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Sager R, Keller LS, Stehli J, Jakob P, Michel J, Kasel M, Templin C, Stähli BE. Association of N-terminal pro-B-type natriuretic peptide with mortality in elderly (≥80 years) patients undergoing percutaneous coronary intervention. Catheter Cardiovasc Interv 2022; 100:535-543. [PMID: 36040724 DOI: 10.1002/ccd.30365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 07/06/2022] [Accepted: 07/27/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVES The aim of this study was to determine the role of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in the prognostication of patients ≥80 years of age undergoing percutaneous coronary intervention (PCI). BACKGROUND Elderly patients with coronary artery disease in need of PCI represent a growing patient population. Advanced risk prediction in this frail and comorbid patient population is important. METHODS A total of 460 consecutive patients ≥80 years of age undergoing PCI for acute (ACS) or chronic coronary syndromes (CCS) at the University Hospital Zurich, Switzerland, between January 2016 and December 2018 and with available baseline NT-proBNP levels were included in the analysis. Patients were stratified according to baseline NT-proBNP levels. The primary endpoint was all-cause mortality at a median follow-up of 33 (interquartile range: 3-392) days. RESULTS Median baseline NT-proBNP levels were 1411 (457-3984) ng/L. All-cause mortality was 7.8% in the lowest and 27.8% in the highest NT-proBNP quartile group (p < 0.001). In patients with ACS, all-cause mortality was 4.8% and 30.4% in the lowest and the highest NT-proBNP quartile (p < 0.001), and corresponding rates in patients with CCS were 11.1% and 22.2% (p = 0.38). In multivariable Cox regression analysis, baseline NT-proBNP levels were independently associated with an increased risk of all-cause mortality (adjusted hazard ratio: 1.00, 95% confidence interval: 1.00-1.00, p = 0.04). CONCLUSIONS Baseline NT-proBNP levels were identified as independent predictor of mortality in elderly (≥80 years) patients undergoing PCI. Hence, baseline NT-proBNP allows for the identification of a high-risk elderly patient subset.
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Affiliation(s)
- Raphael Sager
- Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland
| | - Lukas S Keller
- Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland
| | - Julia Stehli
- Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland
| | - Philipp Jakob
- Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland
| | - Jonathan Michel
- Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland
| | - Markus Kasel
- Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland
| | - Christian Templin
- Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
| | - Barbara E Stähli
- Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
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Liu Y, Wang L, Chen P, Dai Y, Lin Y, Chen W, Xu Z, Zeng L, Fan H, Xue L, Liu S, Chen J, Tan N, He P, Duan C. Risk Estimation for Infection in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Percutaneous Coronary Intervention: Development and Validation of a Predictive Score. Front Cardiovasc Med 2022; 9:845307. [PMID: 35497986 PMCID: PMC9051071 DOI: 10.3389/fcvm.2022.845307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 03/16/2022] [Indexed: 11/29/2022] Open
Abstract
Background Infection during hospitalization is a serious complication among patients who suffered from acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI); however, there are no suitable and accurate means to assess risk. This study aimed to develop and validate a simple scoring system to predict post-AMI infection in such patients. Methods All patients with ST-segment elevation myocardial infarction (STEMI) undergoing PCI consecutively enrolled from January 2010 to May 2016 were served as derivation cohort, and those from June 2016 to May 2018 as validation cohort, respectively. The primary endpoint was post-AMI infection during hospitalization, and all-cause death and major adverse cardiovascular events (MACE) were considered as secondary endpoints. The simplified risk model was established using logistic regression. The area under the receiver operating curve and calibration of predicted and observed infection risk were calculated. Results A 24-point risk score was developed, with infection risk ranging from 0.7 to 99.6% for patients with the lowest and highest score. Seven variables including age, Killip classification, insulin use, white blood cell count, serum albumin, diuretic use, and transfemoral approach were included. This model achieved the same high discrimination in the development and validation cohort (C-statistic:0.851) and revealed adequate calibration in both datasets. The incidences of post-AMI infection increased steadily across risk score groups in both development (1.3, 5.1, 26.3, and 69.1%; P < 0.001) and validation (1.8, 5.9, 27.2, and 79.2%; P < 0.001) cohort. Moreover, the risk score demonstrated good performance for infection, in-hospital all-cause death, and MACE among these patients, as well as in patients with the non-ST-elevation acute coronary syndrome. Conclusion This present risk score established a simple bedside tool to estimate the risk of developing infection and other in-hospital outcomes in patients with STEMI undergoing PCI. Clinicians can use this risk score to evaluate the infection risk and subsequently make evidence-based decisions.
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Affiliation(s)
- Yuanhui Liu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Litao Wang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Pengyuan Chen
- Department of Cardiology, The Second People’s Hospital of Nanhai District, Guangdong General Hospital’s Nanhai Hospital, Foshan, China
| | - Yining Dai
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yaowang Lin
- Department of Cardiology, Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, First Affiliated Hospital of South University of Science and Technology, Shenzhen, China
| | - Wei Chen
- Clinical College of Fujian Provincial Hospital, Fujian Provincial Hospital, Fujian Provincial Key Laboratory of Cardiovascular Disease, Fujian Provincial Center for Geriatrics, Fujian Medical University, Fujian Cardiovascular Institute, Fuzhou, China
| | - Zhengrong Xu
- Department of Cardiology, People’s Hospital of Baoan Shenzhen, Shenzhen, China
| | - Lihuan Zeng
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Hualin Fan
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Ling Xue
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Simin Liu
- Center for Global Cardiometabolic Health, Department of Epidemiology, Medicine, and Surgery, Brown University, Providence, RI, United States
| | - Jiyan Chen
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Ning Tan
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- *Correspondence: Ning Tan,
| | - Pengcheng He
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Pengcheng He,
| | - Chongyang Duan
- Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Chongyang Duan,
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