Apotheek Haagse Ziekenhuizen

This prospective study in 13 Dutch ICUs aims to determine the burden of dyspnea and its association with weaning outcomes in tracheostomized patients weaning from invasive mechanical ventilation (IMV). Dyspnea was evaluated daily in 156 communicative adults (no delirium and RASS between -2 and +2) during the first 28 days of tracheostomized weaning. Main endpoints were the number of days with dyspnea and dyspnea severity on a visual analog scale (D-VAS). Associations between dyspnea and weaning outcomes were analyzed with regression and joint modeling. Post-ICU quality of life and psychological sequelae were evaluated at 90 days post-ICU using validated questionnaires. The cumulative incidence of dyspnea was 3 [2, 6] days per patient, and dyspnea prevalence was 58% (<bold>Fig 1</bold>). Median D-VAS was 6 [4, 7] among patients with dyspnea. Dyspnea was associated with a lower probability of weaning success (HR 0.52, p<0.01). Of 130 (83%) patients successfully liberated from IMV, 34% had probable PTSD, 45% had anxiety, and 43% depression (<bold>Table 1</bold>). In conclusion, dyspnea was associated with longer weaning duration, unsuccessful weaning, and PTSD symptoms post-ICU. <bold>Figure 1:</bold> <fig><object-id>erj;66/suppl_69/PA3133/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig> <fig><object-id>erj;66/suppl_69/PA3133/F2</object-id><object-id>F2</object-id><object-id>F2</object-id><graphic></graphic></fig>

The goal of the study was to describe the population pharmacokinetics of trimethoprim, sulfamethoxazole, and N‐acetyl sulfamethoxazole in hospitalized patients. Furthermore, this study used the model to optimize dosing regimens of cotrimoxazole for Pneumocystis jirovecii pneumonia and in patients with renal insufficiency or with continuous renal replacement therapy (CRRT). This was a retrospective multicenter observational cohort study based on therapeutic drug monitoring (TDM) data from hospitalized patients treated with cotrimoxazole. We developed two population pharmacokinetic (POPPK) models: a model of trimethoprim and an integrated model with both sulfamethoxazole and N‐acetyl sulfamethoxazole concentrations. Monte Carlo simulations were performed to determine the optimal dosing regimen. A total of 348 measurements from 168 patients were available. The estimated glomerular filtration rate (eGFR) and CRRT were included as covariates on the clearance of all three compounds. Cotrimoxazole TID 1,920 mg and b.i.d. 2,400 mg led to sufficient exposure for infections with P. jirovecii in patients without renal insufficiency. To reach equivalent exposure, a dose reduction of 33.3% is needed in patients with an eGFR of 10 mL/minute/1.73 m2 and of 16.7% for an eGFR of 30 mL/minute/1.73 m2. N‐acetyl sulfamethoxazole accumulates in patients with a reduced eGFR. CRRT increased the clearance of sulfamethoxazole, but not trimethoprim or N‐acetyl sulfamethoxazole, compared with the median clearance in the population. Doubling the sulfamethoxazole dose is needed for patients on CRRT to reach equivalent exposure.

Heart failure (HF) is a chronic and progressive disease that often progresses to an advanced stage where conventional therapy is insufficient to relieve patients' symptoms. Despite the availability of advanced therapies such as mechanical circulatory support or heart transplantation, the complexity of defining advanced HF, which requires multiple parameters and multimodality assessment, often leads to delays in referral to dedicated specialists with the result of a worsening prognosis. In this review, we aim to explore the role of cardiac magnetic resonance (CMR) in advanced HF by showing how CMR is useful at every step in managing these patients: from diagnosis to prognostic stratification, hemodynamic evaluation, follow-up and advanced therapies such as heart transplantation. The technical challenges of scanning advanced HF patients, which often require troubleshooting of intracardiac devices and dedicated scans, will be also discussed.

ABSTRACTThe objective of this study was to describe the population pharmacokinetics of remdesivir and GS-441524 in hospitalized coronavirus disease 2019 (COVID-19) patients. A prospective observational pharmacokinetic study was performed in non-critically ill hospitalized COVID-19 patients with hypoxemia. For evaluation of the plasma concentrations of remdesivir and its metabolite GS-441524, samples were collected on the first day of therapy. A nonlinear mixed-effects model was developed to describe the pharmacokinetics and identify potential covariates that explain variability. Alternative dosing regimens were evaluated using Monte Carlo simulations. Seventeen patients were included. Remdesivir and GS-441524 pharmacokinetics were best described by a one-compartment model. The estimated glomerular filtration rate (eGFR) on GS-441524 clearance was identified as a clinically relevant covariate. The interindividual variability in clearance and volume of distribution for both remdesivir and GS-441524 was high (remdesivir, 38.9% and 47.9%, respectively; GS-441525, 47.4% and 42.9%, respectively). The estimated elimination half-life for remdesivir was 0.48 h, and that for GS-441524 was 26.6 h. The probability of target attainment (PTA) of the in vitro 50% effective concentration (EC50) for GS-441524 in plasma can be improved by shortening the dose interval of remdesivir and thereby increasing the total daily dose (PTA, 51.4% versus 94.7%). In patients with reduced renal function, the metabolite GS-441524 accumulates. A population pharmacokinetic model for remdesivir and GS-441524 in COVID-19 patients was developed. Remdesivir showed highly variable pharmacokinetics. The elimination half-life of remdesivir in COVID-19 patients is short, and the clearance of GS-441524 is dependent on the eGFR. Alternative dosing regimens aimed at optimizing the remdesivir and GS-441524 concentrations may improve the effectiveness of remdesivir treatment in COVID-19 patients.

Abstract Background For the analysis of 6-thioguanine nucleotides (6-TGN) and 6-methylmercaptopurine ribonucleotides (6-MMPR), no external quality assessment scheme (EQAS) is currently available and no quality control samples can be made because of the absence of pure substances. An experimental design is tested to compare laboratory analytical results. Methods In this EQAS, participating laboratories were asked to select patient samples from their routine analysis and exchange these with a coupled laboratory. Because of large differences in results between laboratories, all standard operating procedures were reviewed, revealing that the origin of these differences could be in the method of hydrolysis and the preparation of calibrators. To investigate the contribution of the calibrators to these differences, one participating laboratory was asked to prepare a batch of calibrators to be shipped to the participating laboratories for analysis. Results Results for 6-TGN differed more between laboratories, compared with results for 6-MMPR. For 6-TGN and 6-MMPR 43% and 24% of the results, respectively, were out of the 80%–120% range. When correcting the results from the exchange of the patient samples with the results of the calibrators, the mean absolute difference for 6-TGN improved from 24.8% to 16.3% (p&lt;0.001), while the results for 6-MMPR worsened from 17.3% to 20.0% (p=0.020). Conclusions This first EQAS for thiopurine drugs shows that there is a difference between laboratories in the analysis of 6-TGN, and to a lesser extent in the analysis of 6-MMPR. This difference for 6-TGN can partially be explained by the use of in-house-prepared calibrators that differ among the participants.

Several studies have been conducted to assess determinants affecting the performance or accuracy of self-reports. These studies are often not focused on pregnant women, or medical records were used as a data source where it is unclear if medications have been dispensed. Therefore, our objective was to evaluate the concordance between self-reported medication data and pharmacy records among pregnant women and its determinants. We conducted a population-based cohort study within the Generation R study, in 2637 pregnant women. The concordance between self-reported medication data and pharmacy records was calculated for different therapeutic classes using Yule's Y. We evaluated a number of variables as determinant of discordance between both sources through univariate and multivariate logistic regression analysis. The concordance between self-reports and pharmacy records was moderate to good for medications used for chronic conditions, such as selective serotonin reuptake inhibitors or anti-asthmatic medications (0.88 and 0.68, respectively). Medications that are used occasionally, such as antibiotics, had a lower concordance (0.51). Women with a Turkish or other non-Western background were more likely to demonstrate discordance between pharmacy records and self-reported data compared with women with a Dutch background (Turkish: odds ratio, 1.63; 95% confidence interval, 1.16-2.29; other non-Western: odds ratio, 1.33; 95% confidence interval, 1.03-1.71). Further research is needed to assess how the cultural or ethnic differences may affect the concordance or discordance between both medication sources. The results of this study showed that the use of multiple sources is needed to have a good estimation of the medication use during pregnancy.

Risks in the Making: The Mediating Role of Models in Water Management and Civil Engineering in the Netherlands. Reliance on models can make technological cultures susceptible to risks through the assumptions, uncertainties, and blind spots that may accompany modeling practices. Historian of science Peter Galison has described computer modeling practices as "trading zones", conceptual spaces in which a shared language is hammered out in an attempt to facilitate collaboration between different social groups, such as engineers and policymakers. Although such a shared language may enable collaboration between diverse groups, it may also make the relation between modeling practices and knowledge of risks less visible, since the shared language does not necessarily acknowledge how models produce knowledge about their world. In that respect, models have a 'mediating' role, since they are not straightforward representations of the world, but involve a process of translating phenomena into formalized representations that enable experimentation. Drawing on insights from Science and Technology Studies (STS) and empirical work in the domains of hydrology, hydrodynamics, geotechnical engineering, and ecology, this paper emphasizes the importance of understanding the mediating role of models in shaping the understanding that various actors hold with regard to water-related risks. Failing to appreciate the mediating role of models hampers the ability of actors to understand the assumptions, uncertainties, and blind spots that accompany simulation practices, and may put technological cultures at risk.