Comparison of 71 bipolar disorder pharmacotherapies for kidney disorder risk: The potential hazards of polypharmacy

Unveiling drug induced nephrotoxicity using novel biomarkers and cutting-edge preventive strategies

Drug-induced nephrotoxicity is still a significant obstacle in pharmacotherapy of various diseases and it accounts for around 25 % of serious side-effects reported after drug administration. Furthermore, some groups of drugs such as nonsteroidal anti-inflammatory drugs, antibiotics, antiviral drugs, antifungal drugs, immunosuppressants, and chemotherapeutic drugs have the "preference" for damaging the kidney and are often referred to as the kidney's "silent killer". Clinically, the onset of acute kidney injury associated with drug administration is registered in approximately 20 % of patients and many of them develop chronic kidney disease vulnerability. However, current knowledge about the mechanisms underlying this dangerous phenomenon is still insufficient with many unknowns. Hence, the valuable use of these drugs in clinical practice is significantly limited. The main aim of this study is to draw attention to commonly prescribed nephrotoxic drugs by clinicians or drugs bought over the counter. In addition, the complex relationship between immunological, vascular and inflammatory events that promote kidney damage is discussed. The practical use of this knowledge could be implemented in the engineering of novel biomarkers for early detection of drug-associated kidney damage such as Kidney Injury Molecule (KIM-1), lipocalin associated with neutrophil gelatinase (NGAL) and various microRNAs. In addition, the utilization of artificial intelligence (AI) for the development of computer algorithms that could detect kidney damage at an early stage should be further explored. Therefore, this comprehensive review provides a new outlook on drug nephrotoxicity that opens the door for further clinical research of novel potential drugs or natural products for the prevention of drug-induced nephrotoxicity and accessible education.

Treatment-induced mood switching in affective disorders

Many patients under treatment for mood disorders, in particular patients with bipolar mood disorders, experience episodes of mood switching from one state to another. Various hypotheses have been proposed to explain the mechanism of mood switching, spontaneously or induced by drug treatment. Animal models have also been used to test the role of psychotropic drugs in the switching of mood states. We examine the possible relationship between the pharmacology of psychotropic drugs and their reported incidents of induced mood switching, with reference to the various hypotheses of mechanisms of mood switching.

Lithium: Current Clinical Guidelines for Nurse Practitioners

Bipolar disorder is a serious neuroprogressive disorder associated with structural and functional brain changes, multiple comorbidities, and heightened risk for suicide. Lithium has been a first-line treatment for bipolar disorder for more than 50 years and recent research suggests that early identification and treatment of bipolar disorder with lithium can alter the progression of the illness. The purpose of the current article is to review evidence for lithium's neurotrophic and neuroprotective actions and clinical guidelines for safe and effective use. [Journal of Psychosocial Nursing and Mental Health Services, 60(1), 6-9.].

Polypharmacy and the Progression of Chronic Kidney Disease: Korean Cohort Study for Outcome in Patients with Chronic Kidney Disease

INTRODUCTION

The renal hazard of polypharmacy has never been evaluated in predialysis chronic kidney disease (CKD) patients.

OBJECTIVE

We aimed to analyze the renal hazard of polypharmacy in predialysis CKD patients with stage 1-5.

METHOD

The data of 2,238 patients from a large-scale multicenter prospective Korean study (2011-2016), excluding 325 patients with various missing data, were reviewed. Polypharmacy was defined as taking 6 or more medications at the time of enrollment; renal events were defined as a ≥50% decrease in kidney function from baseline values, doubling of the serum creatinine levels, or initiation of renal replacement treatment. Hazard ratio (HR) and 95% confidence interval (CI) were calculated using Cox proportional-hazard regression analysis.

RESULTS

Of the 1,913 patients, the mean estimated glomerular filtration rate was 53.6 mL/min/1.73 m2. The mean medication count was 4.1, and the prevalence of polypharmacy was 27.1%. During the average period of 3.6 years, 520 patients developed renal events (27.2%). Although increased medication counts were associated with increased renal hazard with HR (95% CI) of 1.056 (1.007-1.107, p = 0.025), even after adjusting for various confounders, adding comorbidity score and kidney function nullified the statistical significance. In mediation analysis, 55.6% (p = 0.016) of renal hazard in increased medication counts was mediated by the kidney function, and there was no direct effect of medication counts on renal event development. In subgroup analysis, the renal hazard of the medication counts was evident only in stage 1-3 of CKD patients (p for interaction = 0.014).

CONCLUSIONS

We cannot identify the direct renal hazard of multiple medications, and most of the potential renal hazard was derived from intimate relationship with disease burden and kidney function.

Using Machine Learning Imputed Outcomes to Assess Drug-Dependent Risk of Self-Harm in Patients with Bipolar Disorder: A Comparative Effectiveness Study

BACKGROUND

Incomplete suicidality coding in administrative claims data is a known obstacle for observational studies. With most of the negative outcomes missing from the data, it is challenging to assess the evidence on treatment strategies for the prevention of self-harm in bipolar disorder (BD), including pharmacotherapy and psychotherapy. There are conflicting data from studies on the drug-dependent risk of self-harm, and there is major uncertainty regarding the preventive effect of monotherapy and drug combinations.

OBJECTIVE

The aim of this study was to compare all commonly used BD pharmacotherapies, as well as psychotherapy for the risk of self-harm, in a large population of commercially insured individuals, using self-harm imputation to overcome the known limitations of this outcome being underrecorded within US electronic health care records.

METHODS

The IBM MarketScan administrative claims database was used to compare self-harm risk in patients with BD following 65 drug regimens and drug-free periods. Probable but uncoded self-harm events were imputed via machine learning, with different probability thresholds examined in a sensitivity analysis. Comparators included lithium, mood-stabilizing anticonvulsants (MSAs), second-generation antipsychotics (SGAs), first-generation antipsychotics (FGAs), and five classes of antidepressants. Cox regression models with time-varying covariates were built for individual treatment regimens and for any pharmacotherapy with or without psychosocial interventions ("psychotherapy").

RESULTS

Among 529,359 patients, 1.66% (n=8813 events) had imputed and/or coded self-harm following the exposure of interest. A higher self-harm risk was observed during adolescence. After multiple testing adjustment (P≤.012), the following six regimens had higher risk of self-harm than lithium: tri/tetracyclic antidepressants + SGA, FGA + MSA, FGA, serotonin-norepinephrine reuptake inhibitor (SNRI) + SGA, lithium + MSA, and lithium + SGA (hazard ratios [HRs] 1.44-2.29), and the following nine had lower risk: lamotrigine, valproate, risperidone, aripiprazole, SNRI, selective serotonin reuptake inhibitor (SSRI), "no drug," bupropion, and bupropion + SSRI (HRs 0.28-0.74). Psychotherapy alone (without medication) had a lower self-harm risk than no treatment (HR 0.56, 95% CI 0.52-0.60; P=8.76×10^-58). The sensitivity analysis showed that the direction of drug-outcome associations did not change as a function of the self-harm probability threshold.

CONCLUSIONS

Our data support evidence on the effectiveness of antidepressants, MSAs, and psychotherapy for self-harm prevention in BD.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02893371; https://clinicaltrials.gov/ct2/show/NCT02893371.

Diabetes mellitus risk for 102 drugs and drug combinations used in patients with bipolar disorder

OBJECTIVE

To compare the largest set of bipolar disorder pharmacotherapies to date (102 drugs and drug combinations) for risk of diabetes mellitus (DM).

METHODS

The IBM MarketScan® database was used to retrospectively analyze data on 565,253 adults with bipolar disorder without prior glucose metabolism-related diagnoses. The pharmacotherapies compared were lithium, mood-stabilizing anticonvulsants, antipsychotics, and antidepressants (monotherapy and multi-class polypharmacy). Cox regression modeling included fixed pre-treatment covariates and time-varying drug exposure covariates to estimate the hazard ratio (HR) of each treatment versus "No drug".

RESULTS

The annual incidence of new-onset diabetes during the exposure period was 3.09 % (22,951 patients). The HR of drug-dependent DM ranged from 0.79 to 2.37. One-third of the studied pharmacotherapies, including most of the antipsychotic-containing regimens, had a significantly higher risk of DM compared to "No drug". A significantly lower DM risk was associated with lithium, lamotrigine, oxcarbazepine and bupropion monotherapies, selective serotonin reuptake inhibitors (SSRI) mono-class therapy and several drug combinations containing bupropion and an SSRI. As additional drugs were combined in more complex polypharmacy, higher HRs were consistently observed.

CONCLUSIONS

There is an increased risk of diabetes mellitus associated with antipsychotic and psychotropic polypharmacy use in bipolar disorder. The evidence of a lower-than-baseline risk of DM with lamotrigine, oxcarbazepine, lithium, and bupropion monotherapy should be further investigated.