Background and objectives It is essential to know the proportion of health care workers (HCW) who are COVID 19 positive, as well as the severity and mortality among them. Methods This systematic review was performed according to the Preferred Reporting Items for Systematic review and meta-analysis. Databases including PubMed, EMBASE and Web of Science were searched from December-31, 2019 to April-23, 2020. The search was limited to the studies that reported the data on the number of COVID-19 positive healthcare workers, among the COVID-19 positive patients. Case reports, duplicate publications, reviews, and family-based studies were excluded. The methodological quality of studies was assessed by the Appraisal tool for Cross-Sectional Studies (AXIS) tool. Results In this systematic review and meta-analysis, we pooled eleven studies to investigate the above factors. The overall proportion of HCW who were SARS-CoV-2 positive among all COVID-19 patients was 10.1% (95%CI: 5.3–14.9). This proportion varied according to the country of study i.e. China (7 studies) - 4.2%, 95%CI:2.4–6.0; United States (3 studies) – 17.8%, 95%CI:7.5–28.0; and Italy (1 study) – 9.0%, 95%CI:8.6–9.4. The incidence of severe or critical disease in HCW (9.9%, 95%CI:0.8–18.9) was significantly lower ( p < 0.001) than the incidence of severe or critical disease in all COVID-19 positive patients (29.4%, 95%CI:18.6–40.2). Similarly, the mortality among HCW (0.3%, 95%CI:0.2–0.4) was also significantly lower (p < 0.001) as compared to that of all patients (2.3%, 95%CI:2.2–2.4). Conclusion Health care workers who are COVID-19 positive constituted a significant proportion of all COVID-19 patients; but the severity and mortality were lower among them.

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abbreviatioNs AUC = area under the curve; BBB = blood-brain barrier; DAI = diffuse axonal injury; Eg = estrogen; FIM = functional independence measure; GCS = Glasgow Coma Scale; GFAP = glial fibrillary acidic protein; GOS = Glasgow Outcome Scale; ICP = intracranial pressure; IL = interleukin; IQR = interquartile range; NGF = nerve growth factor; NSE = neuron-specific enolase; Pg = progesterone; ROC = receiver operating characteristic; sTBI = severe traumatic brain injury; TNF-a = tumor necrosis factor-a. Pg]). This analysis was performed using the sandwich enzyme-linked immunosorbent assay technique at admission and 7 days later for 86 patients, irrespective of assigned group. The long-term predictive values of serum biomarkers for dichotomized Glasgow Outcome Scale (GOS) score, functional independence measure, and survival status at 6 and 12 months were analyzed using an adjusted binary logistic regression model and receiver operating characteristic curve. results A favorable GOS score (4-5) at 1 year was predicted by higher admission IL-6 (above 108.36 pg/ml; area under the curve [AUC] 0.69, sensitivity 52%, and specificity 78.6%) and Day 7 Pg levels (above 3.15 ng/ml; AUC 0.79, sensitivity 70%, and specificity 92.9%). An unfavorable GOS score (1-3) at 1 year was predicted by higher Day 7 GFAP levels (above 9.50 ng/ml; AUC 0.82, sensitivity 78.6%, and specificity 82.4%). Survivors at 1 year had significantly higher Day 7 Pg levels (above 3.15 ng/ml; AUC 0.78, sensitivity 66.7%, and specificity 90.9%). Nonsurvivors at 1 year had significantly higher Day 7 GFAP serum levels (above 11.14 ng/ml; AUC 0.81, sensitivity 81.8%, and specificity 88.9%) and Day 7 IL-6 serum levels (above 71.26 pg/ml; AUC 0.87, sensitivity 81.8%, and specificity 87%). In multivariate logistic regression analysis, independent predictors of outcome at 1 year were serum levels of Day 7 Pg (favorable GOS-OR 3.24, CI 1.5-7, p = 0.003; and favorable survival-OR 2, CI 1.2-3.5, p = 0.01); admission IL-6 (favorable GOS-OR 1.04, CI 1.00-1.08, p = 0.04); and Day 7 GFAP p = 0.01; p = 0.01). coNclusioNs Serial Pg, GFAP, and IL-6 monitoring could aid in prognosticating outcomes in patients with acute sTBI. A cause and effect relationship or a mere association of these biomarkers to outcome needs to be further studied for better understanding of the pathophysiology of sTBI and for choosing potential therapeutic targets.Clinical trial registration no

BackgroundThe prevalence of Coronary Atherosclerotic Heart Disease (CASHD) is increasing in India. Several modifiable risk factors contribute directly to this disease burden. Public knowledge of such risk factors among the urban Indian population is largely unknown. This investigation attempts to quantify knowledge of modifiable risk factors of CASHD as sampled among an Indian population at a large metropolitan hospital.MethodsA hospital-based, cross sectional study was conducted at All India Institute of Medical Sciences (AIIMS), a major tertiary care hospital in New Delhi, India. Participants (n = 217) recruited from patient waiting areas in the emergency room were provided with standardized questionnaires to assess their knowledge of modifiable risk factors of CASHD. The risk factors specifically included smoking, hypertension, elevated cholesterol levels, diabetes mellitus and obesity. Identifying 3 or less risk factors was regarded as a poor knowledge level, whereas identifying 4 or more risk factors was regarded as a good knowledge level. A multiple logistic regression model was used to isolate independent demographic markers predictive of a participant's level of knowledge.Results41% of the sample surveyed had a good level of knowledge. 68%, 72%, 73% and 57% of the population identified smoking, obesity, hypertension, and high cholesterol correctly, respectively. 30% identified diabetes mellitus as a modifiable risk factor of CASHD. In multiple logistic regression analysis independent demographic predictors of a good knowledge level with a statistically significant (p < 0.05) adjusted odds ratio (aOR) were: routine exercise of moderate intensity, aOR 8.41 (compared to infrequent or no exercise), no history of smoking, aOR 8.25, and former smokers, aOR 48.28 (compared to current smokers). Although statistically insignificant, a trend towards a good knowledge level was associated with higher levels of education.ConclusionAn Indian population in a hospital setting shows a lack of knowledge pertaining to modifiable risk factors of CASHD. By isolating demographic predictors of poor knowledge, such as current smokers and persons who do not exercise regularly, educational interventions can be effectively targeted and implemented as primary and secondary prevention strategies to reduce the burden of CASHD in India.

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