Evidence map›Paper›PMID 40152765›Full record

ArticleShock (Augusta, Ga.)2025

PREDICTORS AND OUTCOMES OF ACUTE KIDNEY INJURY IN INTRACEREBRAL HEMORRHAGE PATIENTS: EVIDENCE FROM A LARGE-SCALE NATIONAL DATABASE ANALYSIS.

Binbin Tian, Xuanhe Tang, Linling He, Junfen Cheng, Jian Wang, Silin Liang, Junde Mo, Chunbo Chen

Abstract read
In one paragraph

Article in Shock (Augusta, Ga.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Observational
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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

8 authors.

Binbin TianDepartment of Critical Care Medicine, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, China
Xuanhe TangDepartment of Intensive Care Unit of Cardiac Surgery, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
Linling HeDepartment of Critical Care Medicine, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, China
Junfen ChengDepartment of Respiration, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
Jian WangDivision of Orthopaedic Surgery, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
Silin LiangDepartment of Critical Care Medicine, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, China
Junde MoDepartment of Critical Care Medicine, Central People’s Hospital of Zhanjiang, Zhanjiang, Guangdong, China
Chunbo ChenDepartment of Critical Care Medicine, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, ChinaORCID 0000-0001-5662-497

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

abstractBackground: Acute kidney injury (AKI) is a significant complication in patients with intracerebral hemorrhage (ICH). This study sought to explore the incidence, risk factors, and outcomes of AKI in ICH patients using a comprehensive national database. Methods: Data from the Nationwide Inpatient Sample database (2010-2019) were analyzed. This analysis compared demographics, comorbidities, complications, mortality, and healthcare utilization between ICH patients who developed AKI and those who did not. Multivariate logistic regression was used to identify risk factors for AKI and assess their impact on in-hospital outcomes. Results: The incidence of AKI among ICH patients increased from 10.7% in 2010 to 19.6% by 2019, yielding an overall incidence rate of 15%. Risk factors included, Black race, comorbidities (≥3), teaching hospital, and specific preexisting conditions such as congestive heart failure, coagulopathy, diabetes with chronic complications, fluid and electrolyte disorders, other neurological disorders, obesity, paralysis, chronic kidney disease excluding end-stage renal disease, peptic ulcer disease excluding bleeding, and weight loss. Conversely, female sex and elective admissions acted as protective factors. AKI-related in-hospital complications encompassed acute myocardial infarction, pneumonia, sepsis, cardiac arrest, respiratory failure, and mechanical ventilation. AKI was associated with higher in-hospital mortality (26.9% vs. 18.5%), prolonged hospital stays (median duration of 9 days vs. 5 days for non-AKI patients) and increased requirement for dialysis (3.1% vs. 0.0%). Healthcare costs were significantly elevated, with median charges doubling for AKI patients. Conclusion: AKI is a frequent and severe complication among patients with ICH, markedly influencing clinical outcomes and healthcare resource utilization. Early identification of high-risk patients and implementation of effective preventive strategies are critical to enhance patient management and outcomes.

Indexed as

Acute Kidney InjuryCerebral HemorrhageAgedAged, 80 and overDatabases, FactualFemaleHospital MortalityHumansIncidenceMaleMiddle AgedRisk FactorsUnited StatesAcute kidney injuryAKI—acute kidney injuryAMI—acute myocardial infarctionCI—confidence intervalESRD—end-stage renal diseaseICD-10-CM—international classification of Diseases, Tenth Revision, Clinical ModificationICD-9-CM—International Classification of Diseases, Ninth Revision, Clinical ModificationICH—intracerebral hemorrhageintracerebral hemorrhageLOS—length of staynationwide inpatient sampleNIS—nationwide inpatient sampleOR—odds ratiorisk factors

Identifiers

PMID40152765
PMCPMC12105942

What OpenQuestion holds

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Registered trials

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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.