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The predictors of 3- and 30-day mortality in 660 MERS-CoV patients

Overview of attention for article published in BMC Infectious Diseases, September 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

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1 news outlet
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4 X users
facebook
1 Facebook page
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

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74 Dimensions

Readers on

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89 Mendeley
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Title
The predictors of 3- and 30-day mortality in 660 MERS-CoV patients
Published in
BMC Infectious Diseases, September 2017
DOI 10.1186/s12879-017-2712-2
Pubmed ID
Authors

Anwar E. Ahmed

Abstract

The mortality rate of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) patients is a major challenge in all healthcare systems worldwide. Because the MERS-CoV risk-standardized mortality rates are currently unavailable in the literature, the author concentrated on developing a method to estimate the risk-standardized mortality rates using MERS-CoV 3- and 30-day mortality measures. MERS-CoV data in Saudi Arabia is publicly reported and made available through the Saudi Ministry of Health (SMOH) website. The author studied 660 MERS-CoV patients who were reported by the SMOH between December 2, 2014 and November 12, 2016. The data gathered contained basic demographic information (age, gender, and nationality), healthcare worker, source of infection, pre-existing illness, symptomatic, severity of illness, and regions in Saudi Arabia. The status and date of mortality were also reported. Cox-proportional hazard (CPH) models were applied to estimate the hazard ratios for the predictors of 3- and 30-day mortality. 3-day, 30-day, and overall mortality were found to be 13.8%, 28.3%, and 29.8%, respectively. According to CPH, multivariate predictors of 3-day mortality were elderly, non-healthcare workers, illness severity, and hospital-acquired infections (adjusted hazard ratio (aHR) =1.7; 8.8; 6.5; and 2.8, respectively). Multivariate predictors of 30-day mortality were elderly, non-healthcare workers, pre-existing illness, severity of illness, and hospital-acquired infections (aHR =1.7; 19.2; 2.1; 3.7; and 2.9, respectively). Several factors were identified that could influence mortality outcomes at 3 days and 30 days, including age (elderly), non-healthcare workers, severity of illness, and hospital-acquired infections. The findings can serve as a guide for healthcare practitioners by appropriately identifying and managing potential patients at high risk of death.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 89 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 17%
Student > Master 10 11%
Student > Bachelor 10 11%
Student > Postgraduate 8 9%
Other 4 4%
Other 18 20%
Unknown 24 27%
Readers by discipline Count As %
Medicine and Dentistry 21 24%
Nursing and Health Professions 9 10%
Biochemistry, Genetics and Molecular Biology 8 9%
Computer Science 4 4%
Veterinary Science and Veterinary Medicine 3 3%
Other 9 10%
Unknown 35 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 February 2020.
All research outputs
#2,235,801
of 24,654,673 outputs
Outputs from BMC Infectious Diseases
#634
of 8,264 outputs
Outputs of similar age
#42,294
of 320,605 outputs
Outputs of similar age from BMC Infectious Diseases
#5
of 151 outputs
Altmetric has tracked 24,654,673 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,264 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,605 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 151 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.