Prognostic value of stress hyperglycemia ratio in critically Ill patients with acute kidney injury: a machine learning-driven retrospective cohort analysis.

Yichun Shuai, Yan Liu, Xiahong Yang, Zhe Chen, Qiaoqian Wan, Jie Zhao, Xin Wang

Abstract read

In one paragraph

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

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yichun Shuai *Department of Anesthesiology, Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan Province China.

Yan Liu *Department of Anesthesiology, Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan Province China.

Xiahong YangDepartment of Anesthesiology, Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan Province China.

Zhe ChenDepartment of Thoracic Surgery, Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan Province China.

Qiaoqian WanDepartment of Anesthesiology, Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan Province China.

Jie ZhaoDepartment of Anesthesiology, Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan Province China.

Xin WangDepartment of Anesthesiology, Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan Province China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Acute kidney injury (AKI) is a serious complication in critically ill patients, contributing to high morbidity and mortality. The stress hyperglycemia ratio (SHR), defined as the ratio of admission blood glucose to estimated average glucose derived from HbA1c, has been previously linked to outcomes in cardiovascular and cerebrovascular conditions, but its role in predicting short-term mortality in ICU patients with AKI remains unclear. This study explores the association between SHR and short-term mortality, and developed machine learning models to improve prognostic accuracy. Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-026-00443-0.

Indexed as

Acute kidney injuryBoruta algorithmLASSO regressionMachine learningMIMIC-IV databaseMortalityStress hyperglycemia ratio

Identifiers

PMID41867166

DOI10.1007/s13755-026-00443-0

PMCPMC13000052

What Socratic holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

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.