ABSTRACT
Introduction: In common with many aspects of critical illness recovery, there is no universally accepted formula for "weaning," the term used to describe the process of liberating patients from mechanical ventilation.1-3 Understanding a patient's progress during a prolonged wean can be difficult and requires integration of various datasets. Therefore, it is good practice to ensure that weaning prescriptions are clear, easy to follow and adhered to and that weaning-associated data and meta data are recorded accurately and are easy to interpret. The prototype Digitally Enhanced Liberation from VEntilation (DELVE) system has been designed to be used in combination with the Puritan Bennett(TM) 980 (PB980) ventilator (Covidien, USA). DELVE is an open-loop system which provides an interactive weaning chart, combining the weaning prescription entered by the clinical staff, with actual settings recorded from the ventilator in order to display compliance with the prescription (Figure 1). DELVE also collects measured data from the ventilator which could be used to display respiratory performance, both real-time and historical. Figure 1. DELVE set up with the PB980 ventilator (in the simulation suite). Objective(s): This feasibility study was designed to inform development of the first DELVE prototype and a future clinical trial to determine clinical effectiveness and usefulness. The study objectives were to determine whether DELVE could: 1. Present a digital weaning chart that staff could use effectively and would be superior to the current paper version. 2. Record and display the patients' ventilatory performance, both real time and historical, during liberation from mechanical ventilation. Method(s): This was a mixed-methods, prospective feasibility study of a complex intervention.4 Ventilated patients with a tracheostomy, commencing the weaning process, were recruited from an adult intensive care unit. DELVE was used alongside the current paper-based system for weaning planning and data collection. Patients remained in the study until they no longer required the support of the PB980 ventilator. Result(s): Twenty patients were enrolled for between 25 and 270 hours each. There were no safety incidents or data breaches. DELVE was successfully operated by staff, who were able to connect DELVE to the ventilator, prescribe weaning plans and analyse adherence. The digital weaning chart user interface was intuitive and easy to navigate. It was clearer, more complete and easier to interpret when compared to the paper weaning charts (Figure 2). DELVE reliably collected data every ten seconds and safely stored over six million items of measured data and 25000 events, such as alarm triggers and setting changes, in a form that could allow analysis and pictorial or graphical presentation. Conclusion(s): This study supported the feasibility of this and future versions of DELVE to present both a digital weaning chart and to facilitate visual and numerical data presentation. Future iterations of the system could include a user-friendly dashboard representing patient progress during the weaning process. Assimilation of large volumes of data could be used to enhance understanding and inform decision making around the prolonged wean.
ABSTRACT
SARS-COV-2 can contribute to long term consequences associated with sepsis and circulatory dysfunction. In this insightful paper, we highlight the emerging pathophysiology utilizing two case examples. Both systemic and organ specific features are discussed. In addition, a novel laboratory assay is presented that identified SARS-COV-2 in the circulation using conserved SARS ion channels rather than the spike protein. The presentation is linked to the pathophysiology with the emphasis for early recognition and continued research. This paper will serve as a catalyst for continued discovery.
ABSTRACT
When creating mathematical models for forecasting and decision making, there is a tendency to include more complexity than necessary, in the belief that higher-fidelity models are more accurate than simpler ones. In this paper, we analyze the performance of models that submitted COVID-19 forecasts to the U.S. Centers for Disease Control and Prevention and evaluate them against a simple two-equation model that is specified using simple linear regression. We find that our simple model was comparable in accuracy to highly publicized models and had among the best-calibrated forecasts. This result may be surprising given the complexity of many COVID-19 models and their support by large forecasting teams. However, our result is consistent with the body of research that suggests that simple models perform very well in a variety of settings.
ABSTRACT
Background: Limited data are available for risk assessment and outcome of COVID-19 in patients with hematologic malignancies (HM). We present a single center study of COVID-19 pneumonia in a cohort of 31 patients with HM. Methods: Data were abstracted from electronic medical records for patients admitted to NYPH between 3/5/20 and 4/17/20 and entered into a REDCap database. Results: Twenty (64.5%) were male;median age was 71 years. There were 8 patients with Multiple Myeloma (MM), 8 with Chronic Lymphocytic Leukemia (CLL), 6 (19.4%) had AML, 5 (16.1%) NHL, 2 (3.2%) ALL;CML, MDS and Polycythemia Vera occurred in 1 patient each. Twenty-four (77.4%) had active HM;6 (19.4%) were in remission;and 1 relapsed. Nineteen patients (61.3%) received recent chemotherapy and 11 (35.5%) immunosuppressive therapies. There were 7 (22.6%) hematopoietic stem cell transplant (HSCT) recipients (4 allogeneic and 3 autologous). Comorbidities were evenly distributed among all malignancies: 18 (58.1%) had hypertension, 9 (38.7%) obesity, 7 (22.6%) diabetes mellitus, and 11 (35.5%) were former smokers. The most common symptoms included cough (90.3%), fever (83.9%) and dyspnea (61.3%);7 (22.6%) had nausea and vomiting;7 (22.6%) had diarrhea. On presentation, hypoxia (O2 sat ≤94% on room air) occurred in 64.5%;median ALC was 330/ml;23 (74.2%) had ALC< 1000/ml;median CRP was 15.9 mg/dl (2.5-40.4), ferritin 1162 ng/ml (264 - > 16500), and D-dimers 456 ng/ml (< 150-2418). Thirteen patients (41.9%) required ICU admission and were intubated;among those 9 (69.2%) had either MM or CLL. Co-infections were uncommon;two patients developed HSV1 pneumonitis and one of these also had CMV pneumonitis. Twenty-eight (90.3%) were treated with hydroxychloroquine, 5 (16.1%) remdesivir, 2 (6.5%) tocilizumab, 1 (3.2%) sarilumab, and 4 (12.9%) with methylprednisolone 0.5mg/kg Q12h. Seventeen patients (54.8%) recovered and were discharged, 12 (38.7%) died;2 (6.5%) were still hospitalized but left the ICU. Conclusion: In our cohort, there were predominantly more patients with MM and CLL and 56% of these were intubated;larger cohort studies will further define the risk and outcome for COVID-19 in patients with HM.
ABSTRACT
Objective: To review current reports on atypical manifestations of coronavirus disease 2019 (COVID-19). Methods: Review of the literature. Results: Evidence regarding atypical features of COVID-19 is accumulating. SARS-CoV-2 can infect human cells that express the angiotensin-converting enzyme 2 receptor, which would allow for a broad spectrum of illnesses affecting the renal, cardiac, and gastrointestinal organ systems. Neurologic, cutaneous, and musculoskeletal manifestations have also been reported. The potential for SARS-CoV-2 to induce a hypercoagulable state provides another avenue for the virus to indirectly damage various organ systems, as evidenced by reports of cerebrovascular disease, myocardial injury, and a chilblain-like rash in patients with COVID-19. Conclusion: Because the signs and symptoms of COVID-19 may occur with varying frequency across populations, it is important to keep differentials broad when assessing patients with a clinical illness that may indeed be COVID-19.