Predictive Accuracy of the Veterans Aging Cohort Study Index for Mortality With HIV Infection
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Bibliographic record
Abstract
BACKGROUND: By supplementing an index composed of HIV biomarkers and age (restricted index) with measures of organ injury, the Veterans Aging Cohort Study (VACS) index more completely reflects risk of mortality. We compare the accuracy of the VACS and restricted indices (1) among subjects outside the Veterans Affairs Healthcare System, (2) more than 1-5 years of prior exposure to antiretroviral therapy (ART), and (3) within important patient subgroups. METHODS: We used data from 13 cohorts in the North American AIDS Cohort Collaboration (n = 10, 835) limiting analyses to HIV-infected subjects with at least 12 months exposure to ART. Variables included demographic, laboratory (CD4 count, HIV-1 RNA, hemoglobin, platelets, aspartate and alanine transaminase, creatinine, and hepatitis C status), and survival. We used C-statistics and net reclassification improvement (NRI) to test discrimination varying prior ART exposure from 1 to 5 years. We then combined Veterans Affairs Healthcare System (n = 5066) and North American AIDS Cohort Collaboration data, fit a parametric survival model, and compared predicted to observed mortality by cohort, gender, age, race, and HIV-1 RNA level. RESULTS: Mean follow-up was 3.3 years (655 deaths). Compared with the restricted index, the VACS index showed greater discrimination (C-statistics: 0.77 vs. 0.74; NRI: 12%; P < 0.0001). NRI was highest among those with HIV-1 RNA <500 copies per milliliter (25%) and age ≥50 years (20%). Predictions were similar to observed mortality among all subgroups. CONCLUSIONS: VACS index scores discriminate risk and translate into accurate mortality estimates over 1-5 years of exposure to ART and for diverse patient subgroups from North American.
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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) | 0.001 | 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