A Pilot Study to Explore Patterns and Predictors of Delayed Kidney Decline after Cardiopulmonary Bypass
springernature（2024）
Department of Anesthesiology and Critical Care Medicine
Abstract
There is no current consensus on the follow up of kidney function in patients undergoing cardiopulmonary bypass (CPB). The main objectives of this pilot study is to collect preliminary data on kidney function decline encountered on the first postoperative visit of patients who have had CPB and to identify predictors of kidney function decline post hospital discharge. Design: Retrospective chart review. Adult patients undergoing open heart procedures utilizing CPB. Patient demographics, type of procedure, pre-, intra-, and postoperative clinical, hemodynamic echocardiographic, and laboratory data were abstracted from electronic medical records. Acute kidney disease (AKD), and chronic kidney disease (CKD) were diagnosed based on standardized criteria. Interval change in medications, hospital admissions, and exposure to contrast, from hospital discharge till first postoperative visit were collected. AKD, and CKD as defined by standardized criteria on first postoperative visit. 83 patients were available for analysis. AKD occurred in 27 (54%) of 50 patients and CKD developed in 12 (42%) out of 28 patients. Older age was associated with the development of both AKD and CKD. Reduction in right ventricular cardiac output at baseline was associated with AKD (OR: 0.5, 95% CI: 0.3, 0.79, P = 0.01). Prolongation of transmitral early diastolic filling wave deceleration time was associated with CKD (OR: 1.02, 95% CI: 1.01, 1.05, P = 0.03). In-hospital acute kidney injury (AKI) was a predictor of neither AKD nor CKD. AKD and CKD occur after CPB and may not be predicted by in-hospital AKI. Older age, right ventricular dysfunction and diastolic dysfunction are important disease predictors. An adequately powered longitudinal study is underway to study more sensitive predictors of delayed forms of kidney decline after CPB.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined