Crit Care Resusc
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Background: Consent rates for organ donation conversations (ODCs) vary. We hypothesised that a simple grading system could identify challenging ODCs. We further hypothesised that challenging ODCs would have higher consent rates when conducted by ODC specialists. ⋯ Conclusion: The likelihood of consent can be predicted using readily available variables. This allows prospective identification of Grade IV ODCs, which carry low but potentially modifiable likelihood of consent. Involving donation specialists was associated with more consents for organ donation when applied retrospectively to Australian audit data.
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[This corrects the article DOI: 10.1016/S1441-2772(23)00391-5.].
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Background: Deceased organ donation work-up typically takes 24 hours or more. Clinicians may thus discount the possibility of donation when the potential donor is physiologically unstable or family requirements do not allow this length of time. This may lead to loss of transplantable organs. ⋯ Of the two lung recipients, one died at day 622 of chronic rejection. Conclusions: Expedited pathway donation is feasible with acceptable donation outcomes. Clinicians should consider donation even when physiological instability or family requirements preclude standard organ donation work-up times.
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Objective: During the coronavirus disease 2019 (COVID-19) pandemic, baseline demographics and comorbidities of patients with COVID-19 have been presented, but there are limited data on outcomes of severely ill patients. We aimed to examine the association between patient characteristics and 30-day mortality among patients with COVID-19 treated in the intensive care unit (ICU). Design: Population-based cohort study. ⋯ In the multivariable Cox regression model, age (hazard ratio [HR] 1.06; 95% CI, 1.04-1.07 per year), the presence of one or more comorbidities (HR, 1.80; 95% CI, 1.20-2.68), chronic obstructive pulmonary disease or asthma (HR, 1.68; 95% CI, 1.12-2.50), hypertension (HR, 1.41; 95% CI, 1.01-1.99), and acute illness severity (SAPS 3 excluding age and comorbidity) (HR, 1.06; 95% CI, 1.04-1.09) were associated with 30-day mortality. Conclusions: This population-based cohort study presents 30-day mortality of 604 ICU patients with COVID-19. The higher mortality was explained by older age, the presence chronic illness, and acute illness severity.
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Using geotagged Twitter data in Victoria, we created a mobility index and studied the changes during the staged restrictions during the coronavirus disease 2019 (COVID-19) pandemic. We describe preliminary evidence that geotagged Twitter data may be used to provide real-time population mobility data and information on the impact of restrictions on such mobility.