Effect of antitubercular medications on blood pressure control in chronic kidney disease patients with tuberculosis: a prospective cohort study

BACKGROUND: Previous anecdotal reports suggested a decrease in antihypertensive medication potency after starting antitubercular medications. This interaction could be unpredictable in presence of renal failure due to increased half-lives of most commonly used antihypertensive medications. METHODS: In a cohort study involving 135 patients with chronic kidney disease (CKD), 62 patients with tuberculosis star-ted on antitubercular medications (TB group) were prospectively compared with 73 CKD controls (with no TB and not on antitubercular medications) for a change in antihypertensive medications. Antihypertensive dose was converted to unit score. RESULTS: The TB group had a greater increase in antihypertensive medication dose as compared with controls (89% vs. 54%, p<0.0001). In absolute terms an overall increase in antihypertensive medications was observed in 60% of pa-tients in the TB group, with a 2-fold dose increase from the baseline (p<0.0001). Four patients from the TB group de-veloped a hypertensive emergency. In multivariate linear regression, the association between TB group and increase in antihypertensives remained significant ( beta =0.38; p<0.0001). CONCLUSIONS: In CKD patients, antihypertensive medication potency is reduced in TB patients on antitubercular the-rapy in a significant number of patients, to a clinically significant degree with a potential risk for hypertensive emergency.     

Validation of the equations for estimating daily sodium excretion from spot urine in patients with chronic kidney disease

Background

Measuring sodium excretion in a 24-h urine collection is the most reliable method of estimating salt intake, but it is not applicable to all patients. As an alternative, equations for estimating Na excretion from Japanese by a spot urine sample were created, but they have not been validated in patients with chronic kidney disease (CKD), which are frequently associated with nocturia and medication.

Methods

We enrolled 136 patients with CKD and collected both 24-h urine and the first morning urine. Na excretion was estimated from the first morning urine by Kawasaki’s equation, which was originally used for the second morning urine, and Tanaka’s equation, which is applied for spot urine samples taken at any time from 9?am to 7?pm. We evaluated the two equations for bias, RMSE and accuracy within 30 and 50% of the measured Na excretion.

Results

Bias, RMSE and accuracy within 30% of the estimated Na excretion were 48?±?69 and 2?±?69?mmol/day, 84 and 69?mmol/day, and 35 and 49% using Kawasaki’s equation and Tanaka’s equation, respectively. Na excretion in the first morning urine was accurately estimated by Tanaka’s equation, but it was overestimated by Kawasaki’s equation. Nocturia and medication such as diuretics and ACE inhibitor or angiotensin receptor blocker did not affect the accuracy with which Na excretion was estimated by Tanaka’s equation substantially.

Conclusion

Tanaka’s equation for estimating Na excretion from the first morning urine in patients with CKD is accurate enough for use in clinical practice.     

Relation between number of prescribed medication and outcome in peritoneal dialysis patients

BACKGROUND: Many patients with end-stage renal disease need to take a large number of medications. In the present study, we studied the magnitude of problem and explored the relationship between the number of prescribed medications and the clinical outcome of a large cohort of prevalent peritoneal dialysis (PD) patients. METHODS: We studied the medication list of 266 prevalent PD patients. Dialysis adequacy, residual renal function and nutritional assessment were also performed. The patients were followed for 33.7 +/- 20.7 months. RESULTS: On average, each patient required 4.7 +/- 1.8 type of medications or 10.0 +/- 4.9 tablets per day. 40 patients (15.0%) needed at least 7 types of medication; 33 patients (12.4%) had to take more than 15 tablets each day. There is a significant but weak correlation between the number of types of medication and the Charlson's comorbidity score (r = 0.252, p < 0.001). Despite the large number of medication prescribed, the blood pressure control, serum cholesterol level, and the use of aspirin after atherosclerotic disease remained suboptimal in many patients. By multivariate analysis, independent factors for patient survival were Charlson's comorbidity score, number of types of medication, duration of dialysis, overall SGA score, and mean arterial blood pressure. Each additional type of medication conferred 20% increase in risk of death (95% CI, 1.6-41.7%, p = 0.032), and the effect is independent on the Charlson's comorbidity score. The actual number of pills taken by a patient did not influence survival in this model. CONCLUSION: Our results indicate that the number of prescribed medications is related to the clinical outcome of PD patients. The number of prescribed medication may reflect the severity of uremic complications and comorbid diseases not reflected by the Charlson's comorbidity score. Nevertheless, dialysis physicians should carefully balance the clinical need of treating multiple medical conditions with the potential problems of a complicated therapeutic regimen.     

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

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 >or=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).     

Management of Polypharmacy in Dialysis Patients

Most patients receiving dialysis have other common chronic conditions in addition to end‐stage renal disease, including hypertension, diabetes, cardiovascular disease, and mineral and bone disorder, all of which require long‐term medication management. Dialysis patients take an average of 10–12 prescribed and over‐the‐counter medications from an average of 4.7 prescribers, and an average of 19 pills per day. Thus, reducing polypharmacy is not adequate as a medication therapy goal for these patients. Instead, the dialysis community should focus on ensuring that all patients receive medications that are appropriate, effective, safe and convenient. Barriers to this include a fragmented health care system with inadequate communication between multiple prescribers and pharmacies, and frequent care transitions between ambulatory care sites (dialysis centre, ambulatory primary care practice, ambulatory specialty practice) and the hospital, skilled nursing facility or long‐term care facility. Three distinct processes are necessary to prevent and solve the resultant medication‐related problems (and reduce polypharmacy). These are medication reconciliation (creating an accurate medication list that reflects all medications the patients is taking and how they are being taken), medication review (evaluating the list for appropriateness, effectiveness, safety and convenience in conjunction with the patient's health status), and ongoing patient‐centred medication therapy management (e.g., developing treatment plans centred on each patient's medication‐related goals). A team approach including pharmacists as part of the dialysis team with the dialysis facility as the primary medication home is needed.     

Analysis of drug prescription in chronic haemodialysis patients.

BACKGROUND: Information concerning medication use in Asian haemodialysis patients is sparse. We surveyed prescribed medications and examined the relation between the number of medications and mortality and clinical characteristics in chronic haemodialysis patients, in Okinawa, Japan. METHODS: We conducted a cross-sectional multicentre survey in August 1999 and patients were observed during 13 months of follow up. RESULTS: The clinical demographics of 850 chronic haemodialysis patients in seven dialysis units were obtained. Compared with the mean number of medications prescribed in ambulatory patients treated in general practice reported from Ministry of Health and Welfare of Japan (2.7 (n=20 716)), the mean number medications in haemodialysis patients was larger (7.2 (n=850)). The three most prescribed drug types in haemodialysis patients were those related to calcium and phosphate metabolism (88%), antihypertensive agents (71%), and erythropoietin (60%). Among the 850 patients, 38 died during the 13-month follow-up period. The number of medications was positively associated with mortality after adjusting for age, sex, and other clinical factors: the hazard ratio was 1.14 (95% confidence interval 1.03-1.26, P=0.007). A multiple linear regression analysis using the number of medications as a dependent factor and sex and other clinical characteristics as independent factors revealed that male sex (P=0.04), diabetes mellitus (P<0.0001), and duplication of drugs (P<0.0001) were positively correlated with the number of medications. CONCLUSIONS: Multiple drug use was observed in haemodialysis patients. The number of prescribed drugs was a significant predictor of short-term mortality. Male sex, diabetes mellitus, and duplication of drugs were correlated with increases in the number of medications.     

Medication noncompliance in chronic kidney disease

BACKGROUND: Medication noncompliance has a harmful impact on reaching therapeutic goals of delaying the progression of chronic kidney disease (CKD). The aim of the present study is to calculate the prevalence of medication noncompliance and to identify medication noncompliance-associated factors in CKD. METHODS: A cross-sectional study was performed with 130 CKD patients from a university nephrology outpatient clinic, mean age 48.8 +/- 15.8 years, who were continuously self-administering an antihypertensive or immunosuppressive drug, and who were neither on dialysis nor had received a kidney transplant. Noncompliance was measured through self-report (during an interview) and physician assessment. Patients were considered noncompliers if noncompliance had been detected by any of these methods. Sociodemographic, clinical and laboratory and medication characteristics were surveyed, as well as patients' knowledge regarding prescribed medicines and opinions of the quality of the health care service provided. RESULTS: Prevalence of medication noncompliance was 36.9% (95% confidence interval [95% CI], 28.6%-45.8%). Lack of access to medicines was the most commonly reported problem with medication use (62.5%). Multiple logistic regression analysis showed that patients' insufficient knowledge regarding prescribed medicines (p=0.040) and bad opinions of the quality of the provided health care service (p=0.027) were independently associated with noncompliance. CONCLUSIONS: Medication noncompliance prevalence was high among the patients studied. Lack of access to medicines remains an important public health problem. The noncompliance-associated factors identified in CKD were the patients' poor knowledge regarding the pharmacotherapy and dissatisfaction with the health care service provided.