RESUMO
The wildfire-like spread of COVID-19, caused by severe acute respiratory syndrome-associated coronavirus-2, has resulted in a pandemic that has put unprecedented stress on the world's healthcare systems and caused varying severities of socio-economic damage. As there are no specific treatments to combat the virus, current approaches to overcome the crisis have mainly revolved around vaccination efforts, preventing human-to-human transmission through enforcement of lockdowns and repurposing of drugs. To efficiently facilitate the measures implemented by governments, rapid and accurate diagnosis of the disease is vital. Reverse-transcription polymerase chain reaction and computed tomography have been the standard procedures to diagnose and evaluate COVID-19. However, disadvantages, including the necessity of specialized equipment and trained personnel, the high financial cost of operation and the emergence of false negatives, have hindered their application in high-demand and resource-limited sites. Nanoparticle-based methods of diagnosis have been previously reported to provide precise results within short periods of time. Such methods have been studied in previous outbreaks of coronaviruses, including severe acute respiratory syndrome-associated coronavirus and middle east respiratory syndrome coronavirus. Given the need for rapid diagnostic techniques, this review discusses nanoparticle use in detecting the aforementioned coronaviruses and the recent severe acute respiratory syndrome-associated coronavirus-2 to highlight approaches that could potentially be used during the COVID-19 pandemic.
RESUMO
Objective There had been an observed increase in the prevalence of depression as well as many chronic conditions of comorbidity among the elderly population of Ireland above the age of 50. The relationship between different prominent conditions of comorbidity and depression scores amongst older adult men in Ireland was sought to be examined and explored. Methods A cross-sectional analysis of data from wave 1 of The Irish Longitudinal Study on Aging (TILDA) had been used for statistical analysis, which served to be the representative cohort study sample of elderly adults living in Ireland aged 50 and older. Summary statistics (cross-tabulation, t-test, analysis of variance/ANOVA and odds ratio) were used to explore the relationship between depression scores and different conditions of comorbidity. Results Results were drawn from the three different tests conducted; cross-tabulation, t-test, and analysis of variance/ANOVA. Cross-tabulation served to provide the total population of men who suffered from depression (CES-D score ≥ 16), which totaled 123 (1.4%) of the entire 8,504 available candidates. Of the participants that met the criteria for having a significant risk of clinical depression along with an accompanying chronic illness odds ratio (OR) had been calculated. All but one of the conditions yielded a significant increase in OR between having a chronic condition and depression; with the exception of chronic lung disease. Congestive heart failure demonstrated the highest OR of 4.40 (CI 95% 1.77-10.95), followed by arthritis, diabetes and cancer. Subsequent t-tests used to construct an ANOVA then illustrated the mean CES-D score for males suffering from one of the five concomitant illnesses selected (congestive heart failure, chronic lung disease, arthritis, cancer, and diabetes) as well as those free of the selected diseases of the study, with a total count of 2,117. All results had been deemed to be significant with p-values < 0.05, with men suffering from congestive heart failure having the highest mean score of 7.28 (n=39). Those who do not suffer from any of the five conditions reported the lowest scores and also accounted for the largest population group with 3.88 and 1,387, respectively. Conclusions Consistent and significant findings of elderly men suffering from a chronic condition of comorbidity demonstrated having elevated OR and CES-D scores in comparison to those who are disease-free. The findings of this study can be used to evaluate alternative preventative management of chronic diseases of comorbidity in order to improve the depression scores of patients.
