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A prediction tool for nosocomial multi-drug resistant gram-negative bacilli infections in critically ill patients - prospective observational study

Overview of attention for article published in BMC Infectious Diseases, November 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
10 tweeters

Citations

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43 Dimensions

Readers on

mendeley
128 Mendeley
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Title
A prediction tool for nosocomial multi-drug resistant gram-negative bacilli infections in critically ill patients - prospective observational study
Published in
BMC Infectious Diseases, November 2014
DOI 10.1186/s12879-014-0615-z
Pubmed ID
Authors

Anupama Vasudevan, Amartya Mukhopadhyay, Jialiang Li, Eugene Goh Yu Yuen, Paul Ananth Tambyah

Abstract

BackgroundThe widespread use of empiric broad spectrum antibiotics has contributed to the global increase of Resistant Gram-Negative Bacilli (RGNB) infections in intensive care units (ICU). The aim of this study was to develop a tool to predict nosocomial RGNB infections among ICU patients for targeted therapy.MethodsWe conducted a prospective observational study from August¿07 to December¿11. All adult patients who were admitted and stayed for more than 24 hours at the medical and surgical ICU¿s were included. All patients who developed nosocomial RGNB infections 48 hours after ICU admission were identified. A prediction score was formulated by using independent risk factors obtained from logistic regression analysis. This was prospectively validated with a subsequent cohort of patients admitted to the ICUs during the following time period of January-September 2012.ResultsSeventy-six patients with nosocomial RGNB Infection (31bacteremia) were compared with 1398 patients with Systemic Inflammatory Response Syndrome (SIRS) without any gram negative bacterial infection/colonization admitted to the ICUs during the study period. The following independent risk factors were obtained by a multivariable logistic regression analysis - prior isolation of Gram negative organism (coeff:1.1, 95%CI 0.5¿1.7); Surgery during current admission (coeff:0.69,95%CI 0.2¿1.2); prior Dialysis with end stage renal disease (coeff:0.7, 95%CI0.1¿1.1); prior use of Carbapenems (coeff:1.3, 95%CI0.3¿2.3) and Stay in the ICU for more than 5 days (coeff:2.4, 95%CI 1.6¿3.2). It was validated prospectively in a subsequent cohort (n¿=¿408) and the area-under-the-curve (AUC) of the GSDCS score for predicting nosocomial ICU acquired RGNB infection and bacteremia was 0.77 (95%CI 0.68¿0.89 and 0.78 (95%CI 0.69¿0.89) respectively. The GSDCS (0¿4.3) score clearly differentiated the low (0¿1.3), medium (1.4¿2.3) and high (2.4¿4.3) risk patients, both for RGNB infection (p:0.003) and bacteremia (p:0.009).ConclusionGSDCS is a simple bedside clinical score which predicts RGNB infection and bacteremia with high predictive value and differentiates low versus high risk patients. This score will help clinicians to choose appropriate, timely targeted antibiotic therapy and avoid exposure to unnecessary treatment for patients at low risk of nosocomial RGNB infection. This will reduce the selection pressure and help to contain antibiotic resistance in ICUs.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Spain 1 <1%
Unknown 126 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 16%
Researcher 16 13%
Student > Master 16 13%
Other 14 11%
Student > Bachelor 11 9%
Other 25 20%
Unknown 26 20%
Readers by discipline Count As %
Medicine and Dentistry 61 48%
Nursing and Health Professions 11 9%
Immunology and Microbiology 7 5%
Pharmacology, Toxicology and Pharmaceutical Science 4 3%
Agricultural and Biological Sciences 3 2%
Other 8 6%
Unknown 34 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 21 August 2015.
All research outputs
#5,293,645
of 21,321,365 outputs
Outputs from BMC Infectious Diseases
#1,560
of 7,277 outputs
Outputs of similar age
#75,366
of 345,780 outputs
Outputs of similar age from BMC Infectious Diseases
#138
of 642 outputs
Altmetric has tracked 21,321,365 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,277 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done well, scoring higher than 78% 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 345,780 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 78% of its contemporaries.
We're also able to compare this research output to 642 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.