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Comparison of risk-scoring systems in the prediction of outcome after liver resection

Overview of attention for article published in Perioperative Medicine, November 2017
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2 tweeters

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Title
Comparison of risk-scoring systems in the prediction of outcome after liver resection
Published in
Perioperative Medicine, November 2017
DOI 10.1186/s13741-017-0073-4
Pubmed ID
Authors

S. Ulyett, G. Shahtahmassebi, S. Aroori, M. J. Bowles, C. D. Briggs, M. G. Wiggans, G. Minto, D. A. Stell

Abstract

Risk prediction techniques commonly used in liver surgery include the American Society of Anesthesiologists (ASA) grading, Charlson Comorbidity Index (CCI) and cardiopulmonary exercise tests (CPET). This study compares the utility of these techniques along with the number of segments resected as predictive tools in liver surgery. A review of a unit database of patients undergoing liver resection between February 2008 and January 2015 was undertaken. Patient demographics, ASA, CCI and CPET variables were recorded along with resection size. Clavien-Dindo grade III-V complications were used as a composite outcome in analyses. Association between predictive variables and outcome was assessed by univariate and multivariate techniques. One hundred and seventy-two resections in 168 patients were identified. Grade III-V complications occurred after 42 (24.4%) liver resections. In univariate analysis of CPET variables, ventilatory equivalents for CO2 (VEqCO2) was associated with outcome. CCI score, but not ASA grade, was also associated with outcome. In multivariate analysis, the odds ratio of developing grade III-V complications for incremental increases in VEqCO2, CCI and number of liver segments resected were 1.09, 1.49 and 2.94, respectively. Of the techniques evaluated, resection size provides the simplest and most discriminating predictor of significant complications following liver surgery.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 23%
Researcher 3 23%
Student > Doctoral Student 2 15%
Lecturer > Senior Lecturer 1 8%
Student > Master 1 8%
Other 2 15%
Unknown 1 8%
Readers by discipline Count As %
Medicine and Dentistry 7 54%
Immunology and Microbiology 1 8%
Nursing and Health Professions 1 8%
Psychology 1 8%
Environmental Science 1 8%
Other 1 8%
Unknown 1 8%

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 09 December 2017.
All research outputs
#9,803,054
of 12,271,192 outputs
Outputs from Perioperative Medicine
#86
of 111 outputs
Outputs of similar age
#245,984
of 344,833 outputs
Outputs of similar age from Perioperative Medicine
#8
of 10 outputs
Altmetric has tracked 12,271,192 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 111 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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