Prevalence and clinical presentation of long COVID in children: a systematic review.

A systematic literature review was conducted up to 15th February 2022 to summarize long COVID evidence and to assess prevalence and clinical presentation in children and adolescents. Articles reporting long COVID prevalence and symptoms based on original data in the paediatric population were included. Case series quality was assessed through the JBI Critical Appraisal Checklist. For observational studies, adherence to STROBE checklist was evaluated. Twenty-two articles were included: 19 observational studies (12 cohort/7 cross-sectional) and 3 case series. Nine studies provided a control group. We found a high variability in terms of prevalence (1.6-70%). The most frequently reported symptoms were fatigue (2-87%), headache (3.5-80%), arthro-myalgias (5.4-66%), chest tightness or pain (1.4-51%), and dyspnoea (2-57.1%). Five studies reported limitations in daily function due to long COVID. Alterations at brain imaging were described in one study, transient electrocardiographic abnormalities were described in a minority of children, while most authors did not evidence long-term pulmonary sequelae. Older age, female sex, and previous long-term pathological conditions were more frequently associated with persistent symptoms. CONCLUSION: Long COVID evidence in children is limited, heterogeneous, and based on low-quality studies. The lockdown consequences are difficult to distinguish from long COVID symptoms. High-quality studies are required: WHO definition of long COVID should be used, controlled clinical studies should be encouraged, and the impact of new variants on long COVID prevalence should be investigated to ensure an objective analysis of long COVID characteristics in children and a proper allocation of healthcare system resources. WHAT IS KNOWN: • Children rarely develop a severe respiratory disease in the acute phase of COVID-19. • A limited number of patients develop a multisystem inflammatory condition that can lead to multiorgan failure and shock. WHAT IS NEW: • Persistent symptoms after SARS-CoV-2 infection are reported in children and limitations in daily function due to long COVID symptoms affect school attendance. • Functional complaints of post-acute COVID are difficult to be distinguished from those due to social restrictions.

Risk factors for severe COVID-19 in people with cystic fibrosis: A systematic review

Background People with cystic fibrosis (CF) are considered a clinically fragile population with an intrinsic higher risk of developing severe COVID-19, though a certain variability in terms of outcomes and hospitalization has been noticed. Aim To highlight the main risk factors for severe COVID-19 in patients with CF. Methods A systematic review of the current literature was conducted through PubMed and EMBASE databases. English-written articles reporting clinical data on CF subjects with SARS-CoV2 infection were included and analyzed. Selected reports were evaluated for adherence to STROBE recommendations. Results After the selection phase, 9 observational studies were included, 5 of which reported data from CF Registry Global Harmonization Group. The hospitalization rate ranged from 18.2 to 58.1%. The main risk factors for severe outcome were as follows: FEV1 < 70%p, CF-related diabetes, age > 40 years, pancreatic insufficiency, underweight, previous transplant, azithromycin use. Use of dornase alfa was associated with decreased risk for severe disease, while there was insufficient evidence to establish the role of inhaled steroids or CFTR modulators. No solid data regarding specific SARS-CoV-2 therapies in patients with CF emerged. Conclusion Most people with CF experience a mild course of SARS-CoV-2 infection, nevertheless subgroups with higher risk of severe outcome emerged. Maintenance therapies for CF overall did not show a clear preventive effect against severe outcomes, although dornase alfa seems to give some protection. Due to the current lack of data on specific COVID-19 therapies and immunization in patients with CF, further studies are needed to establish their impact in this population.

Business intelligence in the healthcare industry: The utilization of a data-driven approach to support clinical decision making

The pandemic has forced people to use digital technologies and accelerated the digitalization of many businesses. Using digital technologies generates a huge amount of data that are exploited by Business Intelligence (BI) to make decisions and improve the management of firms. This becomes particularly relevant in the healthcare sector where decisions are traditionally made on the physicians’ experience. Much work has been done on applying BI in the healthcare industry. Most of these studies were focused only on IT or medical aspects, while the usage of BI for improving the management of healthcare processes is an under-investigated field. This research aims at filling this gap by investigating whether a decision support system (DSS) model based on the exploitation of data through BI can outperform traditional experience-driven practices for managing processes in the healthcare domain. Focusing on the managing process of the therapeutic path of oncological patients, specifically BRCA-mutated women with breast cancer, a DSS model for benchmarking the costs of various treatment paths was developed in two versions: the first is experience-driven while the second is data-driven. We found that the data-driven version of the DSS model leads to a more accurate estimation of the costs that could potentially be prevented in the treatment of oncological patients, thus enabling significant cost savings. A more informed decision due to a more accurate cost estimation becomes crucial in a context where optimal treatment and unique clinical recommendations for patients are absent, thus permitting a substantial improvement of the decision making in the healthcare industry.