|Year : 2017 | Volume
| Issue : 8 | Page : 885-891
Analysis of Factors Associated with Death in Maintenance Hemodialysis Patients: A Multicenter Study in China
Kang-Kang Song1, De-Long Zhao1, Yuan-Da Wang1, Yong Wang1, Xue-Feng Sun1, Li-Ning Miao2, Zhao-Hui Ni3, Hong-Li Lin4, Fu-You Liu5, Ying Li6, Ya-Ni He7, Nian-Song Wang8, Cai-Li Wang9, Ai-Hua Zhang10, Meng-Hua Chen11, Xiao-Ping Yang12, Yue-Yi Deng13, Feng-Min Shao14, Shu-Xia Fu15, Jing-Ai Fang16, Guang-Yan Cai1, Xiang-Mei Chen1
1 Department of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing 100853, China
2 Department of Nephrology, The Second Hospital of Jilin University, Changchun, Jilin 130041, China
3 Department of Nephrology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Peritoneal Dialysis Research Center, Shanghai 200127, China
4 Department of Nephrology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116011, China
5 Department of Nephrology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
6 Department of Nephrology, Third Hospital of Hebei Medical University, Kidney Disease Research Center of Hebei Province, Shijiazhuang, Hebei 050081, China
7 Department of Nephrology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing 400042, China
8 Department of Nephrology, Shanghai Jiao Tong University, Affiliated The Sixth People's Hospital, Shanghai 200233, China
9 Department of Nephrology, First Affiliated Hospital of Baotou Medical College, Baotou, Inner Mongolia 014040, China
10 Department of Nephrology, Peking University Third Hospital, Beijing 100191, China
11 Department of Nephrology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia 750004, China
12 Department of Nephrology, The First Affiliated Hospital of Shihezi University School of Medicine, Shihezi, Xinjiang 832008, China
13 Department of Nephrology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
14 Department of Nephrology, Henan Provincial People's Hospital, Zhengzhou, Henan 450003, China
15 Department of Nephrology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, China
16 Department of Nephrology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, China
|Date of Submission||02-Dec-2016|
|Date of Web Publication||10-Apr-2017|
Prof. Xiang-Mei Chen
Department of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing 100853
Source of Support: None, Conflict of Interest: None
Background: Patients on hemodialysis have a high-mortality risk. This study analyzed factors associated with death in patients on maintenance hemodialysis (MHD). While some studies used baseline data of MHD patients, this study used the most recent data obtained from patients just prior to either a primary endpoint or the end of the study period to find the characteristics of patients preceding death.
Methods: Participants were selected from 16 blood purification centers in China from January 2012 to December 2014. Patients' data were collected retrospectively. Based on survival status, the participants were divided into two groups: survival group and the death group. Logistic regression analysis was performed to determine factors associated with all-cause mortality.
Results: In total, 4104 patients (57.58% male, median age 59 years) were included. Compared with the survival group, the death group had more men and more patients with diabetic nephropathy (DN) and hypertensive nephropathy. The patients preceding death also had lower levels of diastolic blood pressure, hemoglobin, serum albumin, serum calcium, serum phosphate, Kt/V, and higher age. Multivariate analysis revealed that male sex (odd ratio [OR]: 1.437, 95% confidence interval [CI]: 1.094–1.886), age (OR: 1.046, 95% CI: 1.036–1.057), and presence of DN (OR: 1.837, 95% CI: 1.322–2.552) were the risk factors associated with mortality. High serum calcium (OR: 0.585, 95% CI: 0.346–0.989), hemoglobin (OR: 0.974, 95% CI: 0.967–0.981), albumin (OR: 0.939, 95% CI: 0.915–0.963) levels, and dialysis with noncuffed catheter (OR: 0.165, 95% CI: 0.070–0.386) were protective factors based on a multivariate analysis.
Conclusions: Hemodialysis patients preceding death had lower hemoglobin, albumin, and serum calcium levels. Multivariate analysis showed that male sex, age, DN, low hemoglobin, low albumin, and low serum calcium were associated with death in hemodialysis patients.
Keywords: Hemodialysis; Mortality; Risk Factors
|How to cite this article:|
Song KK, Zhao DL, Wang YD, Wang Y, Sun XF, Miao LN, Ni ZH, Lin HL, Liu FY, Li Y, He YN, Wang NS, Wang CL, Zhang AH, Chen MH, Yang XP, Deng YY, Shao FM, Fu SX, Fang JA, Cai GY, Chen XM. Analysis of Factors Associated with Death in Maintenance Hemodialysis Patients: A Multicenter Study in China. Chin Med J 2017;130:885-91
|How to cite this URL:|
Song KK, Zhao DL, Wang YD, Wang Y, Sun XF, Miao LN, Ni ZH, Lin HL, Liu FY, Li Y, He YN, Wang NS, Wang CL, Zhang AH, Chen MH, Yang XP, Deng YY, Shao FM, Fu SX, Fang JA, Cai GY, Chen XM. Analysis of Factors Associated with Death in Maintenance Hemodialysis Patients: A Multicenter Study in China. Chin Med J [serial online] 2017 [cited 2018 Dec 17];130:885-91. Available from: http://www.cmj.org/text.asp?2017/130/8/885/204103
| Introduction|| |
A survey in China showed that the number of patients with chronic kidney disease, which gradually leads to end-stage renal disease (ESRD), was approximately 119.5 million. According to the Chinese National Renal Data System (CNRDS), the prevalence of hemodialysis was increasing in 2011–2015. On December 31, 2015, 385,000 hemodialysis cases in the Chinese mainland were reported.
Patients on hemodialysis have higher mortality risks compared with the general population., The United States Renal Data System (USRDS) reported that the mortality rate in 2013 of hemodialysis patients was 172/1000 patient-years. Moreover, dialysis patients' risk for fatal hospitalization increased three-fold compared with that of the reference population.
Identifying the factors associated with death in maintenance hemodialysis (MHD) patients is vital. Some studies used baseline data of MHD patients to analyze their survival; however, laboratory data characteristics were variable. Some studies report that hemodialysis patients who are expected to die have certain clinical and biochemical characteristics.,, However, little is known on the state of dialysis patients preceding death, especially in our country. Hence, our study used the most recent data obtained from patients just prior to either a primary endpoint or the end of the study period. This study aimed to determine the characteristics of dying patients and the factors associated with death in MHD patients.
| Methods|| |
This study was approved by the Ethics Committee of the Chinese People's Liberation Army General Hospital. Patients under MHD therapy in 16 blood purification centers from 12 provinces in China from January 2012 to December 2014 were selected. Inclusion criteria were as follows: age ≥20 years, receiving MHD therapy for at least 3 months, and with laboratory data, including blood pressure, Kt/V, hemoglobin, serum albumin, serum calcium, and serum phosphate.
Based on survival status, the participants were divided into two groups: the survival group (still alive on December 31, 2014) and the death group (died of any cause within the study period). Patients who were lost to follow-up for any reason began peritoneal dialysis, or received kidney transplant before December 31, 2014, were included in the survival group.
Data, including sex, age, primary cause of ESRD, dialysis duration, death cause, type of vascular access, dialysis time every week, and laboratory results, were collected retrospectively. Information on the type of vascular access and laboratory results was obtained from the latest hemodialysis records before the primary study endpoints of patient death, lost to follow-up, or the end of the study period. All laboratory data were collected before dialysis.
The primary cause of ESRD was categorized as primary glomerulonephritis (PGN), diabetic nephropathy (DN), hypertensive nephropathy (HTN), and other/unknown. Death causes were classified as cardiovascular events, cerebrovascular events, infection, sudden death of unknown reason, bleeding, cancer, and other/unknown. Dialysis duration was defined as the number of months between their first renal replacement therapy and a primary endpoint or completion of the study. Types of vascular access were arteriovenous fistula (AVF), tunneled cuffed catheter (TCC), noncuffed catheter (NCC), arteriovenous graft, and other/unknown.
Data were expressed as mean ± standard deviation (SD) or median (interquartile range) for continuous variables according to their distribution and as percentages for categorical variables. Between-group comparison was performed using the Student's t-test or Kruskal-Wallis test for continuous variables and Chi-square test for categorical variables.
Univariate analysis was performed for all variables. Variables that affected all-cause mortality (P < 0.05) in the univariate analysis were included in the multivariate logistic regression analysis model to determine factors associated with all-cause mortality. A P < 0.05 was considered statistically significant. All analyses were performed with Statistical Package for the Social Sciences software (Version 21.0, SPSS Inc., Chicago, IL, USA).
| Results|| |
Data from 4104 ESRD patients from 16 centers were obtained (57.58% male; age 59  years), among whom 620 patients were dead. The study profile is shown in [Figure 1]. [Table 1] shows that among the 4104 patients, patients with PGN were the most common (n = 1902, 46.35%), followed by those with DN (n = 788, 19.20%) and HTN (n = 460, 11.21%). The majority of the patients had AVF (n = 3259, 79.41%).
|Table 1: Characteristics of the studied cohort and comparison of the two groups|
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The most common cause of death was cardiovascular events (n = 235, 37.90%), followed by cerebrovascular events (n = 126, 20.32%), infection (n = 73, 11.77%), sudden death of unknown reason (n = 36, 5.81%), bleeding (n = 35, 5.65%), cancer (n = 17, 2.74%), and other/unknown (n = 98, 15.81%).
Comparison of two groups
The studied group was divided into two groups based on their outcome: the death group (n = 620) and the survival group (n = 3484). [Table 1] presents the characteristics and comparisons of the two groups. The death group had 61.90% males, while the survival group had 46.31% males (P = 0.013). The death group had a significantly higher median age than the survival group (68  years vs. 58  years). The median dialysis duration (35 (44) months vs. 34 (55) months) was not significantly different between the two groups. However, the death group had less patients with 3–12 months of dialysis duration (15.97% vs. 21.33%) but more patients with 25–60 months of dialysis duration (39.19% vs. 30.86%).
The percentage of patients with PGN as the primary cause of ESRD in the death group was lower than that in the survival group (31.13% vs. 49.05%, respectively), while the percentage of patients with DN (35.81% vs. 16.25%) or HTN (15.16% vs. 10.51%) was significantly higher in the death group.
Compared with the survival group, the death group had a lower diastolic blood pressure, hemoglobin, serum albumin, serum calcium, serum phosphate, and Kt/V.
Factors associated with all-cause mortality
Univariate analysis identified several factors associated with mortality, including sex, age, cause of ESRD, type of vascular access, dialysis time every week, diastolic blood pressure, hemoglobin, serum albumin, serum calcium, serum phosphate, and Kt/V [Table 2]. Subsequently, two multivariate analysis models were built: one model consisted of all significant factors in the univariate analysis, while the other excluded laboratory examination. In the nonlaboratory examination model, sex, age, dialysis duration, cause of ESRD, type of vascular access, and dialysis time every week were included. The multivariate logistic regression analysis results are shown in [Table 3]. Male sex (odd ratio [OR] 1.302; 95% confidence interval [CI]: 1.080–1.571), age (OR 1.042; 95% CI: 1.035–1.049), DN (OR 2.472; 95% CI: 1.969–3.105), HTN (OR 1.629; 95% CI: 1.224–2.169), and dialysis with TCC (OR 1.640; 95% CI: 1.244–2.161) were independent risk factors for mortality. Dialysis with NCC (OR 0.320; 95% CI: 0.192–0.532) seemed to be associated with better outcome.
|Table 2: Univariate analysis of factors associated with all-cause mortality (n = 4104)|
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|Table 3: Multivariate analyses of factors associated with all-cause mortality unadjusted for laboratory examination (n = 4104)|
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[Table 4] shows the multivariate analyses of factors associated with all-cause mortality adjusted for laboratory examination. These results show that, after adjustment for laboratory variables, male sex, age, and DN were still significantly associated with higher mortality, while dialysis with NCC was associated with lower mortality. Moreover, we observed that high hemoglobin (OR 0.974; 95% CI: 0.967–0.981), serum albumin (OR 0.939; 95% CI: 0.915–0.963), and serum calcium (OR 0.585; 95% CI: 0.346–0.989) levels were protective factors associated with mortality.
|Table 4: Multivariate analyses of factors associated with all-cause mortality adjusted for laboratory examination (n = 4104)|
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| Discussion|| |
There exists abundant literature on the risk factors for death in MHD patients, which are based on the baseline data obtained from those patients. However, little is known about the clinical and laboratory parameters associated with the status of MHD patients preceding death, especially in our country. In this study, we used the latest records, i.e., before patient outcome identification or end of the study period, to find the characteristics and factors associated with death in MHD patients. The results showed that the death group had more men and more patients with DN and HTN. Moreover, patients in the group also had higher age and lower levels of diastolic blood pressure, hemoglobin, albumin, serum calcium, serum phosphate, and kt/v compared with survival group. Multivariate analysis showed that male sex, age, DN, and low hemoglobin, albumin, and serum calcium levels were associated with death in hemodialysis patients.
The logistic regression analysis showed that lower hemoglobin and serum albumin were associated with death. The low levels of albumin and hemoglobin might be the result of both inflammatory and nutritional components. Nevertheless, they could also lead to undesirable outcomes. Low hemoglobin level and erythropoiesis-stimulating agents could lead to cardiovascular events, fatigue, and even mortality,,,, while low serum albumin level in dialysis patients was also known to be associated with malnutrition, inflammation, and all-cause and cardiovascular mortality.,,,, The result was partly in accordance with the studies that have reported that MHD patients experienced a decrease in serum albumin level in their final stages of life.,
Numerous reports have demonstrated that a high level of serum calcium and phosphate could cause vascular calcification and even mortality.,, However, our data showed that serum calcium and phosphate levels of patients in the death group were significantly lower than those of patients in the survival group. Moreover, the logistic regression analysis revealed that lower serum calcium was associated with death. Low serum calcium level could be associated with the hypoalbuminemic status, which might partly explain the results in our study. K/DOQI and KDIGO guidelines state that, because serum calcium is partly bound to serum albumin, total serum calcium decreases 0.8 mg/dl (0.2 mmol/L) for every 1 g decrease in serum albumin below 4 g/dl (40 g/L)., Furthermore, the time before death course is frequently characterized by a loss of regulatory functions in numerous subsystems of dialysis patients; hence, their system cannot react properly to perturbations. We also speculate that the poor diet of patients in their final stages of life might be a cause of the low serum levels of calcium and phosphate. However, we could only provide the results and suggest the phenomena without being able to reason them. Further deep studies are needed to explain these mechanisms and their interactions.
In our study, male was an independent risk factor for mortality, and this study showed that more men than women were undergoing hemodialysis treatment, which is consistent with our national hemodialysis registry data and the USRDS., In our results, male sex was associated with a 1.437 times risk of death, which is also seen in other studies., The reason remains unclear and currently a topic of research. Furthermore, the Dialysis Outcomes and Practice Patterns Study (DOPPS) analyzed 206,374 patients receiving hemodialysis in 12 countries and found that the survival advantage of women over men in the general population was markedly diminished in hemodialysis patients. The DOPPS study also found that the male-to-female mortality rate ratio in the general population varied from 1.5 to 2.6 for age groups under 75 years, while that in hemodialysis patients was close to 1. In the general population, women have longer life expectancy than men, which could be related to a lower prevalence of cardiovascular risk factors and events in women.,, In hemodialysis patients, men were younger, were less frequently obese, received kidney transplant more frequently, and were less frequently depressed. These factors may partly explain the survival advantage of females in the general population and the lack of that survival advantage in females requiring hemodialysis.
According to the CNRDS, glomerulonephritis (54.2%) was the most frequent disease among Chinese hemodialysis patients in 2015, followed by DN (17.0%) and HTN (9.9%). In our study, the leading cause of ESRD in the survival group was similar to that in the Annual Data Report of CNRDS. However, in the death group, DN (n = 222, 35.81%) accounted for a larger proportion of deaths compared with GN (n = 193, 31.13%). The death group also had a higher proportion of HTN patients than that in the report of CNRDS. Logistic regression analysis also showed that the risks of death in patients with DN or HTN were 2.472 times and 1.629 times higher, respectively, than those of patients with PGN before adjusting for laboratory examination. After adjusting for laboratory examination, DN remained risk factors for death. As reported, the incidence of hypertension, coronary heart disease, and cerebral thrombus in DN patients is higher than those in non-DN patients. The absolute cardiovascular disease (CVD) risk in diabetic patients is two-fold greater than that in persons without diabetes. Conditions associated with diabetes mellitus type 2, such as insulin resistance, hyperinsulinemia, and hyperglycemia, may lead to inflammation, dyslipidemia, endothelial dysfunction, and oxidative stress, which could predispose patients to atherosclerosis and CVD.,,
Our results also showed that NCC was apparently a protective factor in dialysis patients. Patients often used catheters when they initiated hemodialysis; thus, the percentage of NCC use was higher at 3–12 months than at 1 year after dialysis initiation., In our study, compared with the death group, more patients in the survival group had a dialysis duration of 3–12 months. Therefore, we hypothesize that this may explain the apparent advantage of NCC.
In this study, we used logistic regression rather than the Cox's proportional hazard model. We began the follow-up on January 1, 2012, rather than the time when patients began their first hemodialysis. The survival time in this study should be calculated from the study entry date (January 1, 2012) to the date of death, lost to follow-up, or the end of the study (December 31, 2014). However, patients who started dialysis before the entry date had survived for a period of time, which should be included in their real survival time. Those might affect the Cox's proportional hazard model analysis to some extent. Thus, we choose the logistic regression to avoid some bias.
This study has some limitations. First, the laboratory data were obtained from the latest records before patient outcome identification. We revealed the characteristics of dying MHD patients. However, patients before death were usually accompanied by complex illness states. We did not study the dynamic changes in these parameters of MHD patients. Thus, longitudinal studies are necessary in the future. Second, there were no lipid profile, uric acid, and body mass index (BMI) data in the analysis, which might be associated with death in MHD patients. Considering that not all the patients underwent the lipid profile or uric acid examination in this study, we did not include these factors into analysis. Moreover, some hospitals did not record patients' height or BMI in the hemodialysis record. We, therefore, thought that the BMI data might not be accurate enough and did not include it. Third, as the data were collected retrospectively, information bias to some extent existed. Finally, the centers in our study were from top-level hospitals. Medical resources possibly differ in middle- or lower-grade hospitals. Hence, our data do not reflect the overall MHD patients' status in our country.
In conclusion, this study revealed the characteristics of MHD patients prior to death and the factors associated with death in MHD patients. Hemodialysis patients preceding death had lower hemoglobin, albumin, and serum calcium levels but higher age. Multivariate analysis showed that male sex, age, DN, low hemoglobin, albumin, and serum calcium levels were associated with death in hemodialysis patients.
We gratefully acknowledge all the participants and investigators for their contribution to the study.
Financial support and sponsorship
This study was supported by grants from the National Key Technology R&D Program (No. 2013BAI09B05; No. 2015BAI12B06; No. 2011BAI10B08); Special Fund for NHFPC Scientific Researchin the Public Welfare (No. 201502023), the Fund of Chinese PLA 12th Five-Year Plan for Medical Sciences (No.BWS14J040; No. BWS11J027) and the Beijing Municipal Science and Technology Commission (No. Z131107002213011).
Conflicts of interest
There are no conflicts of interest.
| References|| |
Zhang L, Wang F, Wang L, Wang W, Liu B, Liu J, et al.
Prevalence of chronic kidney disease in China: A cross-sectional survey. Lancet 2012;379:815-22. doi: 10.1016/S0140-6736(12)60033-6.
United States Renal Data System. 2015 USRDS Annual Data Report: Epidemiology of Kidney Disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD; 2015.
Daratha KB, Short RA, Corbett CF, Ring ME, Alicic R, Choka R, et al.
Risks of subsequent hospitalization and death in patients with kidney disease. Clin J Am Soc Nephrol 2012;7:409-16. doi: 10.2215/CJN.05070511.
Usvyat LA, Barth C, Bayh I, Etter M, von Gersdorff GD, Grassmann A, et al.
Interdialytic weight gain, systolic blood pressure, serum albumin, and C-reactive protein levels change in chronic dialysis patients prior to death. Kidney Int 2013;84:149-57. doi: 10.1038/ki.2013.73.
Kotanko P, Thijssen S, Usvyat L, Tashman A, Kruse A, Huber C, et al.
Temporal evolution of clinical parameters before death in dialysis patients: A new concept. Blood Purif 2009;27:38-47. doi: 10.1159/000167007.
Kotanko P, Kooman J, van der Sande F, Kappel F, Usvyat L. Accelerated or out of control: The final months on dialysis. J Ren Nutr 2014;24:357-63. doi: 10.1053/j.jrn.2014.06.011.
Kaysen GA, Dubin JA, Müller HG, Mitch WE, Rosales LM, Levin NW. Relationships among inflammation nutrition and physiologic mechanisms establishing albumin levels in hemodialysis patients. Kidney Int 2002;61:2240-9. doi: 10.1046/j.1523-1755.2002.00076.x.
Anand IS, Chandrashekhar Y, Ferrari R, Poole-Wilson PA, Harris PC. Pathogenesis of oedema in chronic severe anaemia: Studies of body water and sodium, renal function, haemodynamic variables, and plasma hormones. Br Heart J 1993;70:357-62. doi: 10.1136/hrt.70.4.357.
Johansen KL, Finkelstein FO, Revicki DA, Evans C, Wan S, Gitlin M, et al.
Systematic review of the impact of erythropoiesis-stimulating agents on fatigue in dialysis patients. Nephrol Dial Transplant 2012;27:2418-25. doi: 10.1093/ndt/gfr697.
Port FK, Pisoni RL, Bommer J, Locatelli F, Jadoul M, Eknoyan G, et al.
Improving outcomes for dialysis patients in the international dialysis outcomes and practice patterns study. Clin J Am Soc Nephrol 2006;1:246-55. doi: 10.2215/CJN.01050905.
Regidor DL, Kopple JD, Kovesdy CP, Kilpatrick RD, McAllister CJ, Aronovitz J, et al.
Associations between changes in hemoglobin and administered erythropoiesis-stimulating agent and survival in hemodialysis patients. J Am Soc Nephrol 2006;17:1181-91. doi: 10.1681/ASN.2005090997.
Lukowsky LR, Kheifets L, Arah OA, Nissenson AR, Kalantar-Zadeh K. Nutritional predictors of early mortality in incident hemodialysis patients. Int Urol Nephrol 2014;46:129-40. doi: 10.1007/s11255-013-0459-2.
de Mutsert R, Grootendorst DC, Indemans F, Boeschoten EW, Krediet RT, Dekker FW; Netherlands Cooperative Study on the Adequacy of Dialysis-II Study Group. Association between serum albumin and mortality in dialysis patients is partly explained by inflammation, and not by malnutrition. J Ren Nutr 2009;19:127-35. doi: 10.1053/j.jrn.2008.08.003.
Weng CH, Hu CC, Yen TH, Hsu CW, Huang WH. Nutritional predictors of mortality in long term hemodialysis patients. Sci Rep 2016;6:35639. doi: 10.1038/srep35639.
Herselman M, Esau N, Kruger JM, Labadarios D, Moosa MR. Relationship between serum protein and mortality in adults on long-term hemodialysis: Exhaustive review and meta-analysis. Nutrition 2010;26:10-32. doi: 10.1016/j.nut.2009.07.009.
Chen XN, Chen ZJ, Ma XB, Ding B, Ling HW, Shi ZW, et al.
Aortic artery and cardiac valve calcification are associated with mortality in Chinese hemodialysis patients: A 3.5 years follow-up. Chin Med J 2015;128:2764-71. doi: 10.4103/0366-6999.167315.
] [Full text]
Slinin Y, Foley RN, Collins AJ. Calcium, phosphorus, parathyroid hormone, and cardiovascular disease in hemodialysis patients: The USRDS waves 1, 3, and 4 study. J Am Soc Nephrol 2005;16:1788-93. doi: 10.1681/ASN.2004040275.
Shanahan CM, Crouthamel MH, Kapustin A, Giachelli CM. Arterial calcification in chronic kidney disease: Key roles for calcium and phosphate. Circ Res 2011;109:697-711. doi: 10.1161/CIRCRESAHA.110.234914.
Yang H, Curinga G, Giachelli CM. Elevated extracellular calcium levels induce smooth muscle cell matrix mineralization in vitro
. Kidney Int 2004;66:2293-9. doi: 10.1111/j.1523-1755.2004.66015.x.
National Kidney Foundation. K/DOQI clinical practice guidelines for bone metabolism and disease in chronic kidney disease. Am J Kidney Dis 2003;42 4 Suppl 3:S1-201. doi: 10.1016/S0272-6386(03)00905-3.
Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Work Group. KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). Kidney Int Suppl 2009; (113):S1-130. doi: 10.1038/ki.2009.191.
Hecking M, Bieber BA, Ethier J, Kautzky-Willer A, Sunder-Plassmann G, Säemann MD, et al.
Sex-specific differences in hemodialysis prevalence and practices and the male-to-female mortality rate: The dialysis outcomes and practice patterns study (DOPPS). PLoS Med 2014;11:e1001750. doi: 10.1371/journal.pmed.1001750.
Murray CJ, Lopez AD. Mortality by cause for eight regions of the world: Global burden of disease study. Lancet 1997;349:1269-76. doi: 10.1016/S0140-6736(96)07493-4.
Wingard DL, Suarez L, Barrett-Connor E. The sex differential in mortality from all causes and ischemic heart disease. Am J Epidemiol 1983;117:165-72. doi: 10.1093/oxfordjournals.aje.a113527.
Kardys I, Vliegenthart R, Oudkerk M, Hofman A, Witteman JC. The female advantage in cardiovascular disease: Do vascular beds contribute equally? Am J Epidemiol 2007;166:403-12. doi: 10.1093/aje/kwm115.
Chen H, Wang DG, Yuan L, Liu GL, He HJ, Wang J, et al.
Clinical characteristics of patients with diabetic nephropathy on maintenance hemodialysis: A multicenter cross-sectional survey in anhui province, eastern China. Chin Med J 2016;129:1291-7. doi: 10.4103/0366-6999.182832.
] [Full text]
Fox CS, Coady S, Sorlie PD, Levy D, Meigs JB, D'Agostino RB Sr., et al.
Trends in cardiovascular complications of diabetes. JAMA 2004;292:2495-9. doi: 10.1001/jama.292.20.2495.
Hayden JM, Reaven PD. Cardiovascular disease in diabetes mellitus type 2: A potential role for novel cardiovascular risk factors. Curr Opin Lipidol 2000;11:519-28. doi: 10.1097/00041433-200010000-00010.
Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes 1988;37:1595-607. doi: 10.2337/diab.37.12.1595.
Marfella R, Esposito K, Giunta R, Coppola G, De Angelis L, Farzati B, et al.
Circulating adhesion molecules in humans: Role of hyperglycemia and hyperinsulinemia. Circulation 2000;101:2247-51. doi: 10.1161/01.CIR.101.19.2247.
[Table 1], [Table 2], [Table 3], [Table 4]
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