Prognostic implications of Global Longitudinal Strain versus Ejection Fraction in End-stage Renal Disease: a systematic review protocol
Bibliographic record
Abstract
Background: In hemodialysis (HD) patients, the presence of Heart failure (HF) at the start of dialysis is a strong and independent predictor of short and long-term mortality, and its prevalence increases with declining kidney function and HD time. Left ventricular (LV) ejection fraction (EF) is widely used as a measure of systolic function. Reduced EF (<50%) is an important prognostic marker, however, less than 15% of End-stage Renal Disease (ESRD) patients have detectable systolic dysfunction and the EF is susceptible to loading conditions, which change dramatically during interdialytic intervals. Global Longitudinal Strain (GLS) derived by 2D Speckle-Tracking Echocardiography (STE) is an emerging technique for measuring more subtle disturbances in LV systolic function. Although ESRD patients have subclinical evidence of impaired strain but preserved EF, there is evidence that GLS is better in ESRD group receiving maintenance HD compared with moderate-advanced CKD patients. This systematic review will evaluate the evidence related to the incremental prognostic value of LV GLS by 2D-STE concerning mortality and cardiovascular (CV) events in ESRD patients. Methods: This protocol is reported according to the PRISMA-P guideline. The databases PubMed, EMBASE, LILACS, Web of Science, and Google Scholar system will be searched and double screening for longitudinal studies that assessed the prospective association of STE-derived parameters with at least one of the pre-specified outcomes in ESRD patients. Discrepancies will be resolved through consensus. A modified version of the Newcastle-Ottawa Quality Assessment Scale of cohort studies will be used. We intend to use the random-effects model, considering at least moderate heterogeneity between studies. If data allow, we will perform meta-regression to explore potential sources of between-study heterogeneity. An adaptation of the GRADE framework for prognostic studies will be employed to judge the quality of evidence for each outcome reported in this systematic review. Discussion: This systematic review will summarize current evidence about STE-derived measures in ESRD patients and clarify the incremental prognostic value of this diagnostic tool versus LVEF in these patients. Evidence about other measures (circumferential and radial strain) or 3D STE-derived indices will also be investigated.
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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 | 0.030 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.018 | 0.013 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.049 | 0.004 |
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".