Clinical Analysis of Thalidomide Combined with Erythropoietin and Iron Sucrose Injection in The Treatment of Malignant Tumors Complicated by Anemia of Chronic Disease
Bibliographic record
Abstract
To evaluate the efficacy and safety of thalidomide combined with erythropoietin (EPO) and iron sucrose injection in the treatment of malignant tumors complicated by anemia of chronic disease (ACD). From January 2017 to January 2019, 60 patients with malignant tumors complicated by ACD were enrolled. Patients were randomly assigned to two treatment groups and one control group. The two treatment groups received continuous oral administration of thalidomide at 100/d.; EPO 150IU/kg, subcutaneous injection for 3 times a week; iron sucrose injection of 100mg was intravenously administrated once a week, EPO 150 IU/kg, subcutaneous injection for 3 times a week; iron sucrose injection of 100mg was intravenously administrated once a week; the control group received subcutaneous injection of EPO 150IU/kg for 3 times a week; polysaccharide iron complex of 150 mg was orally administrated once a day; after 8 weeks, reexamination of related indexes was performed, and the efficacy and adverse reactions were evaluated. HGB level was significantly higher in the thalidomide group than in the control group ( P< 0.05); moreover, the response rate was higher compared with the control group ( P< 0.05). Mild adverse reactions occurred in a few patients. Thalidomide combined with EPO and iron sucrose injection was more effective and safer in the treatment of malignant tumors complicated by ACD.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".