Evidence map›Paper›PMID 37936706›Full record

ArticleFrontiers in immunology2023

Association between a four-parameter inflammatory index and all-cause mortality in critical ill patients with non-traumatic subarachnoid hemorrhage: a retrospective analysis of the MIMIC-IV database (2012-2019).

Yong-Wei Huang, Ye Zhang, Zong-Ping Li, Xiao-Shuang Yin

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
7.4field-weighted citation impact, top 2% of its field
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

35 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Observational
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

4 authors at 1 institution in 1 country.

Yong-Wei Huang *Department of Neurosurgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, Sichuan, China.
Ye Zhang *Department of Neurosurgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, Sichuan, China.
Zong-Ping LiDepartment of Neurosurgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, Sichuan, China.
Xiao-Shuang YinDepartment of Immunology, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, Sichuan, China.
Mianyang Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-traumatic subarachnoid hemorrhage (SAH), primarily due to the rupture of intracranial aneurysms, contributes significantly to the global stroke population. A novel biomarker, pan-immune-inflammation value (PIV) or called the aggregate index of systemic inflammation (AISI), linked to progression-free survival and overall survival in non-small-cell lung cancer and mortality in Coronavirus Disease 2019 (COVID-19) patients, has surfaced recently. Its role in non-traumatic SAH patients, however, remains under-researched. This study aims to determine the relationship between PIV and all-cause mortality in non-traumatic SAH patients. Methods: A retrospective analysis was conducted using data from the Medical Information Mart for Intensive Care (MIMIC-IV) database to examine the association between PIV and all-cause mortality in critically ill patients with non-traumatic SAH. PIV measurements were collected at Intensive Care Unit (ICU) admission, and several mortality measures were examined. To control for potential confounding effects, a 1:1 propensity score matching (PSM) method was applied. The optimal PIV cutoff value was identified as 1362.45 using X-tile software that is often used to calculate the optimal cut-off values in survival analysis and continuous data of medical or epidemiological research. The relationship between PIV and short- and long-term all-cause mortality was analyzed using a multivariate Cox proportional hazard regression model and Kaplan-Meier (K-M) survival curve analysis. Interaction and subgroup analyses were also carried out. Results: The study included 774 non-traumatic SAH patients. After PSM, 241 pairs of score-matched patients were generated. The Cox proportional hazard model, adjusted for potential confounders, found a high PIV (≥ 1362.45) independently associated with 90-day all-cause mortality both pre- (hazard ratio [HR]: 1.67; 95% confidence intervals (CI): 1.05-2.65; P = 0.030) and post-PSM (HR: 1.58; 95% CI: 1.14-2.67; P = 0.042). K-M survival curves revealed lower 90-day survival rates in patients with PIV ≥ 1362.45 before (31.1% vs. 16.1%%, P < 0.001) and after PSM (68.9% vs. 80.9%, P < 0.001). Similarly, elevated PIV were associated with increased risk of ICU (pre-PSM: HR: 2.10; 95% CI: 1.12-3.95; P = 0.02; post-PSM: HR: 2.33; 95% CI: 1.11-4.91; P = 0.016), in-hospital (pre-PSM: HR: 1.91; 95% CI: 1.12-3.26; P = 0.018; post-PSM: 2.06; 95% CI: 1.10-3.84; P = 0.034), 30-day (pre-PSM: HR: 1.69; 95% CI: 1.01-2.82; P = 0.045; post-PSM: 1.66; 95% CI: 1.11-2.97; P = 0.047), and 1-year (pre-PSM: HR: 1.58; 95% CI: 1.04-2.40; P = 0.032; post-PSM: 1.56; 95% CI: 1.10-2.53; P = 0.044) all-cause mortality. The K-M survival curves confirmed lower survival rates in patients with higher PIV both pre- and post PSM for ICU (pre-PSM: 18.3% vs. 8.4%, P < 0.001; post-PSM:81.7 vs. 91.3%, P < 0.001), in-hospital (pre-PSM: 25.3% vs. 12.8%, P < 0.001; post-PSM: 75.1 vs. 88.0%, P < 0.001), 30-day (pre-PSM: 24.9% vs. 11.4%, P < 0.001; post-PSM:74.7 vs. 86.3%, P < 0.001), and 1-year (pre-PSM: 36.9% vs. 20.8%, P < 0.001; P = 0.02; post-PSM: 63.1 vs. 75.1%, P < 0.001) all-cause mortality. Stratified analyses indicated that the relationship between PIV and all-cause mortality varied across different subgroups. Conclusion: In critically ill patients suffering from non-traumatic SAH, an elevated PIV upon admission correlated with a rise in all-cause mortality at various stages, including ICU, in-hospital, the 30-day, 90-day, and 1-year mortality, solidifying its position as an independent mortality risk determinant. This study represents an attempt to bridge the current knowledge gap and to provide a more nuanced understanding of the role of inflammation-based biomarkers in non-traumatic SAH. Nevertheless, to endorse the predictive value of PIV for prognosticating outcomes in non-traumatic SAH patients, additional prospective case-control studies are deemed necessary.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsSubarachnoid HemorrhageCritical IllnessHumansInflammationRetrospective StudiesbiomarkersMIMIC-IVmortalitypan-immune-inflammation value (PIV)propensity score matching (PSM)subarachnoid hemorrhage (SAH)

Identifiers

PMID37936706
PMCPMC10626529
OpenAlexW4387879435

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.