Heart failure events in randomized controlled trials for adults receiving maintenance dialysis: a meta-epidemiologic study
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Heart failure is characterized as cardiac dysfunction resulting in elevated cardiac filling pressures with symptoms and signs of congestion. Distinguishing heart failure from other causes of similar presentations in patients with kidney failure is challenging but necessary, and is needed in randomized controlled trials (RCTs) to accurately estimate treatment effects. The objective of this study was to review heart failure events, their diagnostic criteria, and adjudication in RCTs of patients with kidney failure treated with dialysis. We hypothesized that heart failure events, diagnostic criteria, and adjudication were infrequently reported in RCTs in dialysis. METHODS: We conducted a meta-epidemiologic systematic review of RCTs from high-impact medical, nephrology, and cardiology journals from 2000 to 2020. RCTs were eligible if they enrolled adults receiving maintenance dialysis for kidney failure and evaluated any intervention. RESULTS: Of 561 RCTs in patients receiving dialysis, 36 (6.4%) reported heart failure events as primary (10, 27.8%) or secondary (31, 86.1%) outcomes. Ten of the 36 (27.8%) RCTs provided heart failure event diagnostic criteria and five of these (50%) adjudicated heart failure events. These 10 RCTs included event diagnostic criteria for heart failure or heart failure hospitalizations, and their criteria included dyspnoea (5/10), oedema (2/10), rales/crackles (4/10), chest X-ray pulmonary oedema or vascular redistribution (4/10), treatment in an acute setting (6/10), and ultrafiltration or dialysis (4/10). No study explicitly distinguished heart failure from volume overload secondary to non-adherence or underdialysis. CONCLUSION: Overall, we found that heart failure events are infrequently reported in RCTs in dialysis and are heterogeneously defined. Further research is required to develop standardized diagnostic criteria that are practical and meaningful to patients and clinicians.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
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 | 0.027 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.041 | 0.014 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".