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Modelling the consequences of a reduction in alcohol consumption among patients with alcohol dependence based on real-life observational data

Overview of attention for article published in BMC Public Health, December 2015
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Title
Modelling the consequences of a reduction in alcohol consumption among patients with alcohol dependence based on real-life observational data
Published in
BMC Public Health, December 2015
DOI 10.1186/s12889-015-2606-4
Pubmed ID
Authors

Nora Rahhali, Aurélie Millier, Benjamin Briquet, Philippe Laramée, Samuel Aballéa, Mondher Toumi, Clément François, Jürgen Rehm, Jean-Bernard Daeppen

Abstract

Most available pharmacotherapies for alcohol-dependent patients target abstinence; however, reduced alcohol consumption may be a more realistic goal. Using randomized clinical trial (RCT) data, a previous microsimulation model evaluated the clinical relevance of reduced consumption in terms of avoided alcohol-attributable events. Using real-life observational data, the current analysis aimed to adapt the model and confirm previous findings about the clinical relevance of reduced alcohol consumption. Based on the prospective observational CONTROL study, evaluating daily alcohol consumption among alcohol-dependent patients, the model predicted the probability of drinking any alcohol during a given day. Predicted daily alcohol consumption was simulated in a hypothetical sample of 200,000 patients observed over a year. Individual total alcohol consumption (TAC) and number of heavy drinking days (HDD) were derived. Using published risk equations, probabilities of alcohol-attributable adverse health events (e.g., hospitalizations or death) corresponding to simulated consumptions were computed, and aggregated for categories of patients defined by HDDs and TAC (expressed per 100,000 patient-years). Sensitivity analyses tested model robustness. Shifting from >220 HDDs per year to 120-140 HDDs and shifting from 36,000-39,000 g TAC per year (120-130 g/day) to 15,000-18,000 g TAC per year (50-60 g/day) impacted substantially on the incidence of events (14,588 and 6148 events avoided per 100,000 patient-years, respectively). Results were robust to sensitivity analyses. This study corroborates the previous microsimulation modeling approach and, using real-life data, confirms RCT-based findings that reduced alcohol consumption is a relevant objective for consideration in alcohol dependence management to improve public health.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
Unknown 24 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 20%
Student > Master 5 20%
Student > Ph. D. Student 3 12%
Student > Doctoral Student 3 12%
Professor 2 8%
Other 4 16%
Unknown 3 12%
Readers by discipline Count As %
Medicine and Dentistry 7 28%
Engineering 2 8%
Psychology 2 8%
Economics, Econometrics and Finance 2 8%
Philosophy 1 4%
Other 6 24%
Unknown 5 20%
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 24 December 2015.
All research outputs
#18,433,196
of 22,836,570 outputs
Outputs from BMC Public Health
#12,865
of 14,878 outputs
Outputs of similar age
#281,170
of 389,451 outputs
Outputs of similar age from BMC Public Health
#221
of 257 outputs
Altmetric has tracked 22,836,570 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,878 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 6th percentile – i.e., 6% 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 389,451 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 257 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.