A systematic review and meta-analysis of long COVID symptoms.

BACKGROUND: Ongoing symptoms or the development of new symptoms following a SARS-CoV-2 diagnosis has caused a complex clinical problem known as "long COVID" (LC). This has introduced further pressure on global healthcare systems as there appears to be a need for ongoing clinical management of these patients. LC personifies heterogeneous symptoms at varying frequencies. The most complex symptoms appear to be driven by the neurology and neuropsychiatry spheres. METHODS: A systematic protocol was developed, peer reviewed, and published in PROSPERO. The systematic review included publications from the 1st of December 2019-30th June 2021 published in English. Multiple electronic databases were used. The dataset has been analyzed using a random-effects model and a subgroup analysis based on geographical location. Prevalence and 95% confidence intervals (CIs) were established based on the data identified. RESULTS: Of the 302 studies, 49 met the inclusion criteria, although 36 studies were included in the meta-analysis. The 36 studies had a collective sample size of 11,598 LC patients. 18 of the 36 studies were designed as cohorts and the remainder were cross-sectional. Symptoms of mental health, gastrointestinal, cardiopulmonary, neurological, and pain were reported. CONCLUSIONS: The quality that differentiates this meta-analysis is that they are cohort and cross-sectional studies with follow-up. It is evident that there is limited knowledge available of LC and current clinical management strategies may be suboptimal as a result. Clinical practice improvements will require more comprehensive clinical research, enabling effective evidence-based approaches to better support patients.

The prevalence of mental ill-health in women during pregnancy and after childbirth during the Covid-19 pandemic: a systematic review and Meta-analysis.

BACKGROUND: This systematic review aims to explore the prevalence of the impact of the COVID-19, MERS, and SARS pandemics on the mental health of pregnant women. METHODS: All COVID-19, SARS and MERS studies that evaluated the mental health of pregnant women with/without gynaecological conditions that were reported in English between December 2000 - July 2021 were included. The search criteria were developed based upon the research question using PubMed, Science Direct, Ovid PsycINFO and EMBASE databases. A wide search criterion was used to ensure the inclusion of all pregnant women with existing gynaecological conditions. The Newcastle-Ottawa-Scale was used to assess the risk of bias for all included studies. Random effects model with restricted maximum-likelihood estimation method was applied for the meta-analysis and I-square statistic was used to evaluate heterogeneity across studies. The pooled prevalence rates of symptoms of anxiety, depression, PTSD, stress, and sleep disorders with 95% confidence interval (CI) were computed. RESULTS: This systematic review identified 217 studies which included 638,889 pregnant women or women who had just given birth. There were no studies reporting the mental health impact due to MERS and SARS. Results showed that women who were pregnant or had just given birth displayed various symptoms of poor mental health including those relating to depression (24.9%), anxiety (32.8%), stress (29.44%), Post Traumatic Stress Disorder (PTSD) (27.93%), and sleep disorders (24.38%) during the COVID-19 pandemic. DISCUSSION: It is important to note that studies included in this review used a range of outcome measures which does not allow for direct comparisons between findings. Most studies reported self-reported measure of symptoms without clinical diagnoses so conclusions can be made for symptom prevalence rather than of mental illness. The importance of managing mental health during pregnancy and after-delivery improves the quality of life and wellbeing of mothers hence developing an evidence-based approached as part of pandemic preparedness would improve mental health during challenging times. OTHER: The work presented in this manuscript was not funded by any specific grants. A study protocol was developed and published in PROSPERO (CRD42021235356) to explore several key objectives.

International recruitment of mental health nurses to the national health service: a challenge for the UK.

The UK's National Health Service (NHS) has been dealing with a shortage in the nursing workforce for the past few decades. With the ongoing COVID-19 pandemic and post-Brexit effects, it is important now more than ever to concentrate on recruiting new staff and retaining current staff in the National Health Service. The increasing demand for mental health services stresses the importance of prioritising recruitment of mental health nurses. One of the main strategies being implemented to combat this shortage is the recruitment of internationally trained mental health nurses. Whilst this is a favourable solution, the multiple challenges this proposal brings makes it hard for the National Health Service to practically implement this to increase staff numbers. In this discursive position paper, we consider the difficulties the National Health Service is currently facing in terms of recruiting mental health nurses and then discuss the importance of and need for international recruitment including the strategies that are currently being implemented. The challenges and obstacles associated with this proposed resolution will also be addressed.

Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study.

BACKGROUND: Most studies of long COVID (symptoms of COVID-19 infection beyond 4 weeks) have focused on people hospitalized in their initial illness. Long COVID is thought to be underrecorded in UK primary care electronic records. OBJECTIVE: We sought to determine which symptoms people present to primary care after COVID-19 infection and whether presentation differs in people who were not hospitalized, as well as post-long COVID mortality rates. METHODS: We used routine data from the nationally representative primary care sentinel cohort of the Oxford-Royal College of General Practitioners Research and Surveillance Centre (N=7,396,702), applying a predefined long COVID phenotype and grouped by whether the index infection occurred in hospital or in the community. We included COVID-19 infection cases from March 1, 2020, to April 1, 2021. We conducted a before-and-after analysis of long COVID symptoms prespecified by the Office of National Statistics, comparing symptoms presented between 1 and 6 months after the index infection matched with the same months 1 year previously. We conducted logistic regression analysis, quoting odds ratios (ORs) with 95% CIs. RESULTS: In total, 5.63% (416,505/7,396,702) and 1.83% (7623/416,505) of the patients had received a coded diagnosis of COVID-19 infection and diagnosis of, or referral for, long COVID, respectively. People with diagnosis or referral of long COVID had higher odds of presenting the prespecified symptoms after versus before COVID-19 infection (OR 2.66, 95% CI 2.46-2.88, for those with index community infection and OR 2.42, 95% CI 2.03-2.89, for those hospitalized). After an index community infection, patients were more likely to present with nonspecific symptoms (OR 3.44, 95% CI 3.00-3.95; P<.001) compared with after a hospital admission (OR 2.09, 95% CI 1.56-2.80; P<.001). Mental health sequelae were more strongly associated with index hospital infections (OR 2.21, 95% CI 1.64-2.96) than with index community infections (OR 1.36, 95% CI 1.21-1.53; P<.001). People presenting to primary care after hospital infection were more likely to be men (OR 1.43, 95% CI 1.25-1.64; P<.001), more socioeconomically deprived (OR 1.42, 95% CI 1.24-1.63; P<.001), and with higher multimorbidity scores (OR 1.41, 95% CI 1.26-1.57; P<.001) than those presenting after an index community infection. All-cause mortality in people with long COVID was associated with increasing age, male sex (OR 3.32, 95% CI 1.34-9.24; P=.01), and higher multimorbidity score (OR 2.11, 95% CI 1.34-3.29; P<.001). Vaccination was associated with reduced odds of mortality (OR 0.10, 95% CI 0.03-0.35; P<.001). CONCLUSIONS: The low percentage of people recorded as having long COVID after COVID-19 infection reflects either low prevalence or underrecording. The characteristics and comorbidities of those presenting with long COVID after a community infection are different from those hospitalized. This study provides insights into the presentation of long COVID in primary care and implications for workload.

Developing a Long COVID Phenotype for Postacute COVID-19 in a National Primary Care Sentinel Cohort: Observational Retrospective Database Analysis.

BACKGROUND: Following COVID-19, up to 40% of people have ongoing health problems, referred to as postacute COVID-19 or long COVID (LC). LC varies from a single persisting symptom to a complex multisystem disease. Research has flagged that this condition is underrecorded in primary care records, and seeks to better define its clinical characteristics and management. Phenotypes provide a standard method for case definition and identification from routine data and are usually machine-processable. An LC phenotype can underpin research into this condition. OBJECTIVE: This study aims to develop a phenotype for LC to inform the epidemiology and future research into this condition. We compared clinical symptoms in people with LC before and after their index infection, recorded from March 1, 2020, to April 1, 2021. We also compared people recorded as having acute infection with those with LC who were hospitalized and those who were not. METHODS: We used data from the Primary Care Sentinel Cohort (PCSC) of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database. This network was recruited to be nationally representative of the English population. We developed an LC phenotype using our established 3-step ontological method: (1) ontological step (defining the reasoning process underpinning the phenotype, (2) coding step (exploring what clinical terms are available, and (3) logical extract model (testing performance). We created a version of this phenotype using Protégé in the ontology web language for BioPortal and using PhenoFlow. Next, we used the phenotype to compare people with LC (1) with regard to their symptoms in the year prior to acquiring COVID-19 and (2) with people with acute COVID-19. We also compared hospitalized people with LC with those not hospitalized. We compared sociodemographic details, comorbidities, and Office of National Statistics-defined LC symptoms between groups. We used descriptive statistics and logistic regression. RESULTS: The long-COVID phenotype differentiated people hospitalized with LC from people who were not and where no index infection was identified. The PCSC (N=7.4 million) includes 428,479 patients with acute COVID-19 diagnosis confirmed by a laboratory test and 10,772 patients with clinically diagnosed COVID-19. A total of 7471 (1.74%, 95% CI 1.70-1.78) people were coded as having LC, 1009 (13.5%, 95% CI 12.7-14.3) had a hospital admission related to acute COVID-19, and 6462 (86.5%, 95% CI 85.7-87.3) were not hospitalized, of whom 2728 (42.2%) had no COVID-19 index date recorded. In addition, 1009 (13.5%, 95% CI 12.73-14.28) people with LC were hospitalized compared to 17,993 (4.5%, 95% CI 4.48-4.61; P<.001) with uncomplicated COVID-19. CONCLUSIONS: Our LC phenotype enables the identification of individuals with the condition in routine data sets, facilitating their comparison with unaffected people through retrospective research. This phenotype and study protocol to explore its face validity contributes to a better understanding of LC.

Mental health impact of the Middle East respiratory syndrome, SARS, and COVID-19: A comparative systematic review and meta-analysis.

BACKGROUND: Over the last few decades, 3 pathogenic pandemics have impacted the global population; severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV) and SARS-CoV-2. The global disease burden has attributed to millions of deaths and morbidities, with the majority being attributed to SARS-CoV-2. As such, the evaluation of the mental health (MH) impact across healthcare professionals (HCPs), patients and the general public would be an important facet to evaluate to better understand short, medium and long-term exposures. AIM: To identify and report: (1) MH conditions commonly observed across all 3 pandemics; (2) Impact of MH outcomes across HCPs, patients and the general public associated with all 3 pandemics; and (3) The prevalence of the MH impact and clinical epidemiological significance. METHODS: A systematic methodology was developed and published on PROSPERO (CRD42021228697). The databases PubMed, EMBASE, ScienceDirect and the Cochrane Central Register of Controlled Trials were used as part of the data extraction process, and publications from January 1, 1990 to August 1, 2021 were searched. MeSH terms and keywords used included Mood disorders, PTSD, Anxiety, Depression, Psychological stress, Psychosis, Bipolar, Mental Health, Unipolar, Self-harm, BAME, Psychiatry disorders and Psychological distress. The terms were expanded with a 'snowballing' method. Cox-regression and the Monte-Carlo simulation method was used in addition to I 2 and Egger's tests to determine heterogeneity and publication bias. RESULTS: In comparison to MERS and SARS-CoV, it is evident SAR-CoV-2 has an ongoing MH impact, with emphasis on depression, anxiety and post-traumatic stress disorder. CONCLUSION: It was evident MH studies during MERS and SARS-CoV was limited in comparison to SARS-CoV-2, with much emphasis on reporting symptoms of depression, anxiety, stress and sleep disturbances. The lack of comprehensive studies conducted during previous pandemics have introduced limitations to the "know-how" for clinicians and researchers to better support patients and deliver care with limited healthcare resources.

Methodological Issues in Using a Common Data Model of COVID-19 Vaccine Uptake and Important Adverse Events of Interest: Feasibility Study of Data and Connectivity COVID-19 Vaccines Pharmacovigilance in the United Kingdom.

BACKGROUND: The Data and Connectivity COVID-19 Vaccines Pharmacovigilance (DaC-VaP) UK-wide collaboration was created to monitor vaccine uptake and effectiveness and provide pharmacovigilance using routine clinical and administrative data. To monitor these, pooled analyses may be needed. However, variation in terminologies present a barrier as England uses the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), while the rest of the United Kingdom uses the Read v2 terminology in primary care. The availability of data sources is not uniform across the United Kingdom. OBJECTIVE: This study aims to use the concept mappings in the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) to identify common concepts recorded and to report these in a repeated cross-sectional study. We planned to do this for vaccine coverage and 2 adverse events of interest (AEIs), cerebral venous sinus thrombosis (CVST) and anaphylaxis. We identified concept mappings to SNOMED CT, Read v2, the World Health Organization's International Classification of Disease Tenth Revision (ICD-10) terminology, and the UK Dictionary of Medicines and Devices (dm+d). METHODS: Exposures and outcomes of interest to DaC-VaP for pharmacovigilance studies were selected. Mappings of these variables to different terminologies used across the United Kingdom's devolved nations' health services were identified from the Observational Health Data Sciences and Informatics (OHDSI) Automated Terminology Harmonization, Extraction, and Normalization for Analytics (ATHENA) online browser. Lead analysts from each nation then confirmed or added to the mappings identified. These mappings were then used to report AEIs in a common format. We reported rates for windows of 0-2 and 3-28 days postvaccine every 28 days. RESULTS: We listed the mappings between Read v2, SNOMED CT, ICD-10, and dm+d. For vaccine exposure, we found clear mapping from OMOP to our clinical terminologies, though dm+d had codes not listed by OMOP at the time of searching. We found a list of CVST and anaphylaxis codes. For CVST, we had to use a broader cerebral venous thrombosis conceptual approach to include Read v2. We identified 56 SNOMED CT codes, of which we selected 47 (84%), and 15 Read v2 codes. For anaphylaxis, our refined search identified 60 SNOMED CT codes and 9 Read v2 codes, of which we selected 10 (17%) and 4 (44%), respectively, to include in our repeated cross-sectional studies. CONCLUSIONS: This approach enables the use of mappings to different terminologies within the OMOP CDM without the need to catalogue an entire database. However, Read v2 has less granular concepts than some terminologies, such as SNOMED CT. Additionally, the OMOP CDM cannot compensate for limitations in the clinical coding system. Neither Read v2 nor ICD-10 is sufficiently granular to enable CVST to be specifically flagged. Hence, any pooled analysis will have to be at the less specific level of cerebrovascular venous thrombosis. Overall, the mappings within this CDM are useful, and our method could be used for rapid collaborations where there are only a limited number of concepts to pool.

The Effect of the COVID-19 Pandemic on Glycemic Monitoring and Other Processes of Care for Type 2 Diabetes: Protocol for a Retrospective Cohort Study.

BACKGROUND: Social distancing and other nonpharmaceutical interventions to reduce the spread of COVID-19 infection in the United Kingdom have led to substantial changes in delivering ongoing care for patients with chronic conditions, including type 2 diabetes mellitus (T2DM). Clinical guidelines for the management and prevention of complications for people with T2DM delivered in primary care services advise routine annual reviews and were developed when face-to-face consultations were the norm. The shift in consultations from face-to-face to remote consultations caused a reduction in direct clinical contact and may impact the process of care for people with T2DM. OBJECTIVE: The aim of this study is to explore the impact of the COVID-19 pandemic's first year on the monitoring of people with T2DM using routine annual reviews from a national primary care perspective in England. METHODS: A retrospective cohort study of adults with T2DM will be performed using routinely collected primary care data from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). We will describe the change in the rate of monitoring of hemoglobin A1c (HbA1c) between the first year of the COVID-19 pandemic (2020) and the preceding year (2019). We will also report any change in the eight checks that make up the components of these reviews. The change in HbA1c monitoring rates will be determined using a multilevel logistic regression model, adjusting for patient and practice characteristics, and similarly, the change in a composite measure of the completeness of all eight checks will be modeled using ordinal regression. The models will be adjusted for the following patient-level variables: age, gender, socioeconomic status, ethnicity, COVID-19 shielding status, duration of diabetes, and comorbidities. The model will also be adjusted for the following practice-level variables: urban versus rural, practice size, Quality and Outcomes Framework achievement, the National Health Service region, and the proportion of face-to-face consultations. Ethical approval was provided by the University of Oxford Medical Sciences Interdivisional Research Ethics Committee (September 2, 2021, reference R77306/RE001). RESULTS: The analysis of the data extract will include 3.96 million patients with T2DM across 700 practices, which is 6% of the available Oxford-RCGP RSC adult population. The preliminary results will be submitted to a conference under the domain of primary care. The resulting publication will be submitted to a peer-reviewed journal on diabetes and endocrinology. CONCLUSIONS: The COVID-19 pandemic has impacted the delivery of care, but little is known about the process of caring for people with T2DM. This study will report the impact of the COVID-19 pandemic on these processes of care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35971.

Mortality in People with Type 2 Diabetes Following SARS-CoV-2 Infection: A Population Level Analysis of Potential Risk Factors.

INTRODUCTION: Research is ongoing to increase our understanding of how much a previous diagnosis of type 2 diabetes mellitus (T2DM) affects someone's risk of becoming seriously unwell following a COVID-19 infection. In this study we set out to determine the relative likelihood of death following COVID-19 infection in people with T2DM when compared to those without T2DM. This was conducted as an urban population study and based in the UK. METHODS: Analysis of electronic health record data was performed relating to people living in the Greater Manchester conurbation (population 2.82 million) who had a recorded diagnosis of T2DM and subsequent COVID-19 confirmed infection. Each individual with T2DM (n = 13,807) was matched with three COVID-19-infected non-diabetes controls (n = 39,583). Data were extracted from the Greater Manchester Care Record (GMCR) database for the period 1 January 2020 to 30 June 2021. Social disadvantage was assessed through Townsend scores. Death rates were compared in people with T2DM to their respective non-diabetes controls; potential predictive factors influencing the relative likelihood of admission were ascertained using univariable and multivariable logistic regression. RESULTS: For individuals with T2DM, their mortality rate after a COVID-19 positive test was 7.7% vs 6.0% in matched controls; the relative risk (RR) of death was 1.28. From univariate analysis performed within the group of individuals with T2DM, the likelihood of death following a COVID-19 recorded infection was lower in people taking metformin, a sodium-glucose cotransporter 2 inhibitor (SGLT2i) or a glucagon-like peptide 1 (GLP-1) agonist. Estimated glomerular filtration rate (eGFR) and hypertension were associated with increased mortality and had odds ratios of 0.96 (95% confidence interval 0.96-0.97) and 1.92 (95% confidence interval 1.68-2.20), respectively. Likelihood of death following a COVID-19 infection was also higher in those people with a diagnosis of chronic obstructive pulmonary disease (COPD) or severe enduring mental illness but not with asthma, and in people taking aspirin/clopidogrel/insulin. Smoking in people with T2DM significantly increased mortality rate (odds ratio of 1.46; 95% confidence interval 1.29-1.65). In a combined analysis of patients with T2DM and controls, multiple regression modelling indicated that the factors independently relating to a higher likelihood of death (accounting for 26% of variance) were T2DM, age, male gender and social deprivation (higher Townsend score). CONCLUSION: Following confirmed infection with COVID-19 a number of factors are associated with mortality in individuals with T2DM. Prescription of metformin, SGLT2is or GLP-1 agonists and non-smoking status appeared to be associated with a reduced the risk of death for people with T2DM. Age, male sex and social disadvantage are associated with an increased risk of death.

An evaluation of the mental health impact of SARS-CoV-2 on patients, general public and healthcare professionals: A systematic review and meta-analysis.

BACKGROUND: The global impact of COVID-19 pandemic continues to affect the lives of billions of people with recurrent waves. Healthcare systems are struggling to manage pre-existing patient care and recurring covid-19 demands. As a result, we evaluated the mental health impact using systematic review and meta-analysis. METHODS: A comprehensive search was undertaken from April 2020 to 22nd January 2021 using multiple electronic databases. A systematic review protocol was developed and published on PROSPERO registration; CRD42020181481. A random-effects model was used to compute pooled estimates of anxiety, depression, PTSD, insomnia and suicidal thoughts. FINDINGS: Our search yielded 11,295 studies and of those 287 met the inclusion criteria. The meta-analysis of 206 studies revealed minimal differences in prevalence of anxiety, depression, and PTSD among HCPs compared with the public during the pandemic but higher prevalence of suicidal thoughts/ideation or self-harm (11% vs 5.8%) and lower prevalence of wellbeing (28.2% vs 52.6%) among the public compared to HCPs. INTERPRETATION: The pandemic has led to a high mental health burden especially amongst HCPs and higher suicidal ideation and lower wellbeing in general public which warrants further investigation and management globally. These findings highlight an emerging critical public health issue that requires urgent solutions.

History for some or lesson for all? A systematic review and meta-analysis on the immediate and long-term mental health impact of the 2002-2003 Severe Acute Respiratory Syndrome (SARS) outbreak.

BACKGROUND: The aims of this systematic review and meta-analysis are to examine the prevalence of adverse mental health outcomes, both short-term and long-term, among SARS patients, healthcare workers and the general public of SARS-affected regions, and to examine the protective and risk factors associated with these mental health outcomes. METHODS: We conducted a systematic search of the literature using databases such as Medline, Pubmed, Embase, PsycInfo, Web of Science Core Collection, CNKI, the National Central Library Online Catalog and dissertation databases to identify studies in the English or Chinese language published between January 2003 to May 2020 which reported psychological distress and mental health morbidities among SARS patients, healthcare workers, and the general public in regions with major SARS outbreaks. RESULTS: The literature search yielded 6984 titles. Screening resulted in 80 papers for the review, 35 of which were included in the meta-analysis. The prevalence of post-recovery probable or clinician-diagnosed anxiety disorder, depressive disorder, and post-traumatic stress disorder (PTSD) among SARS survivors were 19, 20 and 28%, respectively. The prevalence of these outcomes among studies conducted within and beyond 6 months post-discharge was not significantly different. Certain aspects of mental health-related quality of life measures among SARS survivors remained impaired beyond 6 months post-discharge. The prevalence of probable depressive disorder and PTSD among healthcare workers post-SARS were 12 and 11%, respectively. The general public had increased anxiety levels during SARS, but whether there was a clinically significant population-wide mental health impact remained inconclusive. Narrative synthesis revealed occupational exposure to SARS patients and perceived stigmatisation to be risk factors for adverse mental health outcomes among healthcare workers, although causality could not be determined due to the limitations of the studies. CONCLUSIONS: The chronicity of psychiatric morbidities among SARS survivors should alert us to the potential long-term mental health complications of covid-19 patients. Healthcare workers working in high-risk venues should be given adequate mental health support. Stigmatisation against patients and healthcare workers should be explored and addressed. The significant risk of bias and high degree of heterogeneity among included studies limited the certainty of the body of evidence of the review.

Rapid commentary: Ethical implications for clinical trialists and patients associated with COVID-19 research.

Pandemics disrupt clinical trials worldwide, with lasting effects on research. It can severely impact clinical trialists ability to conduct safe and ethically uncompromised trials. Hence, the mounting pressure results in ethically and morally distressing decisions faced by clinical trial professionals during pandemic situations. Whilst clinical trialists attempt to think about preparedness and responses during a pandemic, the need to have an ethical framework that has real-world applicability is imperative. Pandemics are a challenging time for all, however, the safety and access to support for clinical trialists and patients within clinical trials should be at the forefront for their organisations and the government.

COVID-19 and Black, Asian, and Minority Ethnic Communities: A Complex Relationship Without Just Cause.

Emerging evidence has indicated a negative and disproportionate impact of COVID-19 on Black, Asian, and minority ethnic (BAME) communities. Previous studies have already reported that biological and social risk factors increase disease susceptibility, particularly in BAME communities. Despite frontline workers in ethnic minority communities in the United Kingdom's National Health Service attempting to quell the pandemic, disproportionate numbers of BAME physicians and other health care workers have died of COVID-19. This unprecedented situation highlights ethical and moral implications, which could further augment the impact of the pandemic on their mental health. While the government attempts to mitigate the rate of virus transmission, certain key factors inadvertently augment the negative impact of the pandemic on the mental health and general well-being of BAME communities. This study examined the available literature to explore the association between, and the wider impact of, COVID-19 on BAME communities. Furthermore, this study aims to raise awareness and provide a deeper insight into current scientific discussions.