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      Attributable causes of chronic kidney disease in adults: a five-year retrospective study in a tertiary-care hospital in the northeast of the Malaysian Peninsula : Causas imputáveis da doença renal crônica em adultos: um estudo retrospectivo de cinco anos de um Hospital de Assistência Terciária no nordeste do Península da Malásia

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          ABSTRACT

          CONTEXT AND OBJECTIVE:

          Chronic kidney disease (CKD) is an escalating medical and socioeconomic problem worldwide. Information concerning the causes of CKD, which is a prerequisite for reducing the disease burden, is sparse in Malaysia. Therefore, this study aimed to evaluate the attributable causes of CKD in an adult population at a tertiary referral hospital.

          DESIGN AND SETTING:

          Retrospective study at Hospital Universiti Sains Malaysia (HUSM).

          METHODS:

          This was an analysis based on medical records of adult patients at HUSM. Data regarding demographics, laboratory investigations, attributable causes and CKD stage were gathered.

          RESULTS:

          A total of 851 eligible cases were included. The patients' mean age was 61.18 ± 13.37 years. CKD stage V was found in 333 cases (39.1%) whereas stages IV, IIIb, IIIa, and II were seen in 240 (28.2%), 186 (21.9%), 74 (8.7%) and 18 (2.1%), respectively. The percentage of CKD stage V patients receiving renal replacement therapy was 15.6%. The foremost attributable causes of CKD were diabetic nephropathy (DN) (44.9%), hypertension (HPT) (24.2%) and obstructive uropathy (9.2%). The difference in the prevalence of CKD due to DN, HPT and glomerulonephritis between patients ≤ 50 and > 50 years old was statistically significant.

          CONCLUSION:

          Our results suggest that DN and HPT are the major attributable causes of CKD among patients at a Malaysian tertiary-care hospital. Furthermore, the results draw attention to the possibility that greater emphasis on primary prevention of diabetes and hypertension will have a great impact on reduction of hospital admissions due to CKD in Malaysia.

          RESUMO

          CONTEXTO E OBJETIVO:

          Doença renal crônica (DRC) é um problema médico e socioeconômico crescente. As informações relativas às causas da DRC são pré-requisito para reduzir a carga da doença, e são escassas na Malásia. Este estudo tem como objetivo avaliar as causas atribuíveis à DRC na população adulta de um hospital de referência terciária.

          TIPO DE ESTUDO E LOCAL:

          Estudo retrospectivo realizado no Hospital Universiti Sains Malaysia (HUSM).

          MÉTODOS:

          Análise de prontuários de pacientes adultos de HUSM. Foram obtidos dados demográficos, exames laboratoriais, causas atribuíveis e estágio da DRC.

          RESULTADOS:

          Um total de 851 casos elegíveis foi incluído. A idade média dos pacientes foi de 61,18 ± 13,37 anos. DRC fase V foi contabilizada em 333 casos (39,1%), enquanto casos de estágio IV, IIIb, IIIa e II foram 240 (28,2%), 186 (21,9%), 74 (8,7%) e 18 (2,1%), respectivamente. A porcentagem de pacientes com DRC estágio V recebendo a terapia de substituição renal foi 15,6%. As causas atribuíveis mais importantes da DRC foram nefropatia diabética (ND) (44,9%), hipertensão (24,2%) e uropatia obstrutiva (9,2%). A diferença na prevalência da DRC devido à ND, hipertensão e glomerulonefrite entre pacientes ≤ 50 anos e > 50 anos de idade foi estatisticamente significativa.

          CONCLUSÃO:

          Nossos resultados sugerem que a ND e a hipertensão são as principais causas atribuíveis da DRC em pacientes sob cuidados terciários na Malásia. Os resultados apontam para a possibilidade de maior ênfase na prevenção primária da diabetes e hipertensão como impactante na redução das internações hospitalares devidas a DRC na Malásia.

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          A new equation to estimate glomerular filtration rate.

          Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
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            Chronic kidney disease in the developing world.

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              Section 2: AKI Definition

              (2012)
              Chapter 2.1: Definition and classification of AKI INTRODUCTION AKI is one of a number of conditions that affect kidney structure and function. AKI is defined by an abrupt decrease in kidney function that includes, but is not limited to, ARF. It is a broad clinical syndrome encompassing various etiologies, including specific kidney diseases (e.g., acute interstitial nephritis, acute glomerular and vasculitic renal diseases); non-specific conditions (e.g, ischemia, toxic injury); as well as extrarenal pathology (e.g., prerenal azotemia, and acute postrenal obstructive nephropathy)—see Chapters 2.2 and 2.3 for further discussion. More than one of these conditions may coexist in the same patient and, more importantly, epidemiological evidence supports the notion that even mild, reversible AKI has important clinical consequences, including increased risk of death. 2, 5 Thus, AKI can be thought of more like acute lung injury or acute coronary syndrome. Furthermore, because the manifestations and clinical consequences of AKI can be quite similar (even indistinguishable) regardless of whether the etiology is predominantly within the kidney or predominantly from outside stresses on the kidney, the syndrome of AKI encompasses both direct injury to the kidney as well as acute impairment of function. Since treatments of AKI are dependent to a large degree on the underlying etiology, this guideline will focus on specific diagnostic approaches. However, since general therapeutic and monitoring recommendations can be made regarding all forms of AKI, our approach will be to begin with general measures. Definition and staging of AKI AKI is common, harmful, and potentially treatable. Even a minor acute reduction in kidney function has an adverse prognosis. Early detection and treatment of AKI may improve outcomes. Two similar definitions based on SCr and urine output (RIFLE and AKIN) have been proposed and validated. There is a need for a single definition for practice, research, and public health. 2.1.1: AKI is defined as any of the following (Not Graded): Increase in SCr by ⩾0.3 mg/dl (⩾26.5 μmol/l) within 48 hours; or Increase in SCr to ⩾1.5 times baseline, which is known or presumed to have occurred within the prior 7 days; or Urine volume 4.0 mg/dl (>354 μmol/l), rather than require an acute increase of ⩾0.5 mg/dl (⩾44 μmol/l) over an unspecified time period, we instead require that the patient first achieve the creatinine-based change specified in the definition (either ⩾0.3 mg/dl [⩾26.5 μmol/l] within a 48-hour time window or an increase of ⩾1.5 times baseline). This change brings the definition and staging criteria to greater parity and simplifies the criteria. Recommendation 2.1.2 is based on the RIFLE and AKIN criteria that were developed for average-sized adults. The creatinine change–based definitions include an automatic Stage 3 classification for patients who develop SCr >4.0 mg/dl (>354 μmol/l) (provided that they first satisfy the definition of AKI in Recommendation 2.1.1). This is problematic for smaller pediatric patients, including infants and children with low muscle mass who may not be able to achieve a SCr of 4.0 mg/dl (354 μmol/l). Thus, the pediatric-modified RIFLE AKI criteria 32 were developed using a change in estimated creatinine clearance (eCrCl) based on the Schwartz formula. In pRIFLE, patients automatically reach Stage 3 if they develop an eCrCl 26.5 μmol/l) [within 48 hours or a 50% increase from presumed baseline). Note that a patient can be diagnosed with AKI by fulfilling either criterion 1 or 2 (or 3, urine output) and thus cases B,C,D, and F all fulfill the definition of AKI. Note also that patients may be diagnosed earlier using criterion 1 or 2. Early diagnosis may improve outcome so it is advantageous to diagnose patients as rapidly as possible. For example, case A can be diagnosed with AKI on day 2 by the first criterion, whereas the second criterion is not satisfied until day 3 (increase from 1.3 to 1.9). However, this is only true because the episode of AKI began prior to medical attention, and thus the day 1 SCr level was already increased. If creatinine measurements had available with 48 hours prior to day 1 and if this level had been at baseline (1.0 mg/dl [88.4 μmol/l]), it would have been possible to diagnose AKI on day 1 using the second criterion. Cases F-H do not have a baseline measurement of SCr available. Elevated SCr (reduced eGFR) on day 1 of the hospitalization is consistent with either CKD or AKD without AKI. In Case F, baseline SCr can be inferred to be below the day 1 value because of the subsequent clinical course; thus, we can infer the patient has had an episode of AKI. In case G, AKI can be diagnosed by application of criterion 2, but the patient may have underlying CKD. Case H does not fulfill the definition for AKI based on either criteria, and has either CKD or AKD without AKI. The example of Case A raises several important issues. First, frequent monitoring of SCr in patients at increased risk of AKI will significantly improve diagnostic time and accuracy. If Case A had not presented to medical attention (or if SCr had not been checked) until day 7, the case of AKI would likely have been missed. Frequent measurement of SCr in high-risk patients, or in patients in which AKI is suspected, is therefore encouraged—see Chapter 2.3. The second issue highlighted by Case A is the importance of baseline SCr measurements. Had no baseline been available it would still have been possible to diagnose AKI on day 3 (by either using criterion 2 or by using criterion 1 and accepting the baseline SCr as 1.3); however, not only would this have resulted in a delay in diagnosis, it would have resulted in a delay in staging (see Table 7). On day 7, it can be inferred that the patient's baseline was no higher than 1.0 mg/dl (88 μmol/l) and thus correct staging of Case A as Stage 2 (two-fold increase from the reference SCr, see below and Table 7) on day 3 could have been determined in retrospect. However, if a baseline SCr was available to use as the reference, the correct stage could be determined on day 3. Case B illustrates why criterion 2 can detect cases of AKI missed by criterion 1. It also clarifies why these cases are unusual. Had the SCr increased to 1.5 mg/dl (132.6 μmol/l) as opposed to peaking at 1.4 mg/dl (123.8 μmol/l), it would have been picked up by criterion 1 as well. By contrast Cases C, D, and even F illustrate how criterion 2 may miss cases identified by criterion 1. Note that Case F can only be diagnosed by inference. By day 7, it can be inferred that the baseline was no higher than 1.0 mg/dl (88 μmol/l) and thus it can be determined that the patient presented with AKI. However, if the baseline SCr could be estimated it would be possible to make this inference as early as day 1. Estimating baseline SCr Many patients will present with AKI without a reliable baseline SCr on record. Baseline SCr can be estimated using the Modification of Diet in Renal Disease (MDRD) Study equation assuming that baseline eGFR is 75 ml/min per 1.73 m 2 (Table 9). 22 This approach has been used in many, but not all, studies of AKI epidemiology using RIFLE 2, 5, 25, 30, 31, 32, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63 (see Table 8) and has recently been validated. 64 Hence, most current data concerning AKI defined by RIFLE criteria are based on estimated baseline SCr for a large proportion of patients. Table 9 shows the range of estimated SCr obtained by back-calculation for various age, sex, and race categories. When the baseline SCr is unknown, an estimated SCr can be used provided there is no evidence of CKD (see Appendix B). Fortunately, when there is a history of CKD, a baseline SCr is usually available. Unfortunately, many cases of CKD are not identified, and thus estimating the baseline SCr may risk labeling a patient with AKI when in reality the diagnosis was unidentified CKD. As discussed further in Appendix B, it is essential to evaluate a patient with presumed AKI for presence of CKD. Furthermore, CKD and AKI may coexist. By using all available clinical data (laboratory, imaging, history, and physical exam) it should be possible to arrive at both an accurate diagnosis as well as an accurate estimate of baseline SCr. Importantly, excluding some cases of hemodilution secondary to massive fluid resuscitation (discussed below), the lowest SCr obtained during a hospitalization is usually equal to or greater than the baseline. This SCr should be used to diagnose (and stage) AKI. For example, if no baseline SCr was available in Case A, diagnosis of AKI could be made using the MDRD estimated SCr (Table 9). If Case A were a 70-year-old white female with no evidence or history of CKD, the baseline SCr would be 0.8 mg/dl (71 μmol/l) and a diagnosis of AKI would be possible even on day 1 (criterion 1, ⩾50% increase from baseline). However, if the patient was a 20-year-old black male, his baseline SCr would be estimated at 1.5 mg/dl (133 μmol/l). Since his admission SCr is lower, this is assumed to be the baseline SCr until day 7 when he returns to his true baseline, and this value can be taken as the baseline. These dynamic changes in interpretation are not seen in epidemiologic studies, which are conducted when all the data are present, but are common in clinical medicine. Note that the only way to diagnose AKI (by SCr criteria) in Case H is to use an estimated SCr. Examples of application of AKI stages Once a diagnosis of AKI has been made, the next step is to stage it (Recommendation 2.1.2). Like diagnosis, staging requires reference to a baseline SCr when SCr criteria are used. This baseline becomes the reference SCr for staging purposes. Table 10 shows the maximum stage for each Case described in Table 7. Staging for Case A was already mentioned. The maximum stage is 2 because reference SCr is 1.0 mg/dl (88 μmol/l) and the maximum SCr is 2.0 mg/dl (177 μmol/l). Had the reference SCr been 0.6 mg/dl (53 μmol/l), the maximum stage would have been 3. Case F was staged by using the lowest SCr (1.0 mg/dl [88 μmol/l]) as the reference. Of course, the actual baseline for this case might have been lower but this would not affect the stage, since it is already Stage 3. Note that if this patient was a 35-year-old white male, his MDRD estimated baseline SCr would be 1.2 mg/dl (106 μmol/l) (Table 9) and his initial stage on admission (day 1) would be assumed to be 2. However, once his SCr recovered to 1.0 mg/dl (88 μmol/l) on day 7, it would be possible to restage him as having had Stage 3. Once he has recovered, there may be no difference between Stage 2 or 3 in terms of his care plan. On the other hand, accurately staging the severity of AKI may be important for intensity of follow-up and future risk. Note that Cases G and H can only be staged if the reference SCr can be inferred. Case G may be as mild as stage 1 if the baseline is equal to the nadir SCr on day 7. On the other hand, if this case were a 70-year-old white female with no known evidence or history of CKD, the reference SCr would be 0.8 mg/dl (71 μmol/l) based on an estimated baseline (Table 9). In this case, the severity on day 1 would already be stage 2. Urine output vs. SCr Both urine output and SCr are used as measures of an acute change in GFR. The theoretical advantage of urine output over SCr is the speed of the response. For example, if GFR were to suddenly fall to zero, a rise in SCr would not be detectable for several hours. On the other hand, urine output would be affected immediately. Less is known about the use of urine output for diagnosis and staging compared to SCr, since administrative databases usually do not capture urine output (and frequently it is not even measured, especially outside the ICU). However, studies using both SCr and urine output to diagnose AKI show increased incidence, suggesting that the use of SCr alone may miss many patients. The use of urine output criteria (criterion 3) will also reduce the number of cases where criterion 1 and criterion 2 are discordant (cases B,C,D, and F in Table 7), as many of these cases will be picked up by urine output criteria. Timeframe for diagnosis and staging The purpose of setting a timeframe for diagnosis of AKI is to clarify the meaning of the word “acute”. A disease process that results in a change in SCr over many weeks is not AKI (though it may still be an important clinical entity: see Appendix B). For the purpose of this guideline, AKI is defined in terms of a process that results in a 50% increase in SCr within 1 week or a 0.3 mg/dl (26.5 μmol/l) increase within 48 hours (Recommendation 2.1.1). Importantly, there is no stipulation as to when the 1-week or 48-hour time periods can occur. It is stated unequivocally that it does not need to be the first week or 48 hours of a hospital or ICU stay. Neither does the time window refer to duration of the inciting event. For example, a patient may have a 2-week course of sepsis but only develop AKI in the second week. Importantly, the 1-week or 48-hour timeframe is for diagnosis of AKI, not staging. A patient can be staged over the entire episode of AKI such that, if a patient develops a 50% increase in SCr in 5 days but ultimately has a three-fold increase over 3 weeks, he or she would be diagnosed with AKI and ultimately staged as Stage 3. As with any clinical criteria, the timeframe for AKI is somewhat arbitrary. For example, a disease process that results in a 50% increase in SCr over 2 weeks would not fulfill diagnostic criteria for AKI even if it ultimately resulted in complete loss of kidney function. Similarly, a slow process that resulted in a steady rise in SCr over 2 weeks, and then a sudden increase of 0.3 mg/dl (26.5 μmol/l) in a 48-hour period, would be classified as AKI. Such are the inevitable vagaries of any disease classification. However, one scenario deserves specific mention, and that is the case of the patient with an increased SCr at presentation. As already discussed, the diagnosis of AKI requires a second SCr value for comparison. This SCr could be a second measured SCr obtained within 48 hours, and if it is ⩾0.3 mg/dl (⩾26.5 μmol/l) greater than the first SCr, AKI can be diagnosed. Alternatively, the second SCr can be a baseline value that was obtained previously or estimated from the MDRD equation (see Table 9). However, this poses two dilemmas. First, how far back can a baseline value be retrieved and still expected to be “valid” second, how can we infer acuity when we are seeing the patient for the first time? Both of these problems will require an integrated approach as well as clinical judgment. In general, it is reasonable in patients without CKD to assume that SCr will be stable over several months or even years, so that a SCr obtained 6 months or even 1 year previously would reasonable reflect the patient's premorbid baseline. However, in a patient with CKD and a slow increasing SCr over several months, it may be necessary to extrapolate the baseline SCr based on prior data. In terms of inferring acuity it is most reasonable to determine the course of the disease process thought to be causing the episode of AKI. For example, for a patient with a 5-day history of fever and cough, and chest radiograph showing an infiltrate, it would be reasonable to infer that the clinical condition is acute. If SCr is found to be ⩾50% increased from baseline, this fits the definition of AKI. Conversely, a patient presenting with an increased SCr in the absence of any acute disease or nephrotoxic exposure will require evidence of an acute process before a diagnosis can be made. Evidence that the SCr is changing is helpful in establishing acuity. Clinical judgment While the definitions and classification system discussed in Chapter 2.1 provide a framework for the clinical diagnosis of AKI, they should not be interpreted to replace or to exclude clinical judgment. While the vast majority of cases will fit both AKI diagnostic criteria as well as clinical judgment, AKI is still a clinical diagnosis—not all cases of AKI will fit within the proposed definition and not all cases fitting the definition should be diagnosed as AKI. However, exceptions should be very rare. Pseudo-AKI As with other clinical diagnoses defined by laboratory results (e.g., hyponatremia), the clinician must be cautious to interpret laboratory data in the clinical context. The most obvious example is with laboratory errors or errors in reporting. Erroneous laboratory values should obviously not be used to diagnose disease and suspicious lab results should always be repeated. Another example is when two SCr measurements are obtained by different laboratories. While the coefficient of variation for SCr is very small ( 60, indicating NKD. No indicates GFR <60, and based on prior level of GFR, may indicate stable, new, or worse CKD. Oliguria as a measure of kidney function Although urine flow rate is a poor measure of kidney function, oliguria generally reflects a decreased GFR. If GFR is normal (approximately 125 ml/min, corresponding to approximately 107 ml/kg/h for a 70-kg adult), then reduction in urine volume to <0.5 ml/kg/h would reflect reabsorption of more than 99.5% of glomerular filtrate. Such profound stimulation of tubular reabsorption usually accompanies circulatory disturbances associated with decreased GFR. Oliguria is unusual in the presence of a normal GFR and is usually associated with the non–steady state of solute balance and rising SCr sufficient to achieve the criteria for AKI. As a corollary, if GFR and SCr are normal and stable over an interval of 24 hours, it is generally not necessary to measure urine flow rate in order to assess kidney function. In principle, oliguria (as defined by the criteria for AKI) can occur without a decrease in GFR. For example, low intake of fluid and solute could lead to urine volume of less than 0.5 ml/kg/h for 6 hours or 0.3 ml/kg/h for 24 hours. On the other hand, severe GFR reduction in CKD usually does not lead to oliguria until after the initiation of dialysis. As described in Chapter 2.1, the thresholds for urine flow for the definition of AKI have been derived empirically and are less well substantiated than the thresholds for increase in SCr. Urinary diagnostic indices, such as the urinary concentrations of sodium and creatinine and the fractional reabsorption of sodium and urea, remain helpful to distinguish among causes of AKI, but are not used in the definition (see Appendix D). Kidney damage Table 13 describes measures of kidney damage in AKD and CKD. Kidney damage is most commonly ascertained by urinary markers and imaging studies. Most markers and abnormal images can indicate AKD or CKD, based on the duration of abnormality. One notable exception is small kidneys, either bilateral or unilateral, indicating CKD, which are discussed separately below. Kidney damage is not a criterion for AKI; however, it may be present. Renal tubular epithelial cells and coarse granular casts, often pigmented and described as “muddy brown”, remain helpful in distinguishing the cause of AKI, but are not part of the definition. Small kidneys as a marker of kidney damage Loss of renal cortex is considered a feature of CKD, and is often sought as a specific diagnostic sign of CKD. Kidney size is most often evaluated by ultrasound. In a study of 665 normal volunteers, 69 median renal lengths were 11.2 cm on the left side and 10.9 cm on the right side. Renal size decreased with age, almost entirely because of parenchymal reduction. The lowest 10th percentiles for length of the left and right kidney were approximately 10.5 and 10.0 cm, respectively, at age 30 years, and 9.5 and 9.0 cm, respectively, at age 70 years. Integrated approach to AKI, AKD, and CKD Clinical evaluation is necessary for all patients with alterations in kidney function or structure. The expectation of the Work Group is that the diagnostic approach will usually begin with assessment of GFR and SCr. However, evaluation of kidney function and structure is not complete unless markers of kidney damage—including urinalysis, examination of the urinary sediment, and imaging studies—have been performed. Table 14 shows a summary of the diagnostic approach using measures for kidney function and structure. Based on interpretation of each measure separately, the clinical diagnosis indicated by an “X” can be reached. SPONSORSHIP KDIGO gratefully acknowledges the following sponsors that make our initiatives possible: Abbott, Amgen, Belo Foundation, Coca-Cola Company, Dole Food Company, Genzyme, Hoffmann-LaRoche, JC Penney, NATCO—The Organization for Transplant Professionals, NKF—Board of Directors, Novartis, Robert and Jane Cizik Foundation, Shire, Transwestern Commercial Services, and Wyeth. KDIGO is supported by a consortium of sponsors and no funding is accepted for the development of specific guidelines. DISCLAIMER While every effort is made by the publishers, editorial board, and ISN to see that no inaccurate or misleading data, opinion or statement appears in this Journal, they wish to make it clear that the data and opinions appearing in the articles and advertisements herein are the responsibility of the contributor, copyright holder, or advertiser concerned. Accordingly, the publishers and the ISN, the editorial board and their respective employers, office and agents accept no liability whatsoever for the consequences of any such inaccurate or misleading data, opinion or statement. While every effort is made to ensure that drug doses and other quantities are presented accurately, readers are advised that new methods and techniques involving drug usage, and described within this Journal, should only be followed in conjunction with the drug manufacturer's own published literature.
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                Author and article information

                Journal
                Sao Paulo Med J
                Sao Paulo Med J
                Sao Paulo Med J
                São Paulo Medical Journal
                Associação Paulista de Medicina - APM
                1516-3180
                1806-9460
                14 April 2015
                2015
                : 133
                : 6
                : 502-509
                Affiliations
                [I ] originalPharmD, MSc. Doctoral Student, Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia, and Lecturer, Department of Pharmacy Practice, University College of Pharmacy, University of the Punjab, Lahore-54000, Pakistan.
                [II ] originalBPharm, MPhil, PhD. Senior Lecturer, Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia.
                [III ] originalMD, MMed, FASN. Associate Professor, Chronic Kidney Disease Resource Centre, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kota Bharu, Kelantan, Malaysia.
                [IV ] originalBParm, PharmD. Professor, Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia.
                [V ] originalBPharm, MPhil, PhD. Professor, University College of Pharmacy, University of the Punjab, Lahore-54000, Pakistan.
                [VI ] originalPharmD, MPhil. Doctoral Student, University College of Pharmacy, University of the Punjab, Lahore-54000, Pakistan.
                [VII ] originalMD, MMed. Lecturer, Department of Gynecology and Obstetrics, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kota Bharu, Kelantan, Malaysia.
                Author notes
                Address for correspondence: Muhammad Salman. School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800-Miden, Pulau Pinang, Malaysia. Tel. +6016-4958019. Fax. +609-7642543. E-mail: msk5012@ 123456gmail.com

                Conflict of interest: None declared

                Article
                10.1590/1516-3180.2015.005
                10496555
                26760124
                e0569c5a-1fe5-43bc-a7bc-6a4ffecb007d

                This is an open access article distributed under the terms of the Creative Commons license.

                History
                : 29 July 2015
                : 01 August 2015
                Page count
                Figures: 4, Tables: 0, Equations: 0, References: 28, Pages: 08
                Categories
                Original Article

                renal insufficiency, chronic,kidney failure, chronic,retrospective studies,hospitals,malaysia.

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