Appropriateness of antithrombotics in geriatric inpatients with atrial fibrillation: a retrospective, cross-sectional study.

BACKGROUND: Atrial fibrillation occurs in nearly half of geriatric inpatients and is a major cause of morbidity and mortality. Suboptimal anticoagulation use is an important concern in this population. This study aimed to evaluate the appropriateness of antithrombotic therapies in this patient cohort. METHODS: A retrospective analysis was conducted on the geriatric wards of a teaching hospital in Belgium, on a background of clinical pharmacy services. The first 90 atrial fibrillation patients from 2020 to 2022 were included if they received an oral anticoagulant. We assessed utilisation and appropriateness of antithrombotics at discharge, examined reasons for guideline deviations, and explored factors associated with underdosing. Temporal associations for appropriateness and type of anticoagulant (vitamin K antagonist (VKA) vs direct oral anticoagulant (DOAC)) were assessed. RESULTS: The mean age of patients was 86.5 (±5.3) years and the median CHA2DS2-VASc score was 5 (interquartile range (IQR) 4-6). At discharge, 256 (94.8%) patients used a DOAC; nine (3.3%) used a VKA; one (0.4%) a DOAC-antiplatelet combination, and in four patients (1.5%) all antithrombotics were discontinued. The majority (64.4%) of patients received reduced DOAC doses with apixaban prescribed in 40.7%. In 39 (14.4%) patients, antithrombotic use was considered inappropriate, mostly without a rationale (23/39). Year 2022 (odds ratio (OR) 0.104; 95% confidence interval (CI), 0.012-0.878) was the sole determinant for underdosing. No significant differences were found with respect to appropriateness (p=0.533) or anticoagulant class (p=0.479) over time. CONCLUSION: Most geriatric inpatients received a justified reduced DOAC dose. A significant proportion was managed inappropriately with underdosing (= unjustified reduced dose) being most common. Frequently no rationale was provided for deviating from trial-tested doses.

Should vericiguat be initiated in geriatric inpatients with heart failure with reduced ejection fraction and a worsening heart failure event prior to discharge?

Heart failure (HF) occurs predominantly in older adults. HF patients have an increased risk for an acute exacerbation, which commonly requires hospitalisation. Such a worsening HF (WHF) event has an impact on prognosis. Vericiguat is a novel agent which has been shown to reduce the HF hospitalisation risk in patients with a recent WHF event. It is not fully clear how to position this novel agent in geriatric HF inpatients.

Age is just a number: the concept of time to benefit in older adults.

A female nursing home resident aged >70 years was admitted to the geriatric ward with de novo dysphagia 6 days after being discharged from the stroke unit. Metformin and ezetimibe had been added to her treatment regimen which already consisted of clopidogrel, atorvastatin, denosumab, calcium and vitamin D. At the geriatric ward a multidisciplinary team involving clinical pharmacists reviewed all treatments and appraised the time to benefit, ascertaining whether there was sufficient time left to experience therapeutic benefits. As a result, metformin, ezetimibe, denosumab, calcium and vitamin D were discontinued. This case report illustrates that both mortality risk assessment and evaluation of the time to benefit should be part of any medication review in frail older adults. Conversely, with limited available data pertaining to the concept of time to benefit, we advocate a broader awareness among pharmacists and a systematic assessment in future clinical trials.

Drug-related hospital admissions in older adults: comparison of the Naranjo algorithm and an adjusted version of the Kramer algorithm.

PURPOSE: Drug-related admissions (DRAs) are an important cause of preventable harm in older adults. Multiple algorithms exist to assess causality of adverse drug reactions, including the Naranjo algorithm and an adjusted version of the Kramer algorithm. The performance of these tools in assessing DRA causality has not been robustly shown. This study aimed to evaluate the ability of the adjusted Kramer algorithm to adjudicate DRA causality in geriatric inpatients. METHODS: DRAs were assessed in a convenience sample of patients admitted to the acute geriatric wards of an academic hospital. DRAs were identified by expert consensus and causality was evaluated using the Naranjo and the adjusted Kramer algorithms. Positive agreement with expert consensus was calculated for both algorithms. A multivariable logistic regression analysis was performed to explore determinants for a DRA. RESULTS: A total of 218 geriatric inpatients was included of whom 65 (29.8%) experienced a DRA. Positive agreement was 72.3% (95% confidence interval (CI), 59.6-82.3%) and 100% (95% CI, 93.0-100%) for the Naranjo and the adjusted Kramer algorithm, respectively. Diuretics were the main culprits and most DRAs were attributed to a fall (n = 18; 27.7%). A fall-related principal diagnosis was independently associated with a DRA (odds ratio 20.11; 95% CI, 5.60-72.24). CONCLUSION: The adjusted Kramer algorithm demonstrated a higher positive agreement with expert consensus in assessing DRA causality in geriatric inpatients compared to the Naranjo algorithm. Our results further support implementation of the adjusted Kramer algorithm as part of a standardized DRA assessment in older adults.

Introduction to Bayesian statistics: a practical framework for clinical pharmacists.

OBJECTIVES: Most pharmaceutical investigations have relied on p values to infer conclusions from their study findings. Central to this paradigm is the concept of null hypothesis significance testing. This approach is however fraught with overuse and misinterpretations. Several alternatives have already been proposed, yet uptake remains low. In this study, we aimed to discuss the pitfalls of p value-based testing and to provide readers with the basics to apply Bayesian statistics. METHODS: Jeffreys's Amazing Statistical Package (JASP) was used to evaluate the effect of a clinical pharmacy (CP) intervention (opposed to usual care) on the number of emergency department (ED) visits without hospital admission. Basic Bayesian terminology was explained and compared with classical p value-based testing. In the study example, a Cauchy prior distribution was used to determine the effect size with a scale parameter r=0.707 at location=0 and Bayes factors (BF) were subsequently estimated. A robustness analysis was then performed to visualise the impact of different r values on the BF value. RESULTS: A BF of 4.082 was determined, indicating that the observed data were about four times more likely to occur under the alternative hypothesis that the CP intervention was effective. The median effect size of the CP intervention on ED visits was found to be 0.337 with a 95% credible interval of 0.074 to 0.635. A robustness check was performed and all BF values were in favour of the CP intervention. CONCLUSION: Bayesian inference can be an important addition to the statistical armamentarium of pharmacists, who should become more acquainted with the basic terminology and rationale of such testing. To prove our point, Jeffreys' approach was applied to a CP study example, using an easy-to-use software program JASP.