Evidence map›Paper›PMID 42375137›Full record

ArticleKidney diseases (Basel, Switzerland)

Development and Validation of a Multivariable Nomogram Predictive of Kidney Function after Cardiopulmonary Resuscitation.

Jinxiang Wang, Heng Jin, Yanfen Chai, Guowu Xu, Jinxuan Liu, Wei Han, Qin Li, Zhongliang Ji, Qianlong Xue, Qi Lv and 2 more

Abstract read
In one paragraph

Article in Kidney diseases (Basel, Switzerland). 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Jinxiang WangDepartment of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Heng JinDepartment of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Yanfen ChaiDepartment of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Guowu XuDepartment of Emergency Medicine, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China.
Jinxuan LiuDepartment of Emergency Medicine, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China.
Wei HanDepartment of Emergency Medicine, Shenzhen University General Hospital, Shenzhen, China.
Qin LiDepartment of Emergency Medicine, Shenzhen University General Hospital, Shenzhen, China.
Zhongliang JiDepartment of Emergency Medicine, Shenzhen University General Hospital, Shenzhen, China.
Qianlong XueDepartment of Emergency Medicine, First Affiliated Hospital of Hebei North University, Zhangjiakou, China.
Qi LvSchool of Disaster and Emergency Medicine, Tianjin University, Tianjin, China.
Shike HouSchool of Disaster and Emergency Medicine, Tianjin University, Tianjin, China.
Haojun FanSchool of Disaster and Emergency Medicine, Tianjin University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Kidney injury is an important manifestation of post-resuscitation syndrome and a significant factor leading to high mortality rates after cardiopulmonary resuscitation (CPR).This study aimed to develop and validate a multivariable nomogram to predict estimated glomerular filtration rate (eGFR) after CPR to assess the degree of kidney injury and provide protective strategies. Methods: The clinical data of patients after CPR admitted to Tianjin Medical University General Hospital from January 2017 to June 2024 and Tianjin Medical University General Hospital Airport Hospital from January 2017 to December 2019 were retrospectively analyzed. The patients those who met the inclusion criteria were randomly divided into training and validation cohorts at a ratio of 7∶3.We obtained clinical data from January 2021 to June 2023 at First Affiliated Hospital of Hebei North University as external validation. Univariate and multivariate linear regression methods were used to identify independent risk factors for 7d-eGFR after CPR, develop and validate (internal and external) a multivariate nomogram model. Calibration curve, Bland-Altman plot, and paired-T validation were used to validate the predictive performance of the model. Results: We included 439 patients after CPR, of whom 307 were in training cohort and 132 were in validation cohort. And 105 patients were included as an external validation cohort. Multivariable linear analysis showed that age (beta coefficient [β], 95% confidence interval: -0.344 [-0.528, -0.160]), hypertension (-3.610 [-5.968, -1.252]), diabetes mellitus (-2.992 [-5.295, -0.689]), no flow time (-0.577 [-0.996, -0.158]), baseline eGFR (0.349 [0.269∼0.429]), ACR (-0.042 [-0.073, -0.011]), lactic acid (-0.650 [-1.214,-0.086]) were the independent risk factors for eGFR after CPR. A composite nomogram predicted eGFR with good accuracy in training (97.07%), internal validation (95.45%), and external validation (91.08%) cohorts. The nomogram model has good predictive ability for AKI and CKD in training (AUC = 0.933 and 0.882), internal validation (AUC = 0.915 and 0.859), and external validation (AUC = 0.823 and 0.784) cohorts. Conclusion: The developed nomogram could be used to predict 7d-eGFR after CPR, which helped to accurately quantify kidney function levels and early predict the probability of AKI and CKD progression, achieving early detection and intervention, thereby improving the prognosis of patients after CPR.

Indexed as

Acute kidney injuryChronic kidney diseaseGlomerular filtration rateNomogram prediction modelPost-resuscitation syndrome

Identifiers

PMID42375137
PMCPMC13313628

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.