A comparison of the risk of congestive heart failure-related hospitalizations in patients receiving hemodialysis and peritoneal dialysis - A retrospective propensity score-matched study
Autoři:
Chien-Yao Sun aff001; Junne-Ming Sung aff001; Jung-Der Wang aff001; Chung-Yi Li aff002; Yi-Ting Kuo aff001; Chia-Chun Lee aff001; Jia-Ling Wu aff001; Yu-Tzu Chang aff001
Působiště autorů:
Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
aff001; Department of Public Health, National Cheng Kung University, College of Medicine, Tainan, Taiwan
aff002; Department of Environmental and Occupational Health, National Cheng Kung University Hospital, Tainan, Taiwan
aff003
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223336
Souhrn
Introduction
Congestive heart failure (CHF) is associated with high mortality and a heavy financial and healthcare burden in the dialysis population. Determining which dialysis modality is associated with a higher risk of developing CHF might facilitate clinical decision making and surveillance programs in the dialysis population.
Methods
Using the Taiwan National Health Insurance Database, we recruited all incident dialysis patients during the period from January 1, 1998 to December 31, 2010. The propensity score matching method was applied to establish the matched hemodialysis (HD) and peritoneal dialysis (PD) cohort. Incidence rates and cumulative incidence rates of CHF-related hospitalization were first compared for the HD and PD patients. Multivariable subdistribution hazards models were then constructed to control for potential confounders.
Results
Among a total of 65,899 enrolled dialysis patients, 4,754 matched pairs of HD and PD patients were identified. The incidence rates of CHF in the matched HD and PD patients were 25.98 and 19.71 per 1000 patient-years, respectively (P = 0.001). The cumulative incidence rate of CHF was also higher in the matched HD patients (0.16, 95% confidence interval (CI)(0.12–0.21)] than in the corresponding PD patients (0.09, 95% CI [0.08–0.11])(P<0.0001). HD was consistently associated with an increased subdistribution hazard ratio (HR) of CHF compared with PD in the matched cohort (HR: 1.45, 95% CI [1.23–1.7]). Similar phenomenons were observed in either the subgroup analysis stratified by selected confounders or in the HD and PD group without matching.
Conclusions
HD is associated with a higher risk of developing CHF-related hospitalization than PD. The surveillance program for CHF should differ in patients receiving different dialysis modalities.
Klíčová slova:
Cardiology – Coronary heart disease – Heart failure – Hyperlipidemia – Chronic kidney disease – Medical dialysis – Medical risk factors – Taiwan
Zdroje
1. United States Renal Data System. Volume 2: End-stage Renal Disease (ESRD) in the United States, Chapter 8. Cardiovascular Disease in Patients With ESRD [cited 11 April 2018] [Internet]. Available from: https://www.usrds.org/2017/view/v2_08.aspx.
2. Foley RN. Clinical epidemiology of cardiac disease in dialysis patients: left ventricular hypertrophy, ischemic heart disease, and cardiac failure. Semin Dial. 2003; 16: 111–117. 12641874
3. Chang YT, Wu JL, Hsu CC, Wang JD, Sung JM. Diabetes and end-stage renal disease synergistically contribute to increased incidence of cardiovascular events: a nationwide follow-up study during 1998–2009. Diabetes Care. 2014; 37: 277–285. doi: 10.2337/dc13-0781 23920086
4. Harnett JD, Foley RN, Kent GM, Barre PE, Murray D, Parfrey PS. Congestive heart failure in dialysis patients: prevalence, incidence, prognosis and risk factors. Kidney Int. 1995; 47: 884–890. doi: 10.1038/ki.1995.132 7752588
5. Kontodimopoulos N, Niakas D. An estimate of lifelong costs and QALYs in renal replacement therapy based on patients' life expectancy. Health Policy. 2008; 86: 85–96. doi: 10.1016/j.healthpol.2007.10.002 17996975
6. Ranasinghe P, Perera YS, Makarim MF, Wijesinghe A, Wanigasuriya K. The costs in provision of haemodialysis in a developing country: a multi-centered study. BMC Nephrol. 2011; 12: 42. doi: 10.1186/1471-2369-12-42 21896190
7. Barrett BJ, Parfrey PS, Morgan J, Barre P, Fine A, Goldstein MB, et al. Prediction of early death in end-stage renal disease patients starting dialysis. Am J Kidney Dis. 1997; 29: 214–222. doi: 10.1016/s0272-6386(97)90032-9 9016892
8. Taiwan Society of Nephrology. 2015 Annual Report of Kidney Disease in Taiwan. 2015 [cited 31 August 2017] [Internet]. Available from: http://www.tsn.org.tw/UI/H/H00201.aspx.
9. Vinson JM, Rich MW, Sperry JC, Shah AS, McNamara T. Early readmission of elderly patients with congestive heart failure. J Am Geriatr Soc. 1990; 38: 1290–1295. doi: 10.1111/j.1532-5415.1990.tb03450.x 2254567
10. Lekawanvijit S, Krum H. Cardiorenal syndrome: role of protein-bound uremic toxins. J Ren Nutr. 2015; 25: 149–154. doi: 10.1053/j.jrn.2014.10.009 25556308
11. Schurig R, Gahl GM, Becker H, Schiller R, Kessel M, Paeprer H. Hemodynamic studies in long-term peritoneal dialysis patients. Artif Organs. 1979; 3: 215–218. doi: 10.1111/j.1525-1594.1979.tb01050.x 119525
12. Sniderman AD, Solhpour A, Alam A, Williams K, Sloand JA. Cardiovascular death in dialysis patients: lessons we can learn from AURORA. Clin J Am Soc Nephrol. 2010; 5: 335–340. doi: 10.2215/CJN.06300909 20056762
13. Chang YT, Hwang JS, Hung SY, Tsai MS, Wu JL, Sung JM, et al. Cost-effectiveness of hemodialysis and peritoneal dialysis: A national cohort study with 14 years follow-up and matched for comorbidities and propensity score. Sci Rep. 2016; 6: 30266. doi: 10.1038/srep30266 27461186
14. Locatelli F, Marcelli D, Conte F, D'Amico M, Del Vecchio L, Limido A, et al. Survival and development of cardiovascular disease by modality of treatment in patients with end-stage renal disease. J Am Soc Nephrol. 2001; 12: 2411–2417. 11675417
15. Johnson DW, Dent H, Hawley CM, McDonald SP, Rosman JB, Brown FG, et al. Association of dialysis modality and cardiovascular mortality in incident dialysis patients. Clin J Am Soc Nephrol. 2009; 4: 1620–1628. doi: 10.2215/CJN.01750309 19729428
16. Wang IK, Lu CY, Lin CL, Liang CC, Yen TH, Liu YL, et al. Comparison of the risk of de novo cardiovascular disease between hemodialysis and peritoneal dialysis in patients with end-stage renal disease. Int J Cardiol. 2016; 218: 219–224. doi: 10.1016/j.ijcard.2016.05.036 27236118
17. Trespalacios FC, Taylor AJ, Agodoa LY, Bakris GL, Abbott KC. Heart failure as a cause for hospitalization in chronic dialysis patients. Am J Kidney Dis. 2003; 41: 1267–1277. doi: 10.1016/s0272-6386(03)00359-7 12776280
18. Ministry of Health and Welfare, R.O.C. (Taiwan). 2015 Taiwan Health and Welfare Report. 2017 [cited 10 February 2018] [Internet]. Available from: https://www.mohw.gov.tw/cp-137-522-2.html.
19. Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE Jr., Drazner MH, et al. 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2013; 62: e147–239. doi: 10.1016/j.jacc.2013.05.019 23747642
20. Rosenbaum PR RD. Reducing bias in observational studies using subclassification on the propensity score. J Am Stat Assoc. 1984; 79: 516–524. doi: 10.1080/01621459.1984.10478078
21. Rosenbaum PR RD. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983; 70: 41–55. doi: 10.1093/biomet/70.1.41
22. Brookhart MA, Schneeweiss S, Rothman KJ, Glynn RJ, Avorn J, Sturmer T. Variable selection for propensity score models. Am J Epidemiol. 2006; 163: 1149–1156. doi: 10.1093/aje/kwj149 16624967
23. Berry SD, Ngo L, Samelson EJ, Kiel DP. Competing risk of death: an important consideration in studies of older adults. J Am Geriatr Soc. 2010; 58: 783–787. doi: 10.1111/j.1532-5415.2010.02767.x 20345862
24. Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999; 94: 496–509. doi: 10.2307/2670170
25. Workgroup KD. K/DOQI clinical practice guidelines for cardiovascular disease in dialysis patients. Am J Kidney Dis. 2005; 45: S1–153.
26. Foley RN, Parfrey PS, Harnett JD, Kent GM, O'Dea R, Murray DC, et al. Mode of dialysis therapy and mortality in end-stage renal disease. J Am Soc Nephrol. 1998; 9: 267–276. 9527403
27. Dasselaar JJ, Slart RH, Knip M, Pruim J, Tio RA, McIntyre CW, et al. Haemodialysis is associated with a pronounced fall in myocardial perfusion. Nephrol Dial Transplant. 2009; 24: 604–610. doi: 10.1093/ndt/gfn501 18775808
28. McIntyre CW, Burton JO, Selby NM, Leccisotti L, Korsheed S, Baker CS, et al. Hemodialysis-induced cardiac dysfunction is associated with an acute reduction in global and segmental myocardial blood flow. Clin J Am Soc Nephrol. 2008; 3: 19–26. doi: 10.2215/CJN.03170707 18003765
29. Hiramatsu T, Furuta S, Kakuta H. Longitudinal changes in parameters of cardiovascular function in patients treated for 8 years with hemodialysis or peritoneal dialysis. Adv Perit Dial. 2007; 23: 62–65. 17886605
30. Cao XS, Chen J, Zou JZ, Zhong YH, Teng J, Ji J, et al. Association of indoxyl sulfate with heart failure among patients on hemodialysis. Clin J Am Soc Nephrol. 2015; 10: 111–119. doi: 10.2215/CJN.04730514 25332316
31. Evenepoel P, Bammens B, Verbeke K, Vanrenterghem Y. Superior dialytic clearance of beta(2)-microglobulin and p-cresol by high-flux hemodialysis as compared to peritoneal dialysis. Kidney Int. 2006; 70: 794–799. doi: 10.1038/sj.ki.5001640 16820785
32. Meijers BK, Bammens B, De Moor B, Verbeke K, Vanrenterghem Y, Evenepoel P. Free p-cresol is associated with cardiovascular disease in hemodialysis patients. Kidney Int. 2008; 73: 1174–1180. doi: 10.1038/ki.2008.31 18305466
33. Puttagunta H, Holt SG. Peritoneal Dialysis for Heart Failure. Perit Dial Int. 2015; 35: 645–649. doi: 10.3747/pdi.2014.00340 26702006
34. Chawla LS, Herzog CA, Costanzo MR, Tumlin J, Kellum JA, McCullough PA, et al. Proposal for a functional classification system of heart failure in patients with end-stage renal disease: proceedings of the acute dialysis quality initiative (ADQI) XI workgroup. J Am Coll Cardiol. 2014; 63: 1246–1252. doi: 10.1016/j.jacc.2014.01.020 24530671
35. Green JB, Bethel MA, Armstrong PW, Buse JB, Engel SS, Garg J, et al. Effect of Sitagliptin on cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2015; 373: 232–242. doi: 10.1056/NEJMoa1501352 26052984
36. Scirica BM, Bhatt DL, Braunwald E, Steg PG, Davidson J, Hirshberg B, et al. Saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus. N Engl J Med. 2013; 369: 1317–1326. doi: 10.1056/NEJMoa1307684 23992601
37. Cheng CL, Chien HC, Lee CH, Lin SJ, Yang YH. Validity of in-hospital mortality data among patients with acute myocardial infarction or stroke in National Health Insurance Research Database in Taiwa. Int J Cardiol. 2015; 201: 96–101. doi: 10.1016/j.ijcard.2015.07.075 26292275
38. Su VY, Yang YH, Perng DW, Tsai YH, Chou KT, Su KC, et al. Real-world effectiveness of medications on survival in patients with COPD-heart failure overlap. Aging (Albany NY). 2019; 11: 3650–3667. doi: 10.18632/aging.102004 31175265
Článek vyšel v časopise
PLOS One
2019 Číslo 10
- Proč se v Česku šíří několik „vymýcených“ infekcí najednou? Ptáme se odborníků
- ADHD jako evoluční výhoda? Výzkum se zaměřil na lovce a sběrače
- Není migréna jako migréna: Co pociťují ženy a co muži?
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Není statin jako statin aneb praktický přehled rozdílů jednotlivých molekul
Nejčtenější v tomto čísle
- Correction: Low dose naltrexone: Effects on medication in rheumatoid and seropositive arthritis. A nationwide register-based controlled quasi-experimental before-after study
- Combining CDK4/6 inhibitors ribociclib and palbociclib with cytotoxic agents does not enhance cytotoxicity
- Efficacy of cotrimoxazole (Sulfamethoxazole-Trimethoprim) as a salvage therapy for the treatment of bone and joint infections (BJIs)
- Risk factors associated with IgA vasculitis with nephritis (Henoch–Schönlein purpura nephritis) progressing to unfavorable outcomes: A meta-analysis
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy