| Abstract|| |
Chronic kidney disease (CKD) affects health and life of patients. They confront anemia, hypertension, infections and cardiovascular disease. Due to these health issues, they are at risk of repeated hospitalizations. The risk factors which propel them to hospitalize are important to know, and by controlling these factors, we can impede preventable hospitalization. This case–control study included 1050 adult CKD patients, conducted in two tertiary care hospitals of Karachi. Variables included were age, gender, ethnicity, area of residence, marital status, education smoking status, comorbids, blood pressure, type of angioaccess, hemodialysis (HD) status, stage of CKD, activity level, and laboratory parameters. Two predicted models using multivariable logistic regression analysis were established to evaluate the effect of factors leading toward hospitalization. Patients with ischemic heart disease had 3.56 [95% confidence interval (CI): 2.14–5.9] times higher rate of admission. The nonactive and moderately active patients were admitted 3.8 and 2.26 times more respectively as compared to the active patients (P <0.001). Patients with HD venous catheter were admitted 33.43 (95% CI: 12.45–89.81) times more than patients without any angioaccess. All laboratory parameters had highly significant effect on admission (P <0.001), odds ratio for low albumin, low hemoglobin, and high total leukocyte count were 6.87(95% CI: 4.45–10.6), 4.2 (95% CI: 2.73–6.57) and 7.9 (95% CI: 4.93–12.66) respectively. In conclusion, cardiovascular disease was observed as the most important risk factor of hospitalization for CKD patients. The other plausible risk factors were late referral to nephrologist, low activity level anemia, and hypoalbuminemia.
|How to cite this article:|
Salman B, Hussain M, Shafique K, Imtiaz S, Dhrolia MF. Risk factors of hospitalization among chronic kidney disease patients in tertiary care hospitals - A single-center experience. Saudi J Kidney Dis Transpl 2018;29:1150-8
|How to cite this URL:|
Salman B, Hussain M, Shafique K, Imtiaz S, Dhrolia MF. Risk factors of hospitalization among chronic kidney disease patients in tertiary care hospitals - A single-center experience. Saudi J Kidney Dis Transpl [serial online] 2018 [cited 2020 Sep 25];29:1150-8. Available from: http://www.sjkdt.org/text.asp?2018/29/5/1150/243973
| Introduction|| |
In the last two decades, there has been a rapid upsurge in the incidence of chronic kidney disease (CKD), and it has been estimated that in the next decade or so more than two million individuals will be treated by renal replacement therapy worldwide. The CKD will be more prevalent in low- and middle-income countries than in high-income countries. Both of these factors, i.e. high CKD prevalence and large population residing in these regions resulted in a substantially greater burden of CKD in this region. The cost of that treatment will perhaps exceed 1 trillion dollars during the next decade. Due to the cost of the treatment people living in the developing world would continue to experience the consequences of the CKD.
CKD has deleterious effects on health and life of patients, they suffered high blood pressure (BP) or hypertension (HTN), low hemoglobin, imbalance of water and electrolytes, bone disorders due to imbalance of calcium and phosphorus, malnutrition due to loss of nutrient such as proteins. Due to the prolonged course of the disease, these patients encounter many health issues and are vulnerable to be hospitalized frequently. There are many reasons for this vulnerability such as high incidence of infections, angioaccess problems, cardiovascular events, late referral to nephrologist and anemia. Recurrent hospital admission not only increases the cost of ongoing treatment but also associated with enormous risk to the patient’s health.
Various risk factors are discussed in different studies, among those the low serum albumin was the strongest predictor of hospitalization. Other plausible predictors for hospitalization were high total leukocyte count (TLC), reduced activity level, increasing age, presence of diabetes mellitus (DM), angina, congestive heart failure (CHF), absence of HTN, smoking, and male gender.,,
The other important factors such as background lifestyle and health-related issues do play a significant role. For instance, the background prevalence of DM, HTN and cigarette smoking would be considerably different in our population compare to others. Our impression is that the risk factors of hospitalization may quantitatively be different in our population compared with the western population due to late referral to nephrologist, advance stage of disease at the time of diagnosis, noncompliance, relying on other methods of treatment like homeopathy and hakims.
There is a need to evaluate the causes of morbidity in patients who succumb to repeated hospitalization in our population. This study determined the risk factors which lead to repeated admissions in CKD patients. A better understanding of the rates, causes and risk factors for hospitalization among people with CKD would allow the identification of those who are at higher risk.
| Materials and Methods|| |
It was a case–control study conducted in The Kidney Center Post Graduate Medical Institute and Nephrology Unit of Dow University Hospital. We included all CKD patients, 18 years of age and above who were hospitalized during the study. We also included the patients who were already admitted at the time of study initiation. The controls were those who were not hospitalized and came to outpatient department (OPD) of the Kidney Center and Dow University Hospital for their routine follow-up during the study and had laboratory reports of serum albumin, hemoglobin, total leukocyte count, serum urea, and creatinine performed within one week. The ratio of cases and controls was 1:3 to increase sample size, precision and also to improve the power of the study. A structured questionnaire was used to collect the data on sociodemographic characteristics. The face-to-face interview was conducted by the principal investigator in OPD and wards of both institutes. Variables included in the study were age, gender, ethnicity, area of residence, marital status, education smoking status, comorbid, BP, type of angioaccess, hemodialysis (HD) status, stage of CKD, activity level, and laboratory parameters.
| Statistical Analysis|| |
Data analyses were performed using software IBM Statistical Package for the Social Sciences version 21.0. Cleaning and coding of the data were done before analysis. All continuous variables were categorized at the stage of analysis. Descriptive analysis of variables was presented in the form of frequencies and percentages.
To measure the association of hospital admission with categorical study variables, the chi-square test was executed. To see the amount of effect of different factors on hospitalization univariable logistic regression analysis was done and odds ratios with 95% confidence interval (CI) were obtained.
Two predicted models using multivariable logistic regression analysis were established to evaluate the effect of factors leading toward hospitalization. The first model was built using demographical variables which were adjusted with each other and the second model was constructed by adjusting clinical and laboratory parameters together. The level of significance was considered at 5%.
| Results|| |
Out of 1052 patients, males slightly outnumbered females in both groups (55% in cases and 50.2% in controls), and there was no association of gender with hospitalization (P = 0.172). The age group from 51 to 64 years was predominantly high in both cases and controls (40.9 % and 34.6%, respectively). However, no significant association was found between age and hospitalization status of CKD patients (P = 0.188). Among the different linguistic and ethnic groups, most of the patients who came in these two hospitals, were Urdu speaking (43.1% in cases and 53.4% in controls) while statistically both groups were different in ethnicity (P = 0.006). In the variable of job, most of the females were doing housework in both groups and rest of other works were also approximately same in both groups (P = 0.343). The education level was quite different in controls and cases (P = 0.001), uneducated patients were more in cases (53.4%) than controls (43.1%), while higher-educated patients were more in controls (26.4%) than cases (18.2%). Smoking status was also associated with hospitalization (P = 0.005) as ever smoker were more in cases (23%) as compared to controls (15.5%). Marital status was slightly different in both groups, married were more in cases (82.9%) than controls (77.8%); however, it was not statistically significant (P = 0.075).
Various comorbidities are associated with CKD patients, and in our sample, HTN was the most prevalent comorbid in both the groups (86.2% in cases and 86.8% in controls) followed by DM (54.6% in cases and 48.4% in controls). On the other hand, ischemic heart (IHD) disease was the single comorbid which was associated with more hospitalization (P <0.001) [Table 1].
|Table 1: Comparison of demographic and comorbid characteristics of case and control.|
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Among the clinical parameters, type of HD angioaccess, stages of CKD, and physical activity level were found associated with hospitalization (P <0.001). CKD patients presented late to hospitals as compared to controls (43.9% in stage V versus 26.8%). Activity level was significantly different among CKD cases and controls (P = 0.001). Higher number of patients was inactive (34.9%) in CKD cases as compared to controls (11.4%). On the other hand, active patients were more in control group (59.3%) as compared to those with CKD (23.8%). All laboratory parameters were significantly associated with hospitalization of CKD patients (P <0.001) [Table 2].
|Table 2: Comparison of clinical and laboratory parameters of case and control.|
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Demographical variables were analyzed for their impact on hospitalization and observed that gender, age, ethnicity, and marital status had no significant effect on admission in both unadjusted and adjusted analyses (P >0.005). However, uneducated patients got admitted 2.23 (CI: 1.46–3.41) times more than graduates and above educated patients (P <0.001) in univariable analysis and when the variable of education was adjusted with other covariates, the effect remained the same. The ever smoker CKD patients hospitalized 1.63 (CI: 1.16–2.34) times more than nonsmoker (P = 0.005) however when smoking was adjusted with other demographical risk factors, the variable became insignificant (P = 0.07) [Table 3].
|Table 3: Association of sociodemographic and other characteristics with hospital admission of chronic kidney disease patients.|
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Clinical status of the patients was evaluated for their effect on admission and presented in [Table 4]. Those patients who had ischemic heart disease had 3.56 times higher rate of admission than the patients without ischemic heart disease (P <0.001). BP had no significant effect on admissions in unadjusted analysis however when the analysis included other covariants, systolic and diastolic BP had significant effect on hospitalization. Patients with systolic BP of ≥140 mm Hg had 45% less chance of admission than patient with systolic BP of ≤140 mm Hg (P = 0.013) while the patients who had diastolic BP >90 mm Hg had twice the chances of admission than patients with diastolic BP of <90 mm Hg (P = 0.002). Similarly the HD status of the patient exhibited no significant effect on admission in univariable analysis whereas, in adjusted analysis, the patients who were on maintenance HD had 66% less admission than others (P = 0.004).
|Table 4: Association of clinical parameters with hospitalization of chronic kidney disease patients.|
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HD angioaccess, stage of CKD, and activity level were significant in both univariable and multivariable analysis. Patients who had temporary venous catheter for HD had 33 times more admissions than the patients who did not have any angioaccess.
CKD patients who presented for the first time in the hospitals with Stage V kidney disease had 2.4 times more admissions than Stage I and Stage II patients. In the same way, the CKD patients who were inactive had 3.8 times more admission than active patients. In univariate analysis, the patients who had hemoglobin level <9.5, TLC ≥11 and albumin level <3.5 got admitted 7.3, 9.1 and 6.9 times more respectively as compared to the patients with normal lab parameters (P <0.001), and when these lab parameters were adjusted with other clinical variables there was no change in significance (P <0.001) [Table 4].
| Discussion|| |
This large case–control study unveiled the factors such as the presence of IHD, low activity level, low estimated glomerular filtration rate (eGFR), status of HD angioaccess at the time of admission, diastolic HTN, low albumin, low hemoglobin, and high total leukocyte count, as potential preventable factors of hospitalization.
Among the demographic parameters, we found, smoking status, education level, and ethnicity were associated with increased rate of hospitalization. The mean age of our CKD population was low as compared with the other studies.,, This might be a manifestation of better health parameters of western population and overall longer survival.
Cigarette smoking is a recognized risk factor for a number of systemic and local diseases. Its association with increased progression of the kidney diseases also recognized recently., We also found a strong association between the positive smoking status and higher hospitalization rate. This might be due to the unusually fast progression of disease in this group of the patients.
Education makes a person to understand his disease and treatment plan more appropriately than an uneducated person. In a prospective cohort study, it was observed that inadequate education is associated with higher hospitalization rate., Our study showed the same association between the education level and hospitalization. We found Urdu speaking patients more in our study population; this could be an increased representation of this population because the data collection was done in the city where this ethnic group is predominant. This behavior was also been observed in other parts of the world, for example, there is a characteristic pattern of hospital admission among different ethnic groups, such as Blacks, Hispanics, and Whites in North America.
CKD patients are at increased risk of cardiovascular disease (CVD). Both albuminuria and reduced GFR increased the cardiovascular incidence in CKD population. There is an association between CVD (which includes acute coronary syndrome, stroke, heart failure, and sudden cardiac death) and CKD., This association gets stronger as the severity of renal disease and degree of proteinuria increase. In our study, population 32 (11.9%) patients were admitted with congestive cardiac failure, and 20 (7.4%) of the patients were admitted with acute coronary syndrome. Same increasing trends of cardiovascular hospitalization among CKD patients were found both in dialysis and predialysis patients.
Early reorganization of CKD and referral to nephrologist has many potential benefits. We recognized that most of the patients who were admitted with complication were those who presented with advance kidney disease to nephrologist. This late referred or late recognition of disease causes low hemoglobin, left ventricular hypertrophy, acidosis, hypoalbuminemia, high propensity to have infection, cardiovascular problems, and absence of permanent angioaccess at the time of first presentation to nephrology clinic., Early identification and management of these factors cause a significant improvement in morbidity, mortality, and rate of hospitalization. Our findings are consistent with others data as well.
Access of HD in the form of arteriovenous fistula (AVF) is considered as “Life Line” for CKD patients reaching ahead of dialysis. The presence of AVF in the form of permanent angioaccess at the time of initiation of HD saves the patients from disgusting and hideous complication of temporary angioaccess in the form of central venous catheters. We also found a significant effect of type of angioaccess at the initiation of HD. Those who did not have AVF and were dialyzed through central venous catheter suffered more hospitalization due to infection. In a systematic review, smart and titus compared early versus late referral to the nephrologist and patients who referred late experienced more hospitalization.
The activity level of the patients also predicts the morbidity and mortality. We found low activity level before hospitalization predicts future hospitalization. Our study confirmed the evidence from previous studies that low activity level as a strong predictor of hospitalization.,,
Laboratory parameters which have prognostic implications are well described. We evaluated the effect of hemoglobin, level of TLC, and serum albumin. We found an association of low hemoglobin, low albumin, and high TLC with increase hospitalization. These factors represent an underlying infection or inflammation. Our findings are compatible with various other studies. In a large retrospective trial, low hematocrit level was found to be associated with significantly high admission rate. Similarly, low serum albumin also been evaluated in many studies and showed a strong association with hospitalization.,,
In conclusion, CVD was observed as the most important risk factor of hospitalization for CKD patients. The other plausible risk factors were: late referral to nephrologist, low activity, low hemoglobin level, low albumin level, and high TLC.
Conflict of interest: None declared.
| References|| |
Lysaght MJ. Maintenance dialysis population dynamics: Current trends and long-term implications. J Am Soc Nephrol 2002;13 Suppl 1: S37-40.
Mills KT, Xu Y, Zhang W, et al. A systematic analysis of worldwide population-based data on the global burden of chronic kidney disease in 2010. Kidney Int 2015;88:950-7.
Schena FP. Epidemiology of end-stage renal disease: International comparisons of renal replacement therapy. Kidney Int 2000;57:S39-45.
Bullu A, Kawar B, Kossi ME, Nahas ME. Epidimiology and pathophysiology of chronic kidney disease. In: Johnson RJ, Feehally J, Floege J, editors. Comprehensive Clinical Nephrology. 5th ed. St. Louis: Elsevier Health Sciences; 2014. p. 907-18.
Henrich WL. Principles and Practice of Dialysis. 4th ed. Philadelphia: Lippincott Williams & Wilkins; 2012. p. 106-11.
Naqvi SB, Collins AJ. Infectious complications in chronic kidney disease. Adv Chronic Kidney Dis 2006;13:199-204.
Menon S, Valentini RP, Kapur G, Layfield S, Mattoo TK. Effectiveness of a multidisciplinary clinic in managing children with chronic kidney disease. Clin J Am Soc Nephrol 2009;4:1170-5.
Culleton BF, Larson MG, Wilson PW, et al. Cardiovascular disease and mortality in a community-based cohort with mild renal insufficiency. Kidney Int 1999;56:2214-9.
Smart NA, Titus TT. Outcomes of early versus late nephrology referral in chronic kidney disease: A systematic review. Am J Med 2011;124:1073-8.
Singh AK, Szczech L, Tang KL, et al. Correction of anemia with epoetin alfa in chronic kidney disease. N Engl J Med 2006;355:2085-98.
Rocco MV, Soucie JM, Reboussin DM, McClellan WM. Risk factors for hospital utilization in chronic dialysis patients. South-eastern kidney council (Network 6). J Am Soc Nephrol 1996;7: 889-96.
Holland DC, Lam M. Predictors of hospitalization and death among pre-dialysis patients: A retrospective cohort study. Nephrol Dial Transplant 2000;15:650-8.
Usvyat LA, Kooman JP, van der Sande FM, et al. Dynamics of hospitalizations in hemodialysis patients: Results from a large US provider. Nephrol Dial Transplant 2014;29:442-8.
Daratha KB, Short RA, Corbett CF, et al. Risks of subsequent hospitalization and death in patients with kidney disease. Clin J Am Soc Nephrol 2012;7:409-16.
Xie Y, Bowe B, Xian H, Balasubramanian S, Al-Aly Z. Rate of kidney function decline and risk of hospitalizations in stage 3A CKD. Clin J Am Soc Nephrol 2015;10:1946-55.
Norris K, Nissenson AR. Race, gender, and socioeconomic disparities in CKD in the United States. J Am Soc Nephrol 2008;19:1261-70.
Hall ME, Wang W, Okhomina V, et al. Cigarette smoking and chronic kidney disease in African Americans in the Jackson heart study. J Am Heart Assoc 2016;5. pii: e003280.
Yacoub R, Habib H, Lahdo A, et al. Association between smoking and chronic kidney disease: A case control study. BMC Public Health 2010;10:731.
Baker DW, Parker RM, Williams MV, Clark WS. Health literacy and the risk of hospital admission. J Gen Intern Med 1998;13:791-8.
Morton RL, Schlackow I, Staplin N, et al. Impact of educational attainment on health outcomes in moderate to severe CKD. Am J Kidney Dis 2016;67:31-9.
Yan G, Norris KC, Greene T, et al. Race/ethnicity, age, and risk of hospital admission and length of stay during the first year of maintenance hemodialysis. Clin J Am Soc Nephrol 2014;9: 1402-9.
Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351:1296-305.
Edfors R, Szummer K, Evans M, et al. Renal function is associated with long-term outcomes independent of degree of atherosclerosis: 6-year data from the Swedish Coronary Angiography and Angioplasty Registry. Eur Heart J Qual Care Clin Outcomes 2016;2:91-8.
Gerstein HC, Mann JF, Yi Q, et al. Albuminuria and risk of cardiovascular events, death, and heart failure in diabetic and nondiabetic individuals. JAMA 2001;286:421-6.
Mix TC, St. Peter WL, Ebben J, et al. Hospitalization during advancing chronic kidney disease. Am J Kidney Dis 2003;42:972-81.
Nitsch D, Nonyane BA, Smeeth L, et al. CKD and hospitalization in the elderly: A community-based cohort study in the United Kingdom. Am J Kidney Dis 2011;57:664-72.
London R, Solis A, Goldberg GA, Wade S, Ryu S. Health care resource utilization and the impact of anemia management in patients with chronic kidney disease. Am J Kidney Dis 2002;40:539-48.
Chandna SM, Schulz J, Lawrence C, Greenwood RN, Farrington K. Is there a rationale for rationing chronic dialysis? A hospital based cohort study of factors affecting survival and morbidity. BMJ 1999;318:217-23.
Curtin RB, Lowrie EG, DeOreo PB. Self-reported functional status: An important predictor of health outcomes among end-stage renal disease patients. Adv Ren Replace Ther 1999;6:133-40.
Xia H, Ebben J, Ma JZ, Collins AJ. Hematocrit levels and hospitalization risks in hemodialysis patients. J Am Soc Nephrol 1999;10:1309-16.
Di Napoli A, Pezzotti P, Di Lallo D, et al. Determinants of hospitalization in a cohort of chronic dialysis patients in central Italy. J Nephrol 2005;18:21-9.
Dalrymple LS, Mu Y, Nguyen DV, et al. Risk factors for infection-related hospitalization in incenter hemodialysis. Clin J Am Soc Nephrol 2015;10:2170-80.
Dr. Beena Salman
Department of Community Medicine, Jinnah Medical and Dental College, Karachi, 74800
[Table 1], [Table 2], [Table 3], [Table 4]