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| ORIGINAL ARTICLE |
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| Year : 2021 | Volume
: 18
| Issue : 2 | Page : 95-99 |
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Short-Term outcomes and their predictors among patients with cardiorenal syndrome hospitalized for heart failure
Muhammad N Shehu1, Basil N Okeahialam2, Musa M Borodo3, Mahmoud U Sani3, Simeon A Isezuo4
1 Department of Internal Medicine, General Amadi Specialist Hospital, Katsina, Nigeria
2 Department of Medicine, Jos University Teaching Hospital, Plateau State, Nigeria
3 Department of Medicine, Bayero University Kano and Aminu Kano Teaching Hospital, Kano, Nigeria
4 Department of Medicine, Usman Danfodio University Teaching Hospital Sokoto, Sokoto State, Nigeria
| Date of Submission | 22-Mar-2021 |
| Date of Decision | 01-Jun-2021 |
| Date of Acceptance | 04-Jul-2021 |
| Date of Web Publication | 10-Dec-2021 |
Correspondence Address:
Dr. Muhammad N Shehu
Cardiology Unit, Internal Medicine Department, General Amadi Rimi Specialist Hospital Katsina
Nigeria
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/njbcs.njbcs_12_21
Context: Cardiorenal syndrome (CRS) encompasses a spectrum of disorders involving both the heart and kidneys in which acute or chronic dysfunction in one organ may induce acute or chronic dysfunction in the other organ. Aim: To review the short-term outcomes and their predictors among patients admitted with HF complicated by renal impairment. Settings and Design: This was a cross-sectional study conducted at the Aminu Kano Teaching Hospital, Kano, Nigeria. Materials and Methods: Patients aged 18 years and above were consecutively recruited over a period of 11 months. Detailed history and physical examination as well as relevant baseline blood chemistry, full blood count, urinalysis, estimated glomerular filtration rate, ECG, echocardiography, and renal ultrasound were carried out on all patients. Statistical analysis used: The data was analyzed using SPSS Version 16.0. Student t-test and the nonparametric χ2 or Fisher's exact test were used to test for significance among the noncategorical and categorical variables, respectively. Results: One hundred and twenty four (72.9%) patients had CRS. Patients with CRS had a significantly higher mortality rate compared with those without the syndrome (25% vs. 13%; P = 0.031). There was no significant difference in the duration of hospital stay between patients with CRS and those without CRS (17.86 ± 13.11 vs. 15.85 ± 13.46; P = 0.378). Serum creatinine of ≥170 μmol/L and serum urea of >20 mmol/L were the identified predictors of mortality (95% confidence interval [CI] 1.098–6.243, RR = 2.618, P = 0.030; and 95% CI 1.106–6.757, RR = 2.734, P = 0.029, respectively). Conclusion: CRS is associated with a significantly higher mortality rate. Measures of the renal function, serum creatinine >170 μmol/L and serum urea of >20 mmol/L were identified as the predictors of mortality.
Keywords: Cardiorenal syndrome, Kano, outcomes, short-term
How to cite this article:
Shehu MN, Okeahialam BN, Borodo MM, Sani MU, Isezuo SA. Short-Term outcomes and their predictors among patients with cardiorenal syndrome hospitalized for heart failure. Niger J Basic Clin Sci 2021;18:95-9 |
How to cite this URL:
Shehu MN, Okeahialam BN, Borodo MM, Sani MU, Isezuo SA. Short-Term outcomes and their predictors among patients with cardiorenal syndrome hospitalized for heart failure. Niger J Basic Clin Sci [serial online] 2021 [cited 2022 Dec 9];18:95-9. Available from: https://www.njbcs.net/text.asp?2021/18/2/95/332198 |
| Introduction | |  |
Cardiorenal syndrome (CRS) can be defined as a moderate or severe renal dysfunction that develops in a patient with heart failure (HF) during treatment.[1] The association between renal insufficiency and poor outcome in patients with HF is a marker of advanced cardiac disease, directly associated with morbidity and mortality independent of standardized measures of HF severity.[2],[3],[4],[5],[6],[7],[8], [9,[10],[11]
There has been not much information about the impact of the syndrome on the prognosis of patients with HF, particularly from the study area. This study, therefore, aims at documenting the short-term outcomes (hospital stay and mortality) and their predictors among CRS patients.
| Materials and Methods | | |
The study was conducted at the Aminu Kano Teaching Hospital (AKTH), Kano, Nigeria.
It is cross-sectional in design, and the study population was made up of patients 18 years and above hospitalized for the first time with the diagnosis of HF. Patients were excluded from the study if they were on hemodialysis before admission or if they who denied consent. Detailed history and physical examination were carried out on all suspected cases of HF on arrival. The interview was conducted using a standard pro forma.
Investigations carried out on all patients include serum creatinine (SCr), urea and electrolytes (U/E), complete blood count, blood glucose, serum uric acid, lipid profile, urinalysis, electrocardiography (ECG), and echocardiography. The urinary protein–creatinine ratio was determined to estimate 24 hours urine protein excretions in those who had proteinuria on urinalysis. A renal ultrasound scan was done on all the patients. Glomerular filtration rate (GFR) was estimated using the Cockcroft–Gault equation that has been validated worldwide and in Nigerian patients as representative of the real determined GFR.[12],[13],[14] SCr and U/E were repeated once during the treatment and at Day 7 or at discharge.
HF diagnosis was based on the Framingham criteria,[15] which consist of the major and minor criteria for HF. The major criteria included orthopnea, paroxysmal nocturnal dyspnea, raised jugular venous pressure, cardiomegaly, third heart sound with or without gallop rhythm, and pulmonary rales, whereas the minor criteria included dyspnea on exertion, dry cough, pedal edema, tachycardia, tender hepatomegaly, and ascites. A minimum of two major criteria or one major plus two or more minor criteria were required to make a diagnosis of HF provided they were not attributable to causes other than HF.[15] Renal impairment in HF (CRS) was diagnosed by estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2.[8],[16],[17],[18],[19]
All data generated were collated, checked, and analyzed using computer-based Statistical Package for Social Sciences Version 16.0. Quantitative variables were described using mean and standard deviation. Qualitative variables were presented as percentages, bar charts, and pie charts. Student t-test and the nonparametric χ2 or Fisher's exact test were used to test for significance among the noncategorical and categorical variables, respectively. Multivariate analysis, using the binary regression model, was used to determine the predictors for CRS. Confidence interval (CI) of 95% was used, and a P value of less than 0.05 was considered significant.
Approval for the study was obtained from the Ethical Committee of AKTH with reference number NHREC/21/08/2008a/AKTH/EC/205. The provision of the Helsinki Declaration was respected.
| Results | | |
A total of 170 patients consisting of 70 (41.2%) males and 100 (58.8%) females were studied. The mean age of the patients was 49.6 ± 18.7 (range 18–90 years). [Figure 1] shows the sex and age distribution of the study population. The most frequent age group was that of 55–64 years. Compared with the group without CRS, those with CRS were significantly older (53.2 ± 18.1 vs. 39.6 ± 17.1; P < 0.0001), had higher frequency of hypertension (66.9% vs. 39.1%; P = 0.001) and diabetes (16.1% vs. 4.3%; P = 0.043) [Table 1].
Mortality and duration of hospital stay
[Table 2] shows the outcomes (death and duration of hospital stay) among patients. Of the 170 patients, 37 (21.8%) died. Although no autopsy was done, clinically recognizable causes of death were as follows: 20 patients died of cardiogenic shock, five patients died from uremic encephalopathy, five patients died from pulmonary edema, three patients died from sepsis, and four patients had sudden death likely from ventricular tachycardia or ventricular fibrillation. The mean length of hospital stay for all patients was 17.32 ± 13.2 days. The CRS group had a significantly higher mortality rate compared with those without CRS (P = 0.031). The difference in the duration of hospital stay was not statistically significant between the group with CRS and those without CRS (P = 0.378).
Factors that influence mortality
[Table 3] shows the comparison of clinical and laboratory parameters among the deceased and the survivors of CRS. While the deceased had a significantly higher proportion of patients with SCr of ≥170 μmol/L, urea of >20 mmol/L, eGFR of <53 mL/minute and New York Heart Association (NYHA) Class IV (P = 0.001, 0.001, 0.045, and 0.009, respectively), the survivors had higher proportion of patients with systolic blood pressure (SBP) >160 mmHg (P = 0.001). There was no association found between the mortality and different diastolic blood pressure (DBP) and mean arterial pressure (MAP) levels. Also, no association was found between mortality and the mean levels of DBP and MAP (92.2 ± 24.8 vs. 94.5 ± 26.2; P = 0.672). On multivariate analysis, only SCr >170 μmol/L (95% CI 1.098–6.243, RR = 2.618, P = 0.030) and urea of >20 mmol/L (95% CI 1.106–6.757, RR = 2.734, P = 0.029) were the predictors of mortality among the CRS patients. SBP >160 mmHg and eGFR <53 mL/minute were found to have no effect on mortality or survival after the multivariate analysis.
| Discussion | | |
The study determined the mortality and its predictors, as well as length of hospital stay, among the patients admitted with HF in AKTH.
In-hospital mortality was significantly higher among patients with CRS compared with those without. Registries and clinical trials have consistently confirmed that renal dysfunction is associated with a substantial increase in the risk of in-hospital, intermediate, and long-term death.[20],[21],[22] Risk ratios for death during hospitalization, complications, and length of stay >10 days increased sevenfold, twofold, and threefold, respectively, in those who developed CRS compared with those who did not.[23] In the Study of Left Ventricular Dysfunction, moderate degrees of renal insufficiency were independently associated with an increased risk for all-cause mortality in patients with HF.[22] Even after adjustment for all other prognostic factors, survival was significantly associated with renal function in patients with either systolic or diastolic dysfunction.[24] The mortality rate of 25% among CRS patients in this study was rather lower than what was recorded by other studies.[22],[25],[26] A Nigerian study on advanced HF with aggravated renal dysfunction recorded a total mortality rate of 72.2% over 36 months study period.[27] Other studies recorded a mortality rate of 47% to 72.2%.[22],[26] Although the Nigerian study recruited patients with advanced HF, other studies had larger samples (755 and 1,004 patients) and longer study periods, which may explain the higher mortality recorded in these studies.
There was no difference in the duration of hospital stay among patients with or without CRS. A study on aggravated renal dysfunction among patients with HF in Nigeria also observed no significant difference in the duration of hospital admission among patients with and without aggravated renal dysfunction.[27] However, in the United States, acute kidney injury was estimated to result in a threefold increase in length of hospital stay and a 22% higher mortality rate among HF patients over the age of 65 years.[28] Other studies also reported longer hospital stays >10 days (4 days longer) among HF patients with renal dysfunction compared to those with no renal dysfunction.[29],[30]
Renal dysfunction, in the absence of HF, carries a poor prognosis. It is not surprising, therefore, that the concomitant presence of the two diseases had poorer outcomes.[31] However, it has been speculated that the higher mortality observed in CRS may be attributable, at least in part, to more advanced HF, excess comorbidities, and/or therapeutic nihilism in patients with concomitant renal insufficiency (who are less likely to receive proven efficacious therapies for either the index condition or the comorbidities). It has also been speculated that patients with renal insufficiency are at higher risk for drug toxicities and do not obtain the same benefits from medications shown to be efficacious in the healthier patients enrolled in trials.[24]
The only variables that predicted mortality in this study were SCr ≥ 170 μmol/L and serum urea of >20 mmol/L. Measures of renal dysfunction have been found to be more powerful predictors of mortality than measures of left ventricular dysfunction (left ventricular ejection fraction and NYHA) in patients with CRS.[8],[32] In a Nigerian study, SCr was found to correlate with mortality in HF.[8] In an African multicenter study, only SCr had statistically differing values between the deceased and survivors of HF.[33] In a study of risk stratification for in-hospital mortality in acute decompensated HF, of the 39 variables evaluated serum urea level of ≥15.35 mmol/L at admission was identified as the best single discriminator between hospital survivors and nonsurvivors.[32] In the Enhanced Feedback for Effective Cardiac Treatment Study, increasing serum urea level was a significant and independent predictor of both 30 days and 1 year mortality.[34]
Increasing SCr and urea was identified as significant and independent predictors of mortality or rehospitalization in the Outcomes of a Prospective Trial of Intravenous Milrinone for Exacerbation of Chronic Heart Failure study.[35] Similarly, in a retrospective review of 1,004 consecutive patients hospitalized for HF at 11 geographically diverse hospitals, worsening renal function was associated with a 7.5-fold increase in the adjusted risk of in-hospital mortality.[36] Renal dysfunction causes further congestion and activation of neurohormonal system, which are the factors that have been associated with adverse outcomes in patients with HF.[32]
| Conclusions | | |
CRS was frequent among the study population and was associated with increased mortality. High SCr and high serum urea predicted mortality in these patients. CRS assessment is recommended for all patients with HF, and studies on its long-term outcomes are required.
Acknowledgments
We highly appreciate the efforts and support of the head of the department of medicine, Aminu Kano Teaching Hospital, Kano, in the person of Prof. M. M. Borodo, and the entire staff of the department toward the successful completion of this study.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Kirkwood FA, Alan SM. Challenges in acute heart failure management: The cardiorenal syndrome. Clinician 2006;24:1-20.  |
| 2. | Weinfeld MS, Chertow GM, Stevenson LW. Aggravated renal dysfunction during intensive therapy for advanced chronic heart failure. Am Heart J 1999;138:285-90. |
| 3. | Jardine GA. Cardiovascular complications of renal disease. Heart 2001;86:459-66. |
| 4. | Ritz E, McClellan WM. Overview: Increased cardiovascular risk in patients with minor renal dysfunction: An emerging issue with far reaching consequences. J Am Soc Nephrol 2004;15:513-6. |
| 5. | McAliter FA, Ezekowitz J, Tonelli M, Armstrong PW. Renal insufficiency and Heart failure: Prognostic and therapeutic implications from prospective cohort study. Circulation 2004;109:1004-9. |
| 6. | Mann JF, Gerstein HC, Pogue J, Bosch J, Yusuf S. Renal insufficiency as a predictor of cardiovascular outcomes and the impact of ramipril: The HOPE randomize trial. Ann Intern Med 2001;134:629-36. |
| 7. | Heath ES, Kumar S, Poul JM, Sharon R, Suzanne A, David JW. Renal dysfunction in heart failure patients: What is the evidence? Heart fail Rev 2007;12:37-47. |
| 8. | Kelly VL, Amy W, Eddie LG, Margaret MR. Acute decompensated heart failure and the cardiorenal syndrome. Crit Care Med 2008;36:S75-88. |
| 9. | Anjay R, Gregg C. The cardiorenal connection in heart failure. Curr Cardiol Rep 2008;10:190-7. |
| 10. | Hill JA, Shah MR, Hasselblad V. Pulmonary artery catheter use does not change the contribution of renal dysfunction to outcomes in patients with advanced heart failure: Findings from ESCAPE. Circulation 2004;110(Suppl 3): III-638. Abstract 2964. |
| 11. | Aronson D, Mittleman MA, Burger AJ. Elevated blood urea nitrogen level as a predictor of mortality in patients admitted for decompensated heart failure. Am J Med 2004;116:466-73. |
| 12. | Cockroft DW, Gault MH. Prediction of creatinine clearance using serum creatinine. Nephron 1976;16:31-41. |
| 13. | Packer M. Why do kidneys release renin in patients with heart failure? A nephrocentric view of converting enzyme inhibition. Eur Heart J 1990;11(suppl D):44-52. |
| 14. | Ajayi AA. Estimation of creatinine clearance from serum creatinine: Utility of Cockroft and Gault equation on Nigerian patients. Eur J of Clin Pharmacol 1991;40:429-31. |
| 15. | Mckee PA, Castelli WP, McNemara PM, Kannel WB. The natural history of congestive heart failure. The Framingham Heart study. N Engl J Med 1997;285:1441-6. |
| 16. | Ronco C, Haapio M, House AA, Anavekar N, Bellomo R. Cardiorenal syndrome. J Am Coll Cardiol 2008;52:1527-39. |
| 17. | Arodiwe EB, Ijoma CK, Ulasi II, Onodugo OO. Impaired renal function in Nigerian patients with heart failure. Internet J Intern Med 2012;9:1-9. |
| 18. | Smith GL, Shlipak MG, Havranek EP, Frederick AM, William MM, JoAnne MF, et al. Race and renal impairment in heart failure: Mortality in blacks versus whites. Circulation 2005;111:1270-7. |
| 19. | Sarnak MJ, Levey AS, Schoolwerth AC. Kidney disease as a risk factor for development of cardiovascular disease: A statement from the American Heart Association councils on kidney in cardiovascular disease, high blood pressure research, clinical cardiology, and epidemiology and prevention. Hypertension 2003;42:1050-65. |
| 20. | Ezekowitz J, McAlister FA, Humphries KH. The association among renal insufficiency, pharmacotherapy, and outcomes in 6,427 patients with heart failure and coronary artery disease. J Am Coll Cardiol 2004;44:1587-92. |
| 21. | Dries DL, Exner DV, Domanski MJ, Greenberg B, Stevenson LW. The prognostic implications of renal insufficiency in asymptomatic and symptomatic patients with left ventricular systolic dysfunction. J Am Coll Cardiol 2000;35:681-9. |
| 22. | Bibbins-Domingo K, Lin F, Vittinghoff E, Barrett-Connor E, Grady D, Shlipak MG. Renal insufficiency as an independent predictor of mortality among women with heart failure. J Am Coll Cardiol 2004;44:1593-600. |
| 23. | Daniel EF, Butler J, Wang Y, Abraham TW, O'Connor CM, Gottlieb SS, et al. Incidence, predictors at admission, and impact of worsening renal function among patients hospitalized with heart failure. J Am Coll Cardiol 2004;43:61-7. |
| 24. | Liu PP. Cardiorenal syndrome in heart failure: A cardiologist's perspective. Can J Cardiol 2008;24(Suppl B):25B-29B. |
| 25. | Familoni OB, Olunuga TO, Olufemi BW: A clinical study of pattern and factors affecting outcome in Nigerian patients with advanced heart failure. Cardiovasc J Afr 2007;18:308-11. |
| 26. | McClellan WM, Flanders WD, Langston RD, Jurkovitz C, Presley R. Anaemia and renal insufficiency are independent risk factors for death among patients with congestive heart failure admitted to community hospitals: A population-based study. J Am Soc Nephrol 2002;13:1928-36. |
| 27. | Familoni OB, Alebiosu CO, Olunuga TO. The pattern of aggravated renal dysfunction in patients with advanced heart failure. Trop J Nephrol 2006;1:87-91. |
| 28. | Viswanathan G, Gilbert S. The cardiorenal syndrome: Making the connection. Int J Nephrol 2010;2011:1-10. |
| 29. | Cowie MR, Komajda M, Murray-Thomas T, Underwood J, Ticho B, POSH Investigators. Prevalence and impact of worsening renal function in patients hospitalized with decompensated heart failure: Results of the prospective outcomes study in heart failure (POSH). Eur Heart J 2006;27:1216-22. |
| 30. | Akhter MW, Aronson D, Bitar F. Effect of elevated admission serum creatinine and its worsening on outcome in hospitalized patients with decompensated heart failure. Am J Cardiol 2004;94:957-60. |
| 31. | Nohria A, Hasselblad V, Stebbins A. Cardiorenal interactions: Insights from the ESCAPE trial. J Am Coll Cardiol 2008;47:1268-4. |
| 32. | Fonarow GC, Adams KF Jr, Abraham WT, Yancy CW, Boscardin WJ. Risk stratification for in-hospital mortality in acutely decompensated heart failure: Classification and regression tree analysis. JAMA 2005;293:572-80. |
| 33. | Isezuo AS, Omotoso ABO, Araoye MA, Carr J, Corrah T. Determinants of prognosis among Black Africans with hypertensive heart failure. Afr J Med Med Sci 2003;32:143-9. |
| 34. | Ronco C, House AA, Haapio M. Cardiorenal syndrome: Refining the definition of a complex symbiosis gone wrong. Intensive Care Med 2008;34:957-62. |
| 35. | Felker GM, Gattis WA, Leimberger JD, Adams KF, Cuffe MS, Gheorghiade M, et al. Usefulness of anemia as a predictor of death and rehospitalisation in patients with decompensated heart failure. Am J Cardiol 2003;92:625-8. |
| 36. | Forman DE, Butler J, Wang Y, Abraham WT, O'Connor CM, Gotteleb SS, et al. Incidence, predictors at admission, and impact of worsening renal function among patients hospitalized with heart failure. J Am Coll Cardiol 2004; 43:61-7. |
[Figure 1]
[Table 1], [Table 2], [Table 3]
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