Echocardiographic Evidence of Altered Cardiac Status in Predialysis Diabetics and Those on Dialysis
Bibliographic record
Abstract
Cardiovascular complications affect diabetic subjects early and the more susceptible ones are those on hemodialysis. Objective: This study was designed to observe prevalent cardiac involvement in both pre‐ and already on dialysis diabetics. Method: Sixty diabetics, 30 predialysis (predialysis diabetics, group 1), and 30 on maintenance hemodialysis (MHD, group 2) were randomly selected and their different clinical, biochemical, and echocardiographic parameters were compared. Result: Both groups of patients were matched for age, sex, and body mass index (BMI). Features like systolic and diastolic blood pressure were lower in predialysis diabetics group than in MHD group [138 ± 19 vs. 152 ± 32, p < 0.02 and 74 ± 10 vs. 87 ± 10 mmHg (p < 0.001)]; hemoglobin higher [10.3 ± 2.1 vs. 7.5 ± 1.5 g/dL (p < 0.001)]; serum creatinine was lower [3.49 ± 1.8 vs. 9.5 ± 2.5 mg/dL (p < 0.001)] (due to recruitment criteria); left ventricular muscle mass index (LVMI) also lower [137 ± 96 vs. 211 ± 77 g/m2 (p < 0.001)]; left ventricular end diastolic volume index (LVEDVI) less [58 ± 21 vs. 85 ± 25 mL/m2 (p < 0.001) and fractional shortening (FS, %) higher [33 ± 4.3 vs. 28 ± 5.8 (p < 0.006)]. Only 11% of Pre subjects had LV hypertrophy (LVMI >131 g/m2 in male and in female LVMI >110 g/m2) whereas it was 51% in MHD (p < 0.001). Systolic dysfunction (FS = <25%) was 4% in Pre subjects and 24% in MHD (p < 0.03) group. Correlation study showed systolic and diastolic blood pressure; both had positive correlation with LVMI (r = 0.38, p < 0.008 and r = 0.32, p < 0.02) and LVEDVI (r = 0.36, p < 0.01 and r = 0.35, p < 0.01) and also similarly positive with serum creatinine (r = 0.35, p < 0.02 and r = 0.5, p < 0.001). Conclusion: It may be concluded that cardiac parameters are grossly altered in majority of diabetics on dialysis and higher serum creatinine and uncontrolled blood pressure may be responsible for this.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".