The effect of MySleeve on fluid restriction adherence in hemodialysis patients

In hemodialysis patients, non-adherence to fluid restriction is associated with high interdialytic weight gain (IDWG) and adverse outcomes. Monitoring drinkingbehaviour and direct feedback to the patient can lead to better adherence. We developed the MySleeve, a device that can be wrapped around a drinking glass to monitor fluid intake throughout the day. The MySleeve will also provide a subtle vibration on the glass when the amount drunk exceeds target. The information about drinking behaviour can be found in the accompanying application on a mobile phone. In this study, we investigate the effect of direct feedback and information to the patient on fluid restriction adherence, measured by the IDW

Contextualized Drug–Drug Interaction Management Improves Clinical Utility Compared With Basic Drug–Drug Interaction Management in Hospitalized Patients

Drug–drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy. Most DDI alerts, however, are overridden because of irrelevance for the specific patient. Basic DDI clinical decision support (CDS) systems offer limited possibilities for decreasing the number of irrelevant DDI alerts without missing relevant ones. Computerized decision tree rules were designed to context-dependently suppress irrelevant DDI alerts. A crossover study was performed to compare the clinical utility of contextualized and basic DDI management in hospitalized patients. First, a basic DDI-CDS system was used in clinical practice while contextualized DDI alerts were collected in the background. Next, this process was reversed. All medication orders (MOs) from hospitalized patients with at least one DDI alert were included. The following outcome measures were used to assess clinical utility: positive predictive value (PPV), negative predictive value (NPV), number of pharmacy interventions (PIs)/1,000 MOs, and the median time spent on DDI management/1,000 MOs. During the basic DDI management phase 1,919 MOs/day were included, triggering 220 DDI alerts/1,000 MOs; showing 57 basic DDI alerts/1,000 MOs to pharmacy staff; PPV was 2.8% with 1.6 PIs/1,000 MOs costing 37.2 minutes/1,000 MOs. No DDIs were missed by the contextualized CDS system (NPV 100%). During the contextualized DDI management phase 1,853 MOs/day were included, triggering 244 basic DDI alerts/1,000 MOs, showing 9.6 contextualized DDIs/1,000 MOs to pharmacy staff; PPV was 41.4% (P &lt; 0.01), with 4.0 PIs/1,000 MOs (P &lt; 0.01) and 13.7 minutes/1,000 MOs. The clinical utility of contextualized DDI management exceeds that of basic DDI management.</p

Contextualized Drug–Drug Interaction Management Improves Clinical Utility Compared With Basic Drug–Drug Interaction Management in Hospitalized Patients

Drug–drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy. Most DDI alerts, however, are overridden because of irrelevance for the specific patient. Basic DDI clinical decision support (CDS) systems offer limited possibilities for decreasing the number of irrelevant DDI alerts without missing relevant ones. Computerized decision tree rules were designed to context-dependently suppress irrelevant DDI alerts. A crossover study was performed to compare the clinical utility of contextualized and basic DDI management in hospitalized patients. First, a basic DDI-CDS system was used in clinical practice while contextualized DDI alerts were collected in the background. Next, this process was reversed. All medication orders (MOs) from hospitalized patients with at least one DDI alert were included. The following outcome measures were used to assess clinical utility: positive predictive value (PPV), negative predictive value (NPV), number of pharmacy interventions (PIs)/1,000 MOs, and the median time spent on DDI management/1,000 MOs. During the basic DDI management phase 1,919 MOs/day were included, triggering 220 DDI alerts/1,000 MOs; showing 57 basic DDI alerts/1,000 MOs to pharmacy staff; PPV was 2.8% with 1.6 PIs/1,000 MOs costing 37.2 minutes/1,000 MOs. No DDIs were missed by the contextualized CDS system (NPV 100%). During the contextualized DDI management phase 1,853 MOs/day were included, triggering 244 basic DDI alerts/1,000 MOs, showing 9.6 contextualized DDIs/1,000 MOs to pharmacy staff; PPV was 41.4% (P &lt; 0.01), with 4.0 PIs/1,000 MOs (P &lt; 0.01) and 13.7 minutes/1,000 MOs. The clinical utility of contextualized DDI management exceeds that of basic DDI management.</p

Contextualized Drug–Drug Interaction Management Improves Clinical Utility Compared With Basic Drug–Drug Interaction Management in Hospitalized Patients

Drug–drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy. Most DDI alerts, however, are overridden because of irrelevance for the specific patient. Basic DDI clinical decision support (CDS) systems offer limited possibilities for decreasing the number of irrelevant DDI alerts without missing relevant ones. Computerized decision tree rules were designed to context-dependently suppress irrelevant DDI alerts. A crossover study was performed to compare the clinical utility of contextualized and basic DDI management in hospitalized patients. First, a basic DDI-CDS system was used in clinical practice while contextualized DDI alerts were collected in the background. Next, this process was reversed. All medication orders (MOs) from hospitalized patients with at least one DDI alert were included. The following outcome measures were used to assess clinical utility: positive predictive value (PPV), negative predictive value (NPV), number of pharmacy interventions (PIs)/1,000 MOs, and the median time spent on DDI management/1,000 MOs. During the basic DDI management phase 1,919 MOs/day were included, triggering 220 DDI alerts/1,000 MOs; showing 57 basic DDI alerts/1,000 MOs to pharmacy staff; PPV was 2.8% with 1.6 PIs/1,000 MOs costing 37.2 minutes/1,000 MOs. No DDIs were missed by the contextualized CDS system (NPV 100%). During the contextualized DDI management phase 1,853 MOs/day were included, triggering 244 basic DDI alerts/1,000 MOs, showing 9.6 contextualized DDIs/1,000 MOs to pharmacy staff; PPV was 41.4% (P < 0.01), with 4.0 PIs/1,000 MOs (P < 0.01) and 13.7 minutes/1,000 MOs. The clinical utility of contextualized DDI management exceeds that of basic DDI management

Fusarium: more than a node or a foot-shaped basal cell

Recent publications have argued that there are potentially serious consequences for researchers in recognising distinct genera in the terminal fusarioid clade of the family Nectriaceae. Thus, an alternate hypothesis, namely a very broad concept of the genus Fusarium was proposed. In doing so, however, a significant body of data that supports distinct genera in Nectriaceae based on morphology, biology, and phylogeny is disregarded. A DNA phylogeny based on 19 orthologous protein-coding genes was presented to support a very broad concept of Fusarium at the F1 node in Nectriaceae. Here, we demonstrate that re-analyses of this dataset show that all 19 genes support the F3 node that represents Fusarium sensu stricto as defined by F. sambucinum (sexual morph synonym Gibberella pulicaris). The backbone of the phylogeny is resolved by the concatenated alignment, but only six of the 19 genes fully support the F1 node, representing the broad circumscription of Fusarium. Furthermore, a re-analysis of the concatenated dataset revealed alternate topologies in different phylogenetic algorithms, highlighting the deep divergence and unresolved placement of various Nectriaceae lineages proposed as members of Fusarium. Species of Fusarium s. str. are characterised by Gibberella sexual morphs, asexual morphs with thin- or thick-walled macroconidia that have variously shaped apical and basal cells, and trichothecene mycotoxin production, which separates them from other fusarioid genera. Here we show that the Wollenweber concept of Fusarium presently accounts for 20 segregate genera with clear-cut synapomorphic traits, and that fusarioid macroconidia represent a character that has been gained or lost multiple times throughout Nectriaceae. Thus, the very broad circumscription of Fusarium is blurry and without apparent synapomorphies, and does not include all genera with fusarium-like macroconidia, which are spread throughout Nectriaceae (e.g., Cosmosporella, Macroconia, Microcera). In this study four new genera are introduced, along with 18 new species and 16 new combinations. These names convey information about relationships, morphology, and ecological preference that would otherwise be lost in a broader definition of Fusarium. To assist users to correctly identify fusarioid genera and species, we introduce a new online identification database, Fusarioid-ID, accessible at www.fusarium.org. The database comprises partial sequences from multiple genes commonly used to identify fusarioid taxa (act1, CaM, his3, rpb1, rpb2, tef1, tub2, ITS, and LSU). In this paper, we also present a nomenclator of names that have been introduced in Fusarium up to January 2021 as well as their current status, types, and diagnostic DNA barcode data. In this study, researchers from 46 countries, representing taxonomists, plant pathologists, medical mycologists, quarantine officials, regulatory agencies, and students, strongly support the application and use of a more precisely delimited Fusarium (= Gibberella) concept to accommodate taxa from the robust monophyletic node F3 on the basis of a well-defined and unique combination of morphological and biochemical features. This F3 node includes, among others, species of the F. fujikuroi, F. incarnatum-equiseti, F. oxysporum, and F. sambucinum species complexes, but not species of Bisifusarium [F. dimerum species complex (SC)], Cyanonectria (F. buxicola SC), Geejayessia (F. staphyleae SC), Neocosmospora (F. solani SC) or Rectifusarium (F. ventricosum SC). The present study represents the first step to generating a new online monograph of Fusarium and allied fusarioid genera (www.fusarium.org)

Clinical rule-guided pharmacists' intervention in hospitalized patients with hypokalaemia: A time series analysis

What is known and objective: Physicians’ response to moderate and severe hypokalaemia in hospitalized patients is frequently suboptimal, leading to increased risk of cardiac arrhythmias and sudden death. While actively alerting physicians on all critical care values using telephone or electronic pop-ups can improve response, it can also lead to alert fatigue and frustration due to non-specific and overdue alerts. Therefore, a new method was tested. A clinical rule built into a clinical decision support system (CDSS) generated alerts for patients with a serum potassium level (SPL) 18 years with SPL <2.9 mmol/L measured at least 24 hours after hospitalization in whom no potassium supplementation was initiated within 4 hours after measurement and normalization of SPL was not achieved within these 4 hours were included. Haemodialysis patients were excluded. The percentage of hypokalaemic patients with a subsequent prescription for potassium supplementation, time to subsequent potassium supplementation prescription, the percentage of patients who achieved normokalaemia (SPL ≥ 3.0 mmol/L), time to achieve normokalaemia and total duration of hospitalization were compared. Results and discussion: A total of 693 patients were included, of whom 278 participated in the intervention phase. The percentage of patients prescribed supplementation as well as time to prescription improved from 76.0% in 31.1 hours to 92.0% in 11.3 hours (P <.01). Time to achieve SPL ≥3.0 mmol/L improved, P <.009. No changes, however, were observed in the percentage of patients who achieved normokalaemia or time to reach normokalaemia, 87.5% in 65.2 hours pre-intervention compared to 90.2% (P =.69) in 64.0 hours (P =.71) in the intervention group. A non-significant decrease of 8.2 days was observed in the duration of hospitalization: 25.4 compared to 17.2 days (P =.29). What is new and conclusion: Combining CDSS alerting with a pharmacist evaluation is an effective method to improve response rate, time to supplementation and time to initial improvement, defined as SPL ≥3.0 mmol/L. However, it showed no significant effect on the percentage of patients achieving normokalaemia, time to normokalaemia or hospitalization. The discrepancy between rapid supplementation and improvement on the one hand and failure to improve time to normokalaemia on the other warrants further study

Clinical rule-guided pharmacists' intervention in hospitalized patients with hypokalaemia: A time series analysis

What is known and objective: Physicians’ response to moderate and severe hypokalaemia in hospitalized patients is frequently suboptimal, leading to increased risk of cardiac arrhythmias and sudden death. While actively alerting physicians on all critical care values using telephone or electronic pop-ups can improve response, it can also lead to alert fatigue and frustration due to non-specific and overdue alerts. Therefore, a new method was tested. A clinical rule built into a clinical decision support system (CDSS) generated alerts for patients with a serum potassium level (SPL) 18 years with SPL <2.9 mmol/L measured at least 24 hours after hospitalization in whom no potassium supplementation was initiated within 4 hours after measurement and normalization of SPL was not achieved within these 4 hours were included. Haemodialysis patients were excluded. The percentage of hypokalaemic patients with a subsequent prescription for potassium supplementation, time to subsequent potassium supplementation prescription, the percentage of patients who achieved normokalaemia (SPL ≥ 3.0 mmol/L), time to achieve normokalaemia and total duration of hospitalization were compared. Results and discussion: A total of 693 patients were included, of whom 278 participated in the intervention phase. The percentage of patients prescribed supplementation as well as time to prescription improved from 76.0% in 31.1 hours to 92.0% in 11.3 hours (P <.01). Time to achieve SPL ≥3.0 mmol/L improved, P <.009. No changes, however, were observed in the percentage of patients who achieved normokalaemia or time to reach normokalaemia, 87.5% in 65.2 hours pre-intervention compared to 90.2% (P =.69) in 64.0 hours (P =.71) in the intervention group. A non-significant decrease of 8.2 days was observed in the duration of hospitalization: 25.4 compared to 17.2 days (P =.29). What is new and conclusion: Combining CDSS alerting with a pharmacist evaluation is an effective method to improve response rate, time to supplementation and time to initial improvement, defined as SPL ≥3.0 mmol/L. However, it showed no significant effect on the percentage of patients achieving normokalaemia, time to normokalaemia or hospitalization. The discrepancy between rapid supplementation and improvement on the one hand and failure to improve time to normokalaemia on the other warrants further study

Systems that prevent unwanted represcription of drugs withdrawn because of adverse drug events: A systematic review

Represcription of medication that was withdrawn after the occurrence of an adverse drug event (including allergy), is a recognized medication safety issue on a patient level. We performed a systematic review to identify systems (electronic and nonelectronic) that can prevent the represcription of drugs withdrawn because of an adverse drug event and the effects of these systems. The review was performed using PRISMA and Cochrane guidelines. PubMed and Embase were searched for articles describing systems that can prevent represcription of drugs that had been withdrawn for causing an adverse drug event. Information on the characteristics of the studies, systems, and if present results achieved with such systems, was extracted. The results showed that of 6793 articles screened, 137 full-text articles were assessed for eligibility. A total of 45 studies describing 33 systems (28 electronic) were included. The five nonelectronic systems used allergy bracelets or allergy labels on hospital medical records or on drug orders. Systems differed in the way adverse drug events were documented and how users were alerted to drug represcription. Most systems functioned within a specific healthcare setting. Of 12 studies that compared pre- and post-intervention periods or wards with and without intervention, 7 showed a reduction in represcription after adverse drug event. In conclusion, several systems have been developed that can prevent the represcription of drugs that elicited an adverse drug event, but the evidence that these systems are effective is limited