EFFECT OF AUTOLOGOUS BONE MARROW MONONUCLEAR CELLS TRANSPLANTATION IN DIABETIC PATIENTS WITH ST-SEGMENT ELEVATION MYOCARDIAL INFARCTION
Bibliographic record
Abstract
Objectives To investigate the efficacy and proposed mechanism of bone marrow mononuclear cells (BMMNCs) transplantation for diabetic and non-diabetic patients with ST-segment elevation myocardial infarction (STEMI). Methods One hundred and sixteen patients with STEMI who had successfully undergone percutaneous coronary intervention (PCI) were divided into a diabetic group (n=51) and non-diabetic group (n=65). All of the patients received intracoronary injection of BMMNCs. Results Diabetes down-regulated IGF-1, IGFBP-5, VEGF, SDF-1, IL-6, IL-1α and TNF-α expression and affected the expression of Bmi-1, Gfi1, Tel and Hox-B4 which could prevent premature senescence and maintain the self-renewal capacity of stem cells. Event-free survival rates were not statistically different between the diabetic and non-diabetic group (80% vs 72.5%, p=0.382). LV ejection fraction (LVEF) and wall motion score index (WMSI) were evaluated by echocardiography and found to be significantly improved in the non-diabetic group compared to the diabetic group over the 4-year follow-up period. Improved myocardial perfusion and reduced infarct size in the non-diabetic group compared to the diabetic group was verified using single-photon emission computed tomographic (SPECT) imaging. The non-diabetic group also had reduced anginal symptoms as assessed by changes in their Seattle Angina Questionnaire scores and Canadian Cardiovascular Society (CCS) Functional Angina classification. An improvement of 6-min walk distance (6MWD) was also noted to be higher in the non-diabetic group during the follow-up period. Conclusions This study indicates that the beneficial effect of BMMNCs transplantation for STEMI is less pronounced in diabetic patients. The mechanism is associated with decreased BMMNCs function in diabetic patients.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".