↓ Skip to main content

The evaluation of risk prediction models in predicting outcomes after bariatric surgery: a prospective observational cohort pilot study

Overview of attention for article published in Perioperative Medicine, April 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#44 of 243)
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

news
1 news outlet
twitter
1 X user

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
35 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The evaluation of risk prediction models in predicting outcomes after bariatric surgery: a prospective observational cohort pilot study
Published in
Perioperative Medicine, April 2018
DOI 10.1186/s13741-018-0088-5
Pubmed ID
Authors

David Andrew Gilhooly, Michelle Cole, Suneetha Ramani Moonesinghe

Abstract

As the prevalence of obesity is increasing, the number of patients requiring surgical intervention for obesity-related illness is also rising. The aim of this pilot study was to explore predictors of short-term morbidity and longer-term poor weight loss after bariatric surgery. This was a single-centre prospective observational cohort pilot study in patients undergoing bariatric surgery. We assessed the accuracy (discrimination and calibration) of two previously validated risk prediction models (the Physiological and Operative Severity Score for the enumeration of Morbidity and Mortality, POSSUM score, and the Obesity Surgical Mortality Risk Score, OS-MS) for postoperative outcome (postoperative morbidity defined using the Post Operative Morbidity Survey). We then tested the relationship between postoperative morbidity and longer-term weight loss outcome adjusting for known patient risk factors. Complete data were collected on 197 patients who underwent surgery for obesity or obesity-related illnesses between March 2010 and September 2013. Results showed POSSUM and OS-MRS were less accurate at predicting Post Operative Morbidity Survey (POMS)-defined morbidity on day 3 than defining prolonged length of stay due to poor mobility and/or POMS-defined morbidity. Having fewer than 28 days alive and out of hospital within 30 days of surgery was predictive of poor weight loss at 1 year, independent of POSSUM-defined risk (odds ratio 2.6; 95% confidence interval 1.28-5.24). POSSUM may be used to predict patients who will have prolonged postoperative LOS after bariatric surgery due to morbidity or poor mobility. However, independent of POSSUM score, having less than 28 days alive and out of hospital predicted poor weight loss outcome at 1 year. This adds to the literature that postoperative complications are independently associated with poor longer-term surgical outcomes.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 20%
Student > Master 3 9%
Other 2 6%
Student > Doctoral Student 2 6%
Unspecified 2 6%
Other 5 14%
Unknown 14 40%
Readers by discipline Count As %
Medicine and Dentistry 11 31%
Engineering 4 11%
Nursing and Health Professions 2 6%
Unspecified 2 6%
Computer Science 1 3%
Other 0 0%
Unknown 15 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 22 May 2021.
All research outputs
#3,238,035
of 23,041,514 outputs
Outputs from Perioperative Medicine
#44
of 243 outputs
Outputs of similar age
#68,635
of 329,244 outputs
Outputs of similar age from Perioperative Medicine
#2
of 6 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 243 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has done well, scoring higher than 81% 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 329,244 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 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.