Evidence map›Paper›PMID 39101009›Full record

ArticleFrontiers in nutrition2024

Associations between serum albumin level trajectories and clinical outcomes in sepsis patients in ICU: insights from longitudinal group trajectory modeling.

Xin Tie, Yanjie Zhao, Ting Sun, Ran Zhou, Jianbo Li, Jing Su, Wanhong Yin

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Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

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0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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  20. Dynamic HGI trajectories and their impact on survival in patients with sepsis: a machine learning prognostic model.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025
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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xin Tie *Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Yanjie Zhao *Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
Ting Sun *Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Ran ZhouDepartment of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Jianbo LiDepartment of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Jing SuDepartment of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Wanhong YinDepartment of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis triggers a strong inflammatory response, often leading to organ failure and high mortality. The role of serum albumin levels in sepsis is critical but not fully understood, particularly regarding the significance of albumin level changes over time. This study utilized Group-based Trajectory Modeling (GBTM) to investigate the patterns of serum albumin changes and their impact on sepsis outcomes. Methods: We conducted a retrospective analysis on ICU patients from West China Hospital (2015-2022), employing GBTM to study serum albumin fluctuations within the first week of ICU admission. The study factored in demographics, clinical parameters, and comorbidities, handling missing data through multiple imputation. Outcomes assessed included 28-day mortality, overall hospital mortality, and secondary complications such as AKI and the need for mechanical ventilation. Results: Data from 1,950 patients revealed four serum albumin trajectories, showing distinct patterns of consistently low, increasing, moderate, and consistently high levels. These groups differed significantly in mortality, with the consistently low level group experiencing the highest mortality. No significant difference in 28-day mortality was observed among the other groups. Subgroup analysis did not alter these findings. Conclusion: The study identified four albumin trajectory groups in sepsis patients, highlighting that those with persistently low levels had the worst outcomes, while those with increasing levels had the best. Stable high levels above 30 g/L did not change outcomes significantly. These findings can inform clinical decisions, helping to identify high-risk patients early and tailor treatment approaches.

Indexed as

albumin (ALB)clinical outcomescritical caregroup-based trajectory modelingsepsis

Identifiers

PMID39101009
PMCPMC11294201

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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 OpenQuestion graph.