Faisal Rehman

Calcium-Channel Blocker–Clarithromycin Drug Interactions and Acute Kidney Injury

IMPORTANCE Calcium-channel blockers are metabolized by the cytochrome P450 3A4 (CYP3A4; EC 1.14.13.97) enzyme. Blood concentrations of these drugs may rise to harmful levels when CYP3A4 activity is inhibited. Clarithromycin is an inhibitor of CYP3A4 and azithromycin is not, which makes comparisons between these 2 macrolide antibiotics useful in assessing clinically important drug interactions. OBJECTIVE To characterize the risk of acute adverse events following coprescription of clarithromycin compared with azithromycin in older adults taking a calcium-channel blocker. DESIGN, SETTING, AND PARTICIPANTS Population-based retrospective cohort study in Ontario, Canada, from 2003 through 2012 of older adults (mean age, 76 years) who were newly coprescribed clarithromycin (n = 96,226) or azithromycin (n = 94,083) while taking a calcium-channel blocker (amlodipine, felodipine, nifedipine, diltiazem, or verapamil). MAIN OUTCOMES AND MEASURES Hospitalization with acute kidney injury (primary outcome) and hospitalization with hypotension and all-cause mortality (secondary outcomes examined separately). Outcomes were assessed within 30 days of a new coprescription. RESULTS There were no differences in measured baseline characteristics between the clarithromycin and azithromycin groups. Amlodipine was the most commonly prescribed calcium-channel blocker (more than 50% of patients). Coprescribing clarithromycin vs azithromycin with a calcium-channel blocker was associated with a higher risk of hospitalization with acute kidney injury (420 patients of 96,226 taking clarithromycin [0.44%] vs 208 patients of 94,083 taking azithromycin [0.22%]; absolute risk increase, 0.22% [95% CI, 0.16%-0.27%]; odds ratio [OR], 1.98 [95% CI, 1.68-2.34]). In a subgroup analysis, the risk was highest with dihydropyridines, particularly nifedipine (OR, 5.33 [95% CI, 3.39-8.38]; absolute risk increase, 0.63% [95% CI, 0.49%-0.78%]). Coprescription with clarithromycin was also associated with a higher risk of hospitalization with hypotension (111 patients of 96,226 taking clarithromycin [0.12%] vs 68 patients of 94,083 taking azithromycin [0.07%]; absolute risk increase, 0.04% [95% CI, 0.02%-0.07%]; OR, 1.60 [95% CI, 1.18-2.16]) and all-cause mortality (984 patients of 96,226 taking clarithromycin [1.02%] vs 555 patients of 94,083 taking azithromycin [0.59%]; absolute risk increase, 0.43% [95% CI, 0.35%-0.51%]; OR, 1.74 [95% CI, 1.57-1.93]). CONCLUSIONS AND RELEVANCE Among older adults taking a calcium-channel blocker, concurrent use of clarithromycin compared with azithromycin was associated with a small but statistically significant greater 30-day risk of hospitalization with acute kidney injury. These findings support current safety warnings regarding concurrent use of CYP3A4 inhibitors and calcium-channel blockers.

Atypical Antipsychotic Drugs and the Risk for Acute Kidney Injury and Other Adverse Outcomes in Older Adults: A Population-Based Cohort Study

Context Acute kidney injury (AKI) is reportedly associated with atypical antipsychotic drugs, although the risk has not been quantified. Contribution This population-based cohort study found that persons who had received a prescription for any of 3 atypical antipsychotic drugs in the previous 90 days had an elevated risk for hospitalization with AKI. These drugs were also associated with increased risk for hypotension, acute urinary retention, and death. Caution Only older adults and 3 antipsychotic agents were studied. Implication An association with specific adverse events may explain the increased risk for AKI observed with certain atypical antipsychotic drugs. The Editors Each year, millions of older adults worldwide are prescribed atypical antipsychotic drugs (quetiapine, risperidone, and olanzapine). These drugs are frequently used to manage behavioral symptoms of dementia, which is not an approved indication, and such use has raised safety concerns (1, 2). These drugs antagonize -adrenergic, muscarinic, serotonin, and dopamine receptors (3). Acute kidney injury (AKI) (defined as a sudden loss of kidney function) from atypical antipsychotic drugs is described in several case reports (48). Adverse outcomes potentially attributable to these drugs, such as hypotension, acute urinary retention, and the neuroleptic malignant syndrome or rhabdomyolysis, are known to cause AKI (411). Moreover, pneumonia, acute myocardial infarction, and ventricular arrhythmia have been associated with these drugs in previous population-based studies and AKI may also co-occur with these events (1214). However, no clinical or epidemiologic studies have quantified the risk for AKI from atypical antipsychotic drugs and information on outcomes of hypotension, acute urinary retention, and the neuroleptic malignant syndrome or rhabdomyolysis is limited. Such information would contribute to growing knowledge of potential adverse events from this drug class. The U.S. Food and Drug Administration warns of an increased risk for death in older patients treated with these drugs based on analyses of randomized, placebo-controlled trials (averaging 10 weeks in duration) (1). For these reasons, we did this population-based study of older adults to investigate the 90-day risk for hospitalization with AKI and other adverse outcomes from new use of an oral atypical antipsychotic drug initiated in the nonhospital setting. Methods Design and Setting We conducted this study at the Institute for Clinical Evaluative Sciences according to a prespecified protocol that was approved by the research ethics board at Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada. Patient informed consent was not required. We did a population-based, retrospective cohort study of older adults using linked health care databases in Ontario, Canada. Ontario residents have universal access to hospital care and physician services, and those aged 65 years or older have universal prescription drug coverage. The reporting of this study followed guidelines for observational studies (Table 1 of the Supplement) (15). Supplement. Supplementary material Data Sources We ascertained patient characteristics, drug use, covariate information, and outcome data using records from 5 databases. We obtained vital statistics from the Registered Persons Database of Ontario, which contains demographic information on all Ontario residents who have ever been issued a health card. We used the Ontario Drug Benefit database to identify prescription drug use. This database contains highly accurate recordsthe error rate is less than 1%of all outpatient prescriptions dispensed to patients aged 65 years or older (16). We identified diagnostic and procedural information on all hospitalizations from the Canadian Institute for Health Information Discharge Abstract Database. We obtained covariate information from the Ontario Health Insurance Plan database, which includes health claims for inpatient and outpatient physician services. We identified diagnostic information on all admissions to adult mental health beds from the Ontario Mental Health Reporting System. We have used these databases to research adverse drug reactions and health outcomes (including AKI) (1722). The databases were complete for all variables used in this study, except for prescriber information (which was missing for 10.8% of patients in the cohort). Codes from the International Classification of Diseases, Ninth Revision (before 2002), and Tenth Revision (after 2002), were used to assess baseline comorbid conditions in the 5 years before cohort entry (Table 2 of the Supplement). Codes used to ascertain outcomes are detailed in Table 3 of the Supplement, which lists only codes from the Tenth Revision because all events would have occurred after implementation of that coding system. A subpopulation in southwestern Ontario had information on outpatient serum creatinine levels available before cohort entry; this group was in the catchment area of 12 hospitals in which linked laboratory values were also available (23). Patients We established a cohort of older adults with evidence of a new outpatient prescription for an oral atypical antipsychotic drug (quetiapine, risperidone, or olanzapine) between June 2003 and December 2011. The date of this prescription served as the index date (cohort entry date) for the drug recipients. We matched a group of drug nonrecipients similar in health status to the recipients. We randomly assigned an index date to the entire Ontario population according to the index date of the drug recipients. For example, if more recipients had an index date between 2003 and 2005, a greater proportion of the population would have been randomly assigned an index date between 2003 and 2005. From these adults, after applying our exclusions to both groups, we matched a drug nonrecipient to each recipient on the following 11 characteristics: age (within 2 years); sex; residential status (community-dwelling or long-term care); evidence of comorbid conditions (dementia, schizophrenia or other psychotic disorder, bipolar disorder, major depression or anxiety disorder, Parkinson disease, and chronic kidney disease); constituency in the subpopulation with available information on serum creatinine levels; and the logit of the propensity score for the predicted probability of newly receiving an atypical antipsychotic drug (within a caliper of 0.2 SDs). We derived this propensity score from a logistic regression model and selected 91 variables for inclusion in the score on the basis of their potential association with the study outcomes or atypical antipsychotic drug initiation (variables listed in Table 4 of the Supplement) (24). One of the variables was the Johns Hopkins Adjusted Clinical Group Aggregated Diagnosis Groups (a validated measure of the complexity of comorbid conditions based on groups of diagnoses) (25, 26). Before matching, we excluded the following patients from both groups: those with prescriptions for any antipsychotic drug in the 180 days before their index date to ensure that the drug was newly prescribed (or had the potential to be newly prescribed in the case of the nonrecipients); those who were discharged from a hospital in the 2 days before their index date to ensure that drug use was newly initiated in the nonhospitalized setting (as in Ontario, patients continuing atypical antipsychotic drug treatment initiated in a hospital would have their oral outpatient prescription dispensed the day of or the day after hospital discharge); and those with evidence of end-stage renal disease before their index date (because the development of AKI is no longer relevant). Among the drug recipients, those who received a prescription for more than 1 type of antipsychotic drug (for example, a prescription for quetiapine and olanzapine) on their index date were excluded to compare mutually exclusive groups in subgroup analyses. Among the nonrecipients, those who did not have at least 1 outpatient medication dispensed in the 90 days before their index date were excluded to ensure that such persons were able to receive a prescription. Each drug recipient and nonrecipient could be selected only once for cohort entry. Outcomes We followed patients for 90 days after the index date to assess the prespecified outcomes. We chose 90 days to focus on acute adverse events, avoid potential crossovers between the 2 groups that might occur with longer follow-up, and mimic the duration of follow-up described in clinical trials of atypical antipsychotic drugs in older patients (1, 2, 27). The primary outcome was hospitalization with AKI. The secondary adverse outcomes were known causes of AKI (hospitalization with hypotension, acute urinary retention, the neuroleptic malignant syndrome or rhabdomyolysis, pneumonia, acute myocardial infarction, and ventricular arrhythmia) and all-cause mortality. The diagnosis codes used to identify the outcomes and information on their accuracy are presented in Table 3 of the Supplement (2830). For hospitalization records, up to 25 diagnosis codes can be assigned per hospitalization (for example, codes for AKI or rhabdomyolysis). Therefore, patients with codes for multiple study outcomes were accounted for in the assessment of each outcome. We previously examined the validity of the database code for hospitalization with AKI used in the current study. In this previous validation study (30), the database code for AKI identified a median increase in serum creatinine level of 98 mol/L (1.11 mg/dL) (interquartile range [IQR], 43 to 200 mol/L [0.49 to 2.26 mg/dL]) at the time of hospital presentation from the most recent value before hospitalization. The absence of such a code represented no statistically significant change in serum creatinine level (6 mol/L [0.07 mg/dL]; IQR, 4 to 20 mol/L [0.05 to 0.23 mg/dL]) (30). Although specificity was greater than 95%, the sensitivity of the hospital diagnosis was

Intravenous immunoglobulin as rescue therapy for BK virus nephropathy

Abstract:  BKVN has emerged as an important cause of pediatric renal allograft nephropathy, with significant graft dysfunction in majority of the cases. Reduced immunosuppression and cidofovir therapy are the most commonly used therapeutic options for the treatment of BKVN in these patients. Recently, a preliminary study in adult renal allograft recipients with BKVN showed a therapeutic response to a combined approach of immunosuppression reduction and IVIg administration. A therapeutic benefit of IVIg without another concomitant treatment intervention has not been evaluated. We report stabilization of renal functions, histological resolution of BKVN and significant reduction in BK viremia in pediatric renal transplant with the use of IVIg, after an inadequate response to immunosuppression reduction and cidofovir therapy. In addition, we review the current literature on the use of cidofovir in pediatric renal transplant patients with BKVN and the potential of IVIg use in this condition.

Filtering Medline for a clinical discipline: diagnostic test assessment framework

Objective To develop and test a Medline filter that allows clinicians to search for articles within a clinical discipline, rather than searching the entire Medline database. Design Diagnostic test assessment framework with development and validation phases. Setting Sample of 4657 articles published in 2006 from 40 journals. Reviews Each article was manually reviewed, and 19.8% contained information relevant to the discipline of nephrology. The performance of 1 155 087 unique renal filters was compared with the manual review. Main outcome measures Sensitivity, specificity, precision, and accuracy of each filter. Results The best renal filters combined two to 14 terms or phrases and included the terms “kidney” with multiple endings (that is, truncation), “renal replacement therapy”, “renal dialysis”, “kidney function tests”, “renal”, “nephr” truncated, “glomerul” truncated, and “proteinuria”. These filters achieved peak sensitivities of 97.8% and specificities of 98.5%. Performance of filters remained excellent in the validation phase. Conclusions Medline can be filtered for the discipline of nephrology in a reliable manner. Storing these high performance renal filters in PubMed could help clinicians with their everyday searching. Filters can also be developed for other clinical disciplines by using similar methods.

Re-exposure to mismatched HLA class I is a significant risk factor for graft loss : Multivariable analysis of 259 kidney retransplants

Background. Kidney retransplants carry increased immunologic risk. One possible contributor to this risk may be re-exposure to human leukocyte antigens (HLA) common to a previous donor but foreign to the recipient. Conflicting publications have assessed this risk, so to examine our experience 259 kidney retransplants were analyzed. Methods. A retrospective cohort of retransplant patients from 1973 to 2005 with minimum 12 months follow up was examined. Using multivariable modeling, important confounders were controlled for identifying factors significantly affecting graft survival. Results. Re-exposure to HLA class I (HLA-A or B) antigens, peak panel reactive antibodies and donor source were the most important determinants of allograft survival, despite a negative conventional or anti-human globulin-augmented T cell crossmatch. We failed to demonstrate that recipient re-exposure to HLA class II (HLA-DR) or positive B cell crossmatch were associated with adverse outcomes. Sample size and molecular versus serologic methods may have influenced the former, while inability to determine antibody specificities may have influenced the latter. Controlling for other variables, the adjusted risk of graft loss associated with re-exposure to HLA class I increased by 71% (P=0.006) and occurred early, consistent with recall of memory cytotoxic T lymphocyte or antibody responses. Conclusions. Kidney recipients re-exposed to mismatched HLA class I antigens appear to be at heightened risk of early graft loss. Such patients may benefit from pretransplant identification of donor specific antibodies using solid phase methods and heightened vigilance for acute rejection. Future studies may indicate whether more intensive immunosuppression for these patients is warranted.

Preoperative Cylex assay predicts rejection risk in patients with kidney transplant.

The ImmuKnow assay measures cell‐mediated immunity by quantifying ATP release from CD4+ T‐cells in peripheral blood. Herein, we hypothesized that this assay could predict complications associated with over‐/under‐immunosuppression in patients with kidney transplant (KT).

Kidney transplantation search filters for PubMed, Ovid Medline, and Embase.

Background. Clinicians commonly search bibliographic databases such as Medline to find sound evidence to guide patient care. Unfortunately, this can be a frustrating experience because database searches often miss relevant articles. We addressed this problem for transplant professionals by developing kidney transplantation search filters for use in Medline through PubMed and Ovid Technologies, and Embase. Methods. We began by reading the full-text versions of 22,992 articles from 39 journals published across 5 years. These articles were labeled relevant to kidney transplantation or not forming our “gold standard.” We then developed close to five million kidney transplantation filters using different terms and their combinations. Afterward, these filters were applied to development and validation subsets of the articles to determine their accuracy and reliability in identifying articles with kidney transplantation content. The final kidney transplantation filters used multiple terms in combination. Results. The best performing filters achieved 97.5% sensitivity (95% confidence interval, 96.4%–98.5%), and 98.0% specificity (95% confidence interval, 97.8%–98.3%). Similar high performance was achieved for filters developed for Ovid Medline and Embase. Proof-of-concept searches confirmed more relevant articles are retrieved using these filters. Conclusions. These kidney transplantation filters can now be used in Medline and Embase databases to improve clinician searching.

Apparent low absorbers of cyclosporine microemulsion have higher requirements for tacrolimus in renal transplantation

Abstract:  Bioavailability and exposure of cyclosporine microemulsion and tacrolimus in renal transplantation are governed by many complex factors. Failure to achieve therapeutic two‐h post‐dose (C2) levels despite adequate doses of cyclosporine (“low absorbers”) may merit conversion to tacrolimus. We compared tacrolimus dose requirements in “low absorbers” (n = 15) with a random control group of de novo tacrolimus patients (n = 14). Low absorbers failed to reach target C2 despite increasing dose from 10.1 to 16.2 mg/kg/d. At conversion the mean C2 was 969 ng/mL (95% CI: 684–1255; target 1700 ng/mL). Low absorbers tended to be younger, heavier, and diabetic. Despite a similar initial tacrolimus dose (0.17–0.18 mg/kg/d), low absorbers required a much higher daily dose to achieve target; 0.25 vs. 0.16 mg/kg/d (p = 0.016). Furthermore, daily maintenance tacrolimus remained much higher in low absorbers at three wk (0.22 vs. 0.13 mg/kg/d, p = 0.012). Although not statistically significant, this group experienced an acute rejection rate of 33%, compared with 21% in the control group. Patients treated with cyclosporine as initial immunosuppression who fail to reach target C2 levels in a timely fashion are at risk for impaired bioavailability of tacrolimus. Based on our data, a starting dose of 0.25 mg/kg/d in divided doses may be warranted for low absorbers converting to tacrolimus; however, we encourage larger studies with formal pharmacokinetic analysis in this population.