scholarly journals Demographic Variations of MERS-CoV Infection among Suspected and Confirmed Cases: An Epidemiological Analysis of Laboratory-Based Data from Riyadh Regional Laboratory

2020 ◽  
Vol 2020 ◽  
pp. 1-6 ◽  
Author(s):  
Asmaa Altamimi ◽  
Raghib Abu-Saris ◽  
Ashraf El-Metwally ◽  
Taghreed Alaifan ◽  
Aref Alamri
Keyword(s):  
Risk Factors ◽  
Saudi Arabia ◽  
Epidemiological Analysis ◽  
Future Studies ◽  
Clinical Presentations ◽  
The Subject ◽  
Demographic Risk ◽  
Demographic Risk Factors ◽  
Real Challenge ◽  
Future Plans

Introduction. Middle East respiratory syndrome coronavirus was first recognized in September 2012 in Saudi Arabia. The clinical presentations of MERS and non-MERS SARI are often similar. Therefore, the identification of suspected cases that may have higher chances of being diagnosed as cases of MERS-CoV is essential. However, the real challenge is to flag these patients through some demographic markers. The nature of these markers has not previously been investigated in Saudi Arabia, and hence, this study aims to identify them. Methods. It was a surveillance system-based study, for which data from a total of 23,646 suspected patients in Riyadh and Al Qassim regions were analyzed from January 2017 until December 2017 to estimate the prevalence of MERS-CoV among suspected cases and to determine potential demographic risk factors related to the confirmation of the diagnosis. Results. Of 23,646 suspected cases, 119 (0.5%) were confirmed by laboratory results. These confirmed cases (67.2% of which were males) had a mean age of 43.23 years (SD ± 22.8). Around 42.2% of the confirmed cases were aged between 41 and 60 years and about 47% of confirmed cases had their suspected specimen tested in the summer. The study identified three significant and independent predictors for confirmation of the disease: an age between 41 and 60 years, male gender, and summer season admission. Conclusion. The study provides evidence that the MERS-CoV epidemic in the subject regions has specific characteristics that might help future plans for the prevention and management of such a contagious disease. Future studies should aim to confirm such findings in other regions of Saudi Arabia as well and explore potential preventable risk factors.

scholarly journals Demographic risk factors for extra-pulmonary tuberculosis among adolescents and adults in Saudi Arabia

PLoS ONE ◽  
2019 ◽  
Vol 14 (3) ◽  
pp. e0213846 ◽  
Author(s):  
Hawra Al-Ghafli ◽  
Bright Varghese ◽  
Mushira Enani ◽  
Abdulrahman Alrajhi ◽  
Sameera Al Johani ◽  
...  
Keyword(s):  
Risk Factors ◽  
Saudi Arabia ◽  
Pulmonary Tuberculosis ◽  
Extra Pulmonary Tuberculosis ◽  
Adolescents And Adults ◽  
Extra Pulmonary ◽  
Demographic Risk ◽  
Demographic Risk Factors

Clinical and Demographic Risk Factors for COVID-19 during Delivery Hospitalizations in New York City

2021 ◽  
Author(s):  
Desmond Sutton ◽  
Timothy Wen ◽  
Anna P. Staniczenko ◽  
Yongmei Huang ◽  
Maria Andrikopoulou ◽  
...  
Keyword(s):  
Risk Factors ◽  
New York ◽  
New York City ◽  
Logistic Regression ◽  
York City ◽  
Demographic Data ◽  
Outcome Data ◽  
Demographic Risk ◽  
Demographic Risk Factors ◽  
Zip Code

Objective This study was aimed to review 4 weeks of universal novel coronavirus disease 2019 (COVID-19) screening among delivery hospitalizations, at two hospitals in March and April 2020 in New York City, to compare outcomes between patients based on COVID-19 status and to determine whether demographic risk factors and symptoms predicted screening positive for COVID-19. Study Design This retrospective cohort study evaluated all patients admitted for delivery from March 22 to April 18, 2020, at two New York City hospitals. Obstetrical and neonatal outcomes were collected. The relationship between COVID-19 and demographic, clinical, and maternal and neonatal outcome data was evaluated. Demographic data included the number of COVID-19 cases ascertained by ZIP code of residence. Adjusted logistic regression models were performed to determine predictability of demographic risk factors for COVID-19. Results Of 454 women delivered, 79 (17%) had COVID-19. Of those, 27.9% (n = 22) had symptoms such as cough (13.9%), fever (10.1%), chest pain (5.1%), and myalgia (5.1%). While women with COVID-19 were more likely to live in the ZIP codes quartile with the most cases (47 vs. 41%) and less likely to live in the ZIP code quartile with the fewest cases (6 vs. 14%), these comparisons were not statistically significant (p = 0.18). Women with COVID-19 were less likely to have a vaginal delivery (55.2 vs. 51.9%, p = 0.04) and had a significantly longer postpartum length of stay with cesarean (2.00 vs. 2.67days, p < 0.01). COVID-19 was associated with higher risk for diagnoses of chorioamnionitis and pneumonia and fevers without a focal diagnosis. In adjusted analyses, including demographic factors, logistic regression demonstrated a c-statistic of 0.71 (95% confidence interval [CI]: 0.69, 0.80). Conclusion COVID-19 symptoms were present in a minority of COVID-19-positive women admitted for delivery. Significant differences in obstetrical outcomes were found. While demographic risk factors demonstrated acceptable discrimination, risk prediction does not capture a significant portion of COVID-19-positive patients. Key Points

scholarly journals Iron deficiency in Massachusetts communities: Socioeconomic and demographic risk factors among children.

1996 ◽  
Vol 86 (4) ◽  
pp. 544-550 ◽  
Author(s):  
J D Sargent ◽  
T A Stukel ◽  
M A Dalton ◽  
J L Freeman ◽  
M J Brown
Keyword(s):  
Risk Factors ◽  
Iron Deficiency ◽  
Demographic Risk ◽  
Demographic Risk Factors

scholarly journals Incidence and demographic risk factors for leptospirosis in dogs in the UK

2021 ◽  
Author(s):  
Collette Taylor ◽  
Dan G. O'Neill ◽  
Brian Catchpole ◽  
Dave C. Brodbelt
Keyword(s):  
Risk Factors ◽  
Demographic Risk ◽  
The Uk ◽  
Demographic Risk Factors

scholarly journals Demographic risk factors for mid-urethral sling failure. Do they really matter?

PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0207185 ◽  
Author(s):  
Wojciech Majkusiak ◽  
Andrzej Pomian ◽  
Edyta Horosz ◽  
Aneta Zwierzchowska ◽  
Paweł Tomasik ◽  
...  
Keyword(s):  
Risk Factors ◽  
Demographic Risk ◽  
Demographic Risk Factors
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