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Yang C, Duan R, Yang Z, Qiu J, Pi M, Ling X, Xiao C, Zeng J, He J, Huang J, Zhang L, Qin X, Tang F, Fu L, Hou H, Liu X, Lindholm B, Lu F, Wu Y, Su G. Physical Activity Elements and Adverse Outcomes in Patients with Chronic Kidney Disease in Guangdong (PEAKING) project: protocol for a prospective cohort study. BMJ Open 2024; 14:e086509. [PMID: 39438098 PMCID: PMC11499868 DOI: 10.1136/bmjopen-2024-086509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 10/07/2024] [Indexed: 10/25/2024] Open
Abstract
INTRODUCTION Physical inactivity is prevalent and associated with adverse outcomes among patients with chronic kidney disease (CKD). Most previous studies have relied on subjective questionnaires to assess levels of physical activity (PA) and mainly focused on patients undergoing dialysis. Therefore, the Physical Activity Elements and Adverse Outcomes in Patients with Chronic Kidney Disease in Guangdong study aims to investigate the levels and types of PA elements and their association with adverse outcomes in Chinese non-dialysis CKD (ND-CKD) patients. METHODS AND ANALYSIS In this prospective cohort study, 374 patients with ND-CKD will be recruited from Guangdong province, South of China. The primary exposure will be levels of PA assessed by ActiGraph GT3X+ accelerometer including the intensity, duration, frequency and type of PA. The traditional Chinese exercises such as tai chi and Baduanjin will also be assessed. The primary outcomes will be all-cause mortality. Other variables including demographics, comorbidities, medication and laboratory markers will be registered. All data will be updated annually for at least 5 years, or until the occurrence of death or initiation of renal replacement therapy. The Spearman correlation coefficient will be used to investigate the correlation between questionnaire-derived and accelerometry-derived PA. The Cox proportional hazards model will be used to investigate the association between level of PA and adverse outcomes. Non-linear associations between PA levels and outcomes, as well as the minimum desirable PA level, will be evaluated using restricted cubic splines. ETHICS AND DISSEMINATION The ethical permission for this study was obtained from the ethics committee of Guangdong Provincial Hospital of Chinese Medicine in Guangzhou, China (B2015-152-02). Written informed consent is obtained from all participants. The results will be disseminated by publication in a peer-reviewed journal and presented at relevant conferences.
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Affiliation(s)
- Changyuan Yang
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
- Department of Nephrology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Ruolan Duan
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Zhenhua Yang
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Jiamei Qiu
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Minhui Pi
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Xitao Ling
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Cuixia Xiao
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Jiahao Zeng
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Jiawei He
- Department of Nephrology, Peking University First Hospital, Peking University, Beijing, China
| | - Jiasheng Huang
- Department of Nephrology, Shenzhen Hospital of Guangzhou University of Chinese Medicine, Shenzhen, China
| | - La Zhang
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Xindong Qin
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Fang Tang
- Chronic Disease Management Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lizhe Fu
- Chronic Disease Management Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Haijing Hou
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Xusheng Liu
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Bengt Lindholm
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Fuhua Lu
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Yifan Wu
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
| | - Guobin Su
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Chinese Medicine Guangdong Laboratory, Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases, Big Data Research Center of Chinese Medicine, Department of Nephrology, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
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Malavasi VL, Valenti AC, Ruggerini S, Manicardi M, Orlandi C, Sgreccia D, Vitolo M, Proietti M, Lip GYH, Boriani G. Kidney Function According to Different Equations in Patients Admitted to a Cardiology Unit and Impact on Outcome. J Clin Med 2022; 11:jcm11030891. [PMID: 35160341 PMCID: PMC8837128 DOI: 10.3390/jcm11030891] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 01/28/2022] [Accepted: 02/05/2022] [Indexed: 12/11/2022] Open
Abstract
Background: This paper aims to evaluate the concordance between the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula and alternative equations and to assess their predictive power for all-cause mortality in unselected patients discharged alive from a cardiology ward. Methods: We retrospectively included patients admitted to our Cardiology Division independently of their diagnosis. The total population was classified according to Kidney Disease: Improving Global Outcomes (KDIGO) categories, as follows: G1 (estimated glomerular filtration rate (eGFR) ≥90 mL/min/1.73 m2); G2 (eGFR 89–60 mL/min/1.73 m2); G3a (eGFR 59–45 mL/min/1.73 m2); G3b (eGFR 44–30 mL/min/1.73 m2); G4 (eGFR 29–15 mL/min/1.73 m2); G5 (eGFR <15 mL/min/1.73 m2). Cockcroft-Gault (CG), CG adjusted for body surface area (CG-BSA), Modification of Diet in Renal Disease (MDRD), Berlin Initiative Study (BIS-1), and Full Age Spectrum (FAS) equations were also assessed. Results: A total of 806 patients were included. Good agreement was found between the CKD-EPI formula and CG-BSA, MDRD, BIS-1, and FAS equations. In subjects younger than 65 years or aged ≥85 years, CKD-EPI and MDRD showed the highest agreement (Cohen’s kappa (K) 0.881 and 0.588, respectively) while CG showed the lowest. After a median follow-up of 407 days, overall mortality was 8.2%. The risk of death was higher in lower eGFR classes (G3b HR4.35; 95%CI 1.05–17.80; G4 HR7.13; 95%CI 1.63–31.23; G5 HR25.91; 95%CI 6.63–101.21). The discriminant capability of death prediction tested with ROC curves showed the best results for BIS-1 and FAS equations. Conclusion: In our cohort, the concordance between CKD-EPI and other equations decreased with age, with the MDRD formula showing the best agreement in both younger and older patients. Overall, mortality rates increased with the renal function decreasing. In patients aged ≥75 years, the best discriminant capability for death prediction was found for BIS-1 and FAS equations.
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Affiliation(s)
- Vincenzo Livio Malavasi
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (A.C.V.); (S.R.); (M.M.); (C.O.); (D.S.); (M.V.)
| | - Anna Chiara Valenti
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (A.C.V.); (S.R.); (M.M.); (C.O.); (D.S.); (M.V.)
| | - Sara Ruggerini
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (A.C.V.); (S.R.); (M.M.); (C.O.); (D.S.); (M.V.)
| | - Marcella Manicardi
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (A.C.V.); (S.R.); (M.M.); (C.O.); (D.S.); (M.V.)
| | - Carlotta Orlandi
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (A.C.V.); (S.R.); (M.M.); (C.O.); (D.S.); (M.V.)
| | - Daria Sgreccia
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (A.C.V.); (S.R.); (M.M.); (C.O.); (D.S.); (M.V.)
| | - Marco Vitolo
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (A.C.V.); (S.R.); (M.M.); (C.O.); (D.S.); (M.V.)
- Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy
- Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool L14 3PE, UK; (M.P.); (G.Y.H.L.)
| | - Marco Proietti
- Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool L14 3PE, UK; (M.P.); (G.Y.H.L.)
- Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy
- Geriatric Unit, IRCCS Istituti Clinici Scientifici Maugeri, 20138 Milan, Italy
| | - Gregory Y. H. Lip
- Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool L14 3PE, UK; (M.P.); (G.Y.H.L.)
- Aalborg Thrombosis Research Unit, Department of Clinical Medicine, Aalborg University, 9220 Aalborg, Denmark
| | - Giuseppe Boriani
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (A.C.V.); (S.R.); (M.M.); (C.O.); (D.S.); (M.V.)
- Correspondence:
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Su G, Iwagami M, Qin X, McDonald H, Liu X, Carrero JJ, Stålsby Lundborg C, Nitsch D. Kidney disease and mortality in patients with respiratory tract infections: a systematic review and meta-analysis. Clin Kidney J 2021; 14:602-611. [PMID: 33623685 PMCID: PMC7886553 DOI: 10.1093/ckj/sfz188] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 11/21/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Respiratory tract infections (RTIs) are a common reason for people to seek medical care. RTIs are associated with high short-term mortality. Inconsistent evidence exists in the association between the presence of kidney disease and the risk of death in patient with RTIs. METHODS We searched the PubMed, Cochrane Library and Embase databases from inception through April 2019 for cohort and case-control studies investigating the presence of kidney disease (defined as medical diagnosis of kidney disease, reduced estimated glomerular filtration rate or creatinine clearance, elevated serum creatinine and proteinuria) on mortality in adults with RTIs in different settings including community, inpatient and intensive care units. We assessed the quality of the included studies using Cochrane Collaboration's tool and conducted a meta-analysis on the relative risk (RR) of death. RESULTS Of 5362 records identified, 18 studies involving 16 676 participants met the inclusion criteria, with 15 studies investigating pneumonia and 3 studies exploring influenza. The risk of bias in the available evidence was moderate. Most [17/18 (94.5%)] of studies reported positive associations of underlying chronic kidney disease with mortality. The pooled adjusted risk for all-cause mortality in patients with RTIs almost doubled [RR 1.96 (95% confidence interval 1.48-2.59)] in patients with kidney disease. Associations were consistent across different timings of kidney disease assessment and provenances of RTIs (community-acquired or healthcare-associated). CONCLUSIONS The presence of kidney disease is associated with higher mortality among people with RTIs, especially in those with pneumonia. The presence of kidney disease might be taken into account when considering admission for patients who present with RTIs.
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Affiliation(s)
- Guobin Su
- National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Department of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou City, China
- Department of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou City, China
- Health Systems and Policy, Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Masao Iwagami
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
- Department of Health Services Research, University of Tsukuba, Ibaraki, Japan
| | - Xindong Qin
- Department of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou City, China
| | - Helen McDonald
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Xusheng Liu
- Department of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou City, China
| | - Juan Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Cecilia Stålsby Lundborg
- Health Systems and Policy, Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Dorothea Nitsch
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
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