Small molecules as a source for acute kidney injury therapy

Feng, Ya-Long; Yang, Yang; Chen, Hua

doi:10.1016/j.pharmthera.2022.108169

Cited by 8 publications

(2 citation statements)

References 269 publications

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“…The criteria for diagnosing pneumonia based on the detection of interstitial infiltrate changes on chest CT or radiography in patients with at least one of the following conditions: (1) recent presence of sputum, cough or dyspnoea, (2) peripheral white cell counts >10×10 9 /L or <4×10 9 /L or (3) temperature >38.0°C. 11 In addition, illness onset was specifically in the community rather than in the healthcare setting.…”

Section: Definitions Of Cap and Akimentioning

confidence: 99%

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Dynamic nomogram for predicting acute kidney injury in patients with community-acquired pneumonia

Chen,

Zhao,

et al. 2023

BMJ Open Resp Res

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IntroductionAcute kidney injury (AKI) is a common complication in patients with community-acquired pneumonia (CAP) and negatively affects both short-term and long-term prognosis in patients with CAP. However, no study has been conducted on developing a clinical tool for predicting AKI in CAP patients. Therefore, this study aimed to develop a predictive tool based on a dynamic nomogram for AKI in CAP patients.MethodsThis retrospective study was conducted from January 2014 to May 2017, and data from adult inpatients with CAP at Nanjing First Hospital were analysed. Demographic data and clinical data were obtained. The least absolute shrinkage and selection operator (LASSO) regression model was used to select important variables, which were entered into logistic regression to construct the predictive model for AKI. A dynamic nomogram was based on the results of the logistic regression model. Calibration and discrimination were used to assess the performance of the dynamic nomogram. A decision curve analysis was used to assess clinical efficacy.ResultsA total of 2883 CAP patients were enrolled in this study. The median age was 76 years (IQR 63–84), and 61.3% were male. AKI developed in 827 (28.7%) patients. The LASSO regression analysis selected five important factors for AKI (albumin, acute respiratory failure, CURB-65 score, Cystatin C and white cell count), which were then entered into the logistic regression to construct the predictive model for AKI in CAP patients. The dynamic nomogram model showed good discrimination with an area under the receiver operating characteristics curve of 0.870 and good calibration with a Brier score of 0.129 and a calibration plot. The decision curve analysis showed that the dynamic nomogram prediction model had good clinical decision-making.ConclusionThis easy-to-use dynamic nomogram may help physicians predict AKI in patients with CAP.

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Section: Definitions Of Cap and Akimentioning

confidence: 99%

“…8 AKI is a common and severe clinical syndrome with adverse outcomes, but no effective treatment methods have been developed. 9 Early detection and timely intervention are still effective ways to improve outcomes for patients with AKI. 10 However, there is no research on developing a clinical tool for predicting AKI in CAP patients.…”

Section: Introductionmentioning

confidence: 99%