ArticleMedicine2026
Substitutional value of METS-IR for biochemical components of life's essential 8 in predicting incident mild cognitive impairment: A longitudinal cohort study.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Insulin resistance is closely associated with mild cognitive impairment (MCI) and sarcopenia. The predictive utility of the metabolic score for insulin resistance (METS-IR) for MCI across different sarcopenia strata and its potential as a substitute for life's essential 8 (LE-8) remains unclear. This prospective cohort study used data from the China Health and Retirement Longitudinal Study. Participants aged ≥45 years without baseline MCI or memory-related disease and with biomarker and cognitive data were included. METS-IR was calculated from fasting blood glucose, triglycerides, high-density lipoprotein cholesterol, and body mass index. LE-8 was scored using an adapted American Heart Association framework. Associations between METS-IR and incident MCI stratified by sarcopenia status were assessed using Cox proportional hazards models and restricted cubic splines. Machine-learning analyses using 11 classifiers and stratified 10-fold cross-validation evaluated the incremental and substitutional value of METS-IR within LE-8-based prediction models. A total of 4980 participants were included. Higher METS-IR was associated with a less favorable cardiometabolic profile. In multivariable-adjusted Cox models, compared with the lowest quartile of METS-IR, hazard ratios for incident MCI were 0.94 (95% confidence interval [CI]: 0.79-1.11) for quartile 2, 0.65 (95% CI: 0.53-0.78) for quartile 3, and 0.72 (95% CI: 0.59-0.87) for quartile 4. Restricted cubic spline analyses showed a significant nonlinear association between METS-IR and incident MCI in the overall sample (P for overall < .001, P for nonlinear = .017). A significant overall association was also observed in the possible sarcopenia subgroup, although nonlinearity was not statistically significant. No significant nonlinear or overall association was observed in the nonsarcopenia or confirmed sarcopenia subgroups. In prediction analyses, LE-8-based models achieved moderate discrimination (area under curve, AUC: 0.525-0.696). Adding METS-IR yielded a modest but statistically significant improvement only in AdaBoost (ΔAUC = +0.00487, P < .05). When selected biochemical LE-8 components were substituted by METS-IR, discrimination improved in several algorithms in multiple models, particularly in multilayer perceptron (P < .01). METS-IR showed a significant nonlinear association with incident MCI, with the lowest risk observed at intermediate-to-higher METS-IR levels. The incremental and substitutional value beyond LE-8 was limited, model-dependent, and requires external validation.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.