Development and Internal Validation of a Prognostic Model for 4-Year Risk of Metabolic Syndrome in Adults: A Retrospective Cohort Study
Bibliographic record
Abstract
PURPOSE: A prognostic prediction model for metabolic syndrome can help nurses or physicians evaluate the future individual absolute risk of MetS in order to develop personalized care strategies. We aimed to derive and internally validate a prognostic prediction model for 4-year risk of metabolic syndrome in adults. PATIENTS AND METHODS: This was a retrospective cohort study conducted in a tertiary care setting, and the dataset was obtained from the Healthcare Information and Management Systems of a tertiary hospital. The cohort included Chinese adults attending health examination from 1 January 2011 to 31 December 2014. A total of 6793 participants without metabolic syndrome were included in the cohort and were followed up for 4 years. Available candidate predictors in the dataset were weight, MCV, MCH, AST, ALT, BMI, NGC, TC, serum uric acid, gender, smoking, WBC, LC, Hb, HCT, and age. A logistic regression model was adopted to build the risk equation, and bootstrapping was used when considering internal validation. Calibration, discrimination, and the clinical utility were calculated for the model's performance. RESULTS: Of the 6793 participants, 1750 participants were diagnosed with metabolic syndrome within 4 years. The developed prediction model contained 5 predictors (body mass index, age, total cholesterol, alanine transaminase, and serum uric acid). After internal validation, the C-statistic was 0.783 (95% CI, 0.772-0.795). Additionally, the current model had good calibration. Calibration slope was 0.995 (95% CI, 0.934-1.058), and calibration intercept was -0.008 (95% CI, -0.088-0.073). The Brier score was 0.156. The decision-curve analysis indicated that the prediction model provided greater net benefit than the default strategies of providing treatment or not providing treatment for all patients. CONCLUSION: A prognostic risk prediction model for determining 4-year risk of metabolic syndrome onset in adults was developed and internally validated. This model was based on routine clinical measurements that quantified individual future risk of metabolic syndrome.
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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 | 0.035 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".