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Predictive modeling for chronic pain after ventral hernia repair

Overview of attention for article published in American Journal of Surgery, May 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

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3 news outlets
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3 X users

Citations

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37 Dimensions

Readers on

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72 Mendeley
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Title
Predictive modeling for chronic pain after ventral hernia repair
Published in
American Journal of Surgery, May 2016
DOI 10.1016/j.amjsurg.2016.02.021
Pubmed ID
Authors

Tiffany C. Cox, Ciara R. Huntington, Laurel J. Blair, Tanushree Prasad, Amy E. Lincourt, Brant T. Heniford, Vedra A. Augenstein

Abstract

Few studies predict which patients have dissolution of their postoperative discomfort or develop chronic pain after ventral hernia repair (VHR). This study develops a predictive model to determine which patients are at the greatest risk of chronic pain after VHR. A prospective study of VHR patients was performed via the International Hernia Mesh Registry. Anonymous, self-reported, quality of life data using the Carolinas Comfort Scale (CCS) was recorded preoperatively, and 1,6, and 12 months postoperatively. Pain was identified as a score of 2 or more (mild but bothersome to severe) for any Carolinas Comfort Scale pain-specific questions. Logistic regression analyses were performed to determine statistically significant predictors of chronic pain. Univariate analysis selected potential predictors with a P value less than .15, and a subsequent multivariable model was built using backward elimination setting retention criterion at P < .15. Goodness-of-fit of the model was tested using Hosmer-Lemeshow test. A value of greater than 70% for the area under the curve (AUC) was considered most accurate diagnostically. The final model was then internally validated with bootstrap analysis. A total of 887 patients underwent VHR between 2007 and 2014. The patients had an average age of 57.2 ± 12.8 years, 52.4% were female, 17.0% were active smokers, and 13.2% used narcotics preoperatively. With 74% follow-up at 1 year, 26.0% of the patients reported chronic discomfort. After logistic regression model, independent predictors of pain at 6 months were preoperative pain score 2 or more (P < .0001), preoperative narcotic use (P = .06), and 1-month postoperative pain score 2 or more (P < .0001), AUC = .74. Baseline, 1-month, and 6-month predictors determined the final multivariate regression model for prediction of chronic pain at 1 year, AUC = .73. Older age was protective against chronic pain (odds ratio [OR] .98, 95%confidence interval [CI] = .96 to .998, P = .03), female sex increased risk with an OR of 1.7(CI = 1.1 to 2.7, P = .02); preoperative pain, and recurrent hernia repair nearly doubled the risk of developing chronic pain postoperatively (OR = 3.0, CI = 1.8 to 4.8, P < .0001 and 1.6, CI = .98 to 2.6, P = .06, respectively). Importantly, presence of pain at 1 month was a strong predictor of chronic pain at 1-year follow-up (OR = 2.6, CI = 1.7 to 4.2, P < .0001). Patients who have preoperative pain and at 1 month postoperatively are significantly more likely to have chronic pain. Both short- and long-term pain can be predicted from female sex, younger age, and repair of recurrent hernias. This predictive model may aid in preoperative counseling and when considering postoperative intervention for pain management in VHR patients.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 1%
Unknown 71 99%

Demographic breakdown

Readers by professional status Count As %
Other 11 15%
Researcher 8 11%
Student > Postgraduate 8 11%
Student > Master 8 11%
Student > Bachelor 8 11%
Other 18 25%
Unknown 11 15%
Readers by discipline Count As %
Medicine and Dentistry 38 53%
Pharmacology, Toxicology and Pharmaceutical Science 3 4%
Engineering 3 4%
Nursing and Health Professions 2 3%
Social Sciences 2 3%
Other 9 13%
Unknown 15 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 16 September 2021.
All research outputs
#1,525,130
of 25,374,647 outputs
Outputs from American Journal of Surgery
#119
of 5,052 outputs
Outputs of similar age
#25,854
of 326,216 outputs
Outputs of similar age from American Journal of Surgery
#1
of 67 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,052 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done particularly well, scoring higher than 97% 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 326,216 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.