A frailty index predicts post-liver transplant morbidity and mortality in HIV-positive patients
Bibliographic record
Abstract
BACKGROUND: We hypothesized that frailty acts as a measure of health outcomes in the context of LT. The aim of this study was to explore frailty index across LT, as a measure of morbidity and mortality. This was a retrospective observational study including all consecutive 47 HIV+patients who received LT in Modena, Italy from 2003 to June 2015. METHODS: frailty index (FI) was constructed from 30 health variables. It was used both as a continuous score and as a categorical variable, defining 'most frail' a FI > 0.45. FI change across transplant (deltaFI, ΔFI) was calculated as the difference between year 1 FI (FI-Y1) and pre-transplant FI (FI-t0). The outcomes measures were mortality and "otpimal LT" (defined as being alive without multi-morbidity). RESULTS: Median value of FI-t0 was 0.48 (IQR 0.42-0.52), FI-Y1 was 0.31 (IQR 0.26-0.41). At year five mortality rate was 45%, "optimal transplant" rate at year 1 was 38%. All the patients who died in the post-LT were most frail in the pre-LT. ΔFI was a predictor of mortality after correction for age and MELD (HR = 1.10, p = 0.006) and was inversely associated with optimal transplant after correction for age (HR = 1.04, p = 0.01). CONCLUSIONS: We validated FI as a valuable health measure in HIV transplant. In particular, we found a relevant correlation between FI strata at baseline and mortality and a statistically significant correlation between, ΔFI and survival rate.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".