Preliminary analysis of anemia in patients with active ulcerative coliti
Bibliographic record
Abstract
Objective: The study objective is to investigate the degree and type of anemia in patients with active Ulcerative Colitis(UC). Methods: Retrospective investigation of clinical data of UC patients admitted to the department of gastroenterology of the second hospital of Hebei medical university from March 2014 to January 2018. 152 patients with ulcerative colitis and 44 controls were included. According to the Improved Mayo Scoring System and Montreal Classification, UC patients were further divided into different group. The currently used World Health Organization (WHO) definition of anemia applies also to patients with UC. Statistical package for social sciences (SPSS) software was used for statistical analysis. Result: The prevalence of anemia in the ulcerative colitis patients was higher as compared to the controls (58.6% vs 21.4%, P<0.01). The prevalence of anemia in females in ulcerative colitis patients is higher as compared with the males (P=0.017). But there is no different in ages. In the ulcerative colitis patients having anemia, 60 cases (67.42%) had mild anemia, 27 cases (30.34%) had moderate anemia and 2 cases (2.25%) had severe anemia. Microcytic anemia was 40.44% (36 cases), normocytic anemia was 44.94% and macrocytic anemia was 14.62%. In the UC patients, mean corpuscular volume (MCV) is smaller than that in the controls (P=0.014) and red blood cell distribution width(RDW-CV) is bigger (P=0.036). There was no significant difference between the range of UC and anemia. However, the more sever of UC, the more sever of anemia. Conclusion: 1. The prevalence of mild and moderate anemia in UC is common, particularly in female patients. 2. The prevalence of iron deficiency anemia and mix anemia were common.3. The more sever of UC, the more sever of anemia. 4. In the UC patients, MCV is smaller and RDW-CV is bigger as compared to controls.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".