Susceptibility of ABO blood group to COVID-19 infections: clinico-hematological, radiological, and complications analysis.

ABSTRACT: In the wake of the COVID-19 pandemic, research indicates that the COVID-19 disease susceptibility varies among individuals depending on their ABO blood groups. Researchers globally commenced investigating potential methods to stratify cases according to prognosis depending on several clinical parameters. Since there is evidence of a link between ABO blood groups and disease susceptibility, it could be argued that there is a link between blood groups and disease manifestation and progression. The current study investigates whether clinical manifestation, laboratory, and imaging findings vary among ABO blood groups of hospitalized confirmed COVID-19 patients.This retrospective cohort study was conducted between March 1, 2020 and March 31, 2021 in King Faisal Specialist Hospital and Research Centre Riyadh and Jeddah, Saudi Arabia. Demographic information, clinical information, laboratory findings, and imaging investigations were extracted from the data warehouse for all confirmed COVID-19 patients.A total of 285 admitted patients were included in the study. Of these, 81 (28.4%) were blood group A, 43 (15.1%) were blood group B, 11 (3.9%) were blood group AB, and 150 (52.6%) were blood group O. This was almost consistent with the distribution of blood groups among the Saudi Arabia community. The majority of the study participants (79.6% [n = 227]) were asymptomatic. The upper respiratory tract infection (P = .014) and shortness of breath showed statistically significant differences between the ABO blood group (P = .009). Moreover, the incidence of the symptoms was highly observed in blood group O followed by A then B except for pharyngeal exudate observed in blood group A. The one-way ANOVA test indicated that among the studied hematological parameters, glucose (P = .004), absolute lymphocyte count (P = .001), and IgA (P = .036) showed statistically significant differences between the means of the ABO blood group. The differences in both X-ray and computed tomography scan findings were statistically nonsignificant among the ABO age group. Only 86 (30.3%) patients were admitted to an intensive care unit, and the majority of them were blood groups O 28.7% (n = 43) and A 37.0% (n = 30). However, the differences in complications' outcomes were statistically nonsignificant among the ABO age group.ABO blood groups among hospitalized COVID-19 patients are not associated with clinical, hematological, radiological, and complications abnormality.

Towards Energy-Aware Feedback Planning for Long-Range Autonomous Underwater Vehicles.

Ocean ecosystems have spatiotemporal variability and dynamic complexity that require a long-term deployment of an autonomous underwater vehicle for data collection. A new generation of long-range autonomous underwater vehicles (LRAUVs), such as the Slocum glider and Tethys-class AUV, has emerged with high endurance, long-range, and energy-aware capabilities. These new vehicles provide an effective solution to study different oceanic phenomena across multiple spatial and temporal scales. For these vehicles, the ocean environment has forces and moments from changing water currents which are generally on the order of magnitude of the operational vehicle velocity. Therefore, it is not practical to generate a simple trajectory from an initial location to a goal location in an uncertain ocean, as the vehicle can deviate significantly from the prescribed trajectory due to disturbances resulted from water currents. Since state estimation remains challenging in underwater conditions, feedback planning must incorporate state uncertainty that can be framed into a stochastic energy-aware path planning problem. This article presents an energy-aware feedback planning method for an LRAUV utilizing its kinematic model in an underwater environment under motion and sensor uncertainties. Our method uses ocean dynamics from a predictive ocean model to understand the water flow pattern and introduces a goal-constrained belief space to make the feedback plan synthesis computationally tractable. Energy-aware feedback plans for different water current layers are synthesized through sampling and ocean dynamics. The synthesized feedback plans provide strategies for the vehicle that drive it from an environment's initial location toward the goal location. We validate our method through extensive simulations involving the Tethys vehicle's kinematic model and incorporating actual ocean model prediction data.