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The COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.
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AimCOVID-19 clinical presentation is heterogeneous, ranging from asymptomatic to severe cases. While there are a number of early publications relating to risk factors for COVID-19 infection, low sample size and heterogeneity in study design impacted consolidation of early findings. There is a pressing need to identify the factors which predispose patients to severe cases of COVID-19. For rapid and widespread risk stratification, these factors should be easily obtainable, inexpensive, and avoid invasive clinical procedures. The aim of our study is to fill this knowledge gap by systematically mapping all the available evidence on the association of various clinical, demographic, and lifestyle variables with the risk of specific adverse outcomes in patients with COVID-19. MethodsThe systematic review was conducted using standardized methodology, searching three electronic databases (PubMed, Embase, and Web of Science) for relevant literature published between 1st January 2020 and 9th July 2020. Included studies reported characteristics of patients with COVID-19 while reporting outcomes relating to disease severity. In the case of sufficient comparable data, meta-analyses were conducted to estimate risk of each variable. ResultsSeventy-six studies were identified, with a total of 17,860,001 patients across 14 countries. The studies were highly heterogeneous in terms of the sample under study, outcomes, and risk measures reported. A large number of risk factors were presented for COVID-19. Commonly reported variables for adverse outcome from COVID-19 comprised patient characteristics, including age >75 (OR = 2.65 (1.81-3.90)), male sex (OR = 2.05(1.39-3.04)) and severe obesity (OR = 2.57 (1.31-5.05)). Active cancer (OR = 1.46 (1.04-2.04)) was associated with increased risk of severe outcome. A number of common symptoms and vital measures (respiratory rate and SpO2) also suggested elevated risk profiles. ConclusionsBased on the findings of this study, a range of easily assessed parameters are valuable to predict elevated risk of severe illness and mortality as a result of COVID-19, including patient characteristics and detailed comorbidities, alongside the novel inclusion of real-time symptoms and vital measurements.
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AIMS: Despite rapid progress in device technologies for patent foramen ovale (PFO) closure over the past decade, long-tunnel anatomies still constitute a challenge. The present study investigated the performance of a novel in-tunnel device (Flatstent EF; Coherex Medical) in long-tunnel PFOs. METHODS AND RESULTS: Three different umbrella devices (n = 61) and the Coherex Flatstent (n = 27) were used for PFO closure. The Flatstent was the preferred device in long-tunnel anatomies. Seven patients with long PFO tunnels underwent "detunnelization" by stepwise inflation of a low-pressure balloon followed by implantation of an umbrella device. Complete occlusion or trivial residual shunting ("clinical" occlusion) was achieved in 93% of the Flatstent and 92% of the umbrella device procedures (P=.92). Device performance in long-tunnel anatomies was in favor of the Flatstent (n = 24) compared with conventional occluders (n = 7), with "clinical" occlusion of 96% vs 86% (P=.24) and procedure time of 44 ± 16 minutes vs 59 ± 21 minutes (P=.04). Furthermore, postprocedural arrhythmias were significantly less frequent after Flatstent implantations (0.0% vs 9.1%; P=.03). CONCLUSION: In long-tunnel PFOs, the Flatstent device was quicker to deploy, was at least as equally efficacious as umbrella devices, and reduced the incidence of symptomatic arrhythmias following PFO closure.
