|Year : 2016 | Volume
| Issue : 4 | Page : 255-260
Predictors of mortality among patients on maintenance hemodialysis
D Ratna Prabha, G Prasad
Department of Nephrology, Andhra Medical College, Visakhapatnam, Andhra Pradesh, India
|Date of Web Publication||23-Dec-2016|
Department of Nephrology, King George Hospital, Visakhapatnam, Andhra Pradesh
Source of Support: None, Conflict of Interest: None
Context: Despite the continuous improvement of dialysis technology and pharmacological treatment, mortality rates for dialysis patients were still high. A 2-year prospective study was conducted at a tertiary care hospital to determine the factors influencing survival among patients on maintenance hemodialysis.
Patients and Methods: A total of 198 patients with end-stage renal disease who were started on hemodialysis (8 h/week) were studied. Follow-up was censored at the time of death or at the end of the 2-year study period, whichever occurred first.
Statistical Analysis Used: The Statistical Package for the Social Sciences version 15.0, Stata 8.0, MedCalc 9.0.1, and Systat 11.0 were used for data analysis.
Results: Of the 198 patients studied (mean age 49.95 ± 14.55 years, 68.3% male and 50.56% diabetics), 107 died with an estimated mortality rate of 54.04% at 1 year. On an age-adjusted multivariate analysis, female gender and independently predicted mortality. In Cox analyses, patient survival was associated with female sex, low serum albumin, native kidney urine output, presence of left ventricular hypertrophy (LVH) (ejection fraction <50% on two-dimensional echocardiography), compliance to dialysis, and interdialytic weight gain independently predicted mortality. There was no significant difference between diabetes and nondiabetes in relation to death (Relative Risk = 0.214; 95% CI = 0.005-10.02, P = 0.005).
Conclusions: This study revealed that mortality among hemodialysis patients remained high mostly due to sepsis and ischemic heart disease. Patient survival was better with good native kidney urine output, adequate serum albumin, absence of LVH and ejection fraction >50% on two-dimensional echocardiography, compliance to dialysis, and interdialytic weight gain <3 kg. Comprehensive predialytic nephrology care prevents mortality and improves survival among hemodialysis patients.
Keywords: Hemodialysis, mortality, survival
|How to cite this article:|
Prabha D R, Prasad G. Predictors of mortality among patients on maintenance hemodialysis. J NTR Univ Health Sci 2016;5:255-60
| Introduction|| |
Prevalence of end-stage renal disease (ESRD) is increasing with enormous financial burden on society. , Approximately 50 years ago, ESRD was invariably lethal. Although maintenance dialysis methods have now successfully prolonged the life of patients, mortality remains high.  Approximately 9-13% of patients on hemodialysis in India die within 1 year.  The adjusted rates of all-cause mortality are 6.3-8.2 times greater for dialysis patients than the general population.  The gold standard of dialysis therapy is yet to be identified. Research is required to improve overall mortality rates and to achieve improved survival and rehabilitation in hemodialysis patients.  We investigated the outcome of hemodialysis and the factors which had an impact on survival.
| Patients and Methods|| |
Consecutive patients with ESRD who were started on maintenance hemodialysis were enrolled prospectively over a period of 2 years. Both the patient and his/her relatives were subsequently interviewed and data entered into an electronically compatible proforma. Patients were diagnosed to have ESRD if they had an irreversible decline in renal function (estimated glomerular filtration rate by CKD EPI formula)  for more than 3 months. The diagnosis of underlying kidney disease was based on clinical, laboratory, and radiological features.
Patients with acute renal failure, those who dropped out or who were switched over to other forms of renal replacement therapy such as continuous ambulatory peritoneal dialysis (CAPD) and renal transplantation, and all who were positive for HbsAg and hepatitis C virus (HCV) were excluded.
At baseline, i.e., within 1 month after the start of dialysis, information was collected regarding demographic profile, underlying kidney disease, and comorbid conditions. After the start of therapy, information was gathered on the probable native kidney disease using clinical history, examination of the patient, and necessary investigations. Information on nutritional status [body mass index (BMI)], native kidney urine output, blood pressure, presence or absence of diabetes, and investigations including hemoglobin, serum albumin, calcium, phosphorus, two-dimensional (2D) echocardiographic features, i.e., presence of left ventricular hypertrophy (LVH), and ejection fraction (EF) <50%, as well as hemodialysis characteristics which includes compliance to scheduled sessions of hemodialysis, interdialytic weight gain were noted as per the standard proforma. Those who missed two or more sessions of hemodialysis in a month were considered to be poorly compliant. The patients were followed-up for 2 years from the start of the study or until death. At the end of the study period, population was divided into two groups based on the survival time, i.e. those who survived for at least a period of 1 year were considered as survived and those who died within 1 year were considered as died. In addition, all the abovementioned clinical, lab, echocardiographic, and dialysis-related factors were compared between the two groups, and the risk factors associated with death were identified.
Standard bicarbonate hemodialysis was performed for 4 h twice weekly. Individual proportioning dialysis machines were used with reverse-osmosis treated water. Volumetric ultrafiltration control was available in all the machines. Polysulfone hollow fiber dialyzers of mass transfer area coefficient of 578 ml/min (500-600 ml/min) and ultrafiltration coefficient 5.5 ml/h-mmHg were used. Dialyzate flow rate was 500 ml/min, and blood flow rates were targeted as per the patient requirement. Dialyzer reuse was uniformly performed using automated methods. Details regarding the type of vascular access, hepatitis B vaccination, erythropoietin use, and the complications on hemodialysis including vascular access-related ones were recorded. The outcome of all patients in terms of survival and mortality was assessed at the end of the study. Factors associated with increased risk of death which had an impact on survival were analyzed.
Mean ± standard deviation (SD) and percentages were used for summarizing the data. Continuous variables were studied using the Student's t-test (two-tailed, independent). Categorical variables were analyzed using the Chi-square and 2 × 2, 2 × 4 Fisher's exact tests. The primary endpoint of the analysis was death or completion of study period. Cox proportional hazard analysis were used for calculation of survival. Multivariate logistic regression analysis was performed to identify independent predictors of mortality. All statistical analyses were performed with the Statistical Package for the Social Sciences version 15.0, Stata 8.0, MedCalc 9.0.1, and Systat 11.0.
| Results|| |
A total of 286 patients fulfilled the inclusion criteria. After excluding transfer to other hemodialysis centre's, dropouts, renal transplantation, and Continuous Ambulatory Peritoneal Dialysis (CAPD), a total of 198 patients were included in the study. Majority of the patients were above 40 years of age (age 49.95 ± 14.55) and males outnumbered females in a ratio of 2.9:1 [Table 1] and [Table 2]. Diabetics comprised 50.56% of the patient population. Chronic interstitial nephritis was the most common underlying kidney disease (34.3%). Chronic glomerulonephritis accounted for 16.6%, hypertensive nephrosclerosis 15.84%, Autosomal Dominant Polycystic Kidney Disease (ADPKD) 15.84%, obstructive nephropathy 15.7%, chronic pyelonephritis 11.88%, diabetic kidney disease 10.6%, Rapidly Progressing Renal Failure (RPRF) 9.9%, igA nephropathy 7.92%, and alport syndrome 3.96%. However, unknown kidney disease accounted for 53.46% of the total cases [Table 3].
|Table 1: Comparing the various variables between dead and surviving patients|
Click here to view
|Table 3: Comparing the etiology of chronic kidney disease between the two groups|
Click here to view
Mean time for formation of arteriovenous fistula in the present study was 40 days. All of the patients were initiated on dialysis through right internal jugular vein access. A total of 107 (54%) out of the 198 patients studied died by the end of 1 year.
Among the variables included for assessing survival functions using Cox-regression model, female sex, native kidney urine output >250 ml, serum albumin >2.5 g/dl, echocardiographic findings of EF >50%, and absence of LVH and interdialytic weight gain of <3 kg were found to be significantly affecting the survival [Table 4]. Though the proportion of patients with diabetes mellitus was large, there was no significant difference between those with and without diabetes in relation to survival.
|Table 4: Binary logistic regression analysis to identify predictors of mortality |
Click here to view
| Discussion|| |
Analysis of our data at the end of 2 years revealed an estimated mortality rate of 54.04%, which is higher than that reported by Chandrasekar et al.,  in which 19 patients died out of 96 patients at the end of 2 years with an estimated mortality rate of 19.8%. In a study by Shibiru et al.,  which was a retrospective analysis of 91 patients on maintenance hemodialysis of 8 years duration in Ethiopia, 45.1% patients died during dialysis treatment and 23.1% patients died within the first 90 days. In the DOPPS  phase 1 data, which was a multicentric study done from 2007 to 2010, reported a 1-year mortality rate of 17.5%.
Out of the total 107 deaths, with an estimated mortality of 54.04%, 71 (66%) deaths occurred in the first 120 days after initiation of dialysis and 36 deaths (44%) occurred between 121 days and 365 days after initiation of hemodialysis, indicating a high period of risk in the first 4 months after initiation of dialysis. USRDS data also portrayed a consistent pattern of higher mortality rates in the first few months of dialysis, especially in the 2 to 4 months of starting the treatment.  In the DOPPS study also significant period of increased difference in mortality was identified during 121 days after dialysis initiation. In the present study, the mean age was 54 ± 5 years and 45.9 ± 7 years in the died and survived group, respectively. This was similar to that reported by Chandrasekahar et al.  in which the mean age of the cohort was 50.89 ± 17. The mean age at dialysis initiation in a study from Ethiopia by Shiribu et al. was 58 ± 15 years. Our study results are comparable with these results. 
Female sex was independently associated with mortality, as evidenced by the hazard ratio of 0.001 with 95% CI of 0.000-0.0065. This finding was in contrast to those of Depner et al. and USRDS  data, which demonstrated survival advantage for females. In a study by Chandrasekhar et al.,  diabetes mellitus per se did not have a statistically significant impact on the study outcome. Presence of hypertension was not associated with an increased risk of mortality in our study.The results are similar to that obtained by Chandrasekhar et al.,  in which risk of death in the died group was 94% when compared to 92%, which was not statistically significant. Bradbury et al.  demonstrated 75% versus 22% risk of death between hypertensives and nonhypertensives, respectively, which was statistically significant. Hence, our results are similar to those of Chandrasekhar et al.,  and there was no significant impact of hypertension on mortality.
A strong association exists between nutritional status and morbidity and mortality in patients with ESRD who were treated with hemodialysis.  Studies reported by Owen et al.  and Dwyer et al.  demonstrated an increased mortality in undernourished patients; however, there was no significant risk of death among patients with low BMI and this was not an independent predictor of mortality. In our present study, serum albumin was 2.9 g/dl in the died group and 2.09 g/dl in the survived group. Serum albumin value was significantly associated with an increased risk of death, as evidenced by a significant P value of 0.00. This finding is similar to the study by Soucle et al. 
Mean hemoglobin values in the present study was 6.67g/dl, which were much lower than the recommendations made by Kidney diseases improving global outcome (KDIGO), and anemia was not found to be an independent predictor of mortality. , In the present study, mean calcium in the survived group was 7.58 mg/dl, with a SD of 0.66; in the died group, mean calcium was 7.93 mg/dl with a SD of 0.48. A total of 89.7% of total population in the died group had calcium below 8.3 mg/dl and in the survived group it was 84%. The mean phosphorous values in the present study was 4.56 ± 0.68 and 4.49 ± 0.69 in the died and survived groups, respectively. This low mean calcium values in the survived group and higher calcium values in the died group was similar to those reported by Chandrasekhar et al.  The mean calcium value of 7.93 in the died group is similar to the study by Geofrey et al., in which higher serum calcium values and low phosphorous values were found in incident hemodialysis patients, which correlated positively with mortality and low serum phosphorous also correlated with poor nutritional status and low protein intake.  However, there was no statistical correlation between high calcium and phosphorous values and increased risk of death.
IDWG has been regarded as a surrogate of volume overload in ESRD patients on hemodialysis. Higher interdialytic weight gain was associated with adverse cardiovascular outcomes by Lee et al.  In the present study interdialytic weight gain of more than 3 kg was an independent predictor of mortality. Previous studies have revealed that excessive IDWG is associated with adverse clinical outcomes. , Furthermore, a very recent study demonstrated that IDWG >3.0 kg was associated with a 1.29-fold increase in all-cause mortality, independent of dialysis session length. ,
A study by Kjaergaard et al.  documented that preservation of residual renal function in dialysis patients improves quality of life as well as survival. Observational studies have shown that preservation of residual renal function (RRF) in dialysis patients was an independent factor in patient survival. In the present study, native kidney urine output in the died group was 185 ml with a SD of 19 and that in the survived group was 142 ml with a SD of 13.8, which was statistically significant. This observation was similar than what was obtained in two studies by Shafi et al. and Leoct et al. ,,
Cardiovascular disease is the most important cause of mortality in ESRD.  In a study by Foley, in a cohort of dialysis patients, there was high prevalence of clinically manifested cardiovascular disease. However, in the present study presence of LVH and EF <50% were found to be independent predictors of mortality. Cardiac disease is the major cause of death in dialysis patients, accounting for 40% of deaths in international registries. ,
All the patients in the present study had temporary right internal jugular vein access at the beginning of dialysis and none of them had arteriovenous fistula; hence, the impact of temporary access versus arteriovenous fistula on mortality was not studied.
In the present hospital-based study, 1-year mortality rate of 54% was noted, and an increased mortality was noted in the first 120 days after dialysis initiation. Female sex, serum albumin, ejection fraction, and presence of LVH on 2D echocardiography, as well as native kidney urine output dialysis related factors, i.e., compliance to dialysis and interdialytic weight gain were found to be independent predictors of mortality.
| Conclusions|| |
Increased early mortality was noted in the first 120 days after initiation of dialysis. Although female population was relatively less in both the groups, females were at a greater risk of death when compared to males. Diabetes and hypertension were not significantly associated with mortality. Majority of patients had a haemoglobin, which was far less than that recommended by KDIGO guidelines. Poor nutritional status and low socioeconomic status as evidenced by low BMI and low serum albumin were noted. Low EF and concentric LVH association were independent predictors of mortality.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Hsu CY, Vittinghoff E, Lin F, Shlipak MG. The incidence of end-stage renal disease is increasing faster than the prevalence of chronic renal insufficiency. Ann Intern Med 2004;141:95-101.
Grassmann A, Gioberge S, Moeller S, Brown G. ESRD patients in 2004. Global overview of patient numbers, treatment modalities and associated trends. Nephrol Dial Transplant 2005;20:2587-93.
Pozzoni P, Del Vecchio L, Pontoriero G, Di Filippo S, Locatelli F. Long-term outcome in hemodialysis Morbidity and mortality. J Nephrol 2004;17:87-95.
Rao M, Juneja R, Shirly RB, Jacob CK. Haemodialysis for end-stage renal disease in Southern India: A perspective from a tertiary referral care centre. Nephrol Dial Transplant 1998;13:2494-500.
Collins AJ, Foley RN, Herzog C, Chavers B, Gilbertson D, Herzog C, et al
. US Renal Data System 2012 Annual Data Report. Am J Kidney Dis 2013;61:e1-476.
Cambi V. Dialysis strategies. In: Davison AM, Cameron JS, Grünfeld JP, Kerr DN, Ritz E, Winearls CG, editors. Oxford Textbook of Clinical Nephrology. 3 rd
ed. Vol. 3. New York: Oxford University Press Inc; 2005. p. 1899-908.
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976;16:31-41.
Chandrashekar A, Ramakrishnan S, Rangarajan D. Survival analysis of patients on maintenance hemodialysis. Indian J Nephrol 2014;24:206-13.
Shibiru T, Gudina EK, Habte B, Derbew A, Agonafer T. Survival patterns of patients on maintenance hemodialysis for end stage renal disease in Ethiopia: Summary of 91 cases. BMC Nephrol 2013;14:127.
Bradbury BD, Fissell RB, Albert JM, Anthony MS, Critchlow CW, Pisoni RL, et al
. Predictors of early mortality among incident US hemodialysis patients in the Dialysis Outcomes and Practice Patterns Study (DOPPS). Clin J Am Soc Nephrol 2007;2:89-99.
United States Renal Data System. Excerpts from USRDS 2008 Annual Data Report. U.S. Department of Health and Human Services. The National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases. Am J Kidney Dis 2009;1:S1.
Leavey SF, Strawderman RL, Jones CA, Port FK, Held PJ. Simple Nutritional Indicators as Independent Predictors of Mortality in Hemodialysis Patients. Am J Kidney Dis 1998;31:997-1006.
Owen WF, Lew NL, Liu Y, Lowrie EG, Lazarus JM. The urea reduction ratio and serum albumin concentration as predictors of mortality in patients undergoing hemodialysis. N Engl J Med 1993;329:1001-6.
Dwyer JT, Larive B, Leung J, Rocco MV, Greene T, Burrowes J, et al
. Are nutritional status indicators associated with mortality in the Hemodialysis (HEMO) Study. Kidney Int 2005;68:1766-76.
Soucie JM, McClellan WM. Early Death in Dialysis Patients: Risk Factors and Impact on Incidence and Mortality Rates. J Am Soc Nephrol 1996;7:2169-75.
Kidney disease improving global outcomes (KDIGO) Anemia work group: KDIGO clinical practice guidelines for anemia in chronic kidney disease: Kidney international;suppl.2012;2:279-335.
Block G. Calcium, Calcimimetics and Clinical Outcomes. Clin J Am Soc Nephrol 2006;1:170-1.
Cabrera C, Brunelli SM, Rosenbaum D, Anum E, Ramakrishnan K, Jensen DE, et al
. A retrospective, longitudinal study estimating the association between interdialytic weight gain and cardiovascular events and death in hemodialysis patients. BMC Nephrol 2015;16:113.
Lee MJ, Doh FM, Kim CH, Koo HM, Oh HJ, Park JT, et al
. Interdialytic Weight Gain and Cardiovascular Outcome in Incident Hemodialysis Patients. Am J Nephrol 2014;39:427-35.
Flythe JE, Curhan GC, Brunelli SM. Disentangling the ultrafiltration rate-mortality association: The respective roles of session length and weight gain. Clin J Am Soc Nephrol 2013;8:151-61.
Kjaergaard KD, Jensen JD, Peters CD, Jespersen B. Preserving residual renal function in dialysis patients: An update on evidence to assist clinical decision making. NDT Plus 2011;4:225-30.
Shafi T, Jaar BG, Plantinga LC, Fink NE, Sadler JH, Parekh RS, et al
. Association of residual urine output with mortality, quality of life, and inflammation in incident hemodialysis patients: The Choices for Healthy Outcomes in Caring for End-Stage Renal Disease (CHOICE) Study. Am J Kidney Dis 2010;56:348-58.
Liao CT, Chen YM, Shiao CC, Hu FC, Huang JW, Kao TW, et al
. Rate of decline of residual renal function is associated with all-cause mortality and technique failure in patients on long-term peritoneal dialysis. Nephrol Dial Transplant 2009;24:2909-14.
Lindner A, Charra B, Sherrard DJ, Scribner BH. Accelerated atherosclerosis on prolonged maintenance hemodialysis. N Engl J Med 1974;290:697-701.
US. Renal Data System, USRDA 1991 Annual Report. Bethesda. The National Institute of Diabetes and Digestive and Kidney Diseases; 1991.
Fassbinder W, Brunner FP, Brynger H, Ehrici JH, Geerlings W, Raine AE, et al
. Combined report on regular dialysis and transplantation in Europe XX, 1989. Nephrol Dial Transplant 1991;6:5-35.
Depner T, Daugirdas J, Greene T, Allon M, Beck G, Chumlea C, et al
. Dialysis dose and the effect of gender and body size on outcome in the HEMO Study. Kidney Int 2004;65:1386-94.
[Table 1], [Table 2], [Table 3], [Table 4]