Hemodialysis‐induced regional left ventricular systolic dysfunction
Bibliographic record
Abstract
Introduction Hemodialysis (HD) patients are under observably elevated cardiovascular mortality. Cardiac dysfunction is closely related to death caused by cardiovascular diseases (CVD). In the general population, repetitive myocardial ischemia induced left ventricular (LV) dysfunction may progress to irreversible loss of contraction step by step, and finally lead to cardiac death. In HD patients, to remove water and solute accumulated from 48 or 72 hours of interdialysis period in a 4-hour HD session will induce myocardial ischemia. In this study, we evaluated the prevalence and potential risk factors associated with HD-induced LV systolic dysfunction and provide some evidences for clinical strategies. Methods We recruited 31 standard HD patients for this study from Fudan University Zhongshan hospital. Echocardiography was performed predialysis, at peak stress during HD (15 minutes prior to the end of dialysis), and 30 minutes after HD. Auto functional imaging (AFI) was used to assess the incidence and persistence of HD-induced regional wall motion abnormalities (RWMAs). Blood samples were drawn to measure biochemical variables. Findings Among totally 527 segments of 31 patients, 93.54% (29/31) patients and 51.40% (276/527) segments were diagnosed as RWMAs. Higher cTnT (0.060 ± 0.030 vs. 0.048 ± 0.015 ng/mL, P = 0.023), phosphate (2.07 ± 0.50 vs. 1.49 ± 0.96 mmol/L, P = 0.001), UFR (11.00 ± 3.89 vs. 8.30 ± 2.66 mL/Kg/h, P = 0.039) and lower albumin (37.83 ± 4.48 vs. 38.38 ± 2.53 g/L, P = 0.050) were found in patients with severe RWMAs (RWMAs in more than 50% segments). After univariate and multivariate analysis, interdialytic weight gain (IDWG) was found as independent risk factor of severe RWMAs (OR = 1.047, 95%CI 1.155-4.732, P = 0.038). Discussion LV systolic dysfunction induced by HD is prevalent in conventional HD patients and should be paid attention to. Patients would benefit from better weight control during interdialytic period to reduce ultrafiltration rate.
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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 | 0.000 |
| 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) | 0.002 | 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".