Prognostic value of non‐invasive scores based on liver stiffness measurement, spleen diameter and platelets in <scp>HIV</scp>‐infected patients
Bibliographic record
Abstract
BACKGROUND AND AIMS: People living with HIV (PLWH) are at high risk for advanced chronic liver disease and related adverse outcomes. We aimed to validate the prognostic value of non-invasive scores based on liver stiffness measurement (LSM) and on markers of portal hypertension (PH), namely platelets and spleen diameter, in PLWH. METHODS: We combined data from eight international cohorts of PLWH with available non-invasive scores, including LSM and the composite biomarkers liver stiffness-spleen size-to-platelet ratio score (LSPS), LSM-to-Platelet ratio (LPR) and PH risk score. Incidence and predictors of all-cause mortality, any liver-related event and classical hepatic decompensation were determined by survival analysis, controlling for competing risks for the latter two. Non-invasive scores were assessed and compared using area under the receiver operating curve (AUROC). RESULTS: We included 1695 PLWH (66.8% coinfected with hepatitis C virus). During a median follow-up of 4.7 (interquartile range 2.8-7.7) years, the incidence rates of any liver-related event, all-cause mortality and hepatic decompensation were 13.7 per 1000 persons-year (PY) (95% confidence interval [CI], 11.4-16.3), 13.8 per 1000 PY (95% CI, 11.6-16.4) and 9.9 per 1000 PY (95% CI, 8.1-12.2), respectively. The AUROC of LSM was similar to that of the composite biomarkers, ranging between 0.83 and 0.86 for any liver-related event, 0.79-0.85 for all-cause mortality and 0.87-0.88 for classical hepatic decompensation. All individual non-invasive scores remained independent predictors of clinical outcomes in multivariable analysis. CONCLUSIONS: Non-invasive scores based on LSM, spleen diameter and platelets predict clinical outcomes in PLWH. Composite biomarkers do not achieve higher prognostic performance compared to LSM alone.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".