Colchicine anti-inflammatory therapy for non-intensive care unit hospitalized COVID-19 patients: results from a pilot open-label, randomized controlled clinical trial.

Systemic inflammation is a hallmark of severe coronavirus disease-19 (COVID-19). Anti-inflammatory therapy is considered crucial to modulate the hyperinflammatory response (cytokine storm) in hospitalized COVID-19 patients. There is currently no specific, conclusively proven, cost-efficient, and worldwide available anti-inflammatory therapy available to treat COVID-19 patients with cytokine storm. The present study aimed to investigate the treatment benefit of oral colchicine for hospitalized COVID-19 patients with suspected cytokine storm. Colchicine is an approved drug and possesses multiple anti-inflammatory mechanisms. This was a pilot, open-label randomized controlled clinical trial comparing standard of care (SOC) plus oral colchicine (colchicine arm) vs. SOC alone (control arm) in non-ICU hospitalized COVID-19 patients with suspected cytokine storm. Colchicine treatment was initiated within first 48 hours of admission delivered at 1.5 mg loading dose, followed by 0.5 mg b.i.d. for next 6 days and 0.5 mg q.d. for the second week. A total of 96 patients were randomly allocated to the colchicine (n=48) and control groups (n=48). Both colchicine and control group patients experienced similar clinical outcomes by day 14 of hospitalization. Treatment outcome by day 14 in colchicine vs control arm: recovered and discharged alive: 36 (75.0%) vs. 37 (77.1%), remain admitted after 14-days: 4 (8.3%) vs. 5 (10.4%), ICU transferred: 4 (8.3%) vs. 3 (6.3%), and mortality: 4 (8.3%) vs. 3 (6.3%). The speed of improvement of COVID-19 acute symptoms including shortness of breath, fever, cough, the need of supplementary oxygen, and oxygen saturation level, was almost identical in the two groups. Length of hospitalization was on average 1.5 day shorter in the colchicine group. There was no evidence for a difference between the two groups in the follow-up serum levels of inflammatory biomarkers including C-reactive protein (CRP), D-dimer, lactate dehydrogenase (LDH), ferritin, interleukin-6 (IL-6), high-sensitivity troponin T (hs-TnT) and N-terminal pro b-type natriuretic peptide (NT pro-BNP). According to the results of our study, oral colchicine does not appear to show clinical benefits in non-ICU hospitalized COVID-19 patients with suspected cytokine storm. It is possible that the anti-inflammatory pathways of colchicine are not crucially involved in the pathogenesis of COVID-19.

PSYCHOLOGICAL IMPACT OF COVID-19 PANDEMIC ON HEALTH CARE WORKERS OF TERTIARY CARE HOSPITALS

Healthcare workers (HCWs) are at increased risk of mental health issues when faced with the challenges associated with pandemics. This study was conducted to assess the psychological impact of pandemic o n HCWs working in tertiary care hospitals of Khyber-Pakhtunkhwa province of Pakistan. This cross-sectional study was conducted between April & June 2020. By convenience sampling an electronic form of Goldberg General Health Questionnaire was distributed among HCWs of the private sector and public tertiary care hospitals. Data were analyzed using SPSS version 22. Inferential analysis was done. The significant level was considered at p=< 0. 05. Total of 186 HCWs among which 105 (56.5%) males and 81 (43.5%) females participated in the survey, a mean age of 37.6 +/- 9.28 years. The highest prevalence was found for social dysfunction 184 (97.8%) followed by somatization, 169 (92.8%). Significance of difference was found between age group and anxiety (p=0.018), specialty of HCWs with somatization and social dysfunction (p=0.041 and 0.037 respectively). Pandemic poses a significant risk for the mental health of HCWs. During pandemics at its peak, proper mental health support program, personal and family protection assurance is highly recommended for provision of quality care by HCWs.

Isaric 4c Mortality Score As A Predictor Of In-Hospital Mortality In Covid-19 Patients Admitted In Ayub Teaching Hospital During First Wave Of The Pandemic

BACKGROUND: Many factors have been identified which can predict severe outcomes and mortality in hospitalized patients of COVID-19. This study was conducted with the objective of finding out the association of various clinical and laboratory parameters as used by International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO)- ISARIC/WHO 4C Mortality score in predicting high risk patients of COVID-19. Ascertaining the parameters would help in triage of patients of severe disease at the outset, and shall prove beneficial in improving the standard of care. METHODS: This cross-sectional study was carried out in COVID-19 Department of Ayub Teaching Hospital, Abbottabad. All COVID-19 patients admitted from 15th April to 15th July 2020 were included. RESULTS: A total of 347 patients were included in the study. The mean age was 56.46±15.44 years. Male patients were 225 (65%) and female 122 (35%). Diabetes (36%) was the most common co-morbidity, followed by hypertension (30.8%). Two hundred & six (63.8%) patients recovered and 117 (36.2%) patients died. Shortness of breath (80%), fever (79%) and cough (65%) were the most common presenting symptoms. Patients admitted with a 4C Mortality score of 0-3 (Low Risk Category), the patients who recovered were 36 (90%) and those who died were 4 (10.0%). In patients admitted with a 4C Mortality score of more than 14 (Very High-Risk Category), the number of patients who recovered was 1 (20%), and those who died were 4 (80%). The difference in mortality among the categories was statistically significant (p<0.001). Hypertension was a risk factor for death in patients of COVID-19 (Odds ratio=1.24, 95% CI [0.76-2.01]). Lymphopenia was not associated with statistically significant increased risk for mortality. CONCLUSIONS: The ISARIC 4C mortality score can be used for stratifying and predicting mortality in COVID-19 patients on arrival in hospital. We propose that it should be used in every patient of COVID-19 presenting to the hospital. Those falling in Low and Intermediate Risk Category should be managed in ward level. Those falling in High and Very High Category should be admitted in HDU/ICU with aggressive treatment from the start.

Estimating The Possible Role Of Testing Capacity And Social Distancing In Predicting The Growth Rate Of Daily Covid-19 Cases

Background: The purpose of this study was to estimate the effect of social distancing (days since the imposition of a lock-down) and the number of daily tests conducted per million population on the daily growth rate of COVID-19 cases. Methods: After excluding the first 30 days since the announcement of an index case in a country, relevant data for the next forty days was collected from four countries: Belgium, Italy, South Korea and United Kingdom. Two online databases: Our World in Data and worldometer were used for the collection of data which included the number of new COVID-19 cases and the number of tests conducted on a given day. The acquired figures were transformed into per million population of the given country. The growth rate of daily COVID-19 cases was derived and was used as the regress and in a multiple linear regression with the number of tests per million population per day and the number of days since a lock-down was imposed as the regressors. Results: It was found that the growth rate of daily COVID-19 cases decreased by .051% when the number of daily tests conducted per million population increased by 1. A .532% decrease in the growth rate of daily COVID-19 cases was observed with each passing day of a lock-down, which essentially represented the most effective form of social distancing. A significant regression was calculated (F (2, 155) = 35.191, p=.014), with an R2 of .054. Neither the daily number of tests conducted per million population nor the number of days of maintaining social distancing (lock-down) was individually significant contributors to the prediction of the growth rate of daily COVID-19 cases (p=.267 and p=.554 respectively). Conclusion: An extensive and rapid increase in the daily number of testing capacity and maintaining social distancing can decrease the growth rate of daily COVID-19 cases. Depending on the availability of the required resources, timely implementation of these measures can lead to better outcomes for a given population.