ArticleMedicine2026
Correlation between red cell distribution width to total calcium ratio and in-hospital mortality in patients with non-idiopathic pulmonary fibrosis interstitial lung diseases: A retrospective cohort study from the MIMIC-IV database.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Development of interpretable machine learning models for predicting the probability of sepsis in patients with pulmonary fibrosis in the intensive care unit: based on MIMIC-IV and multi-database validation.Frontiers in cellular and infection microbiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This study aims to investigate the potential of the red cell distribution width to total calcium ratio (RCR) as a biomarker for in-hospital mortality in patients with non-idiopathic pulmonary fibrosis (IPF) interstitial lung diseases. A retrospective cohort analysis was carried out utilizing the Medical Information Mart for Intensive Care database, including 1138 patients with non-idiopathic pulmonary fibrosis interstitial lung diseases. Patients were divided into a survivor group (n = 1023) and a non-survivor group (n = 115) based on in-hospital mortality. The Boruta algorithm combined with a machine learning-based random forest algorithm was employed to calculate Shapley Additive Explanations (SHAP) values to identify clinical indicators significantly contributing to in-hospital mortality. A nomogram model based on logistic regression was constructed to assess the relationship between RCR and in-hospital mortality. Compared to the survivor group, the non-survivor group's average age was significantly older (73.00 ± 10.67 years vs 69.83 ± 13.24 years, P = .013), and RCR was significantly elevated in the non-survivor group (1.83 ± 0.30 vs 1.73 ± 0.27, P <.001). After adjusting for white blood cell count, blood urea nitrogen (BUN), sodium levels, and pneumonia in the model, the odds ratio for RCR was 2.283 (95% CI: 1.108-4.649, P = .024). BUN was identified as a mediator, accounting for approximately 14.6% of the indirect effect. Subgroup analyses revealed a stronger association of RCR with in-hospital mortality in female patients, those aged ≤65 years, and patients with hypertension. The nomogram model's C-index was 0.771 for the training set and 0.764 for the validation set. The training set's area under the curve was 0.771 (95% CI: 0.712-0.829), while the validation set's was 0.764 (95% CI: 0.706-0.821). RCR serves as a simple and effective biomarker for predicting in-hospital mortality risk in patients with non-idiopathic pulmonary fibrosis, with BUN playing a mediating role in this association.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.