10
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      CPAP delivered outside critical care during the second wave of COVID-19: outcomes from a UK respiratory surge unit

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          NHS England recommends non-invasive continuous positive airway pressure (CPAP) as a possible treatment for type 1 respiratory failure associated with COVID-19 pneumonitis, either to avoid intubation or as a ceiling of care. However, data assessing this strategy are sparse, especially for the use of CPAP as a ceiling of care, and particularly when delivered outside of a traditional critical care environment. We describe a cohort of patients from Liverpool, UK, who received CPAP on a dedicated respiratory surge unit at the start of the second wave of the COVID-19 pandemic in UK.

          Methods

          Retrospective cohort analysis of consecutive patients receiving CPAP for the treatment of respiratory failure secondary to COVID-19 on the respiratory surge unit at the Royal Liverpool Hospital, Liverpool, UK from 21 September until 30 November 2020.

          Results

          88 patients were included in the analysis. 56/88 (64%) were deemed suitable for escalation to invasive mechanical ventilation (IMV) and received CPAP as a trial; 32/88 (36%) received CPAP as a ceiling of care. Median age was 63 years (IQR: 56–74) and 58/88 (66%) were men. Median SpO 2/FiO 2 immediately prior to CPAP initiation was 95 (92–152). Among patients for escalation to IMV, the median time on CPAP was 6 days (IQR 4–7) and survival at day 30 was 84% (47/56) with 14/56 (25%) escalated to IMV. Of those patients for whom CPAP was ceiling of care, the median duration of CPAP was 9 days (IQR 7–11) and 18/32 (56%) survived to day 30. Pulmonary barotrauma occurred in 9% of the cohort. There were no associations found on multivariant analysis that were associated with all-cause 30-day mortality.

          Conclusions

          With adequate planning and resource redistribution, CPAP may be delivered effectively outside of a traditional critical care setting for the treatment of respiratory failure due to COVID-19. Clinicians delivering CPAP to patients with COVID-19 pneumonitis should be alert to the dangers of pulmonary barotrauma. Among patients who are for escalation of care, the use of CPAP may avoid the need for IMV in some patients. Our data support the NHS England recommendation to consider CPAP as a ceiling of care.

          Related collections

          Most cited references20

          • Record: found
          • Abstract: found
          • Article: not found

          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A global clinical measure of fitness and frailty in elderly people.

            There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use. We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools. The CSHA Clinical Frailty Scale was highly correlated (r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%-30.6%) and entry into an institution (23.9%, 95% CI 8.8%-41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality). Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study

              Abstract Objective To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase of the first wave of this outbreak who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study, and to explore risk factors associated with mortality in hospital. Design Prospective observational cohort study with rapid data gathering and near real time analysis. Setting 208 acute care hospitals in England, Wales, and Scotland between 6 February and 19 April 2020. A case report form developed by ISARIC and WHO was used to collect clinical data. A minimal follow-up time of two weeks (to 3 May 2020) allowed most patients to complete their hospital admission. Participants 20 133 hospital inpatients with covid-19. Main outcome measures Admission to critical care (high dependency unit or intensive care unit) and mortality in hospital. Results The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity. Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date. 17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to receive care at the reporting date. Of those receiving mechanical ventilation, 17% (276/1658) were discharged alive, 37% (618/1658) died, and 46% (764/1658) remained in hospital. Increasing age, male sex, and comorbidities including chronic cardiac disease, non-asthmatic chronic pulmonary disease, chronic kidney disease, liver disease and obesity were associated with higher mortality in hospital. Conclusions ISARIC WHO CCP-UK is a large prospective cohort study of patients in hospital with covid-19. The study continues to enrol at the time of this report. In study participants, mortality was high, independent risk factors were increasing age, male sex, and chronic comorbidity, including obesity. This study has shown the importance of pandemic preparedness and the need to maintain readiness to launch research studies in response to outbreaks. Study registration ISRCTN66726260.
                Bookmark

                Author and article information

                Journal
                BMJ Open Respir Res
                BMJ Open Respir Res
                bmjresp
                bmjopenrespres
                BMJ Open Respiratory Research
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2052-4439
                2021
                14 September 2021
                14 September 2021
                : 8
                : 1
                : e000907
                Affiliations
                [1 ]departmentClinical Sciences , Liverpool School of Tropical Medicine , Liverpool, UK
                [2 ]departmentDepartment of Respiratory Medicine, Tropical and Infectious Disease Unit, Intensive care Unit , Liverpool University Hospitals NHS Foundation Trust , Liverpool, UK
                [3 ]departmentInstitute of Infection, Veterinary and Ecological Sciences , Univeristy of Liverpool , Liverpool, UK
                [4 ]departmentSchool of Medicine , Univeristy of Liverpool , Liverpool, UK
                Author notes
                [Correspondence to ] Dr Rebecca Nightingale; rebecca.nightingale@ 123456lstmed.ac.uk
                Author information
                http://orcid.org/0000-0001-5636-8531
                Article
                bmjresp-2021-000907
                10.1136/bmjresp-2021-000907
                8441225
                34521649
                5ba99b6c-9bee-4e22-860f-2510c94555a3
                © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 19 February 2021
                : 07 August 2021
                Categories
                Non-Invasive Ventilation
                1506
                2474
                2223
                Custom metadata
                unlocked

                covid-19
                covid-19

                Comments

                Comment on this article