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)

医学 重症监护室 倾向得分匹配 蛛网膜下腔出血 比例危险模型 内科学 回顾性队列研究 人口 危险系数 混淆 创伤性脑损伤 冲程(发动机) 生存分析 机械工程 置信区间 环境卫生 精神科 工程类
作者
Yongwei Huang,Ye Zhang,Zongping Li,Xiao-Shuang Yin
出处
期刊:Frontiers in Immunology [Frontiers Media SA]
卷期号:14 被引量:5
标识
DOI:10.3389/fimmu.2023.1235266
摘要

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.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.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.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.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
2秒前
3秒前
4秒前
lyk发布了新的文献求助10
4秒前
辛勤大米完成签到,获得积分10
5秒前
大知闲闲发布了新的文献求助10
5秒前
恭喜发布了新的文献求助10
7秒前
挡住所有坏运气888完成签到,获得积分10
7秒前
Li发布了新的文献求助10
8秒前
ding应助神勇的煎蛋采纳,获得10
9秒前
辛勤大米发布了新的文献求助10
9秒前
JamesPei应助从容的白容采纳,获得10
9秒前
Penzias发布了新的文献求助10
12秒前
ZSS完成签到,获得积分10
13秒前
斯文败类应助嘟嘟图图采纳,获得10
13秒前
顾矜应助zzzzw采纳,获得10
14秒前
Hedya完成签到,获得积分10
15秒前
16秒前
20秒前
21秒前
蜘蛛侠发布了新的文献求助150
22秒前
kavins凯旋完成签到,获得积分10
23秒前
23秒前
这届视网膜好带不完成签到,获得积分10
23秒前
花佩剑完成签到,获得积分10
24秒前
科研通AI2S应助蜗牛采纳,获得10
24秒前
嘟嘟图图发布了新的文献求助10
25秒前
核桃发布了新的文献求助30
27秒前
27秒前
花佩剑发布了新的文献求助10
27秒前
牛马学生完成签到,获得积分10
27秒前
大知闲闲完成签到,获得积分20
28秒前
止戈完成签到,获得积分10
28秒前
Kevin63完成签到,获得积分10
29秒前
30秒前
一个橙完成签到,获得积分10
31秒前
31秒前
32秒前
33秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6025037
求助须知:如何正确求助?哪些是违规求助? 7659561
关于积分的说明 16178111
捐赠科研通 5173271
什么是DOI,文献DOI怎么找? 2768125
邀请新用户注册赠送积分活动 1751495
关于科研通互助平台的介绍 1637631