Associations of Multimarkers of Metabolic Malnutrition and Inflammation with All-Cause Mortality by Multimorbidity Status
Bibliographic record
Abstract
Background/Objectives: The metabolic vulnerability index (MVX)—a composite biomarker reflecting metabolic malnutrition and inflammation—is associated with increased mortality risk, but its association across different levels of chronic disease burden has not been explored. We aimed to examine the associations of MVX and its subcomponents (Inflammation Vulnerability Index, IVX and Metabolic Malnutrition Index, MMX) with all-cause mortality according to multimorbidity status. Methods: In the PREVEND study, which included 6054 participants (mean age 54 years; 49.5% male), MVX was calculated using six plasma biomarkers measured simultaneously via nuclear magnetic resonance spectroscopy. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated. Results: During a median follow-up of 14.0 years, 911 deaths were recorded. In analyses adjusted for several established risk factors, the HRs (95% CIs) of mortality per 1 standard deviation increment in MVX were 1.32 (1.13–1.54; p < 0.001), 1.23 (1.08–1.40; p = 0.002), and 1.29 (1.16–1.43; p < 0.001) for individuals with no disease, one disease, and multimorbidity, respectively. The corresponding HRs (95% CIs) were 1.22 (1.05–1.42; p = 0.010), 1.17 (1.03–1.34; p = 0.015), and 1.25 (1.13–1.38; p < 0.001) for IVX and 1.29 (1.11–1.48; p = 0.001), 1.16 (1.02–1.31; p = 0.032), and 1.14 (1.03–1.25; p = 0.004) for MMX. The ratio of HRs showed no statistical evidence that sex modified the associations of MVX, IVX, and MMX with mortality in each multimorbidity category. However, the associations appeared stronger in males with chronic disease and in females without chronic conditions, suggesting possible sex-related trends. Conclusions: MVX, IVX, and MMX are independent risk indicators of all-cause mortality regardless of the burden of chronic disease, with MVX showing the strongest associations across different multimorbidity statuses. MMX should be interpreted as a proxy for metabolic malnutrition rather than a direct nutritional assessment tool.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".