Neutrophil-Lymphocyte Ratio as an Independent Predictor of Survival in Pulmonary Arterial Hypertension: An Exploratory Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BackgroundThe blood neutrophil-to-lymphocyte ratio (NLR) has recently emerged as a powerful predictor of adverse outcomes in some cardiovascular and lung diseases. Pulmonary arterial hypertension (PAH) is a lethal vasculopathy associated with increased inflammation. Although PAH exhibits a higher prevalence among women, men have a poorer prognosis. We investigated the NLR as an independent predictor of transplant-free survival in PAH.MethodsWe performed a retrospective analysis of 78 PAH patients from the Quebec PAHBiobank (71% female). We used univariate and multivariate (adjusted for age, sex, renal function, and disease severity) Cox regression analyses to assess the relationship between the NLR and transplant-free survival, in the whole sample, and according to sex. The NLR was categorized as high (≥ 4.8) or low (< 4.8) using receiver operating characteristic analysis. Unadjusted Kaplan-Meier analysis estimated survival per NLR category.ResultsThe NLR was higher in patients who died, compared to that in patients who had transplant-free survival (P < 0.05). The NLR was an independent predictor of event-free survival in PAH (unadjusted hazard ratio: 1.11, 95% confidence interval: 1.04-1.18, which remained significant after adjustment for covariates). The high-NLR group had lower 1-, 3-, and 5-year survival compared to those with a low NLR (P < 0.001). The NLR remains a predictor of survival in women.ConclusionsThe NLR is an independent predictor of transplant-free survival in PAH. We report a potential sexual dimorphism in the ability of the NLR to predict mortality in PAH, emphasizing the importance of considering sex-related differences in the development of biomarkers in PAH.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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