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Objective: To compare different strategies predicting hyperkalemia (serum potassium level ≥5.5 mEq/l) in hospitalized patients for whom medications triggering potassium-increasing drug-drug interactions (DDIs) were ordered. Materials and Methods: We investigated 5 strategies that combined prediction triggered at onset of DDI versus continuous monitoring and taking into account an increasing number of patient parameters. The considered patient parameters were identified using generalized additive models, and the thresholds of the prediction strategies were calculated by applying Youden's J statistic to receiver operation characteristic curves. Half of the data served as the calibration set, half as the validation set. Results: We identified 132 incidences of hyperkalemia induced by 8413 potentially severe potassium-increasing DDIs among 76 467 patients. The positive predictive value (PPV) of those strategies predicting hyperkalemia at the onset of DDI ranged from 1.79% (undifferentiated anticipation of hyperkalemia due to the DDI) to 3.02% (additionally considering the baseline serum potassium) and 3.10% (including further patient parameters). Continuous monitoring significantly increased the PPV to 8.25% (considering the current serum potassium) and 9.34% (additional patient parameters). Conclusion: Continuous monitoring of the risk for hyperkalemia based on current potassium level shows a better predictive power than predictions triggered at the onset of DDI. This contrasts with efforts to improve DDI alerts by taking into account more patient parameters at the time of ordering.

BACKGROUND AND OBJECTIVE: Clinical decision support (CDS) might improve management of potassium-increasing drug-drug interactions (DDI). We studied CDS with five features intended to increase effectiveness: (i) focus on serious DDIs, (ii) fewer notifications, (iii) presentation of current laboratory results, (iv) timing (when adverse event becomes likelier), (v) removal of notification when appropriate. METHODS: We conducted a 1-year, hospital-wide, cluster- randomised controlled trial in the inpatient setting at a large tertiary-care academic medical centre. Three CDS types were implemented: monitoring reminders (unknown potassium, no monitoring ordered), elevated potassium warnings (≥4.9 mEq/l), and hyperkalaemia alerts (≥5.5 mEq/l). The primary endpoint was the frequency of potassium- monitoring intervals >72 h. RESULTS: We analysed 15,272 and 18,981 stays with 2804 and 2057 potassium-increasing DDIs in the intervention and control groups, respectively. Patient-specific notifications: displayed were 869 reminders (1 per 3.2 potassium- increasing DDIs), 356 warnings (1:7.9), and 62 alerts (1:45.2). Nevertheless, insufficiently monitored DDIs were not reduced (intervention 451 of 9686 intervals >72 h [4.66%]; control 249 of 6140 [4.06%]). The only secondary outcome improved was the length of potassium monitoring intervals (intervention group mean 22.9 h, control 23.7 h; p <0.001). However, in the intervention group, during 50 of 2804 observed potassium-increasing DDI periods (1.78%) one or more serum potassium values ≥ 5.5mEq/ l were measured, in the control group, during 27 of 2057 (1.31%; p = 0.20). CONCLUSIONS: A highly patient-specific CDS feature combination had a negligible impact on the management of potentially serious potassium-increasing DDIs and was unable to improve safety among hospitalised patients. Trial registration number: The study was registered at ClinicalTrials.gov (NCT02020317). Keywords: drug interactions, hyperkalaemia, potassium, medical or

Purpose: Hyperkalaemia due to potassium-increasing drug-drug interactions (DDIs) is a clinically important adverse drug event. The purpose of this study was to identify patient- and physician-related risk factors for the development of hyperkalaemia. Methods: The risk for adult patients hospitalised in the University Hospital Zurich between 1 December 2009 and 31 December 2011 of developing hyperkalaemia was correlated with patient characteristics, number, type and duration of potassium-increasing DDIs and frequency of serum potassium monitoring. Results: The 76,467 patients included in this study were prescribed 8,413 potentially severe potassium-increasing DDIs. Patient-related characteristics associated with the development of hyperkalaemia were pulmonary allograft [relative risk (RR) 5.1; p < 0.0001), impaired renal function (RR 2.7; p < 0.0001), diabetes mellitus (RR 1.6; p = 0.002) and female gender (RR 1.5; p = 0.007). Risk factors associated with medication were number of concurrently administered potassium-increasing drugs (RR 3.3 per additional drug; p < 0.0001) and longer duration of the DDI (RR 4.9 for duration ≥6days; p < 0.0001). Physician-related factors associated with the development of hyperkalaemia were undetermined or elevated serum potassium level before treatment initiation (RR 2.2; p < 0.001) and infrequent monitoring of serum potassium during a DDI (interval >48h: RR 1.6; p < 0.01). Conclusion: Strategies for reducing the risk of hyperkalaemia during potassium-increasing DDIs should consider both patient- and physician-related risk factors.

The anticonidial activity of human monocytes deactivated by cytokines interleukin (IL)-4 and IL-10 and the hormone dexamethasone was studied and compared with antilisterial activity. Dexamethasone had the largest effect on the anticonidial activity and suppressed germination-inhibiting activity and elimination of ingested spores by macrophages more than the cytokines did. Maximally active concentrations of IL-10 had a similar but significantly smaller deactivating effect. IL-4, in contrast to IL-10 and dexamethasone, did not reduce anticonidial activity. However, IL-4 and IL-10 were equally potent in deactivating human macrophages against Listeria monocytogenes, whereas dexamethasone was significantly less potent in the Listeria model. These observations indicate that all three mediators lessen antimicrobial activity but that this effect depends on the test organism studied and is apparently mediated through regulation of different antimicrobial systems operating against a particular microorganism