Characteristics of Hemorheology in Patients with Acute Severe Ulcerative Colitis and the Clinical Study of Rivaroxaban Anticoagulant Therapy
Bibliographic record
Abstract
Objectives: The present study aimed to determine the hemorheological characteristics of patients with acute severe ulcerative colitis (ASUC) and the effect of rivaroxaban anticoagulation therapy. The study also aimed to further explore the mechanisms and novel pathways underlying ASUC therapy. Methods: Various hemorheology tests were performed on 88 hospitalized ASUC patients, including mean platelet volume (MVP), platelet count, prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB) D-dimer and indicators of thrombelastogram (TEG). All results were compared with those of 40 colonic polyp controls. The ASUC patients were randomly divided into control and treatment groups (n = 44 each). The control group received routine mesalazine and methylprednisolone therapy, while the treatment group received rivaroxaban in addition to routine medicines. Montreal classification was used to evaluate the lesion range and the Mayo scoring system was used to evaluate the activity and treatment efficacy of the disease. The Endoscopic Severity Index of Ulcerative Colitis (UCEIS) was used to evaluate mucosal inflammation and Geboes index was used to evaluate mucosa histology. The percentage of microthrombus in pathological sections was calculated via immunohistochemical staining. The two groups were compared for efficacy, side effects, microthrombosis and hemorrheology after 30 days. Results and Conclusions: The results revealed that hypercoagulation is an important pathological stage of ASUC. Rivaroxaban anticoagulant therapy added to routine treatment was more effective than conventional treatment alone, which significantly improved the blood coagulation status of patients, alleviated clinical symptoms, relieved the endoscopic and histological outcomes, reduced the required hormone dosage and were worthy of clinical promotion.
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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 | 0.000 | 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) | 0.001 | 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".