Evidence map›Paper›PMID 39780494›Full record

ArticleRenal failure2025

Association between renal mean perfusion pressure and prognosis in patients with sepsis-associated acute kidney injury: insights from the MIMIC IV database.

Yipeng Fang, Aizhen Dou, Hui Xie, Yunfei Zhang, Weiwei Zhu, Yingjin Zhang, Caifeng Li, Yanchao Su, Ying Gao, Keliang Xie

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Article in Renal failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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9citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Yipeng FangDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Aizhen DouDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Hui XieFirth Clinical College, XinXiang Medical University, Xinxiang, Henan, China.
Yunfei ZhangEditorial Department of Journal, Tianjin Hospital, Tianjin, China.
Weiwei ZhuDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Yingjin ZhangState Key Laboratory of Experimental Hematology, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Caifeng LiDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Yanchao SuDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Ying GaoDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Keliang XieDepartment of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the association between renal mean perfusion pressure (MPP) and prognosis in sepsis-associated acute kidney injury (SA-AKI).

methodsData were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Group-based trajectory modeling (GBTM) was applied to identify dynamic MPP patterns, while restricted cubic spline (RCS) curves were utilized to confirm the non-linear relationship between MPP and mortality. Cox regression analysis assessed the risk of mortality across different MPP levels, adjusting for potential confounders. Subgroup analyses and sensitivity analyses were conducted to ensure the robustness of the findings.

resultsA total of 2318 patients with SA-AKI were stratified into five MPP trajectories by GBTM. Patients in Traj-1 and Traj-2, characterized by consistently low MPP (<60 mmHg), demonstrated markedly higher 90-d mortality (62.86% and 26.98%). RCS curves revealed a non-linear inverse relationship between MPP and 90-d mortality, identifying 60 mmHg as the optimal threshold. Patients with MPP ≤ 60 mmHg exhibited significantly elevated 90-d mortality compared to those with MPP > 60 mmHg (29.81%

conclusionsDynamic MPP trajectory serves as a valuable prognostic biomarker for SA-AKI. Early monitoring of MPP trends offers critical insights into renal perfusion management, potentially improving outcomes in SA-AKI.

Indexed as

Acute Kidney InjuryDatabases, FactualSepsisAgedFemaleHumansIntensive Care UnitsKidneyMaleMiddle AgedPrognosisProportional Hazards ModelsRetrospective StudiesRisk Factorscentral venous pressuremean arterial pressuremean perfusion pressureSepsissepsis-associated acute kidney injury

Identifiers

PMID39780494
PMCPMC11722017

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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.