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Background: New data collection in established longitudinal population studies provides an opportunity for studying the risk factors and sequelae of the novel coronavirus disease 2019 (COVID-19), plus the indirect impacts of the COVID-19 pandemic on wellbeing. The Extended Cohort for E-health, Environment and DNA (EXCEED) cohort is a population-based cohort (N>11,000), recruited from 2013 in Leicester, Leicestershire and Rutland. EXCEED includes consent for electronic healthcare record (EHR) linkage, spirometry, genomic data, and questionnaire data.
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Telemedicine, also known as telehealth, has been around for decades, but despite its many perceived benefits, its adoption has remained low. The objective our study was to know how consumers felt about telemedicine service during COVID -19 and to find out factors influencing consumers' perceptions of telemedicine services, a survey was done using a questionnaire. Social media and e-mail were used to inform people about the research due to onset of pandemic. An e online survey was done from the period of April 1st to June 30th, 2021 in India's capital Delhi and adjoining areas, 122 service users were sampled for the survey. A 10-item scale was used to assess telemedicine satisfaction, revealing that all participants were satisfied with their telemedicine experience(s) in general. The elements of perception were studied using factor analysis. The results of the analysis revealed that an individual's intention to utilize a system or technology may be influenced not only by factors affecting the user's direct encounter with the system or technology but also by factors affecting the service provider. Patients place a high value on these qualities, thus service providers can design their interface, appointment procedure, and consultation process around them.
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P130 Figure 1Features of COVID-19 on the CT were very common in hospitalised patients and were related to all-cause mortality one year following hospitalisation[Figure omitted. See PDF]ConclusionEvidence of COVID-19 pneumonia on CTT is more common and severe in patients from ethnic minority groups and is independently associated with worse prognosis following hospitalisation.
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Background: Clinical outcomes for people living with HIV (PLWH) hospitalized with COVID-19 infections have shown mixed outcomes. We conducted a multicentre, UK retrospective matched cohorts' analysis. Methods: Index cases were HIV+ COVID-19 PCR+ patients hospitalized between dates 1st February - 31st May 2020. HIV-negative patients were matched to PLWH up to a 3:1 ratio across 6 sites in England, by hospital site, test date +/- 7 days, age +/- 5 years, gender, index of multiple deprivation decile (IMDD) +/- 1. The primary outcome was patients achieving ≥2-point improvement on a 7-point ordinal scale or discharge from hospital by day 28, whichever was earlier. Follow up was right-censored at day 28 for patients still in hospital. Baseline characteristics and outcomes were analysed by Coxproportional hazards regression stratified by matching clusters using multiple imputation for missing data. The model adjusted for ethnicity, clinical frailty score, body mass index, baseline hypoxia, duration of symptoms, hypertension, diabetes, malignancy, cardiac, lung and renal disease. Results: 68 PLWH and 181 HIV-negative patients were included. PLWH had an HR of 0.57 (95%CI 0.39, 0.85;p=0.005) of achieving 2-point improvement or discharge compared to HIV-negative patients. The effect size of HIV-status was attenuated (aHR 0.70;0.43, 1.17;P=0.18) after adjustment in the multivariable model (Table 1), with baseline frailty (aHR=0.79;95%CI 0.65, 0.95;p=0.011 ), malignancy (aHR=0.37;95%CI 0.17, 0.82;p=0.014) having a greater impact on the primary outcome. Proportion of deaths (19.1% vs 19.3%, p=0.266) and patients requiring ventilation (23.5% vs 17.1%, p=0.25) were similar between PLWH and HIV-negative patients. Sensitivity analyses adjusting for age and excluding missing data, remained consistent with main findings. PLWH were frailer (median clinical frailty score 3 vs 2, p=0.0069), and had higher proportion of malignancies (14.7% vs 9.9%, p=0.29) although not statistically significant. Number of non-HIV co-morbidities (2 vs 2, p=0.16) and median BMI (27.7 vs 29.4, p=0.19) were similar. The median CD4 count of PLWH was 352cells/ μL (IQR 235, 619), and 63/68 (92.3%) were taking antiretroviral therapy. Conclusion: Although PLWH were less likely to achieve improvement or discharge, after adjustment the effect of HIV-status was attenuated. Increased baseline frailty and active malignancies remain associated with poorer COVID-19 outcomes.
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BACKGROUND: Health and key workers have elevated odds of developing severe COVID-19; it is not known, however, if this is exacerbated in those with irregular work patterns. We aimed to investigate the odds of developing severe COVID-19 in health and shift workers. METHODS: We included UK Biobank participants in employment or self-employed at baseline (2006-2010) and with linked COVID-19 data to 31st August 2020. Participants were grouped as neither a health worker nor shift worker (reference category) at baseline, health worker only, shift worker only, or both, and associations with severe COVID-19 investigated in logistic regressions. RESULTS: Of 235,685 participants (81·5% neither health nor shift worker, 1·4% health worker only, 16·9% shift worker only, and 0·3% both), there were 580 (0·25%) cases of severe COVID-19. The odds of severe COVID-19 was higher in health workers (adjusted odds ratio: 2·32 [95% CI: 1·33, 4·05]; shift workers (2·06 [1·72, 2·47]); and in health workers who worked shifts (7·56 [3·86, 14·79]). Being both a health worker and a shift worker had a possible greater impact on the odds of severe COVID-19 in South Asian and Black and African Caribbean ethnicities compared to White individuals. CONCLUSIONS: Both health and shift work (measured at baseline, 2006-2010) were independently associated with over twice the odds of severe COVID-19 in 2020; the odds were over seven times higher in health workers who work shifts. Vaccinations, therapeutic and preventative options should take into consideration not only health and key worker status but also shift worker status.