Prognostic roles of neutrophil–lymphocyte, monocyte-lymphocyte and platelet-lymphocyte ratios for long-term all-cause mortality in heart failure
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Bibliographic record
Abstract
• White cell counts reflect the bidirectional relationship of heart failure and inflammation. • NLR, MLR and PLR are associated with survival outcomes in heart failure patients. • NLR was independently correlated with all-cause long term-mortality of heart failure patients. • We suggest the cut-off NLR≥3.56 for long-term fatality prediction in heart failure. Heart failure (HF) and inflammation have a bidirectional relation leading to activation and adaptation of multiple cellular lines, including leucocyte subtypes and platelets. We aimed to assess and compare the predictive value of the neutrophil–lymphocyte (NLR), monocyte-lymphocyte (MLR) and platelet-lymphocyte (PLR) ratios for all-cause long-term mortality in HF. This is an observational retrospective cohort study that included patients from the HI-HF cohort that survived the initial hospitalization. Vital status and survival time were assessed in June 2020. We analyzed 1018 HF patients with a mean age of 72.32 ± 10.29 years and 53.54 % women. All-cause long-term mortality was 38.21 % after a median follow-up time of 68 [38 – 82] months. NLR (AUC 0.667, 95 %CI 0.637 – 0.697), MLR (AUC 0.670, 95 %CI 0.640 – 0.700) and PLR (AUC 0.606, 95 %CI 0.574 – 0.636) were predictors of all-cause mortality. In multivariable Cox proportional hazards analysis, NLR≥3.56 was the only hematological index independent predictor of fatality (HR 1.36, 95 %CI 1.05 – 1.76). Of the three hematological indices, NLR was the only independent predictor of all-cause long-term mortality of HF patients. We suggest NLR≥3.56 as an auxiliary prognostic biomarker for the evaluation of HF patients.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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