Background: The role of tracheostomy in coronavirus disease 2019 (COVID-19) is unclear, with several consensus guidelines advising against this practice. We developed both a dedicated airway team and coordinated education programme to facilitate ward management of tracheostomised COVID-19 patients. Here, we report outcomes in the first 100 COVID-19 patients who underwent tracheostomy at our institution. Methods: This was a prospective observational cohort study of patients confirmed to have COVID-19 who required mechanical ventilation at Queen Elizabeth Hospital, Birmingham, UK. The primary outcome measure was 30-day survival, accounting for severe organ dysfunction (Acute Physiology and Chronic Health [APACHE]-II score>17). Secondary outcomes included duration of ventilation, ICU stay, and healthcare workers directly involved in tracheostomy care acquiring COVID-19. Results: A total of 164 patients with COVID-19 were admitted to the ICU between March 9, 2020 and April 21, 2020. A total of 100 patients (mean [standard deviation] age: 55 [12] yr; 29% female) underwent tracheostomy; 64 (age: 57 [14] yr; 25% female) did not undergo tracheostomy. Despite similar APACHE-II scores, 30-day survival was higher in 85/100 (85%) patients after tracheostomy, compared with 27/64 (42%) non-tracheostomised patients {relative risk: 3.9 (95% confidence intervals [CI]: 2.3e6.4); P<0.0001}. In patients with APACHE-II scores !17, 68/100 (68%) tracheotomised patients survived, compared with 12/64 (19%) non-tracheotomised patients (P<0.001). Tracheostomy within 14 days of intubation was associated with shorter duration of ventilation (mean difference: 6.0 days [95% CI: 3.1e9.0]; P<0.0001) and ICU stay (mean difference: 6.7 days [95% CI: 3.7e9.6]; P<0.0001). No healthcare workers developed COVID-19. Conclusion: Independent of the severity of critical illness from COVID-19, 30-day survival was higher and ICU stay shorter in patients receiving tracheostomy. Early tracheostomy appears to be safe in COVID-19.
1. A central challenge of today's ecological research is predicting how ecosystems will develop under future global change. Accurate predictions are complicated by (a) simultaneous effects of different drivers, such as climate change, nitrogen deposition and management changes; and (b) legacy effects from previous land use. 2. We tested whether herb layer biodiversity (i.e. richness, Shannon diversity and evenness) and functional (i.e. herb cover, specific leaf area [SLA] and plant height) responses to environmental change drivers depended on land-use history. We used resurvey data from 192 plots across nineteen European temperate forest regions, with large spatial variability in environmental change factors. We tested for interactions between land-use history, distinguishing ancient and recent (i.e. post-agricultural) forests and four drivers: temperature, nitrogen deposition, and aridity at the regional scale and light dynamics at the plot-scale. 3. Land-use history significantly modulated global change effects on the functional signature of the herb layer (i.e. cover, SLA and plant height). Light availability was the main environmental driver of change interacting with land-use history. We found greater herb cover and plant height decreases and SLA increases with
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Questions: 1. What are the distribution and habitat associations of non‐native (neophyte) species in riparian zones? 2. Are there significant differences, in terms of plant species diversity, composition, habitat condition and species attributes, between plant communities where non‐natives are present or abundant and those where non‐natives are absent or infrequent? 3. Are the observed differences generic to non‐natives or do individual non‐native species differ in their vegetation associations? Location: West Midlands Conurbation (WMC), UK. Methods: 56 sites were located randomly on four rivers across the WMC. Ten 2 m × 2 m quadrats were placed within 15 m of the river to sample vegetation within the floodplain at each site. All vascular plants were recorded along with site information such as surrounding land use and habitat types. Results: Non‐native species were found in many vegetation types and on all rivers in the WMC. There were higher numbers of non‐natives on more degraded, human‐modified rivers. More non‐native species were found in woodland, scrub and tall herb habitats than in grasslands. We distinguish two types of communities with non‐natives. In communities colonized following disturbance, in comparison to quadrats containing no non‐native species, those with non‐natives had higher species diversity and more forbs, annuals and shortlived monocarpic perennials. Native species in quadrats containing non‐natives were characteristic of conditions of higher fertility and pH, had a larger specific leaf area and were less stress tolerant or competitive. In later successional communities dominated by particular non‐natives, native diversity declined with increasing cover of non‐natives. Associated native species were characteristic of low light conditions. Conclusions: Communities containing non‐natives can be associated with particular types of native species. Extrinsic factors (disturbance, eutrophication) affected both native and non‐native species. In disturbed riparian habitats the key determinant of diversity is dominance by competitive invasive species regardless of their native or non‐native origin.
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