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Cystic Fibrosis Cloud database: Un sistema informático para el almacenamiento y manejo de datos clínicos y microbiológicos del paciente con fibrosis quística

Overview of attention for article published in Revista Argentina de Microbiología, February 2016
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Title
Cystic Fibrosis Cloud database: Un sistema informático para el almacenamiento y manejo de datos clínicos y microbiológicos del paciente con fibrosis quística
Published in
Revista Argentina de Microbiología, February 2016
DOI 10.1016/j.ram.2015.11.002
Pubmed ID
Authors

Claudia I. Prieto, María J. Palau, Pablo Martina, Carlos Achiary, Andrés Achiary, Marisa Bettiol, Patricia Montanaro, María L. Cazzola, Mariana Leguizamón, Cintia Massillo, Cecilia Figoli, Brenda Valeiras, Silvia Perez, Fernando Rentería, Graciela Diez, Osvaldo M. Yantorno, Alejandra Bosch

Abstract

The epidemiological and clinical management of cystic fibrosis (CF) patients suffering from acute pulmonary exacerbations or chronic lung infections demands continuous updating of medical and microbiological processes associated with the constant evolution of pathogens during host colonization. In order to monitor the dynamics of these processes, it is essential to have expert systems capable of storing and subsequently extracting the information generated from different studies of the patients and microorganisms isolated from them. In this work we have designed and developed an on-line database based on an information system that allows to store, manage and visualize data from clinical studies and microbiological analysis of bacteria obtained from the respiratory tract of patients suffering from cystic fibrosis. The information system, named Cystic Fibrosis Cloud database is available on the http://servoy.infocomsa.com/cfc_database site and is composed of a main database and a web-based interface, which uses Servoy's product architecture based on Java technology. Although the CFC database system can be implemented as a local program for private use in CF centers, it can also be used, updated and shared by different users who can access the stored information in a systematic, practical and safe manner. The implementation of the CFC database could have a significant impact on the monitoring of respiratory infections, the prevention of exacerbations, the detection of emerging organisms, and the adequacy of control strategies for lung infections in CF patients.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 19%
Other 9 13%
Student > Master 8 12%
Researcher 6 9%
Student > Ph. D. Student 4 6%
Other 5 7%
Unknown 24 35%
Readers by discipline Count As %
Engineering 13 19%
Computer Science 6 9%
Agricultural and Biological Sciences 5 7%
Biochemistry, Genetics and Molecular Biology 4 6%
Medicine and Dentistry 4 6%
Other 12 17%
Unknown 25 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 February 2016.
All research outputs
#20,656,820
of 25,374,917 outputs
Outputs from Revista Argentina de Microbiología
#166
of 327 outputs
Outputs of similar age
#230,696
of 311,954 outputs
Outputs of similar age from Revista Argentina de Microbiología
#3
of 9 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 327 research outputs from this source. They receive a mean Attention Score of 1.7. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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 311,954 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.