J-Shaped Relationship of the Triglyceride-Glucose Index with All-Cause Mortality in Initial Hemodialysis Patients in China: A Multicenter, Retrospective Cohort Study
Bibliographic record
Abstract
INTRODUCTION: The relationship between the triglyceride-glucose (TyG) index and mortality in hemodialysis patients remains uncertain. This study aimed to investigate the correlation between TyG index and all-cause mortality in initial hemodialysis patients in China. METHODS: 783 patients participated in the study and were grouped into quintiles according to the TyG index. Multivariate Cox models and subgroup analyses were utilized. Nonlinear correlations were explored using restricted cubic splines, and a two-piecewise Cox proportional hazards model was developed around the inflection point. RESULTS: During a median follow-up of 44 months, 231 (29.50%) patients occurred mortality. Multivariate Cox regression confirmed that both lower and higher TyG indices independently predicted all-cause mortality (all p < 0.05). The predictive value of a high TyG index for all-cause mortality remained consistent across age, sex, BMI, and diabetes subgroups. A restricted cubic spline unveiled a J-shaped relationship between the two variables in initial hemodialysis patients. A TyG index exceeding 8.83 exhibited a positive correlation with all-cause mortality (hazard ratio, 1.78; 95% CI: 1.27-2.46, p < 0.001). CONCLUSIONS: A J-shaped relationship was identified between the TyG index and all-cause mortality in initial hemodialysis patients in China, with a threshold of 8.83 for all-cause mortality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".