RESUMO
The severe acute respiratory syndrome Coronavirus 2 (SARS COV-2) caused a global pandemic of COVID-19. Most of people affected are admitted to hospital with various grades of ADRS. A small proportion of these patients requires intensive care unit management and treatment. However not all of them survive. This study aims to describe the epidemiological and clinical characteristics of patients admitted to the intensive care units in Panama main hospital in the first six months of pandemic with available information. Special focus has been oriented to blood and respiratory biomarkers to correlate with survivors and non-survivors. Our results show that patients between 56-75 years old, with hypertension, obesity, and diabetes comorbid conditions are more likely to die in intensive care units. Regarding the PaFi ratio, we observed a greater proportion of non-survivor with values less than 200. The triglycerides, urea nitrogen, creatinine and procalcitonin levels resulted significantly higher in those non survivors. During clinical management, half of patient that were administered Tocilizumab did not survived. These results support the notion that age, comorbidities as well as therapeutic management of patient in intensive care units contribute to the final outcome. We recommend reinforcing patient care strategy, especially in those patients with clinical conditions that favor fatal outcomes.
RESUMO
ObjectiveThe COVID-19 pandemic was accompanied by varying movement restriction measures across populations worldwide. These restrictions altered daily activities at all levels, including food access and intake, as well as psychological feelings during lockdown. The main objective of the present study was to evaluate health, and nutrition behaviors during confinement during the first wave of the COVID-19 pandemic. MethodWe conducted a cross-sectional study using an online survey for data collection; a total of 1,561 surveys were validated. ResultsThe majority of respondents were women (74.2%) between 18 and 49 years old. Among the respondents, 83.3% indicated a university education level, and 49.9% reported a monthly family income equal to or less than 1,000 USD. In addition, more than 50% self-reported overweight or obesity. Responses were analyzed using k-means algorithms to identify food intake patterns; we found three patterns: a healthy food intake pattern, a non-healthy food intake pattern and a mixed food intake pattern. The respondents with healthy food intake and non-healthy food intake patterns reported better socioeconomic conditions. Individuals classified as having mixed food intake patterns had lower incomes, less education and higher unemployment rates. Regarding emotions, we found that women experienced more negative emotions, such as fear, worry and anxiety, during the lockdown period. ConclusionsTaken together, these results suggest that the mobility restriction measures imposed during the COVID-19 pandemic affected food intake patterns by exacerbating existing inequalities. We believe that directing resources towards strategies with the greatest positive impacts on public health remains key, especially in critical situations such as the COVID-19 pandemic.
RESUMO
COVID-19 is the name of the acute respiratory disease caused by the new coronavirus SARS-CoV-2, a close relative of those that caused the severe outbreaks of SARS and MERS several years ago. Since first appearance on December of 2019, the COVID-19 pandemic has cause extremely high levels of mortality, morbidity, global economic breakdown and the consequent human suffering. While vaccination efforts are not extensive and rapid enough, the main tools to keep the virus under control are still keeping physical distancing, reinforce personal hygiene measures, using masks and early diagnosis of virus infected persons, either symptomatic or not. The main diagnostic test for the confirmation of symptomatic individuals is the detection of viral RNA by reverse transcriptase - quantitative real time PCR (RT-PCR). Additionally, serology techniques, such as ELISA are extremely useful to measure the antibodies generated in humans after virus contact, as well as the direct presence of viral antigens. In this study we aim to assemble and evaluate four ELISAs assays to measure the presence of IgG or IgM specific for the viral Spike protein in COVID-19 patients, using either the full recombinant SARS-CoV-2 Spike protein or the fragment corresponding to the receptor binding domain. As a control, we also analyzed a group of prepandemic serum samples obtained before 2017. Strong reactivity was observed against both antigens. A few prepandemic samples displayed high OD values, suggesting the possibility of some crossreactivity. All four assays show very good repeatability, both intra- and inter-assay; however, no clear relationship could be detected between positivity and time of sample collection for serology. Receiver operating characteristic analysis allowed the definition of cutoffs and evaluation of performance for each ELISA by estimation of the area under the curve. This performance parameter was high for all tests (AUC range: 0.98-0.995). Multiple comparisons between tests revealed no significant difference between each other (P values: 0.24-0.95). Our results show that both antigens are very effective to reveal both specific IgG and IgM antibodies, with high sensitivity (range 0.929-0.99) and specificity (range 0.933-0.977). The estimated congruence with the RT-PCR test, as estimated by Cohens Kappa, indicates a high agreement in all cases (range 0.874-0.937). This test will allow health authorities to have a new tool to estimate seroprevalence, and to manage and improve the serious sanitary situation created by this virus.
RESUMO
Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic, which has reached 28 million cases worldwide in eight months. The serological detection of antibodies against the virus will play a pivotal role in complementing molecular tests to improve diagnostic accuracy, contact tracing, vaccine efficacy testing and seroprevalence surveillance. Here, we aimed first to evaluate a lateral flow assays ability to identify specific IgM and IgG antibodies against SARS-CoV-2 and second, to report the seroprevalence of these antibodies among health care workers and healthy volunteer blood donors in Panama. We recruited study participants between April 30th and July 7th, 2020. For the test validation and performance evaluation, we analyzed serum samples from participants with clinical symptoms and confirmed positive RT-PCR for SARS-CoV-2, participants with other confirmed infectious diseases, and a set of pre-pandemic serum samples. We used two by two table analysis to determine the test sensitivity and specificity as well as the kappa agreement value with a 95% confidence interval. Then, we used the lateral flow assay to determine seroprevalence among serum samples from COVID-19 patients, potentially exposed health care workers, and healthy volunteer donors. Our results show this assay reached a positive percent agreement of 97.2% (95% CI 84.2-100.0%) for detecting both IgM and IgG. The assay showed a kappa of 0.898 (95%CI 0.811-0.985) and 0.918 (95% CI 0.839-0.997) for IgM and IgG, respectively. The evaluation of serum samples from hospitalized COVID-19 patients indicates a correlation between test sensitivity and the number of days since symptom onset; the highest positive percent agreement (87% (95% CI 67.0-96.3%)) was observed at [≥]15 days post-symptom onset. We found an overall antibody seroprevalence of 11.6% (95% CI 8.5-15.8%) among both health care workers and healthy blood donors. Our findings suggest this lateral flow assay could contribute significantly to implementing seroprevalence testing in locations with active community transmission of SARS-CoV-2.
