for intermittent claudication are not always adequate to determine whether other diseases are the primary cause of any walking complaints. This makes it difficult to determine the optimal treatment for the patient and impairs proper follow-up. The objective was to investigate the feasibility of measuring disease specific changes in the gait pattern of intermittent claudication patients by using a smartphone accelerometer. Methods: This study is a clinical Proof-of-concept study. Included were 12 subjects. Seven of the subjects were healthy controls, the other five intermittent claudication patients. Raw accelerometer data was collected during a standardized walking test with an Iphone. Processed data was analyzed using the GaitPy package in Python, resulting in 20 different gait parameters per gait cycle. The data were divided, resulting in three groups: The control group, the patient group without symptoms and the patient group with active symptoms. Mann-Whitney U tests and Wilcoxon ranks test were used to examine the outcomes. Results: Five of the 20 parameters are significantly different between patients before symptoms and patients with active symptoms. All parameters except cadence and stride duration differ between our control group and the patients while experiencing symptoms. Nine of 20 parameters where significantly different between the control group and the patient group without symptoms. Conclusions: This study demonstrated the potential clinical applicability of measuring changes in intermittent claudication gait characteristics with a smartphone