Search

Kratom is a widely used Asian botanical that has gained popularity in the United States due to a perception that it can treat pain, anxiety, and opioid withdrawal symptoms. The American Kratom Association estimates 10–16 million people use kratom. Kratom‐associated adverse drug reactions (ADRs) continue to be reported and raise concerns about the safety profile of kratom. However, studies are lacking that describe the overall pattern of kratom‐associated adverse events and quantify the association between kratom and adverse events. ADRs reported to the US Food and Drug Administration Adverse Event Reporting System from January 2004 through September 2021 were used to address these knowledge gaps. Descriptive analysis was conducted to analyze kratom‐related adverse reactions. Conservative pharmacovigilance signals based on observed‐to‐expected ratios with shrinkage were estimated by comparing kratom to all other natural products and drugs. Based on 489 deduplicated kratom‐related ADR reports, users were young (mean age 35.5 years), and more often male (67.5%) than female patients (23.5%). Cases were predominantly reported since 2018 (94.2%). Fifty‐two disproportionate reporting signals in 17 system‐organ‐class categories were generated. The observed/reported number of kratom‐related accidental death reports was 63‐fold greater than expected. There were eight strong signals related to addiction or drug withdrawal. An excess proportion of ADR reports were about kratom‐related drug complaints, toxicity to various agents, and seizures. Although further research is needed to assess the safety of kratom, clinicians and consumers should be aware that real‐world evidence points to potential safety threats. [ABSTRACT FROM AUTHOR]

Background: Goals of managing patients with acute kidney injury (AKI) are mitigating disease progression and ensuring safety while providing supportive care because no effective treatment exists. One strategy recommended in guidelines to meet these goals is optimizing medication management. Unfortunately, guideline implementation appears to be lacking as observed by the frequent occurrence of medication errors and adverse drug events. Objective: To address this performance gap in the care of hospitalized patients receiving nephrotoxins and renally eliminated drugs, we sought to provide a potential intervention based on theory-informed behavior change. Methods: Formative research with a qualitative analysis identifying what needs to change in patient care was completed by obtaining clinician opinion and expert opinion and reviewing the published literature. Frontline providers, including 8 physicians, 4 pharmacists, and a multiprofessional group of authors, provided insight into possible barriers to appropriate prescribing. Capability, Opportunity, Motivation and Behavior model and Theoretical Domain Framework were applied to characterize behavior change interventions and inform a potential implementation intervention for changing inappropriate prescribing behaviors. Results: Lack of knowledge about appropriate drug management in patients at risk for adverse outcomes was provided as a major barrier. Other reported barriers included a lack of: (1) tools to assist with drug management, (2) motivation to make changes, (3) routinization, and (4) an accountable clinician. Conclusions and Relevance: Assigning a designated clinician to execute a stepwise, routine care process following the checklist provided is a recommended intervention to overcome barriers. The intended impact is behavior change that reduces inappropriate prescribing. [ABSTRACT FROM AUTHOR]

BACKGROUND: Between 2012 and 2017, 25 new medications or combination products were approved by the Food and Drug Administration (FDA) for use in treatment of chronic lower respiratory diseases (CLRDs). With limited data on post-marketing patient exposure to these drugs, their safety profiles remain unknown. This study aims to provide post-marketing surveillance of these medications. METHODS: A list of new CLRD medications approved between 2012 and 2017 was generated through searches on Drugs.com (https://www.drugs.com), FDA.gov (https://www.fda.gov), and IBM Micromedex (https://www.micromedexsolutions.com/home/dispatch/ssl/true). Data describing adverse drug reactions (ADRs) were collected from the FDA Adverse Event Reporting System for analysis. Of the 25 identified medications, we selected 4 medications indicated for asthma or COPD with at least 500 reports. Only ADRs catalogued with these medications as the primary suspect were analyzed. Reporting odds ratios were calculated for the top 10 ADRs of each CLRD medication. RESULTS: A total of 61,682 ADR reports were collected for newly approved CLRD medications (n = 27,190 older adults; n = 30,502 male). Reports of COPD medications (umeclidinium and umeclidinium/vilanterol) indicate that umeclidinium/vilanterol yielded a higher reporting odds ratio than umeclidinium alone for reports of pain. Fluticasone furoate/vilanterol had higher reporting odds ratios for cough, pain, and dizziness than budesonide/formoterol and fluticasone propionate/salmeterol. CONCLUSIONS: Our findings suggest that the incidence of different adverse events experienced by patients in post-marketing reports resembles the incidence reported in pre-marketing clinical trials for COPD medications, except for fluticasone furoate/vilanterol, which has several differences. [ABSTRACT FROM AUTHOR]

Introduction: Drug-induced QTc-prolongation is a well-known adverse drug reaction (ADR), however there is limited knowledge of other drug-induced arrhythmias. Purpose: The objective of this study is to determine the drugs reported to be associated with arrhythmias other than QTc-prolongation using the FAERS database, possibly identifying potential drug causes that have not been reported previously. Methods: FAERS reports from 2004 quarter 1 through 2019 quarter 1 were combined to create a dataset of approximately 11.6 million reports. Search terms for arrhythmias of interest were selected from the Standardized MedDRA Queries (SMQ) Version 12.0. Frequency of the cardiac arrhythmias were determined for atrial fibrillation, atrioventricular block, bradyarrhythmia, bundle branch block, supraventricular tachycardia, and ventricular fibrillation and linked to the reported causal medications. Reports were further categorized by prior evidence associations using package inserts and established drug databases. A reporting odds ratio (ROR) and confidence interval (CI) were calculated for the ADRs for each drug and each of the 6 cardiac arrhythmias. Results: Of the 11.6 million reports in the FAERS database, 68,989 were specific to cardiac arrhythmias of interest. There were 61 identified medication-reported arrhythmia pairs for the 6 arrhythmia groups with 33 found to have an unknown reported association. Rosiglitazone was the most frequently medication reported across all arrhythmias [ROR 6.02 (CI: 5.82-6.22)]. Other medications with significant findings included: rofecoxib, digoxin, alendronate, lenalidomide, dronedarone, zoledronic acid, adalimumab, dabigatran, and interferon beta-1b. Conclusion: Upon retrospective analysis of the FAERS database, the majority of drug-associated arrhythmias reported were unknown suggesting new potential drug causes. Cardiac arrhythmias other than QTc prolongation are a new area of focus for pharmacovigilance and medication safety. Consideration of future studies should be given to using the FAERS database as a timely pharmacovigilance tool to identify unknown adverse events of medications. [ABSTRACT FROM AUTHOR]

Nephrotoxin exposure accounts for up to one-fourth of acute kidney injury episodes in hospitalized patients, and the associated consequences are as severe as acute kidney injury due to other etiologies. As the use of nephrotoxic agents represents one of the few modifiable risk factors for acute kidney injury, clinicians must be able to identify patients at high risk for drug-induced kidney injury rapidly. Recently, significant advancements have been made in the field of biomarker utilization for the prediction and detection of acute kidney injury. Such biomarkers may have a role both for detection of drug-induced kidney disease and implementation of preventative and therapeutic strategies designed to mitigate injury. In this article, basic principles of renal biomarker use in practice are summarized, and the existing evidence for six markers specifically used to detect drug-induced kidney injury are outlined, including liver-type fatty acid binding protein, neutrophil gelatinase-associated lipocalin, tissue inhibitor of metalloproteinase-2 times insulin-like growth factor-binding protein 7 ([TIMP-2]·[IGFBP7]), kidney injury molecule-1 and N-acetyl-β-D-glucosaminidase. The results of the literature search for these six kidney damage biomarkers identified 29 unique articles with none detected for liver-type fatty acid binding protein and [TIMP-2]·[IGFBP7]. For three biomarkers, kidney injury molecule-1, neutrophil gelatinase-associated lipocalin and N-acetyl-β-D-glucosaminidase, the majority of the studies suggest utility in clinical practice. While many questions need to be answered to clearly articulate the use of biomarkers to predict drug-induced kidney disease, current data are promising. [ABSTRACT FROM AUTHOR]

The article focuses on concerns related to medication errors (MEs) and adverse drug events (ADEs) in intensive care unit (ICU) for the critically ill patient. Topics discussed include use of technology including computerized prescriber order entry (CPOE), clinical decision support systems (CDSS) and bar-coded medication administration (BCMA) systems, patient safety surveillance system and safe use of medications in the ICU.

Purpose: This investigation evaluated the incidence, severity, and harm of adverse drug reactions (ADRs) associated with antipsychotic use for intensive care unit (ICU) delirium. Methods: In this prospective, observational study patients were screened for development of delirium with the Intensive Care Delirium Screening Checklist (ICDSC). An ICDSC score of ≥4 was considered delirious. Patients with delirium were screened daily for ADRs. Suspected ADRs were evaluated for drug causality using 3 published, objective assessment tools. Suspected ADRs were considered positive when 2 of 3 instruments had an agreement rating of “possible” or greater. ADR severity was defined as “mild/moderate” or “severe” using the National Cancer Institute’s Common Terminology Criteria for Adverse Events scale. A modified National Coordinating Council Medication Error Reporting Index for Categorizing Errors categorized ADRs into “no harm” or “harmful.” Results: Of 90 patients with delirium, 56 received antipsychotics. Ten suspected ADRs occurred attributed to antipsychotic use. QTc prolongation was the most observed ADR (50%). Patients with ADRs had higher mean Acute Physiology and Chronic Health Evaluation II (APACHE II) scores (P = .038). Patients who received haloperidol experienced more severe (P = .048) ADRs. Conclusions: ADRs were observed in 18% of patients having delirium treated with antipsychotics with about half considered severe or harmful. A risk versus benefit assessment is needed before initiating antipsychotic therapy in ICU patients. [ABSTRACT FROM AUTHOR]

The article focuses on innovations in medication safety. Topics discussed include use of services and technologies for enhancing the understanding and prevention of adverse drug reactions. Topics include role of health care professionals in improving patients quality of life; capitalization of existing data for postmarketing surveillance approaches; and use of computerized prescriber order entry, and clinical decision support for preventing the same.

Objectives To determine whether a clinical surveillance system could be used to detect drug-associated hypoglycemia events and determine their incidence in nursing home ( NH) residents. Design Retrospective cohort. Setting Four NHs in western Pennsylvania. Participants Any resident of the four NHs who had a computer-generated alert detecting potential drug-associated hypoglycemia over a 6-month period were included. Measurements Descriptive statistics were used to summarize all variables, including the frequency and distribution of alert type according to glucose threshold. Analyses were conducted according to numbers of alerts and residents. The medications associated with the drug-associated hypoglycemia alerts were identified, and frequency of their inclusion in alerts was calculated. Additional calculations included time to drug-associated hypoglycemic event alert from date of admission and frequency of events associated with postacute, short-stay (≤35 days) admissions. Results Seven hundred seventy-two alerts involving 141 residents were detected. Ninety (63.8%) residents had a glucose level of 55 mg/dL or less, and 42 (29.8%) had a glucose level of 40 mg/dL or less. Insulin orders were associated with 762 (98.7%) alerts. Overall incidence of drug-associated hypoglycemia events was 9.5 per 1,000 resident-days. Conclusion Hypoglycemia can be detected using a clinical surveillance system. This evaluation found a high incidence of drug-associated hypoglycemia in a general NH population. Future studies are needed to determine the potential benefits of use of a surveillance system in real-time detection and management of hypoglycemia in NHs. [ABSTRACT FROM AUTHOR]

Introduction: Adverse events in the intensive care unit (ICU) may be associated with several possible causes, so determining a drug-related causal assessment is more challenging than in general ward patients. Therefore, the hypothesis was that automated trigger alerts may perform differently in various patient care settings. The purpose of this study was to compare the frequency and type of clinically significant automated trigger alerts in critically ill and general ward patients as well as evaluate the performance of alerts for drug-related hazardous conditions (DRHCs).Methods: A retrospective cohort study was conducted in adult ICU and general ward patients at three institutions (academic, community, and rural hospital) in a health system. Automated trigger alerts generated during two nonconsecutive months were obtained from a centralized database. Pharmacist responses to alerts and prescriber response to recommendations were evaluated for all alerts. A clinical significant event was defined as an actionable intervention requiring drug therapy changes that the pharmacist determined to be appropriate for patient safety and where the physician accepted the pharmacist's recommendation. The positive predictive value (PPV) was calculated for each trigger alert considered a DRHC (i.e., abnormal laboratory values and suspected drug causes).Results: A total of 751 alerts were generated in 623 patients during the study period. Pharmacists intervened on 39.8 and 44.8 % alerts generated in the ICU and general ward, respectively. Overall, the physician acceptance rate of approximately 90 % was comparable irrespective of patient care setting. Therefore, the number of clinically significant alerts was 88.9 and 83.4 % for the ICU and non-ICU, respectively. The types of drug therapy changes were similar between settings. The PPV of alerts identifying a DRHC was 0.66 in the ICU and 0.76 in general ward patients.Conclusions: The number and type of clinically significant alerts were similar irrespective of patient population, suggesting that the alerts may be equally as beneficial in the ICU population, despite the challenges in drug-related event adjudication. An opportunity exists to improve the performance of alerts in both settings, so quality improvement programs for measuring alert performance and making refinements is needed. [ABSTRACT FROM AUTHOR]

Opioids are the cornerstone of pain management; however, their use is associated with a variety of adverse drug events (ADEs) ranging from nausea and vomiting to urinary retention and respiratory depression. The purpose of this review is to describe the frequency and cost associated with different types of opioid-related ADEs to better understand their economic impact. A search of studies published in journals from 1946 to December, 2013, was conducted using MEDLINE and EMBASE. A total of 20 articles were reviewed. Data reflect a substantial economic burden of opioid-related ADEs resulting in high hospital costs, prolonged hospital stays, and substantial health care resource usage. Nausea, vomiting, and constipation are frequent and increased costs occur in all types of pain (surgical, nonsurgical, cancer, noncancer) in both inpatients and outpatients. Given the large economic burden of opioid-related ADEs, prevention rather than treatment may be the most effective strategy. [ABSTRACT FROM AUTHOR]

While medication reconciliation at ICU admission and discharge are lower-tier approaches on the engagement ladder, reconciliation is an important patient safety activity ([3]). There is only a suggestion - and not a strong recommendation - for implementing medication reconciliation pertaining to ADE and medication error prevention within the Safe Medication Use Guideline due to a lack of rigorous evidence at the time of publication ([5]). There is now an opportunity to leverage recently published recommendations to expand inpatient pharmacist roles and link them to non-ICU acute inpatient, as well as, with outpatient care activities in support of patient and family centered care ([4]). [Extracted from the article]

Background: Pharmacovigilance algorithms are used to assess the likelihood of adverse drug reaction (ADR) occurrence. The preferred instrument for use in the intensive care unit (ICU) is not established. Objective: The primary objective of this study was to compare the agreement between the Kramer algorithm, Naranjo criteria and Jones algorithm for the evaluation of ADRs in the ICU. A secondary objective was to compare the agreement between the same pharmacovigilance algorithms for ADR determination when applied in a retrospective versus concurrent fashion in the ICU. Study Design: There were two phases in this ~tudy. Phase I was the retrospective evaluation (i.e. after the patient was discharged from the hospital) conducted in patients admitted during July 2005 to June 2006. Phase II was the concurrent phase (i.e. while the patient was in the hospital) conducted over 6 weeks in 2008. Both phases were conducted at the University of Pittsburgh Medical Center and included adult patients admitted to the medical ICU. Intervention: In phase I, a random sample of 261 medication signals were evaluated individually for potential ADRs using the Kramer algorithm, Naranjo criteria and Jones algorithm. In phase II, an active medication monitoring system was used to detect live abnormal laboratory values, resulting in a random sample of 253 signals that were evaluated using the same three algorithms. Main Outcome Measure: Percentage agreement among the algorithms for all levels of causality was estimated using a kappa statistic for both phases of the study. Results: For phase I, the kappa values were all >0.7 ranging from 0.721 to 0.855 between instruments, with Naranjo versus Kramer having the highest kappa, which is considered excellent agreement. The kappa statistic between individual instruments for phase II are <0.7 ranging from 0.423 to 0.635, which is considered moderate agreement, with Naranjo versus Jones displaying the lowest kappa while still exhibiting moderate agreement. For phase II, the Kramer algorithm had better agreement with both the Naranjo criteria and the Jones algorithm. Conclusions: These instruments demonstrated similar results for evaluating ADRs in the ICU retrospectively, suggesting that instrument selection with any of the three instruments is reasonable. For concurrent ADR evaluations, there is greater variability in the level of causality obtained among pharmacovigilance algorithms and Kramer displayed better agreement with its comparators. A suggestion for a more definitive concurrent ADR assessment is to use more than one algorithm. This may be challenging in daily clinical practice; however, it is a reasonable expectation for research. [ABSTRACT FROM AUTHOR]

The article provides information on a study which identified potential risk factors for patients have adverse drug events (ADE) while in the intensive care unit (ICU). The retrospective case-control study was conducted at the University of Pittsburgh Medical Center-Presbyterian, which has 647 beds that contains approximately 120 ICU beds. The study enrolled patients who were admitted to ICU during a 7.5-year period.

Abstract: Objective: Clinical event monitors are a type of active medication monitoring system that can use signals to alert clinicians to possible adverse drug reactions. The primary goal was to evaluate the positive predictive values of select signals used to automate the detection of ADRs in the medical intensive care unit. Method: This is a prospective, case series of adult patients in the medical intensive care unit during a six-week period who had one of five signals presents: an elevated blood urea nitrogen, vancomycin, or quinidine concentration, or a low sodium or glucose concentration. Alerts were assessed using 3 objective published adverse drug reaction determination instruments. An event was considered an adverse drug reaction when 2 out of 3 instruments had agreement of possible, probable or definite. Positive predictive values were calculated as the proportion of alerts that occurred, divided by the number of times that alerts occurred and adverse drug reactions were confirmed. Results: 145 patients were eligible for evaluation. For the 48 patients (50% male) having an alert, the mean±SD age was 62±19 years. A total of 253 alerts were generated. Positive predictive values were 1.0, 0.55, 0.38 and 0.33 for vancomycin, glucose, sodium, and blood urea nitrogen, respectively. A quinidine alert was not generated during the evaluation. Conclusions: Computerized clinical event monitoring systems should be considered when developing methods to detect adverse drug reactions as part of intensive care unit patient safety surveillance systems, since they can automate the detection of these events using signals that have good performance characteristics by processing commonly available laboratory and medication information. [Copyright &y& Elsevier]

Abstract: Purpose: Limited information addressing the safety and efficacy of diazepam in the intensive care unit, particularly in trauma patients, is available. The purpose of this study is to evaluate the safety and efficacy of diazepam when used in routine clinical practice as a component of a goal-directed sedation regimen in critically ill trauma patients. Material and methods: This is a prospective observational evaluation of adult trauma patients admitted to an intensive care unit with orders for as-needed midazolam or lorazepam followed by scheduled diazepam. Medication administration and Sedation-Agitation Scale scores were recorded. Results: Twenty-four patients were evaluated. The most common diazepam dosage was 10 mg every 6 hours, and individual doses ranged from 5 to 30 mg. Sedation-Agitation Scale scores were recorded a median of 20 times per day (interquartile range, 15-24), and the majority (68%) were in the target range. No diazepam-related adverse events were observed. Conclusions: Based on this limited sample, the use of diazepam as a component of goal-directed therapy appears safe and effective in providing adequate sedation in critically ill trauma patients using an average dosage of 40 mg/d. [Copyright &y& Elsevier]

The article discusses medication errors in intensive care units (ICU). A preventable adverse drug event (ADE) is an injury associated with a medication error and its prevention is important to avoid the possibility of consequential patient injury. Near misses or potential ADEs are serious medication errors such as preventable ADEs and errors with the potential to cause harm. One approach to preventing medication errors in the ICU is the formation of a multiprofessional patient care team.

The article offers techniques for the improvement of the assessment of intensive care unit (ICU) care. The methods in use for the identification of adverse drug events (ADEs) are varied. These methods are national surveillance for hospitals, nontargeted and targeted medical record review, morbidity and mortality conferences, review of target-stimulated reports, interpretation of methodologic considerations, and voluntary reporting, among others. The authors suggest a surveillance system for errors that use varying methods to provide sufficient input.

A letter to the editor is presented in response to the paper "Relationship Between Potential Opioid-Related Adverse Effects and Hospital Length of Stay in Patients Receiving Opioids After Orthopedic Surgery" published in "Pharmacotherapy" journal.

Objective: Prior research indicates that off-label use is common in the ICU; however, the safety of off-label use has not been assessed. The study objective was to determine the prevalence of adverse drug reactions associated with off-label use and evaluate off-label use as a risk factor for the development of adverse drug reactions in an adult ICU population. Design: Multicenter, observational study Setting: Medical ICUs at three academic medical centers. Patients: Adult patients (age ≥ 18 yr old) receiving medication therapy. Interventions: All administered medications were evaluated for Food and Drug Administration-approved or off-label use. Patients were assessed daily for the development of an adverse drug reaction through active surveillance. Three adverse drug reaction assessment instruments were used to determine the probability of an adverse drug reaction resulting from drug therapy. Severity and harm of the adverse drug reaction were also assessed. Cox proportional hazard regression was used to identify a set of covariates that influenced the rate of adverse drug reactions. Measurements and Main Results: Overall, 1,654 patient-days (327 patients) and 16,391 medications were evaluated, with 43% of medications being used off-label. One hundred and sixteen adverse drug reactions were categorized dichotomously (Food and Drug Administration or off-label), with 56% and 44% being associated with Food and Drug Administration-approved and offlabel use, respectively. The number of adverse drug reactions for medications administered and the number of harmful and severe adverse drug reactions did not differ for medications used for Food and Drug Administration-approved or off-label use (0.74% vs 0.67%; p = 0.336; 33 vs 31 events, p = 0.567; 24 vs 24 events, p = 0.276). Age, sex, number of high-risk medications, number of off-label medications, and severity of illness score were included in the Cox proportional hazard regression. It was found that the rate of adverse drug reactions increases by 8% for every one additional off-label medication (hazard ratio = 1.08; 95% CI, 1.018-1.154). Conclusion: Although adverse drug reactions do not occur more frequently with off-label use, adverse drug reaction risk increases with each additional off-label medication used. [ABSTRACT FROM AUTHOR]