Pilot phase results of a prospective, randomized controlled trial of narrowband ultraviolet B phototherapy in hospitalized COVID-19 patients.

COVID-19 morbidity and mortality are driven by poor immune regulation. Narrowband ultraviolet B (NB-UVB) phototherapy is standard of care in a number of immune-dysregulated diseases. To assess the efficacy of NB-UVB phototherapy for improving COVID-19 outcomes in high-risk, hospitalized, we developed the Adaptive Photo-Protection Trial. This is a multi-center, prospective, double-blinded, randomized, placebo-controlled trial. The pilot phase results are reported here. Consecutive patients admitted with a positive COVID-19 PCR were screened for eligibility. Enrolled subjects were computer randomized 1:1 to NB-UVB or placebo phototherapy. Subjects were treated daily with escalating doses on 27% of their body surface area for up to 8 consecutive days. Primary outcomes were safety and efficacy, defined as persistent or painful erythema and 28-day mortality. Comparisons were made via non-parametric exact tests. Patients in treatment (n = 15) and placebo (n = 15) arms had similar demographics. No adverse events occurred. Twenty eight-day mortality was 13.3% in treatment vs. 33.3% in placebo arms (p = 0.39). NB-UVB phototherapy in hospitalized COVID-19 patients was safe. Decreased mortality was observed in treated patients but this was statistically non-significant. Given its low-cost, scalability, and adjunctive nature, NB-UVB has the potential to improve COVID-19 outcomes. Continuation of this trial is warranted.

Improving the forward solver for the complete electrode model in EIT using algebraic multigrid.

Image reconstruction in electrical impedance tomography is an ill-posed nonlinear inverse problem. Linearization techniques are widely used and require the repeated solution of a linear forward problem. To account correctly for the presence of electrodes and contact impedances, the so-called complete electrode model is applied. Implementing a standard finite element method for this particular forward problem yields a linear system that is symmetric and positive definite and solvable via the conjugate gradient method. However, preconditioners are essential for efficient convergence. Preconditioners based on incomplete factorization methods are commonly used but their performance depends on user-tuned parameters. To avoid this deficiency, we apply black-box algebraic multigrid, using standard commercial and freely available software. The suggested solution scheme dramatically reduces the time cost of solving the forward problem. Numerical results are presented using an anatomically detailed model of the human head.