The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
| Title |
Predicting endoscopic remission in Crohn’s disease by the modified multiplier SES-CD (MM-SES-CD)
|
|---|---|
| Published in |
Gut, March 2021
|
| DOI | 10.1136/gutjnl-2020-323799 |
| Pubmed ID | |
| Authors |
Neeraj Narula, Emily C L Wong, Jean-Frederic Colombel, William J Sandborn, John Kenneth Marshall, Marco Daperno, Walter Reinisch, Parambir S Dulai |
| Abstract |
The Simple Endoscopic Score for Crohn's disease (SES-CD) is the primary tool for measurement of mucosal inflammation in clinical trials but lacks prognostic potential. We set to develop and validate a modified multiplier of the SES-CD (MM-SES-CD), which takes into consideration each individual parameter's prognostic value for achieving endoscopic remission (ER) while on active therapy. In this posthoc analysis of three CD clinical trial programmes (n=350 patients, baseline SES-CD ≥ 3 with confirmed ulceration), data were pooled and randomly split into a 70% training and 30% testing cohort. The MM-SES-CD was designed using weights for individual parameters as determined by logistic regression modelling, with 1-year ER (SES-CD < 3) being the dependent variable. A cut point score for low and high probability of ER was determined by using the maximum Youden Index and validated in the testing cohort. Baseline ulcer size, extent of ulceration and presence of non-passable strictures had the strongest association with 1-year ER as compared with affected surface area, with differential weighting of individual parameters across disease segments being observed during logistic regression. The MM-SES-CD was generated using this weighted regression model and demonstrated strong discrimination for ER in the training dataset (area under the receiver operator curve (AUC) 0.83, 95% CI 0.78 to 0.94) and in the testing dataset (AUC 0.82, 95% CI 0.77 to 0.92). In comparison to the MM-SES-CD scoring model, the original SES-CD score lacks accuracy (AUC 0.60, 95% CI 0.55 to 0.65) for predicting the achievement of ER. We developed and internally validated the MM-SES-CD as an endoscopic severity assessment tool to predict one-year ER in patients with CD on active therapy. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 15% |
| Argentina | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 9 | 69% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 54% |
| Scientists | 2 | 15% |
| Science communicators (journalists, bloggers, editors) | 2 | 15% |
| Practitioners (doctors, other healthcare professionals) | 2 | 15% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 5 | 17% |
| Student > Doctoral Student | 4 | 13% |
| Student > Ph. D. Student | 3 | 10% |
| Student > Master | 3 | 10% |
| Researcher | 2 | 7% |
| Other | 1 | 3% |
| Unknown | 12 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 30% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 7% |
| Engineering | 2 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Computer Science | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 12 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 14 May 2022.
All research outputs
#3,930,873
of 23,577,654 outputs
Outputs from Gut
#2,022
of 6,956 outputs
Outputs of similar age
#96,327
of 430,787 outputs
Outputs of similar age from Gut
#62
of 106 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,956 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.0. This one has gotten more attention than average, scoring higher than 70% 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 430,787 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 77% of its contemporaries.
We're also able to compare this research output to 106 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.