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Record W2586669419 · doi:10.1093/ecco-jcc/jjx002.338

P213 Agreement between Crohn's disease endoscopy severity scores derived from live local, delayed local video-recorded and central readings

2017· article· en· W2586669419 on OpenAlexaff
Justin Côté-Daigneault, Farhad Peerani, Konstantinos H. Katsanos, Thomas Ullman, James F. Marion, Peter Legnani, Burton Cohen, J F Colombel

Bibliographic record

VenueJournal of Crohn s and Colitis · 2017
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of AlbertaCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineCrohn's diseaseEndoscopyRectumColonoscopyGastroenterologyInternal medicineEndoscopeDiseaseSurgeryColorectal cancer

Abstract

fetched live from OpenAlex

Background: The Crohn's Disease Endoscopic Index of Severity (CDEIS) and the Simple Endoscopic Score for Crohn's Disease (SES-CD) are used to assess endoscopic disease severity in Crohn's disease (CD). Central reading has become the standard practice in clinical trials for inclusion and evaluation of endoscopic response to therapy. However, the agreement between severity scores (CDEIS or SES-CD) derived from live local, delayed local video-recorded and central readings has not been studied. Methods: We conducted a monocentric prospective study between April 2015 and December 2015. Fifty-three CD patients were recruited by three endoscopists trained to endoscopic readings for score calculation (TU, JM and BC). All colonoscopies were recorded on-site and videos were labeled according to the segment of interest: ileum, right colon, transverse colon, left and sigmoid colon, and rectum. Each endoscopist performed immediate readings of his patients and delayed local video-recorded readings of his patients' colonoscopies at least 3 months after the live local reading. Two central readers (JCD and FP) read all videos. CDEIS and SES-CD scores were then computed automatically based on all readings. Intra-class correlation coefficients (ICC) were estimated and Bland and Altman plots were used to assess the agreement between severity scores derived from various readings. In a first step, we studied the agreement between severity scores derived from live local (L) and central (C1 and C2) readings and L and delayed local video-recorded (D) readings. Results: ICC estimates of CDEIS (n=44) and SES-CD (n=46) scores were respectively 0.89; 95% confidence interval (CI), 0.80–0.94 and 0.94; 95% CI, 0.87–0.97 between L and C1 and 0.80; 95% CI, 0.58–0.90 and 0.85; 95% CI, 0.74–0.91 between L and C2. ICC estimates between L and D were respectively 0.87; 95% CI, 0.78–0.93 and 0.88; 95% CI, 0.79–0.93. An example of Bland and Altman plots derived from L and C1 are shown in figure 1 for CDEIS and figure 2 for SES-CD scores. Figure 1. Bland and Altman plots of CDEIS derived from live local reading and central reading 1. Figure 2. Bland and Altman plots of SES-CD derived from live local reading and central reading 1. Conclusions: Overall, the agreement between severity scores (CDEIS or SES-CD) derived from live local, delayed local video-recorded and central readings is excellent. This data suggests that both local readings by trained endoscopists and central reading could be used in clinical trials.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.273
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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