Evidence mapPaperPMID 42332525Full record

ArticleMedicine2026

Association between the advanced lung cancer inflammation index and all-cause mortality in critically ill patients with atrial fibrillation.

Yingshan Lin, Renzhe Lin, Duo Yang, Shujun Ye, Longsheng Zhang, Yuxin Lin

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Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Yingshan LinDepartment of Anesthesiology, Dongguan Houjie Hospital, Dongguan, Guangdong Province, China.
Renzhe LinDepartment of Anesthesiology, Jieyang's Hospital, Jieyang, Guangdong Province, China.
Duo YangDepartment of Anesthesiology, Jieyang's Hospital, Jieyang, Guangdong Province, China.
Shujun YeDepartment of Anesthesiology, Jieyang's Hospital, Jieyang, Guangdong Province, China.
Longsheng ZhangDepartment of Anesthesiology, Jieyang's Hospital, Jieyang, Guangdong Province, China.
Yuxin LinDepartment of Anesthesiology, Dongguan Guancheng Hospital, Dongguan, Guangdong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evidence indicates that the advanced lung cancer inflammation index (ALI) is a prognostic tool for patient outcomes across various diseases. Nevertheless, its application in atrial fibrillation (AF) patients remains underexplored. This study aimed to evaluate the prognostic significance of ALI in critically ill AF patients. AF patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database were enrolled. ALI was evaluated using body mass index, serum albumin levels, and neutrophil-to-lymphocyte ratio. Patients were stratified into quartiles based on log2-transformed ALI. Clinical endpoints were 30- and 90-day all-cause mortality (ACM). The relationship between ALI and patient outcomes was assessed using Cox proportional hazards models and Kaplan-Meier curves. Restricted cubic splines (RCS) were employed to investigate the nonlinear association between ALI and outcomes. Subgroup and sensitivity analyses were performed to verify the stability. Receiver operating characteristic curves evaluated ALI's predictive efficacy. Multivariable Cox analysis revealed that a higher log2-ALI was linked to a reduced risk of 30-day ACM in AF patients (HR, 0.85; 95% CI: 0.79-0.92; P < .001). Compared with quartile Q1, quartiles Q2 (HR, 0.75; 95% CI: 0.59-0.96), Q3 (HR, 0.58; 95% CI: 0.44-0.78), and Q4 (HR, 0.52; 95% CI: 0.38-0.71) were associated with lower 30-day ACM risk. Similar results were observed for 90-day ACM. Kaplan-Meier curves showed that patients with higher log2-ALI levels had better survival rates at both 30 days and 90 days. RCS indicates a nonlinear association between log2-ALI and 30-day and 90-day ACM, revealing a threshold effect. When the indicator is below 5.39, higher log2-ALI levels are strongly linked to a lower ACM in AF patients, whereas values above 5.39 correlate with an increased ACM. These findings were consistent across most subgroups. The receiver operating characteristic curve demonstrates that ALI outperforms single nutritional or inflammatory markers in predicting prognosis in AF patients. Its predictive accuracy is further improved when combined with the sequential Organ Failure Assessment score. Elevated log2-ALI is independently associated with reduced ACM risk in AF patients. Maintaining ALI within an optimal range via targeted interventions is crucial for reducing short-to-medium-term mortality, highlighting ALI's potential as a valuable prognostic biomarker for risk assessment and individualized management.

Indexed as

Atrial FibrillationCritical IllnessInflammationLung NeoplasmsAgedAged, 80 and overFemaleHumansKaplan-Meier EstimateMaleMiddle AgedNeutrophilsPrognosisProportional Hazards ModelsROC Curveadvanced lung cancer inflammation indexAll-cause mortalityAtrial fibrillationMIMIC-IV

Identifiers

PMID42332525
PMCPMC13286451

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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 Socratic graph.