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[Nutritional risk screening in patients with Crohn's disease].

2016· article· en· W2412094526 on OpenAlexaboutno aff
Yue Wu, Yan He, Fangling Chen, Ting Feng, Maoyin Li, Guo J, Yu Q, Hom‐Lay Wang, Tang Rh, Li T, Mao R, Shenghong Zhang, Chen Bl, Zeng Zr, Chen Mh

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineCrohn's diseaseDiseaseLogistic regressionInflammatory bowel diseaseGastroenterology

Abstract

fetched live from OpenAlex

OBJECTIVE: To screen the nutritional risk in patients with Crohn's disease (CD), to explore the prevalence and characteristics of nutritional risk in CD patients, and to identify the possible risk factors. METHOD: A cross-sectional study was performed in 712 patients who was diagnosed as CD in the Center for Inflammatory Bowel Disease of First Affiliated Hospital of Sun Yat-sen University between January 2003 and January 2014. Montreal classification was used to classify CD, Crohn's Disease Activity Index (CDAI) was used to evaluate disease activity, and Nutritional Risk Screening 2002 (NRS2002) was used to assess the nutritional risk in each patient. Reappraisal with NRS 2002 was conducted in patients followed up for 1 year to identify the possible effect of treatment on nutritional risk of the CD patients. RESULTS: The prevalence of nutritional risk was 65.2% (464/712) in the enrolled CD patients. The prevalence of nutritional risk was significantly different among patients with different disease activity (χ(2)=117.169, P<0.001), also significantly different among patients of different age at diagnosis (χ(2)=11.256, P=0.004), with different lesion location (χ(2)=18.841, P=0.001) and different disease behavior (χ(2)=15.793, P<0.001), but not significantly different in patients of different sex (χ(2)=0.601, P=0.245). Multivariate Logistic regression showed that the independent predictive risk factors for nutritional risk included abdominal tenderness (OR=1.895, 95%CI: 1.080-3.324); mild (OR=1.846, 95%CI: 1.179-2.890), moderate (OR=4.410, 95%CI: 2.701-7.200) and severe (OR=14.069, 95%CI: 1.718-115.192) disease activity; B2 (stricturing) (OR=1.620, 95%CI: 1.034-2.538) and B3 (penetrating) (OR=1.920, 95%CI: 1.025-3.596) types of disease behavior; and high level with erythrocyte sedimentation rate (ESR) (OR=1.024, 95%CI: 1.015-1.034). On the other hand, >40 years at diagnosis (A3 type) (OR=0.332, 95%CI: 0.135-0.814) and high albumin level (OR=0.962, 95%CI: 0.934-0.990) were independent protective factors for nutritional risk. After 1-year follow-up, nutritional risk was eliminated in 32.0%(111/347)of the patients, and the rate was higher in patients received surgery than in those treated with medicine alone (42.9%(54/126)vs 25.8%(57/221), χ(2)=10.742, P=0.001). CONCLUSIONS: Two thirds of CD patients may have nutritional risk at diagnosis, which may differ with disease activity and Montreal classification. Abdominal tenderness, disease activity, B2 and B3 types of disease behavior, and high ESR may be independent risk factors for nutritional risk, whereas A3 type of age at diagnosis and high albumin level may be independent protective factors.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.176
Teacher spread0.171 · 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".

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Citations3
Published2016
Admission routes1
Has abstractyes

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