The prognostic role of micronutrient status and supplements in COVID-19 outcomes: A systematic review.

Micronutrients constitute an adjuvant treatment for respiratory viral infections. Since there is no effective antiviral therapy for COVID-19 yet, adjuvant intervention for the survival of critically ill patients may be significant. Search of the PubMed, CINAHL and Cochrane databases was carried out to find human studies investigating the prognostic role of micronutrient status and the effects of micronutrient supplementation intervention in COVID-19 outcomes of adult patients. Patients with certain comorbidities (diabetes mellitus type 2, obesity, renal failure, liver dysfunction etc.) or pregnant women were excluded. 31 studies (27 observational studies and 4 clinical trials) spanning the years 2020-2021, pertaining to 8624 COVID-19 patients (mean age±SD, 61 ± 9 years) were included in this systematic review. Few studies provided direct evidence on the association of serum levels of vitamin D, calcium, zinc, magnesium, phosphorus and selenium to patients' survival or death. Vitamin D and calcium were the most studied micronutrients and those with a probable promising favorable impact on patients. This review highlights the importance of a balanced nutritional status for a favorable outcome in COVID-19. Micronutrients' deficiency on admission to hospital seems to be related to a high risk for ICU admission, intubation and even death. Nevertheless, evidence for intervention remains unclear.

Artificial intelligence for imaging-based COVID-19 detection: Systematic review comparing added value of AI versus human readers.

PURPOSE: A growing number of studies have examined whether Artificial Intelligence (AI) systems can support imaging-based diagnosis of COVID-19-caused pneumonia, including both gains in diagnostic performance and speed. However, what is currently missing is a combined appreciation of studies comparing human readers and AI. METHODS: We followed PRISMA-DTA guidelines for our systematic review, searching EMBASE, PUBMED and Scopus databases. To gain insights into the potential value of AI methods, we focused on studies comparing the performance of human readers versus AI models or versus AI-supported human readings. RESULTS: Our search identified 1270 studies, of which 12 fulfilled specific selection criteria. Concerning diagnostic performance, in testing datasets reported sensitivity was 42-100% (human readers, n = 9 studies), 60-95% (AI systems, n = 10) and 81-98% (AI-supported readers, n = 3), whilst reported specificity was 26-100% (human readers, n = 8), 61-96% (AI systems, n = 10) and 78-99% (AI-supported readings, n = 2). One study highlighted the potential of AI-supported readings for the assessment of lung lesion burden changes, whilst two studies indicated potential time savings for detection with AI. CONCLUSIONS: Our review indicates that AI systems or AI-supported human readings show less performance variability (interquartile range) in general, and may support the differentiation of COVID-19 pneumonia from other forms of pneumonia when used in high-prevalence and symptomatic populations. However, inconsistencies related to study design, reporting of data, areas of risk of bias, as well as limitations of statistical analyses complicate clear conclusions. We therefore support efforts for developing critical elements of study design when assessing the value of AI for diagnostic imaging.