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BACKGROUND: Following the onset of the COVID-19 pandemic, telerehabilitation (TR) has been expanding to address the challenges and risks of in-person delivery. It is likely that a level of TR delivery will continue after the pandemic because of its advantages, such as reducing geographical barriers to service. Many pandemic-related TR initiatives were put in place quickly. Therefore, we have little understanding of current TR delivery, barriers and facilitators, and how therapists anticipate integrating TR into current practice. Knowing this information will allow the incorporation of competencies specifically related to the use and provision of TR into professional profiles and entry-to-practice education, thereby promoting high-quality TR care. OBJECTIVE: This study aimed to obtain a descriptive overview of current TR practice among rehabilitation therapists in Canada and the Netherlands and identify perceived barriers to and facilitators of practice. METHODS: A web-based cross-sectional survey was conducted with occupational, physical, and respiratory therapists and dietitians in Canada (in French and English) and the Netherlands (in Dutch and English) between November 2021 and March 2022. Recruitment was conducted through advertisements on social media platforms and email invitations facilitated by regulatory and professional bodies. The survey included demographic and practice setting information; whether respondents delivered TR, and if so, components of delivery; confidence and satisfaction ratings with delivery; and barriers to and facilitators of use. TR satisfaction and uptake were measured using the Telehealth Usability Questionnaire and modified Technology Acceptance Model. Data were first summarized descriptively, and then, comparisons were conducted between professions. RESULTS: Overall, 723 survey responses were received, mostly from Canada (n=666, 92.1%) and occupational therapists (n=434, 60%). Only 28.1% (203/723) reported receiving specific training in TR, with 1.2% (9/723) indicating that it was part of their professional education. Approximately 19.5% (139/712) reported not using TR at all, whereas most participants (366/712, 51.4%) had been using this approach for 1 to 2 years. Services delivered were primarily teleconsultation and teletreatment with individuals. Respondents offering TR were moderately satisfied with their service delivery and found it to be effective; 90.1% (498/553) indicated that they were likely to continue offering TR after the pandemic. Technology access, confidence, and setup were rated the highest as facilitators, whereas technology issues and the clinical need for physical contact were the most common barriers. CONCLUSIONS: Professional practice and experience with TR were similar in both countries, suggesting the potential for common strategic approaches. The high prevalence of current practice and strong indicators of TR uptake suggest that therapists are likely to continue TR delivery after the pandemic; however, most therapists (461/712, 64.7%) felt ill prepared for practice, and the need to target TR competencies during professional and postprofessional education is critical. Future studies should explore best practice for preparatory and continuing education.
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Objective: To describe clinical manifestations of SARS-CoV-2 infection in children, adolescents, and young adults with established type 1 diabetes and explore the effects of COVID-19 on glycemic control and disease course. Method(s): Observational study conducted at three pediatric diabetes clinics in Israel between mid-March-2020 and mid- March-2021. Included were young people with established type 1 diabetes, <30years, who tested positive for SARS-CoV-2 (qRTPCR). Data was collected from medical files, diabetes devices, and COVID-19 questionnaire. Outcome measures were analyzed by presence/absence of clinical symptoms (symptomatic/asymptomatic) and by age group (pediatric, <19years/young adults, 19-30years). Result(s): Of 132 patients, mean age 16.9+/-5.3years, with COVID- 19 confirmed infection, 103 (78%) had related symptoms;the most common were headaches, fatigue, fever and loss of sense of smell. All had mild disease course, but four required hospitalization and two cases were directly related to COVID-19 infection (pleuropneumonia in a patient with immunodeficiency syndrome, one case of diabetic-ketoacidosis). Logistic regression analysis showed that age (OR=1.11, 95%CI, 1.01, 1.23;P=0.033), elevated glucose levels (OR=5.23, 95%CI, 1.12, 24.41;P=0.035) and comorbidities (OR=8.21, 95%CI, 1.00, 67.51;P=0.050) were positively associated with symptomatic infection. Persistent symptoms occurred in 16.5% of the cohort over a median of 6.7 months;age (OR=1.14, 95%CI, 1.01, 1.29;P=0.030) and elevated glucose levels (OR=3.42, 95%CI, 1.12, 10.40;P=0.031) were positively associated with persistent symptoms. Usually, no change was reported in glucose levels (64%) except for a temporary deterioration in glycemic control during the short infection period. Conclusion(s): Young people with established type 1 diabetes experience mild COVID-19 infection. Elevated glucose levels during COVID-19 infection and older age were associated with prolonged disease course.
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IntroductionCoronavirus disease 2019 (COVID-19) has a high burden on the healthcare system and demands information on the outcome early after admission to the emergency department (ED). Previously developed prediction models may assist in triaging patients when allocating healthcare resources. We aimed to assess the value of several prediction models when applied to COVID-19 patients in the ED. MethodsAll consecutive COVID-19 patients who visited the ED of a combined secondary/tertiary care center were included. Prediction models were selected based on their feasibility. The primary outcome was 30-day mortality, secondary outcomes were 14-day mortality, and a composite outcome of 30-day mortality and admission to the medium care unit (MCU) or the intensive care unit (ICU). The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC). ResultsA total of 403 ED patients were diagnosed with COVID-19. Within 30 days, 95 patients died (23.6%), 14-day mortality was 19.1%. Forty-eight patients (11.9%) were admitted to the MCU, 66 patients (16.4%) to the ICU and 152 patients (37.7%) met the composite endpoint. Eleven models were included: RISE UP score, 4C mortality score, CURB-65, MEWS, REMS, abbMEDS, SOFA, APACHE II, CALL score, ACP index and Host risk factor score. The RISE UP score and 4C mortality score showed a very good discriminatory performance for 30-day mortality (AUC 0.83 and 0.84 respectively, 95% CI 0.79-0.88 for both), for 14-day mortality (AUC 0.83, 95% CI: 0.79-0.88, for both) and for the composite outcome (AUC 0.79 and 0.77 respectively, 95% CI 0.75-0.84). The discriminatory performance of the RISE UP score and 4C mortality score was significantly higher compared to that of the other models. ConclusionThe RISE UP score and 4C mortality score have good discriminatory performance in predicting adverse outcome in ED patients with COVID-19. These prediction models can be used to recognize patients at high risk for short-term poor outcome and may assist in guiding clinical decision-making and allocating healthcare resources.
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COVID-19ABSTRACT
ObjectiveTo mitigate the burden of COVID-19 on the healthcare system, information on the prognosis of the disease is needed. The recently developed RISE UP score has very good discriminatory value with respect to short-term mortality in older patients in the emergency department (ED). It consists of six items: age, abnormal vital signs, albumin, blood urea nitrogen (BUN), lactate dehydrogenase (LDH), and bilirubin. We hypothesized that the RISE UP score could have discriminatory value with regard to 30-day mortality in ED patients with COVID-19. SettingTwo EDs of the Zuyderland Medical Centre (MC), secondary care hospital in the Netherlands. ParticipantsThe study sample consisted of 642 adult ED patients diagnosed with COVID-19 between March 3rd until May 25th 2020. Inclusion criteria were: 1) admission to the hospital with symptoms suggestive of COVID-19, and 2) positive result of the polymerase chain reaction (PCR), or (very) high suspicion of COVID-19 according to the chest computed tomography (CT) scan. OutcomePrimary outcome was 30-day mortality, secondary outcome was a composite of 30-day mortality and admission to intensive care unit (ICU). ResultsWithin 30 days after presentation, 167 patients (26.0%) died and 102 patients (15.9%) were admitted to ICU. The RISE UP score showed good discriminatory value with respect to 30-day mortality (AUC 0.77, 95% CI 0.73-0.81), and to the composite outcome (AUC 0.72, 95% CI 0.68-0.76). Patients with RISE UP scores below 10% (121 patients) had favourable outcome (0% mortality and 5% ICU admissions). Patients with a RISE UP score above 30% (221 patients) were at high risk of adverse outcome (46.6% mortality and 19% ICU admissions). ConclusionThe RISE UP score is an accurate prognostic model for adverse outcome in ED patients with COVID-19. It can be used to identify patients at risk of short-term adverse outcome, and may help guiding decision-making and allocating healthcare resources.