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Background. One of Singapore's national strategies for the COVID-19 pandemic was containment. Efforts included a fourteen-day quarantine of close contacts, were subjected to an entry and exit SARS-CoV-2 PCR test, the latter being done between 11-14 days post exposure. Additionally, symptomatic contacts were tested for SARS-CoV-2. We aim to determine the trend in COVID-19 incubation periods during three distinct pandemic waves corresponding to different SARS-CoV-2 variants. Incubation Period Incubation period of the prevalent SARS-CoV-2 variant in circulation Methods. This is an ecological study and information collected from the SingHealth COVID-19 Registry, a database of all inpatients admitted to any of the SingHealth hospitals. For patients under quarantine, the start date of the quarantine period was assumed to be the last date of exposure to the index case. Incubation period was determined by the duration between date of exposure and date of the first positive SARS-CoV-2 PCR test. The prevalent strain in circulation was identified from the Singapore database in the GISAID collection. Only variants of concern, as categorized by WHO, Alpha (23rd Jan 2020 - 1st Mar 2021), Delta (5th May 2021 - 31st Oct 2021) and Omicron (1st Jan 2022 - Present) were considered. For the Omicron variant, quarantine was discontinued, hence the last date of arrival from international travel was assumed to be the date of exposure. Results. From January 2020 to March 2022, there were 19,905 patients in the COVID-19 registry, of whom 11,235 were under quarantine and 8,612 had preceding international travel. Of the 11,235 patients under quarantine, 8,189 patients were infected when SARS-CoV-2 Alpha variant and 3,046 patients were infected when SARS-CoV-2 Delta variant were in circulation. Of the 8,612 patients with preceding travel, 6,503 patients were infected when SARS-CoV-2 Omicron variant was in circulation. The median incubation period for the Alpha variant was 11 days (IQR: 7-14 days) versus 3 days (IQR: 2-4 days) for the Delta variant versus 3 days (IQR: 0-5 days) for the Omicron variant. Pairwise comparisons between the variants were (p-value = < .001) Conclusion. The significant differences between incubation periods of the SARS-CoV-2 variants in circulation poses a challenge to containment efforts and has emphasize the importance of dynamic national strategies.
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Background and Aims: Mechanical thrombectomy can only be performed in comprehensive stroke centres (CSC) which provide onsite interventional radiology and neurosurgical services. The benefits of direct admission to a CSC versus secondary transfer following initial admission to a stroke unit without MT service are heavily contested. Nottingham University Hospitals provides the East Midlands' Mechanical Thrombectomy (MT) service in the United Kingdom. With an aim to reduce the number of transfers for patients eligible for MT within the region, we relocated our stroke services from Nottingham City Hospital (NCH) to Queens' Medical Centre (QMC), a major trauma centre with on-site interventional services in July 2020. Method(s): We compared timings of stroke assessment and outcomes for consecutive patients transferred from NCH to those who were directly admitted to QMC after the change in our service model. Result(s): 101 patients admitted from Nottingham underwent MT between January 2019 and January 2022. For patients transferred (n=48) and patients directly admitted (n=53) respectively: average time from CT scan to groin puncture were 163 and 151 minutes;reperfusion rates (TICI>2a) were 100% and 96%. The median modified Rankin Score on discharge were 3.5 and 3.6 respectively. Conclusion(s): Although shorter imaging-to-groin puncture time was demonstrated post-relocation, comparable functional outcomes were seen between patients transferred and directly admitted to our CSC. This could be attributed to an increased time window of MT eligibility from 6 to 24 hours post symptom onset after our relocation. Further studies are required to establish its effects and explore the impacts of the COVID-19 pandemic on our stroke service.
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BACKGROUND: Previous studies suggest that increased learning satisfaction may encourage learning engagement in an online learning environment. OBJECTIVES: To evaluate the level of learning engagement and its relationship with students' perceived learning satisfaction in an online clinical nursing elective course. DESIGN: A prospective interventional study. SETTINGS: A nursing course was converted to an online format because of the coronavirus disease COVID pandemic. PARTICIPANTS: Part-time post-registration nursing undergraduates enrolled in an elective online clinical course. METHODS: Related teaching and learning strategies were deployed in the course using the Community of Inquiry framework. All students who completed the course were invited to complete an online survey that included a validated Online Student Engagement questionnaire (OSE). Pearson's correlations were used to determine the association between perceived learning satisfaction and learning engagement. A logistic regression model was used to explore the associations of gender, age, working experience and perceived learning satisfaction with higher learning engagement. RESULTS: The questionnaires were completed by 56 of 68 students (82%). The Pearson's correlation coefficient between the mean perceived learning satisfaction and OSE scores was 0.75 (p < .001). Twenty-five students (45%) were identified as highly engaged, using a cut-off of ≥3.5 for the mean OSE score. The mean perceived learning satisfaction (SD) score differed significantly between highly engaged and not highly engaged students [4.02 (0.49) vs. 3.27 (0.62), p < .001]. The logistic regression model showed that a greater perceived learning satisfaction [adjusted odds ratio (OR): 17.2, 95% C.I.: 3.46-86.0, p = .001] was associated with an increased likelihood of higher learning engagement, and >1 year of working experience (adjusted OR: 0.11, 95% C.I.: 0.01-0.89, p = .0039) was associated with a decreased likelihood of higher learning engagement. CONCLUSIONS: The study findings suggest that perceived learning satisfaction predicts learning engagement among nursing students in this online learning course.