Medication prescribing patterns in ambulatory haemodialysis patients: comparisons of USRDS to a large not-for-profit dialysis provider

Harold J. Manley1,2, Cory G. Garvin1, Debra K. Drayer2, Gerald M. Reid2,3, Walter L. Bender2,3, Timothy K. Neufeld2,3, Sudarshan Hebbar2,3 and Richard S. Muther2,3

1 University of Missouri, Kansas City, School of Pharmacy, Kansas City, MI, USA, 2 Dialysis Clinic, Inc., Kansas City, MI, USA and 3 Kidney Associates of Kansas City, Kansas City, MI, USA

Correspondence and offprint requests to: Harold J. Manley, Pharm D, BCPS, Assistant Professor of Pharmacy Practice, University of Missouri, Kansas City, 2411 Holmes M3-C19, Kansas City, MI 64108, USA. Email: manleyh{at}umkc.edu



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. End-stage renal disease (ESRD) patients are prescribed numerous medications. The United States Renal Data System (USRDS) reported on medication prescribing patterns in 1998. Since then, several new medications, treatment guidelines and recommendations have been introduced. The objective was to analyse and compare haemodialysis (HD) patient medication prescribing patterns between the Dialysis Clinic, Inc. (DCI) database and the USRDS report.

Methods. Point-prevalent (01/01/03) medication use data from the DCI national database was obtained. Data collected included patient demographics, reason for and duration of ESRD, and medication listed on profile. All medications were classified similar to the USRDS and by where taken (clinic vs home). Medication prescribing patterns were compared between DCI and USRDS databases. Comparisons between age groups (<65 and ≥65 years) and diabetic status [diabetes mellitus (DM) vs non-DM] were made.

Results. There were 128 477 medication orders categorized in 10 474 patients. DCI patient demographics were similar to present USRDS patients except for fewer Hispanics (P<0.001). Patients were prescribed 12.3±5.0 (median 12) different medications (2.6±1.4 clinic medications and 10.0±4.5 home medications). This is higher than reported by USRDS (median 9 medications). Patient age did not influence number of medications used (P = 0.54). DM patients are prescribed more medications than non-DM (13.3±5.0 DM vs 11.6±4.8 non-DM; P<0.00001). All medication class prescribing patterns were markedly different.

Conclusion. The data suggest that medication prescribing patterns in HD patients have changed. The audit identified appropriate and questionable prescribing patterns. Various prescribing patterns identified areas for improvement in care (e.g. increased use of aspirin, beta-blockers and hyperlipidaemia medications) and areas requiring further investigation (e.g. high use of anti-acid, benzodiazepine and non-aluminum/non-calcium phosphate-binding medications).

Keywords: evaluation; haemodialysis; medication; pattern



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
End-stage renal disease (ESRD) patients have, on average, five to six chronic medical conditions that require eight to 12 medications [14]. Since 1988, in a joint effort with the Center for Medicaid and Medicare Services and National Institute of Diabetes and Digestive and Kidney Disease, the United States Renal Data System (USRDS) annually collects data on the ESRD patient population and publishes their findings in the Annual Data Report (ADR) [5]. The USRDS last reported on medication use patterns in haemodialysis (HD) patients in 1998 [1]. The report provided a point-prevalent, descriptive analysis of medication use from a sample of US dialysis units. The data reported were collected prior to 1996 on a sample of HD patients (n = 1998).

Currently there are approximately 246 000 HD patients in the US [6]. Since the last nationwide medication use audit, nearly 500 medications have been approved for use by the Food and Drug Administration. In addition, several treatment guidelines [79], recommendations [10,11] and/or landmark trials [12] have been published since the last medication audit. These factors may influence the prescribing patterns of various medications or medication classes. By highlighting practices that are at odds with current recommendations, a medication use audit can identify opportunities to improve care [4].

We hypothesized that HD patients’ prescribing patterns are markedly different than that reported previously. We describe point-prevalent medication prescribing patterns in ambulatory HD patients within the Dialysis Clinic, Inc. (DCI) database. DCI is a not-for-profit dialysis provider that utilizes an electronic medical record system that captures medication use data. DCI presently provides care for approximately 10 000 HD patients at 200 clinics located in 26 states.



   Subjects and methods
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
All medication prescribing data for ambulatory HD patients within the DCI database were included. Patient age, gender, cause of and duration (years) of ESRD were recorded. A medication point-prevalence study was conducted for all patients on one single day (January 01, 2003), from data obtained from each patient's current electronic medication record. Individual medications were entered into a database for each patient. All records were considered accurate because of strict procedures for monthly medication reviews and previous subset record validation demonstrating >95% accuracy [2]. Medication dose and frequency of administration are not reported.

All medications were recorded and were classified a priori into categories [1,4]. Medication categories were as follows: anaemia medications [erythropoetin (EPO) and iron therapy]; renal osteodystrophy therapy [vitamin D analogues (calcitriol, doxercalciferol, paricalcitol)], phosphate binders (aluminum salts, calcium salts and non-aluminum/non-calcium salts); cardiac medications (any agent that can be used for hypertension, congestive heart failure, coronary artery disease, arrhythmia), cholesterol lowering medications (niacin, fibric acid agent, HMG-CoA reductase inhibitor), agents to treat endocrine disorders (diabetes agent, thyroid disorders, menopause), anti-infective medications (including antiviral), antithrombotic medications (agents that may affect platelet function or prolong coagulation), psychotropics (antidepressives, antipsychotics), gastrointestinal medications [histamine-2 receptor antagonist (H2RA), proton pump inhibitor (PPI), promotility agents, laxatives], vitamins, analgesics, antipruritics and other (agents with a prevalence of less than 10%). Medications were also classified as clinic medications (e.g. EPO, i.v. iron, vitamin D analogues, miscellaneous i.v. medications) and home medications (i.e. all non-clinic medications). Herbal medication use was not captured.

Continuous variables (patient age, duration of ESRD, number of medications per patient) were expressed as mean ± SD. Discrete variables [reason for ESRD, gender, race, medication category, age groups and diabetes mellitus (DM) status] were expressed as counts or percentages. Data were analysed by diabetes status and age groups (≤65 or >65 years of age). Demographic data were compared with that reported in the 1998 and 2002 USRDS ADR reports [1,6]. Data reported in the 1998 and 2002 USRDS ADR were collected in 1996 and 2000, respectively. Only data on HD patients were included. Medication prevalence results were compared with that reported in the 1998 USRDS ADR [1].

Comparison of discrete and continuous variables was made by {chi}2 analysis and ANOVA, respectively. For non-normally distributed continuous variables, the Kruskal–Wallis test was used. All statistical tests were two-sided and a P-value <0.05 was considered statistically significant. Analyses were conducted utilizing SPSS version 10.0 (SPSS Inc., Chicago, IL). The committee on protection of human subjects approved this project and waived the need for consent. This study was supported by a grant provided by DCI.



   Results
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
10 474 patients’ medication profiles were surveyed (5477 male, 4997 female). Table 1 provides the patient demographic data. The mean±SD age of all patients was 60.2±15.6 (range: 7–101) Only 10 patients were <15 years old. The duration of HD was 3.73±4.0 years. Compared with the 1998 USRDS ADR [1], the patient population at the DCI clinics was markedly different for all variables except gender and ‘Other’ as a cause of ESRD. A lower prevalence of diabetes and hypertension and higher prevalence for glomerulonephritis was observed in our population. However, compared with the current HD patients as reported in the 2002 USRDS ADR (data obtained in 2000), our population was not significantly different other than number of Hispanic patients (P<0.0001).


View this table:
[in this window]
[in a new window]
 
Table 1. Patient demographicsa

 
There were 128 477 medication orders categorized with 905 unique medications identified. Of the 128 477 medications there were 27 050 clinic medications (21.1%) and 101 427 home medications (78.9%). Patients’ records showed a mean of 12.3±5.0 (range: 1–38) different medications. The median number of different medications, is 12 for all DCI patients, compared with the median of nine medications per HD patient reported in the USRDS ADR [1]. Patients were prescribed 2.6±1.4 clinic medications and 10.0±4.5 home medications.

Figure 1 depicts the frequency distribution of number of medications used per patient overall. There was no observed effect of patient age for the number of medications used by a patient (12.3±5.2 <65 years old vs 12.2±4.8 ≥65 years old; P = 0.54). Similar to that reported by the USRDS [1], diabetic patients are prescribed more medications than non-diabetic patients (13.3±5.0 diabetics vs 11.6±4.8 non-diabetics; P<0.00001).



View larger version (10K):
[in this window]
[in a new window]
 
Fig. 1. Distribution of number of medications on profile: all patients (n = 10 474).

 
The prevalence of patients using medications for anaemia management (EPO and iron preparations) and renal bone disease (phosphate binders and vitamin-D analogues) are reported in Tables 2 and 3. EPO was administered by i.v. route 91.5% and s.c. route 9.5% of the time. Only four patients were prescribed darbepoeitin. I.v. administration of iron and vitamin D analogues is the preferred route of administration and used with greater frequency in DCI patients compared with that reported in the USRDS ADR [1]. The predominant vitamin D analogue used is doxercalciferol. Phosphate binders consisted of calcium, aluminum and non-aluminum/non-calcium. The predominant phosphate binder is the non-aluminum/non-calcium agent (e.g. sevelamer) with 31.1% of patients prescribed this agent. Calcium acetate was the most frequently used calcium phosphate binder and aluminum products were infrequently used. Compared with the USRDS ADR [1], more patients used more than one agent to manage phosphorus (P<0.0001).


View this table:
[in this window]
[in a new window]
 
Table 2. Medication prevalence for management of anaemia in the two study groups

 

View this table:
[in this window]
[in a new window]
 
Table 3. Medication prevalence for management of renal bone disease in the two study groups

 
Most patients (90.9%) were taking a medication that could be used for a cardiac condition (Table 4). The mean±SD of different cardiac medications per patient was 3.5±1.8. Calcium channel blocker and digoxin use has decreased significantly (P = 0.03 and P<0.0001, respectively). ACE inhibitor/angiotensin receptor blocker, beta-blocker and central alpha agonist use increased significantly (P<0.0001 for all classes). Diuretic and antiarrhythmic agents were used in 16.2 and 4.0% of patients, respectively.


View this table:
[in this window]
[in a new window]
 
Table 4. Prevalence of individual cardiac medication usage in the two study groups

 
Table 5 contains the prevalence of various medication classes prescribed for patients. More of the surveyed patients were taking a lipid lowering agent (29.2 vs 8.0%; P<0.0001) and vitamins (75.0 vs 64.0%; P<0.0001) than reported by the USRDS [1]. In patients treated for hypercholesterolaemia, the majority use a HMG-CoA reductase inhibitor (90.6%) whereas only 8.6% use a fibric acid derivative. Of the 2769 HMG-CoA reductase inhibitor orders reviewed, atorvastatin accounted for 51.8% of orders: simvastatin, pravastatin, lovastatin and fluvastatin accounted for 36.9, 6.8, 2.7 and 1.8%, respectively. Twenty-four patients are on niacin. Antithrombotic agents were more prevalent compared with the USRDS ADR [1].


View this table:
[in this window]
[in a new window]
 
Table 5. Prevalence of individual medication usage in the two study groups

 
The majority of patients taking a vitamin are using a combination product especially designed for patients on dialysis therapy (75.0%; e.g. Nephrovite®, Nephrocap®). There were 197 patients taking a dietary supplement and 328 patients taking an appetite stimulant. Our population had a higher use compared with the USRDS report [1] of H2RAs and PPIs (49.9 vs 30%, respectively, P<0.0001) Pro-motility agents continue to be prescribed at the same rate (11.7 DCI vs 13% USRDS; P = 0.109).

There are 28.5% of our patients treated with an antidiabetic agent (Table 5). However, only 70.8% of our patients with diabetes listed as the reason for ESRD were treated with an antidiabetic agent. This prescribing pattern differs from the 42.5% reported in the USRDS ADR (P<0.0001) [1]. The most common agent used for control of diabetes is insulin, 72.8% of the time. Sulfonylureas and thiazolidinediones are used 18.3 and 9.0% of the time, respectively. One patient was on metformin therapy.



   Discussion
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Medication use in DCI units (January 2003) reveals several differences in medication use as compared with a national sample of HD patients in 1996. The prevalence of patients receiving medications in various medication categories has changed. Possible reasons for the observed differences may include changes in patient demographics, publication of treatment guidelines [79], recommendations [10,11] and/or landmark trials [12]. These reports stress the importance of iron therapy [7], cholesterol management [8,10] and tight control of phosphorus levels requiring use of non-calcium, non-aluminum phosphate binders [9,11]. Another factor that may influence prescribing patterns is direct pharmaceutical marketing.

Overall, our HD patients were prescribed more medications than reported previously (median 12 vs median 9) as compared with a national sample of HD patients. Consistent with previous reports, the HD patients surveyed were on multiple medications and patients with diabetes required, on average, one additional medication [1,3]. However, there are limitations to the 1998 USRDS ADR. The medication use survey data collection sheet only had room for 15–20 medications, depending upon the time period in which data were collected. Additionally, only medications prescribed, not those actually taken (e.g. non-prescription and alternative medicine remedies), were reported in the ADR. These limitations could have led to under-reporting of medications in the 1998 ADR.

The observed increase in number of medications recorded in the profile could be attributed to increases in use of phosphate binders, cardiovascular medications, aspirin, anti-hyperlipidaemic agents, acid-reducing agents, dietary stimulants and psychotropic agents. These changes in prescribing patterns are likely due to efforts stressing preventative healthcare measures (aspirin, anti-hyperlipidaemic agents, cardiovascular medications) [1,10], lower calcium x phosphorus product goals (phosphate binders) [11], better nutritional outcomes (dietary stimulants) [9], and recognition of depression as a frequent co-morbid condition in ESRD (psychotropic agents) [13].

Unlike earlier reports, older age (>65 years) did not predict the number of medications a patient is prescribed [1]. One interpretation is that, regardless of age, all dialysis patients have several co-morbid conditions, which require several medications. Being young appears to not confer protection from the cardiac conditions nearly all dialysis patients have. Goodman and colleagues demonstrated that dialysis patients as young as 20 years old have significant vasculature calcification [12]. Sarnak and Levey illustrated that risk of cardiovascular death in dialysis patients was greater at all age groups (range 25–85+ years old) compared with the general population [14]. Surprisingly, the annual percentage rate of cardiovascular death in dialysis is relatively flat across all age groups [14].

Calcitriol was the only available vitamin D analogue at the time of the last medication audit, so it is not surprising that the vitamin D analogues used today are different than that reported earlier [1]. Recently, emphasis on lower calcium x phosphorus product and acceptable serum calcium and phosphorus ranges in dialysis patients have shifted use of newer vitamin D analogues, doxercalciferol and paricalcitol, which purportedly have fewer incidences of hypercalcaemia and hyperphosphataemia than calcitriol therapy. An alternative interpretation could be that corporate purchasing contracts or Medicare reimbursement rates may have influenced which agents are administered at the dialysis clinic. This may explain why i.v. doxercalciferol is the preferred vitamin D analogue. Although outpatient medications, e.g. oral phosphate binders, are not influenced by corporate purchasing contracts or Medicare reimbursement rates, reliance on non-aluminum/non-calcium-based phosphate binders and avoidance of calcium salt-based phosphate binders may be explained by the emphasis on lower calcium xphosphorus products and acceptable serum calcium [11].

A previous medication audit provided medication use data that could be used to improve patient care [4]. Our current medication audit has also provided insight on a number of appropriate prescribing practices as well as identified prescribing patterns that warrant further investigation. Examples of appropriate prescribing practices are the high prevalence of i.v. iron for anaemia management and vitamin supplementation and evidence of low reliance of aluminium as a phosphate binder, all consistent with current recommendations [7,9,11]. It is encouraging that aspirin, beta-blockers and lipid lowering agent use have increased. Analysis of the USRDS, Dialysis Outcome Practice Patterns Study and Henry Ford Health System databases have shown aspirin [15], beta-blockers [15] and lipid lowering agent [16] use are associated with reduced cardiovascular death.

Another prescribing pattern that is encouraging is that the use of antidepressant agents (e.g. selective serotonin re-uptake inhibitors, tri-cyclic antidepressants) has increased. Depression is a common problem in HD patients and is associated with increased morbidity and mortality in HD patients [13]. Unfortunately, HD patients are seldom treated for depression despite a high prevalence of depressive symptoms and evidence that medical therapy improves depression-rating scores [17]. We do not know whether or not all antidepressants prescribed were used for treatment of depressive symptoms. These agents oftentimes are used for neuropathic pain treatment, of which are common problems in HD patients.

There are several prescribing practices that warrant further investigation. First, it is surprising that nearly 50% patients are prescribed a H2RA or PPI. A possible explanation for this finding is that the incidence of inflammatory mucosal lesions, peptic ulcers and gastro-oesophageal reflux disease occur with higher rates than the general population. Secondly, the nearly 3-fold increase in benzodiazepine use warrants justification. Although sleep disorders (e.g. restless leg syndrome) and anxiety are commonplace in HD patients, there are concerns over potentially inappropriate benzodiazepine use for treatment of depressive symptoms. As discussed above, depression is common and masking of symptoms with inappropriate therapy may cause significant morbidity and mortality. Thirdly, despite the increase in the per cent of patients receiving aspirin therapy, overall there remains a continued low use of aspirin therapy in a population that has a high cardiovascular mortality risk. Finally, as determined in the previous USRDS medication audit [1], there appears to be a mismatch between the number of patients with diabetes and the number of patients treated for diabetes. Although the degree of discordance has declined, there remains nearly 30% DM patients without an antidiabetic agent on their profile. This prescribing pattern still may be appropriate as many DM patients may not need an antidiabetic agent given that their decreased renal function may prolong exogenous insulin action.

The strength of our findings is that our patient population demographics matches that reported by the most recent USRDS ADR [6]. The lone exception to this is our limited sample of Hispanic patients. Therefore, our findings may not truly represent prescribing patterns in this patient subset. There may be concerns of regional prescribing patterns and accuracy of the data. Nonetheless, our report is based on data from 200 clinics in 26 states, so these prescribing patterns are likely not due to regional effects. Another limitation to our study is that we do not have medication indication(s) or patient co-morbid conditions to determine if medication use practices meet current treatment guidelines. Future medication use audits should incorporate this information. Finally, we assumed that the medication records were accurate. This assumption was based upon previous work validating the electronic medication record system [2].

HD patients are at risk for medication-related problems [3]. They have multiple co-morbid conditions, which require several medications for treatment. The patients require frequent monitoring, which oftentimes result in dose manipulations. Additionally, it is well known that as the number of medications taken by patients’ increases, compliance with the prescribed medications decreases.

As medical studies come out, additional beneficial medications are found for various disease states. This is evident in that newer recommendations for these diseases include the use of more, not fewer, medications. For example, historically chronic heart failure was treated with just digoxin and diuretic therapy. Today clinicians treating these patients are encouraged to utilize angiotensin-converting enzyme inhibitors, beta-blockers, spironolactone, digoxin and diuretics.

Regarding the HD patient population, this trend to utilize an increasing number of medications is concerning. A recent report of 850 HD patients followed up for 13 months demonstrated that patients prescribed greater than six medications are at increased risk for mortality as compared with those patients on five or fewer medications (P = 0.003) [18]. After controlling for age, gender, duration of ESRD, presence of DM or hypertension, body mass index, serum albumin and serum creatinine, the number of medications prescribed was a significant predictor of mortality [odds ratio: 1.21 (95% CI 1.07–1.36)]. Several reasons exist for these results. First, these results may simply be a reflection of sicker patients requiring more medications. Alternatively, the higher mortality rate may be reflective of the increased medication-related problem risk seen in patients that take multiple medications.

This medication audit also provides insight to the financial burden non-dialysis centre medications place on HD patients. According to the National Association of Chain Drug stores, the average prescription cost in ambulatory patients in 2002 was $53.10 per prescription [19]. We determined that our HD patients take on average 10 home medications. Therefore, the resultant yearly expenditure for home medications would be $6372 per patient (10 medications x $53.10/medication x 12 months therapy). Expenditures for HD related clinic medications (EPO, injectable iron, vitamin D analogues and other miscellaneous injectable medications) per patient per year are $8600 [12]. Combined yearly medication cost per patient is ~$14 972. Extrapolation of these figures to the entire HD population results in mean medication expenditures in excess of $3.6 billion per year.

Previous work has shown that the review of a HD patient's medication profile provided a useful tool in identifying medication-related problems and that provision of pharmaceutical care improves patient outcomes while reducing cost of care [20]. The data from this medication audit suggests that the HD population is rich with opportunity for identification and resolution of real and potential medication-related problems. Healthcare providers taking care of these patients should maintain a heightened awareness of medication-related issues.

The data reported here have been supplied by USRDS. The interpretation and reporting of the data are the responsibility of the author(s) and in no way should be seen as an official policy or interpretation of the US government.

Conflict of interest statement. None declared.



   References
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

  1. United States Renal Data Systems (USRDS) 1998 Annual Data Report, National Institutes of Health, National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD, April 1998
  2. Manley HJ, Overbay DK, McClaran M, Bender W, Muther RS. Medication record discrepancies in an outpatient electronic medical record: frequency, type, and potential impact on patient care at a hemodialysis clinic. Pharmacotherapy 2003; 23: 231–239[CrossRef][ISI][Medline]
  3. Manley HJ, McClaran ML, Overbay DK et al. Factors associated with medication-related problems in ambulatory hemodialysis patients. Am J Kidney Dis 2003; 41: 386–393[CrossRef][ISI][Medline]
  4. Manley HJ, Bailie GR, Grabe DW. Comparing medication use in two hemodialysis units against national dialysis databases. Am J Health Syst Pharm 2000; 57: 902–906[ISI][Medline]
  5. Wish JB. Data management to understand outcomes and trends in ESRD. Am J Kidney Dis 1998; 32 [6, Suppl 4]: S165–S172
  6. United States Renal Data Systems (USRDS) 2002 Annual Data Report, National Institutes of Health, National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD, April 2002
  7. IV. NKF-K/DOQI Clinical Practice Guidelines for Anemia of Chronic Kidney Disease: update 2000 [Erratum in: Am J Kidney Dis 2001; 38: 442]. Am J Kidney Dis 2001; 37 [1 Suppl 1]: S182–238
  8. K/DOQI Clinical practice guidelines for managing dyslipidemias in chronic kidney disease. Am J Kidney Dis 2003; 41: S39–S58[CrossRef]
  9. Clinical practice guidelines for nutrition in chronic renal failure. K/DOQI, National Kidney Foundation [Erratum in: Am J Kidney Dis 2001; 38: 917]. Am J Kidney Dis 2000; 35 [6 Suppl 2]: S1–140
  10. Levy AS, Beto JA, Coronado BE et al. Controlling the epidemic of cardiovascular disease in chronic renal disease: what do we know? What do we need to learn? Where do we go from here? National Kidney Foundation Task Force on Cardiovascular Disease. Am J Kidney Dis 1998; 32: 853–906[ISI][Medline]
  11. Block GA, Port FK. Re-evaluation of risks associated with hyperphosphatemia and hyperparathyroidism in dialysis patients: recommendations for a change in management. Am J Kidney Dis 2000; 35: 1226–1237[ISI][Medline]
  12. Goodman WG, Goldin J, Kuizon BD et al. Coronary-artery calcification in young adults with end-stage renal disease who are undergoing dialysis. N Engl J Med 2000; 342: 1478–1483[Abstract/Free Full Text]
  13. Lopes AA, Bragg J, Young E et al. Dialysis Outcomes and Practice Patterns Study (DOPPS). Depression as a predictor of mortality and hospitalization among hemodialysis patients in the United States and Europe. Kidney Int 2002; 62: 199–207[CrossRef][ISI][Medline]
  14. Sarnak MJ, Levey AS. Epidemiology of cardiac disease in dialysis patients. Semin Dial 1999; 12: 69–76[CrossRef][ISI]
  15. McCullough PA, Sandberg KR, Borzak S, Hudson MP, Garg M, Manley HJ. Benefits of aspirin and beta-blockade after myocardial infarction in patients with chronic renal disease. Am Heart J 2002; 144: 226–232[CrossRef][ISI][Medline]
  16. Seliger SL, Weiss NS, Gillen DL et al. HMG-CoA reductase inhibitors are associated with reduced mortality in ESRD patients. Kidney Int 2002; 61: 297–304[CrossRef][ISI][Medline]
  17. Blumenfield M, Levy NB, Spinowitz B et al. Fluoxetine in depressed patients on dialysis. Int J Psychiatry Med 1997; 27: 71–80[ISI][Medline]
  18. Tozawa M, Iseki K, Iseki C et al. Analysis of drug prescription and survival in patients on chronic hemodialysis. J Am Soc Nephrol 2001; 12: 349A (abstract A1795)[CrossRef]
  19. National Association of Chain Drug Stores. http://www.nacds.org/wmspage.cfm?parm1=507, last accessed 05/26/03
  20. Manley HJ, Carroll C. The clinical and economic impact of pharmaceutical care in end-stage renal disease patients. Semin Dial 2002; 15: 45–49[CrossRef][ISI][Medline]
Received for publication: 20.10.03
Accepted in revised form: 24. 3.04





This Article
Abstract
FREE Full Text (PDF)
All Versions of this Article:
19/7/1842    most recent
gfh280v1
Alert me when this article is cited
Alert me if a correction is posted
Services
Email this article to a friend
Similar articles in this journal
Similar articles in ISI Web of Science
Similar articles in PubMed
Alert me to new issues of the journal
Add to My Personal Archive
Download to citation manager
Search for citing articles in:
ISI Web of Science (3)
Disclaimer
Request Permissions
Google Scholar
Articles by Manley, H. J.
Articles by Muther, R. S.
PubMed
PubMed Citation
Articles by Manley, H. J.
Articles by Muther, R. S.