Emerging coronavirus diseases and future perspectives

Barriers to gene therapy, understanding the concerns people with haemophilia have: an exigency sub-study

BACKGROUND

Gene therapy has the potential to offer people with haemophilia (PwH) a life free from bleeding and the burden posed by current treatment regimens. To date, gene therapy has only been available in clinical trial settings, to PwH without pre-existing or historical factor inhibitors, significant concomitant liver damage or pre-existing neutralising antibodies to the adeno-associated viruses used to deliver the therapy. Thus, most PwH treated at centres not currently involved in gene therapy trials, either as a referral/follow-up centre or as a dosing centre, have been unable to access the therapy. This Exigency sub-study aims to gain a greater understanding of the opinions of PwH in the United Kingdom who have not had access to gene therapy: asking what they understand, what concerns they have, and whether they perceive any barriers preventing their access to gene therapy.

RESULTS

Twenty-three PwH were approached; 14 consented, and one withdrew prior to interview. The mean age of the participants was 35.7 years (range 25-74 years). Eleven had haemophilia A and two haemophilia B. Two were treated with standard half-life factor products, five with extended half-life products, five with a FVIII mimetic and one with a clinical trial product. One family member (a participant's partner) was also interviewed. The participants identified four barriers to gene therapy: concerns about the process of gene therapy (Expectations), uncertainty about the results (outcomes), (Access) to treatment, and a lack of understanding about gene therapy (education).

CONCLUSIONS

This Exigency study subgroup sees gene therapy as a positive treatment development that promises an improved quality of life. For this participant group, four issues impact their decision to undergo gene therapy. If the promise of gene therapy is to be realised, these barriers need to be acknowledged and addressed by healthcare professionals, patient organisations, and gene therapy providers.

The Accuracy of Machine Learning Approaches Using Non-image Data for the Prediction of COVID-19: A Meta-Analysis

Objective

COVID-19 is a novel, severely contagious disease with enormous negative impact on humanity as well as the world economy. An expeditious, feasible tool for detecting COVID-19 remains yet elusive. Recently, there has been a surge of interest in applying machine learning techniques to predict COVID-19 using non-image data. We have therefore undertaken a meta-analysis to quantify the diagnostic performance of machine learning models facilitating the prediction of COVID-19.

Materials and methods

A comprehensive electronic database search for the period between January 1st, 2021 and December 3rd, 2021 was undertaken in order to identify eligible studies relevant to this meta-analysis. Summary sensitivity, specificity, and the area under receiver operating characteristic curves were used to assess potential diagnostic accuracy. Risk of bias was assessed by means of a revised Quality Assessment of Diagnostic Studies.

Results

A total of 30 studies, including 34 models, met all of the inclusion criteria. Summary sensitivity, specificity, and area under receiver operating characteristic curves were 0.86, 0.86, and 0.91, respectively. The purpose of machine learning models, class imbalance, and feature selection are significant covariates useful in explaining the between-study heterogeneity, in terms of both sensitivity and specificity.

Conclusions

Our study findings show that non-image data can be used to predict COVID-19 with an acceptable performance. Further, class imbalance and feature selection are suggested to be incorporated whenever building models for the prediction of COVID-19, thus improving further diagnostic performance.

Prospects for controlling future pandemics of SARS in highlights of SARS-CoV-2

Throughout human history infectious diseases have emerged to become global threats once in a while. Sometimes the previously established infections surfaced due to geographical extension or by increasing their transmissibility or pathogenicity while in other instances new infections have periodically emerged by transmitting from animals to humans. A proper strengthening of the existing health care system, disease surveillance, advancement in medical technology and healthy lifestyle is a must for controlling the future re-emergence of pandemics. Similarly, a deeper understanding of (1) key medical and social elements; (2) treatment and prevention options; (3) epidemic preparedness of the health care system; and (4) investing in ethno medicine research is necessary to prevent the future devastating pandemic emergencies.