Flow chart of patients.

Flow chart of patients.

<div><p><b>Background:</b> TIMP-2 and IGFBP7 have shown effectiveness as biomarkers for predicting Acute Kidney Injury (AKI). However, the variations in the predictive capacity of urinary [TIMP-2]• [IGFBP7] for AKI across different etiologies remain unexplored. This study aim...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Chaoyun Jiang (22411268) (author)
مؤلفون آخرون:	Cheng Yang (273624) (author), Hui Chen (28597) (author), Xiaofang Jiang (3799252) (author), Jiahao Zhang (4859203) (author), Juan Felipe Alvarez (19067877) (author), Haichuan Yu (1598662) (author), Yao Zhu (441601) (author), Lianjiu Su (10033978) (author), Zhiyong Peng (1457443) (author)
منشور في:	2025
الموضوعات:	Biochemistry Medicine Cell Biology Physiology Pharmacology Developmental Biology Marine Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified results :</ b methods :</ b independent risk factors conclusion :</ b combined prediction model binary logistic regression background :</ b among three cohorts cardiac surgery group cardiac surgery cohorts varying aki causes aki risk factors cardiac surgery patients 6 %) post identify aki ’ exhibited predictive value aki among sepsis cardiac surgery aki among predictive value delong ’ 337 patients aki occurred aki ). predictive capacity predictive capability test indicated study aimed significant differences shown effectiveness final analysis
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مواد مشابهة

Calculated AUC, sensitivities, specificities, predictive values of [TIMP-2]• [IGFBP7] for secondary outcomes AKI degree, CRRT usage, and 28-day mortality.
حسب: Chaoyun Jiang (22411268)
منشور في: (2025)

Calculated AUC, sensitivities, specificities, predictive values, and compare the diagnostic efficiency of different models for AKI.
حسب: Chaoyun Jiang (22411268)
منشور في: (2025)

Multivariate analysis of risk factors for acute kidney injury.
حسب: Chaoyun Jiang (22411268)
منشور في: (2025)

Demographic and clinical characteristics of patients, stratified according to incidence of acute kidney injury.
حسب: Chaoyun Jiang (22411268)
منشور في: (2025)

ROC curve for [TIMP2]• [IGFBP7] predicts the 28-day mortality in all people and three cohorts (stroke, sepsis, and cardiac surgery) differing in AKI etiology.
حسب: Chaoyun Jiang (22411268)
منشور في: (2025)

ROC curve for [TIMP2]• [IGFBP7] predicts the CRRT usage in all people and three cohorts (stroke, sepsis, and cardiac surgery) differing in AKI etiology.
حسب: Chaoyun Jiang (22411268)
منشور في: (2025)

ROC curve for [TIMP2]• [IGFBP7] and joint prediction model predict the incidence of AKI in all people and three cohorts (stroke, sepsis and cardiac surgery) differing in AKI etiology.
حسب: Chaoyun Jiang (22411268)
منشور في: (2025)

Table 1_Preexisting statin therapy is not associated with reduced acute kidney injury following cardiac surgery: a retrospective analysis.docx
حسب: Jia Wang (51945)
منشور في: (2025)

Table 1_Development and validation of a risk prediction model for perioperative acute kidney injury in non-cardiac and non-urological surgery patients: a retrospective cohort study.pdf
حسب: Xuhui Cong (10034308)
منشور في: (2025)

Table 2_Development and validation of a risk prediction model for perioperative acute kidney injury in non-cardiac and non-urological surgery patients: a retrospective cohort study.pdf
حسب: Xuhui Cong (10034308)
منشور في: (2025)

Predictive performance of CSA-AKI’s nine predictive modeling systems in a three -group cohort.
حسب: Yang Xu (178421)
منشور في: (2025)

Characterization of patients in the training and validation cohort at baseline.
حسب: Yang Xu (178421)
منشور في: (2025)

Nomogram to predict the incidence of postoperative AKI in patients undergoing cardiac surgery.
حسب: Yang Xu (178421)
منشور في: (2025)

A, Calibration curves for Q2’s logistic model; B, Calibration curves for Q3’s logistic model; C, Calibration curves for Q3’s LASSO model.
حسب: Yang Xu (178421)
منشور في: (2025)

A, The results of the decision curve analysis for group Q1; B, The results of the decision curve analysis for group Q2; C, The results of the decision curve analysis for group Q3.
حسب: Yang Xu (178421)
منشور في: (2025)

A, ROC curves for Logistic models constructed on the basis of three cohort groups; B, ROC curves for Lasso models constructed on the basis of three cohort groups; C, ROC curves for RF models constructed on the basis of three cohort groups.
حسب: Yang Xu (178421)
منشور في: (2025)

A, Coefficient profile plot for Q1; B, Coefficient profile plot for Q2; C, Coefficient profile plot for Q3; D, Lasso regression variable trajectories for Q1; E, Lasso regression variable trajectories for Q2; F, Lasso regression variable trajectories for Q3.
حسب: Yang Xu (178421)
منشور في: (2025)

Flowchart of cohort screening. ICU, intensive care unit; MIMIC-IV, Medical Information Mart for Intensive Care IV; CABG, coronary artery bypass grafting; AKI, acute kidney injury.
حسب: Yang Xu (178421)
منشور في: (2025)

Raw data.
حسب: Yang Xu (178421)
منشور في: (2025)

Predictors included in the models.
حسب: Yang Xu (178421)
منشور في: (2025)

VIF values for random forest prediction models.
حسب: Yang Xu (178421)
منشور في: (2025)

VIF values for lasso prediction models.
حسب: Yang Xu (178421)
منشور في: (2025)

VIF values for logistic prediction models.
حسب: Yang Xu (178421)
منشور في: (2025)

Variability between modelling and validation groups.
حسب: Yang Xu (178421)
منشور في: (2025)

Discriminative performances for postoperative AKI risk by ensemble models.
حسب: Sehoon Park (1466026)
منشور في: (2025)

Discriminative performances for postoperative AKI risk by intraoperative vital sign signals.
حسب: Sehoon Park (1466026)
منشور في: (2025)

Baseline characteristics.
حسب: Sehoon Park (1466026)
منشور في: (2025)

Discriminative performances for postoperative AKI and critical AKI risk by intraoperative vital sign signals at preset thresholds.
حسب: Sehoon Park (1466026)
منشور في: (2025)

Calibration plot for the Ensemble_PCFs 11.
حسب: Sehoon Park (1466026)
منشور في: (2025)

Feature importance of the deep-learning-based models using the intraoperative vital sign signals.
حسب: Sehoon Park (1466026)
منشور في: (2025)

Study flow diagram.
حسب: Sehoon Park (1466026)
منشور في: (2025)

Study design and deep-learning model architecture.
حسب: Sehoon Park (1466026)
منشور في: (2025)

Quantitative Proteomic and Metabolomic Profiling Reveals Altered Purine Metabolism in Acute Kidney Injury after On-Pump Coronary Artery Bypass Graft
حسب: Mindi Zhao (5543243)
منشور في: (2025)

Quantitative Proteomic and Metabolomic Profiling Reveals Altered Purine Metabolism in Acute Kidney Injury after On-Pump Coronary Artery Bypass Graft
حسب: Mindi Zhao (5543243)
منشور في: (2025)

Quantitative Proteomic and Metabolomic Profiling Reveals Altered Purine Metabolism in Acute Kidney Injury after On-Pump Coronary Artery Bypass Graft
حسب: Mindi Zhao (5543243)
منشور في: (2025)

Quantitative Proteomic and Metabolomic Profiling Reveals Altered Purine Metabolism in Acute Kidney Injury after On-Pump Coronary Artery Bypass Graft
حسب: Mindi Zhao (5543243)
منشور في: (2025)

Quantitative Proteomic and Metabolomic Profiling Reveals Altered Purine Metabolism in Acute Kidney Injury after On-Pump Coronary Artery Bypass Graft
حسب: Mindi Zhao (5543243)
منشور في: (2025)

Quantitative Proteomic and Metabolomic Profiling Reveals Altered Purine Metabolism in Acute Kidney Injury after On-Pump Coronary Artery Bypass Graft
حسب: Mindi Zhao (5543243)
منشور في: (2025)

Patient distribution between acute kidney injury (AKI) stage 1,2 and 3.
حسب: Vicky Jenny Rebecka Wetterstrand (20542428)
منشور في: (2025)

pNGAL performance at optimal cutoff values.
حسب: Vicky Jenny Rebecka Wetterstrand (20542428)
منشور في: (2025)

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