J-Shaped Relationship of the Triglyceride-Glucose Index with All-Cause Mortality in Initial Hemodialysis Patients in China: A Multicenter, Retrospective Cohort Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it