Evidence map›Paper›PMID 39839831›Full record

ArticleFrontiers in cardiovascular medicine2024

Association between red blood cell distribution width-to-albumin ratio and prognosis in post-cardiac arrest patients: data from the MIMIC-IV database.

Yinhe Cai, Yao Zhang, Ningzhi Zhou, Yong Tang, Haixia Zheng, Hong Liu, Jiahua Liang, Ruixiang Zeng, Shengqing Song, Yu Xia

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yinhe Cai *Department of Cardiology, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Yao Zhang *Department of Cardiology, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Ningzhi ZhouDepartment of Cardiology, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Yong TangDepartment of Cardiology, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Haixia ZhengDepartment of Cardiology, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Hong LiuDepartment of Cardiology, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Jiahua LiangThe Department of Cardiovascular Disease, Meizhou Hospital of Traditional Chinese Medicine, Meizhou, China.
Ruixiang ZengDepartment of Critical Care Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Shengqing SongThe Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Yu XiaDepartment of Cardiology, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiac arrest (CA) triggers a systemic inflammatory response, resulting in brain and cardiovascular dysfunction. The red blood cell distribution width (RDW)-to-albumin ratio (RAR) has been widely explored in various inflammation-related diseases. However, the predictive value of RAR for the prognosis of CA remains unclear. We aimed to explore the correlation between the RAR index and the 30- and 180-day mortality risks in post-CA patients. Methods: Clinical data were extracted from the MIMIC-IV database. The enrolled patients were divided into three tertiles based on their RAR levels (<3.7, 3.7-4.5, >4.5). Restricted cubic spline, Kaplan-Meier (K-M) survival curves, and Cox proportional hazards regression model were used to explicate the relationship between the RAR index and all-cause mortality risk. Subgroup analyses were also conducted to increase stability and reliability. The receiver operator characteristic (ROC) analysis was used to assess the predictive ability of the RAR index, red blood cell distribution width, and serum albumin for 180-day all-cause mortality. Results: A total of 612 patients were eligible, including 390 men, with a mean age of 64.1 years. A non-linear relationship was observed between the RAR index and 180-day all-cause mortality, with a hazards ratio (HR) >1 when the RAR level exceeded 4.54. The K-M survival curve preliminarily indicated that patients in higher tertiles (T2 and T3) of the RAR index presented lower 30- and 180-day survival rates. An elevated RAR index was significantly associated with an increased 30-day [adjusted HR: 1.08, 95% confidence interval (CI): 1.01-1.15] and 180-day (adjusted HR: 1.09, 95% CI: 1.03-1.16) mortality risk. According to the ROC curve analysis, the RAR index outperformed the RDW and albumin in predicting all-cause 180-day mortality [0.6404 (0.5958-0.6850) vs. 0.6226 (0.5774-0.6679) vs. 0.3841 (0.3390-0.4291)]. The prognostic value of the RAR index for 180-day mortality was consistent across subgroups, and a significant interaction was observed in patients who were white, those with chronic pulmonary disease, or those without cerebrovascular disease. Conclusion: The RAR index is an independent risk factor for 30- and 180-day all-cause mortality in post-CA patients. The higher the RAR index, the higher the mortality. An elevated RAR index may be positively associated with adverse prognosis in post-CA patients, which can remind clinicians to quickly assess these patients.

Indexed as

albuminall-cause mortalitycardiac arrestMIMIC-IV databasered blood cell distribution width

Identifiers

PMID39839831
PMCPMC11747227

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.