Blood cell counts as a source of evidence for prognostic information in patients with acute heart failure: findings from a large, single-centre study
Bibliographic record
Abstract
Abstract Background Inflammatory processes are increasingly recognised as pivotal in the pathophysiology of heart failure (HF) and several inflammatory biomarkers have emerged as potential tools for predicting adverse outcomes in patients with chronic HF. Red blood cell distribution width (RDW), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and monocyte-to-lymphocyte ratio (MLR) are easy to obtain, inexpensive and rapidly available through routine blood tests. Their combined assessment may represent a valuable tool for predicting prognosis in the context of acute heart failure (AHF). Aims To assess the prognostic utility of RDW, NLR, MLR and PLR in a cohort of inpatients with AHF. Methods In this single-centre, observational study, data from patients admitted to our hospital between 1st January 2016 and 31st December 2023 were retrospectively collected. AHF was diagnosed according to the updated European Society of Cardiology guidelines. RDW, NLR, MLR and PLR measurements were considered elevated if values exceeded 14.6%, 2, 0.4 and 137, respectively. Participants were stratified into five cohorts according to the number of increased biomarkers reported (none, 1, 2, 3, or 4). Baseline characteristics and echocardiographic measurements were assessed for each group. Independent predictors of RDW, NLR, MLR and PLR were identified using linear regression analysis and the association between different cohorts and outcomes was assessed using Cox proportional hazards analysis. The outcomes were the composite of all-cause mortality or readmission due to heart failure (HF) and all-cause mortality at 90 days after discharge. Results A total of 8,127 patients, aged 81 years, of whom 4,312 (53%) men, were enrolled. Only 260 (3%) participants had normal biomarker levels, while 1,031 (13%), 1,717 (21%), 2,654 (33%) and 2,465 (30%) had 1, 2, 3 or all biomarkers elevated, respectively. Patients with higher biomarker levels were older, more likely to be male, had a higher prevalence of diabetes and hypertension and exhibited greater N-terminal pro-brain natriuretic peptide (NT-proBNP) measurements. RDW, NLR, MLR and PLR were found to be independent predictors of the composite outcome of all-cause mortality or rehospitalisation due to HF, as well as all-cause mortality. Compared with the cohort of patients with all normal biomarkers, those with increased biomarker levels presented a greater risk of developing adverse events, both in univariate and multivariate analyses. Conclusions RDW, NLR, MLR and PLR are frequently elevated in patients diagnosed with acute HF. Each biomarker independently predicts adverse events and their combination may be adopted as a valid tool to provide prognostic information.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".