Experimental Technologies in the Diagnosis and Treatment of COVID-19 in Patients with Comorbidities.

The COVID-19 pandemic has impacted the whole world and raised concerns about its effects on different human organ systems. Early detection of COVID-19 may significantly increase the rate of survival; thus, it is critical that the disease is detected early. Emerging technologies have been used to prevent, diagnose, and manage COVID-19 among the populace in the USA and globally. Numerous studies have revealed the growing implementation of novel engineered systems during the intervention at various points of the disease's pathogenesis, especially as it relates to comorbidities and complications related to cardiovascular and respiratory organ systems. In this review, we provide a succinct, but extensive, review of the pathogenesis of COVID-19, particularly as it relates to angiotensin-converting enzyme 2 (ACE2) as a viral entry point. This is followed by a comprehensive analysis of cardiovascular and respiratory comorbidities of COVID-19 and novel technologies that are used to diagnose and manage hospitalized patients. Continuous cardiorespiratory monitoring systems, novel machine learning algorithms for rapidly triaging patients, various imaging modalities, wearable immunosensors, hotspot tracking systems, and other emerging technologies are reviewed. COVID-19 effects on the immune system, associated inflammatory biomarkers, and innovative therapies are also assessed. Finally, with emphasis on the impact of wearable and non-wearable systems, this review highlights future technologies that could help diagnose, monitor, and mitigate disease progression. Technologies that account for an individual's health conditions, comorbidities, and even socioeconomic factors can drastically reduce the high mortality seen among many COVID-19 patients, primarily via disease prevention, early detection, and pertinent management.

Patient blood management interventions do not lead to important clinical benefits or cost-effectiveness for major surgery: a network meta-analysis.

BACKGROUND: Patient blood management (PBM) interventions aim to improve clinical outcomes by reducing bleeding and transfusion. We assessed whether existing evidence supports the routine use of combinations of these interventions during and after major surgery. METHODS: Five systematic reviews and a National Institute of Health and Care Excellence health economic review of trials of common PBM interventions enrolling participants of any age undergoing surgery were updated. The last search was on June 1, 2019. Studies in trauma, burns, gastrointestinal haemorrhage, gynaecology, dentistry, or critical care were excluded. The co-primary outcomes were: risk of receiving red cell transfusion and 30-day or hospital all-cause mortality. Treatment effects were estimated using random-effects models and risk ratios (RR) with 95% confidence intervals (CIs). Heterogeneity assessments used I2. Network meta-analyses used a frequentist approach. The protocol was registered prospectively (PROSPERO CRD42018085730). RESULTS: Searches identified 393 eligible randomised controlled trials enrolling 54 917 participants. PBM interventions resulted in a reduction in exposure to red cell transfusion (RR=0.60; 95% CI 0.57, 0.63; I2=77%), but had no statistically significant treatment effect on 30-day or hospital mortality (RR=0.93; 95% CI 0.81, 1.07; I2=0%). Treatment effects were consistent across multiple secondary outcomes, sub-groups and sensitivity analyses that considered clinical setting, type of intervention, and trial quality. Network meta-analysis did not demonstrate additive benefits from the use of multiple interventions. No trial demonstrated that PBM was cost-effective. CONCLUSIONS: In randomised trials, PBM interventions do not have important clinical benefits beyond reducing bleeding and transfusion in people undergoing major surgery.

Assessment of the frequency of the transforming growth factor beta-1 sequence polymorphisms in patients with alcohol dependence syndrome.

Alcohol abuse is one of the most significant factors in the development of liver fibrosis. The pathomechanism of liver fibrosis is the same regardless of its etiology. Fibrosis is a sign of an imbalance between the synthesis of the extracellular matrix components and their degradation. Among the many cytokines that affect hepatic stellate cell activation it seems that transforming growth factor beta (TGF-ß) is the most significant, either as the direct factor stimulating polymerase chain reaction (HSC) proliferation and transformation into myofibroblasts, or as the direct factor causing an increase in the activity of genes responsible for the synthesis of extracellular matrix components. The aim of the study was to reveal possible dependencies and differences between the presence of certain alleles of the TGF-ß1 gene and its blood level in the study and control group. Blood samples were obtained from 39 patients, the control group consisted of 21 patients. The results obtained in the course of this study showed no statistically significant differences between the frequencies of particular polymorphisms. In the case of haplotype frequencies, insignificant differences were found for the algorithm Excoffier-Laval-Balding predicted haplotypes while one significant difference between the study and control groups was detected in case of the TC haplotype frequency predicted using the Expectation-Maximization algorithm. However, the difference in frequency of TC haplotype predicted by both algorithms was not significant. Genetic analysis of two single nucleotide polymorphisms (SNPs) in exon I of the TGF-ß1 gene did not show significant differences between the occurrence of particular polymorphisms and haplotypes in the populations under study.