European journal of hospital pharmacy : science and practice最新文献

Background: Candidemia is an opportunistic infection of intensive care units (ICUs) and causes morbidity and mortality. Multiple antibiotic exposure was found to be an independent risk factor for mortality and non-albicans candidemia (NAC) in candidemia patients.

Aim: The aim of this study was to determine the relationship between antibiotics and clinical features of patients with candidemia, and to determine the independent risk factors for hospital stay >50 days, 30-day mortality in hospital, candidemia types, and septic shock in candidemia patients.

Methods: Patients were evaluated retrospectively for 5 years. A total of 148 candidemia cases were detected and included in the study. Characteristics of cases were defined and recorded. The relationship between qualitative data was determined by the χ² test. Logistic regression analysis was used to determine the independent risk factors for hospital stay >50 days, 30-day mortality in hospital, candidemia types, and septic shock in candidemia patients.

Results: The incidence of candidemia for 5 years was 4.5%. Candida parapsilosis was the most reported species with 65% (n=97). Linezolid and central venous catheters (CVC) were found to be independent risk factors for NAC. Carbapenems and cephalosporins were found in association to lower mortality. No antibiotics or characteristics were found to be independent risk factors for mortality. Some broad spectrum antibiotics and antibiotic combinations were found in relationship with hospital stay >50 days; however, none of them were found to be independent risk factors. Metisilin resistant staphylococcus aureus (MRSA) antibiotics, meropenem+linezolid piperacillin-tazobactam+fluoroquinolones and comorbidity were found in association with septic shock, although only piperacillin-tazobactam+fluoroquinolones and comorbidity were found to be independent risk factors for septic shock.

Conclusions: This study concluded that many antibiotics were safe for candidemia patients. However, clinicians should pay attention when prescribing linezolid or piperacillin-tazobactam and flouroquinolons concomitantly or sequentially for patients with candidemia risk factors.

Objective: The objective of this study was to explore factors that affect the clearance of imipenem in critically ill patients and to provide a dosing regimen for such patients.

Methods: A prospective open-label study enrolled 51 critically ill patients with sepsis. Patients were between the ages of 18 and 96. Blood samples were collected in duplicate before (0 hour) and at 0.5, 1, 1.5, 2, 3, 4, 6, and 8 hours after imipenem administration. The plasma imipenem concentration was determined by the high-performance liquid chromatography-ultraviolet detection (HPLC-UV) method. A population pharmacokinetic (PPK) model was developed using nonlinear mixed-effects modelling methods to identify covariates. Monte Carlo simulations were performed using the final PPK model to explore the effect of different dosing regimens on the probability of target attainment (PTA).

Results: The imipenem concentration data were best described by a two-compartment model. Creatinine clearance (CrCl, mL/min) was a covariate that affected central clearance (CLc). Patients were divided into four subgroups based on different CrCl rates. Monte Carlo simulations were performed to assess the PTA differences between empirical dosing regimens (0.5 g every 6 hours (q6h), 0.5 g every 8 hours (q8h), 0.5 g every 12 hours (q12h), 1 g every 6 hours (q6h), 1 g every 8 hours (q8h), and 1 g every 12 hours (q12h)) and to determine the target achievement rate covariate.

Conclusion: This study identified covariates for CLc, and the proposed final model can be used to guide clinicians administering imipenem in this particular patient population.

Gene therapy is becoming increasingly prevalent, with new gene therapy medicinal products (GTMPs) being approved for use every year. Hospital pharmacists are expected to prepare and dispense these products, but there is substantial heterogeneity in the availability of up-to-date, practical guidance at a national level in Europe. Many institutions have no or very limited experience in handling GTMPs. As such, there is a need for updated, practical guidance to aid hospital pharmacy teams in developing institutional standard operating procedures (SOPs) for the safe handling of GTMPs across the entire workflow. Here, we present the European Association of Hospital Pharmacists' updated guidance on the handling of GTMPs, developed by a team of recognised experts from around Europe. Each aspect of the GTMP handling process is addressed, including receipt and storage, dispensing and reconstitution, transportation, administration, waste disposal, decontamination of spills and accidental exposure. A series of figures are provided to aid the development of practical workflows. This guidance document is intended as a framework to help develop institutional SOPs and should always be used in conjunction with local regulations.

Objectives: Parenteral drug products should be essentially free from visible particulate contamination. To ensure this, every batch produced must be subject to a 100% visual inspection. Monograph 2.9.20 of the European Pharmacopoeia (Ph. Eur.) describes a method for visual inspection of parenteral drug units in front of a black and white panel using a white light source. Nevertheless, several Dutch compounding pharmacies rely on an alternative method for visual inspection by means of polarised light. The objective of this study was to compare the performance of both methods.

Methods: Trained technicians in three different hospitals inspected a predetermined set of samples using both methods for visual inspection of parenteral drugs.

Results: The results of this study show that the alternative method for visual inspection yields a higher recovery than the Ph. Eur. method, while no significant difference in false positive results was found.

Conclusions: Based on these findings, it can be concluded that the alternative method for visual inspection by means of polarised light can very well replace the Ph. Eur. method in pharmacy practice, provided that local validation of the alternative method is performed.

Objective: Elastomeric devices or pumps are a valuable tool to deliver outpatient parenteral therapy and have been used for administration of chemotherapy, antibiotics and pain medication. A key determinant of effective treatment is to consider the stability of medicines within these devices. It is widely known that an increase in temperature positively correlates to an increase in drug degradation. The objective of our work was to measure the temperature within soft shell elastomeric devices, under simulated outpatient treatment conditions in summer and winter months, and to determine the maximum temperature reached within these periods of use.

Methods: Thermocouples were inserted within soft shell Easypump II (B Braun Medical, Sheffield, UK) elastomeric pumps and the temperature was monitored under simulated outpatient conditions during cold and warm weather with different fill volumes. Temperature monitoring was also conducted with varying levels of insulation around the devices.

Results: Our results show that internal temperatures remained below 32°C±1°C in winter and summer months, including during times defined as a heatwave. Fill volume and ambient temperature were shown to be significant factors affecting the internal temperatures reached.

Conclusion: A soft shell Easypump II elastomeric pump, if used within its carry pouch, will maintain the internal solution below a temperature of 32°C±1°C if patients correctly adhere to handling guidance. Our results show that further improvements to the insulation material used in carry pouches can significantly restrict the rate of temperature rise within the pumps and will give more assurance in relation to preventing degradation especially considering the increases in extreme weather conditions observed in recent years due to global warming.

Objectives: Therapeutic drug monitoring is performed routinely in patients on anti-epileptic drugs (AEDs) for optimisation and individualisation of therapy. The dried blood spot (DBS) sampling technique is a suitable, more patient-friendly alternative for conventional venous sampling methods. However, before DBS can be used in routine care, data are needed to establish the correlation between standard plasma concentrations obtained from venous puncture and concentrations measured through DBS obtained by finger prick. This study aims to investigate the correlation between carbamazepine, lamotrigine and levetiracetam drug concentrations in venous blood and DBS samples in the same patients at the same time.

Methods: Clinical validation was conducted by direct comparison of paired DBS and venous plasma samples. Method agreement was evaluated using Passing-Bablok regression analysis and Bland-Altman plots to provide insight into the relationship between the two analytically validated methods. For Bland-Altman analysis the acceptance limit required by both FDA and EMA guidelines is at least two-thirds (67%) of the paired samples within 80-120% of the mean of both methods.

Results: Paired samples from 79 patients were studied. For all three AEDs, plasma and DBS concentrations correlated highly (r=0.90 for carbamazepine, r=0.93 for lamotrigine and r=0.93 for levetiracetam), indicating a linear relationship. For carbamazepine and lamotrigine, no proportional or constant bias was revealed. For levetiracetam, concentrations were higher in plasma samples than in DBS (slope 1.21), implying a conversion factor is needed. The acceptance limit was met for carbamazepine and levetiracetam with a value of 72% and 81%, respectively. For lamotrigine, this acceptance limit was not met with a value of 60%.

Conclusions: The method was successfully validated and will be used for therapeutic drug monitoring in patients using carbamazepine, lamotrigine and/or levetiracetam.

Objectives: The trough concentration of vancomycin and the area under the concentration-time curve (AUC)/minimum inhibitory concentration (MIC) ratio are crucial in determining vancomycin efficacy against methicillin-resistant Staphylococcus aureus. However, the use of similar pharmacokinetic principles in determining antibiotic efficacy against other gram-positive cocci is lacking. We performed a pharmacokinetic/pharmacodynamic analysis (association of target trough concentration values and AUC/MIC with therapeutic outcome) of vancomycin in patients with Enterococcus faecium bacteraemia.

Methods: Between January 2014 and December 2021 we performed a retrospective cohort study of patients with E. faecium bacteraemia treated with vancomycin. Patients who received renal replacement therapy or had chronic kidney disease were excluded. Clinical failure, the primary outcome, was defined as a composite of 30-day all-cause mortality, vancomycin-susceptible infection requiring change of treatment, and/or recurrence. AUC₂₄ was estimated using a Bayesian estimation approach based on an individual vancomycin trough concentration. The MIC for vancomycin was determined using a standardised agar dilution method. Additionally, classification was used to identify the vancomycin AUC₂₄/MIC ratio associated with clinical failure.

Results: Of the 151 patients identified, 69 were enrolled. All MICs of vancomycin for E. faecium were ≤1.0 µg/mL. The AUC₂₄ and AUC₂₄/MIC ratio were not significantly different between the clinical failure group and the clinical success group (432±123 µg/mL/hour vs 488±92 µg/mL/hour; p=0.075). However, 7 of 12 patients (58.3%) in the clinical failure group and 49 of 57 patients (86.0%) in the clinical success group had a vancomycin AUC₂₄/MIC ratio ≥389 (p=0.041). No significant association between trough concentration or AUC₂₄ ≥600 µg/mL×hour and acute kidney injury was observed (p=0.365 and p=0.487, respectively).

Conclusion: The AUC₂₄/MIC ratio is associated with the clinical outcome of vancomycin administration in E. faecium bacteraemia. In Japan, where vancomycin-resistant enterococcal infection is rare, empirical therapy with a target AUC₂₄ ≥389 should be recommended.

Objectives: Several drug-drug interaction (DDI) checkers such as DDI-Predictor have been developed to detect and grade DDIs. DDI-Predictor gives an estimate of the magnitude of an interaction based on the ratio of areas under the curve. The objective of the present study was to analyse the frequencies of DDIs involving well-known strong interactors such as rifampicin and selective serotonin reuptake inhibitors (SSRIs), as reported by a clinical pharmacy team using DDI-Predictor, and the pharmacist intervention acceptance rate.

Methods: The pharmacist intervention rate and the physician acceptance rate were calculated for DDIs involving rifampicin or the SSRIs fluoxetine, paroxetine, duloxetine and sertraline. The rates were compared with a bilateral χ² test or Fisher's exact test.

Results: Of the 284 DDIs recorded, 38 (13.4%) involved rifampicin and 78 (27.5%) involved SSRIs. The pharmacist intervention rate differed significantly (68.4% for rifampicin vs 48.8% for SSRIs; p=0.045) but the physician acceptance rate did not (84.6% for rifampicin vs 81.6% for SSRIs; p=1). Pharmaceutical interventions for SSRIs were more frequent when the ratio of the area under the drug concentration versus time curve in DDI-Predictor was >2. Pharmacists were more likely to issue a pharmacist intervention for DDIs involving rifampicin because of a high perceived risk of treatment failure and were less likely to issue a pharmacist intervention for DDIs involving an SSRI, except when the suspected interaction was strong.

Conclusions: DDI checkers can help pharmacists to manage DDIs involving strong interactors. DDIs involving strong inhibitors versus a strong inducer differ with regard to their intervention and acceptance rates, notably due to the estimation of the magnitude of the DDI.

Objective: To determine the pharmaceutical interventions in patients eligible for phase I cancer clinical trials, focusing specifically on exclusion criteria related to medication or relevant interactions.

Method: Descriptive, observational study conducted at a comprehensive cancer centre. Patients undergoing screening for phase I clinical trials (March 2019-December 2022) were included. The pharmacist reviewed concomitant medication and provided a recommendation.

Results: The concomitant medication of 512 patients eligible to participate in 84 phase I clinical trials was analysed. In 230 (44.9%) patients, the clinical trial treatment included oral medication. The median number of concomitant medications was 5 (IQR 3-8) per patient.A total of 280 pharmaceutical interventions were performed in 140 (27.3%) patients: 240 (85.7%) were due to interactions in 124 (24.2%) patients, and 40 (14.3%) were due to exclusion criteria in 34 (6.6%) patients. Interactions and exclusion criteria were detected in 18 (3.5%) patients. The main groups of drugs involved were 68 (24.3%) antacids and antiulcer drugs, 28 (10.0%) antidepressants and 26 (9.3%) opioids. Acceptance analysis of the recommendation was applicable in 215 cases; in 208 (96.7%), the pharmaceutical intervention was accepted.Differences were identified for exclusion criteria (7 vs 27) and interactions (37 vs 87) between parenteral and oral clinical trial medication (p<0.001).

Conclusion: The pharmacist's review of concomitant medication during the screening period in phase I clinical trials enables the detection of prohibited medication or relevant interactions, potentially avoiding screening failures and increasing the efficacy and safety of treatments.

Objectives: Pharmaceutical interventions are proposals made by hospital clinical pharmacists to address sub-optimal uses of medications during prescription review. Pharmaceutical interventions include the identification of drug-related problems, their prevention and resolution. The objective of this study was to exploit a newly developed deep neural network classifier to identify drug-related problems from pharmaceutical interventions and perform a large retrospective descriptive analysis of them in a French university hospital over a 3-year period.

Methods: Data were collected from prescription support software from 2018 to 2020. A classifier running in Python 3.8 and using Keras library was then used to automatically categorise drug-related problems from pharmaceutical interventions according to the coding of the French Society of Clinical Pharmacy.

Results: 2 930 656 prescription lines were analysed for a total of 119 689 patients. Among these prescription lines, 153 335 (5.2%) resulted in pharmaceutical interventions (n=48 202 patients; 40.2%). Pharmaceutical interventions were predominantly observed in patients aged 65 years or older (n=26 141 patients out of 53 186; 49.1%) and in patients taking five or more medications (44 702 patients out of 93 419; 47.8%). The most frequently identified types of drug-related problems associated with pharmaceutical interventions were 'Non-conformity to guidelines or contra-indication' (n=88 523; 57.7%), 'Overdosage' (16 975; 11.1%) and 'Improper administration' (13 898; 9.1%). The most frequently encountered drugs were: paracetamol (n=10 585; 6.9%), esomeprazole (6031; 3.9%), hydrochlorothiazide (2951; 1.9%), enoxaparin (2191; 1.4%), tramadol (1879; 1.2%), calcium (2073; 1.3%), perindopril (1950; 1.2%), amlodipine (1716; 1.1%), simvastatin (1560; 1.0%) and insulin (1019; 0.7%).

Conclusions: The deep neural network classifier used met the challenge of automatically classifying drug-related problems from pharmaceutical interventions from a large database without mobilising significant human resources. The use of such a classifier can lead to alerting caregivers about certain risky practices in prescription and administration, and triggering actions to improve patients' therapeutic outcomes.