Changes in inpatient medicine prescribing during COVID-19 lockdown.

BACKGROUND: New Zealand went into lockdown March 2020 successfully eliminating the circulation of the coronavirus disease 2019 (COVID-19) virus. During lockdown there were reduced rates of respiratory infections and hospital admission numbers were low. At the time, rumours of benefit and harm of medicines for COVID-19 were widespread in the lay and medical media. AIM: To describe changes in inpatient prescribing in an acute general medicine service during the New Zealand COVID-19 lockdown in 2020. METHODS: Rates of prescribing of medicines during the 33 days of lockdown were compared with a 33-day control period before lockdown. Prescriptions, patients and bed days were calculated from the hospital patient administration and electronic prescribing and administration systems. RESULTS: In the general medicine service, acute admissions were 20% lower during lockdown (from 1216 pre-lockdown to 974). There was a small decrease in the rate of prescriptions per patient (10.1 vs 10.4, P = 0.01) during lockdown, and the average length of stay was shorter (3.2 vs 3.6 days). Nebulised administration decreased by 75% (1.3% vs 5.3% of admissions) but unexpectedly there was no change in the prescribing rates of antibacterial medicines, e.g. amoxicillin (26% vs 26%). There were no changes in rates of prescribing of medicines being rumoured to potentially improve (e.g. hydroxychloroquine) or worsen (e.g. angiotensin-converting enzyme inhibitors) COVID-19 outcomes. CONCLUSIONS: Acute medical admissions decreased 20% during lockdown for COVID-19, with a proportional decrease in prescriptions. Reduced rates of respiratory tract infections did not lead to decreased prescribing of antibacterial medicines. Rumour-based prescribing did not eventuate.

Drug metabolism in severe chronic obstructive pulmonary disease: A phenotyping cocktail study.

AIMS: To evaluate the effect of severe chronic obstructive pulmonary disease (COPD) on drug metabolism by comparing the pharmacokinetics of patients with severe COPD with healthy volunteers and using the modified Inje drug cocktail. METHODS: This was a single-centre pharmacokinetic study with 12 healthy participants and 7 participants with GOLD D COPD. Midazolam 1 mg, dextromethorphan 30 mg, losartan 25 mg, omeprazole 20 mg, caffeine 130 mg and paracetamol 1000 mg were simultaneously administered and intensive pharmacokinetic sampling was conducted over 8 hours. Drug metabolism by CYP3A4, CYP2D6, CYP2C9, CYP2C19, CYP1A2, UGT1A6 and UGT1A9 in participants with COPD were compared with phenotypes in healthy controls. RESULTS: The oral clearance (95% confidence interval) in participants with COPD relative to controls was: midazolam 63% (60-67%); dextromethorphan 72% (40-103%); losartan 53% (52-55%); omeprazole 35% (31-39%); caffeine 52% (50-53%); and paracetamol 73% (72-74%). There was a 5-fold increase in AUC for omeprazole and approximately 2-fold increases for caffeine, losartan, dextromethorphan, and midazolam. The AUC of paracetamol, which is mostly glucuronidated, was increased by about 60%. CONCLUSION: Severe COPD is associated with a clinically significant reduction in oral drug clearance. This may be greater for cytochrome P450 substrates than for glucuronidated drugs. This supports reduced starting doses when prescribing for patients with severe COPD.

The pharmacokinetics of metformin in patients receiving intermittent haemodialysis.

The aims of this study were to characterise the population pharmacokinetics of metformin in patients receiving haemodialysis, and to determine the doses that will maintain median metformin plasma concentrations below 5 mg L-1 for a typical individual. Metformin plasma concentrations from 5 patients receiving thrice weekly intermittent haemodialysis followed by metformin 500 mg postdialysis were fitted to a published pharmacokinetic model. Additional models to describe the dialytic pharmacokinetics of metformin were explored. Doses of 250 and 500 postdialysis were simulated from the model for a typical haemodialysis patient. The published 2-compartment pharmacokinetic model with an additional parameter to describe haemodialysis clearance provided a reasonable fit to the data. Deterministic simulations from the model for a typical individual suggest that metformin doses of 250-500 mg postdialysis and 250 mg given once daily should maintain median metformin plasma concentrations below 5 mg L-1 .

Routine Therapeutic Drug Monitoring of Dabigatran: Experience at a Tertiary Center.

BACKGROUND: A liquid chromatography-mass spectrometry assay to determine plasma dabigatran concentrations has been available for routine clinical use at our tertiary institutions since 2017. The aim of the study was to describe (1) the use of the assay over time; (2) the indications for testing; and (3) subsequent dabigatran prescribing decisions. METHODS: Patients for whom dabigatran concentrations were measured were identified using the laboratory database, and clinical data were extracted from the associated electronic health records. RESULTS: There were 233 samples in 24 months. The use of dabigatran increased over time, with a mean (95% confidence interval) increase of +0.5 (0.3-0.7) samples per month. Dabigatran concentrations ranged from <1 to 1060 mcg/L. The main reasons for testing were uncertainty about impact on renal function and drug interactions (39%), to inform prescribing decisions after thromboembolic or bleeding events (21%), and for investigation following dose-adjustment (16%). Dabigatran dose was changed after 30% (68/233) of assay results. CONCLUSIONS: The clinical use of the dabigatran assay has increased, with almost one-third of results associated with a subsequent change in dabigatran prescribing.

Clinical decision support in a hospital electronic prescribing system informed by local data: experience at a tertiary New Zealand centre.

BACKGROUND: An electronic prescribing and administration (ePA) system has been progressively rolled out to Canterbury District Health Board (CDHB, Christchurch, New Zealand) public hospitals since 2014, and is currently used for around 1300 tertiary beds. ePA data can be used to monitor user behaviour, and to evaluate and inform the local customisation of clinical decision support (CDS) tools within the ePA system. AIMS: To describe retrospectively illustrative vignettes of CDHB ePA analyses that have been used for CDS. METHODS: Alerts were developed according to a set of common principles agreed upon by the CDHB CDS Working Group. Alerts were informed and evaluated by extracting and parsing data for various time periods during 2016 to 2018 from the CDHB ePA database. RESULTS: There was a median of 74 000 prescriptions a month. After examining 525 spironolactone prescriptions, the high dose alert threshold was set at 100 mg with an expected alert burden of 3%. The presence of a ceftriaxone shortage prescribing alert for 1 week was associated with a prescribing rate that was lower than 95% of the preceding 52 weeks. Following review of 367 fentanyl patch alerts, revision of the alert led to false positives falling from 43% to 3% (P < 0.0001). At the point of firing, 6% of antithrombotic drug interactions alerts led to immediate changes in prescriptions (94% overridden), and a further 22% were changed within 30 min after the alert. CONCLUSIONS: Local data extracts from ePA systems can inform iterative configuration of the software and monitor user behaviour.

A population pharmacokinetic model to predict oxypurinol exposure in patients on haemodialysis.

PURPOSE: The aims of this study were to characterise the population pharmacokinetics of oxypurinol in patients receiving haemodialysis and to compare oxypurinol exposure in dialysis and non-dialysis patients. METHODS: Oxypurinol plasma concentrations from 6 gout people receiving haemodialysis and 19 people with gout not receiving dialysis were used to develop a population pharmacokinetic model in NONMEM. Deterministic simulations were used to predict the steady-state area under the oxypurinol plasma concentration time curve over 1 week (AUC7days). RESULTS: The pharmacokinetics of oxypurinol were best described by a one-compartment model with a separate parameter for dialytic clearance. Allopurinol 100 mg daily produced an AUC7days of 279 µmol/L h in dialysis patients, a value 50-75 % lower than the AUC7days predicted for patients with normal renal function taking 200 to 400 mg daily (427-855 µmol/L h). Dosing pre-dialysis resulted in about a 25-35 % reduction in exposure compared to post-dialysis. CONCLUSIONS: Oxypurinol is efficiently removed by dialysis. The population dialytic and total (non-dialytic) clearance of oxypurinol were found to be 8.23 and 1.23 L/h, standardised to a fat-free mass of 70 kg and creatinine clearance of 6 L/h, respectively. Our results suggest that if the combination of low-dose allopurinol and haemodialysis does not result in sustained urate lowering below treatment targets (serum urate ≤0.36 mmol/L), then allopurinol doses may be increased to optimise oxypurinol exposure.

Warfarin resistance associated with genetic polymorphism of VKORC1: linking clinical response to molecular mechanism using computational modeling.

The variable response to warfarin treatment often has a genetic basis. A protein homology model of human vitamin K epoxide reductase, subunit 1 (VKORC1), was generated to elucidate the mechanism of warfarin resistance observed in a patient with the Val66Met mutation. The VKORC1 homology model comprises four transmembrane (TM) helical domains and a half helical lid domain. Cys132 and Cys135, located in the N-terminal end of TM-4, are linked through a disulfide bond. Two distinct binding sites for warfarin were identified. Site-1, which binds vitamin K epoxide (KO) in a catalytically favorable orientation, shows higher affinity for S-warfarin compared with R-warfarin. Site-2, positioned in the domain occupied by the hydrophobic tail of KO, binds both warfarin enantiomers with similar affinity. Displacement of Arg37 occurs in the Val66Met mutant, blocking access of warfarin (but not KO) to Site-1, consistent with clinical observation of warfarin resistance.

Antimicrobial Treatment Options for Granulomatous Mastitis Caused by Corynebacterium Species.

Corynebacterium species are increasingly recognized as important pathogens in granulomatous mastitis. Currently, there are no published treatment protocols for Corynebacterium breast infections. This study describes antimicrobial treatment options in the context of other management strategies used for granulomatous mastitis. Corynebacterium spp. isolated from breast tissue and aspirate samples stored from 2002 to 2013 were identified and determined to the species level using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), 16S RNA sequencing, and rpoB gene targets. The MICs for 12 antimicrobials were performed using Etest for each isolate. Correlations of these with antimicrobial characteristics, choice of antimicrobial, and disease outcome were evaluated. Corynebacterium spp. from breast tissue and aspirate samples were confirmed in 17 isolates from 16 patients. Based on EUCAST breakpoints, Corynebacterium kroppenstedtii isolates (n = 11) were susceptible to seven antibiotic classes but resistant to ß-lactam antibiotics. Corynebacterium tuberculostearicum isolates (n = 4) were multidrug resistant. Two nonlipophilic species were isolated, Corynebacterium glucuronolyticum and Corynebacterium freneyi, both of which have various susceptibilities to antimicrobial agents. Short-course antimicrobial therapy was common (median, 6 courses per subject; range, 1 to 9 courses). Patients with C. kroppenstedtii presented with a hot painful breast mass and underwent multiple surgical procedures (median, 4 procedures; range, 2 to 6 procedures). The management of Corynebacterium breast infections requires a multidisciplinary approach and includes culture and appropriate sensitivity testing to guide antimicrobial therapy. Established infections have a poor outcome, possibly because adequate concentrations of some drugs will be difficult to achieve in lipophilic granulomata. Lipophilic antimicrobial therapy may offer a therapeutic advantage. The role of immunotherapy has not been defined.

A proposal for dose-adjustment of dabigatran etexilate in atrial fibrillation guided by thrombin time.

Dabigatran is an oral anticoagulant that is increasingly used for atrial fibrillation (AF). Presently, many authorities state that routine laboratory coagulation monitoring is not required. However, data have recently been published demonstrating that higher trough plasma dabigatran concentrations are associated with lower thromboembolic and higher haemorrhagic event rates. Using these data, we simulate a range of AF patients with varying risks for these events and derive a target range of trough plasma dabigatran concentrations (30-130 µg l(-1) ). Finally, we propose that a conventional screening coagulation assay, the thrombin time (TT), can be used to discern whether or not patients are within this range of dabigatran concentrations.

Evaluation of felodipine as a potential perpetrator of pharmacokinetic drug-drug interactions.

OBJECTIVE: To evaluate felodipine as a potential perpetrator of pharmacokinetic drug-drug interactions (PK-DDIs) involving cytochrome P450 (CYP) enzymes and P-glycoprotein (P-gp). METHODS: Felodipine extended-release 10 mg was administered daily to six healthy subjects for 7 days (days 1-7). Subjects were administered a modified Inje cocktail comprising the selective probe substrates caffeine 100 mg (CYP1A2), losartan 25 mg (CYP2C9), omeprazole 20 mg (CYP2C19), dextromethorphan 30 mg (CYP2D6), midazolam 2 mg (CYP3A) and digoxin 250 µg (P-gp) on day 0 (prior to felodipine exposure) and day 7 (after felodipine exposure). Plasma samples were collected over 24 h and drug concentrations measured by UPLC-MS/MS. RESULTS: The geometric means of the area under the plasma concentration-time curve ratios (probe AUC after felodipine exposure/probe AUC prior to felodipine exposure) and 95% confidence intervals for each probe were: caffeine 0.91 (0.64-1.30), losartan 1.05 (0.95-1.15), omeprazole 1.17 (0.78-1.76), dextromethorphan 1.46 (1.00-2.12), midazolam 1.23 (0.99-1.52) and digoxin 1.01 (0.89-1.15). CONCLUSION: Felodipine may be a weak in vivo inhibitor of CYP3A and CYP2D6 but is unlikely to act as a significant perpetrator of PK-DDIs.

Predicted metabolic drug clearance with increasing adult age.

AIM: To determine the effect of increasing adult age on predicted metabolic drug clearance. METHOD: Predicted metabolic drug clearances (CLPT ) were determined using in vitro-in vivo extrapolation coupled with physiological-based pharmacokinetic modelling and simulation (IVIVE-PBPK) in Simcyp®. Simulations were conducted using CYP-selective 'probe' drugs with subjects in 5 year age groups (20-25 to 90-95 years). CLPT values were compared with human pharmacokinetic data stratified according to age (young = 20-40 years and elderly = 65-85 years) and gender. Age-related changes in the physiological parameters used for IVIVE of CLPT were described. RESULTS: Predicted metabolic drug clearances decreased with increasing adult age to approximately 65-70 years: caffeine from 1.5 to 1.0 ml min(-1) kg(-1) (a 33% decrease), S-warfarin from 0.100 to 0.064 ml min(-1) kg(-1) (36%), S-mephenytoin from 4.1 to 2.5 ml min(-1) kg(-1) (39%), desipramine from 10.6 to 7.3 ml min(-1) kg(-1) (31%) and midazolam from 5.4 to 3.9 ml min(-1) kg(-1) (27%). Except for S-mephenytoin, predictions were within 3.5-fold of clearances from clinical studies when stratified by age and gender. A trend towards higher CLPT was observed in females, but this was only statistically significant in larger virtual trials. Physiological parameters that determine CLPT decreased with increasing adult age: mean microsomal protein g(-1) of liver, liver weight, hepatic blood flow and human serum albumin concentration. CONCLUSION: Decreased metabolic clearance in the elderly was predicted by Simcyp® and was generally consistent with limited clinical data for four out of five drugs studied and the broader literature for drugs metabolized by CYP enzymes. IVIVE-PBPK may be increasingly useful in predicting metabolic drug clearance in the elderly.

Mass or molar? Recommendations for reporting concentrations of therapeutic drugs.

A working party (WP) from the Australasian Association of Clinical Biochemists, Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists, Royal College of Pathologists of Australasia and Royal Australasian College of Physicians recommends the following: *mass units should be used for reporting therapeutic drug concentrations in Australia and New Zealand; and the litre (L) should be used as the denominator when expressing concentration. Examples of these units are mg/L and µg/L Exceptions to these principles include: *drugs for which there is current uniformity of reporting and supporting information using molar units, notably lithium (mmol/L) and methotrexate (µmol/L); *drugs that are also present as endogenous substances, where the units used routinely should continue to be used. This applies to many substances, including minerals (eg, iron; µmol/L), vitamins (eg, vitamin D; nmol/L) and hormones (eg, thyroxine; pmol/L). *drugs for which the denominator is not a 198 of fluid and there is international uniformity of reporting (eg, thiopurine metabolites; per 109 red blood cells). These recommendations relate to drugs that are used therapeutically, whether measured for therapeutic drug monitoring purposes or for assessment of overdose. Other substances, such as drugs of misuse, heavy metals or environmental toxins, were not considered by the WP and are thus not covered by this document. These recommendations should also be applied to other supporting documentation such as published guidelines, journal articles and websites. The implementation of these recommendations in New Zealand is subject to local confirmation.

Chronic kidney disease and automatic reporting of estimated glomerular filtration rate: new developments and revised recommendations.

The publication of the Australasian Creatinine Consensus Working Group's position statements in 2005 and 2007 resulted in automatic reporting of estimated glomerular filtration rate (eGFR) with requests for serum creatinine concentration in adults, facilitated the unification of units of measurement for creatinine and eGFR, and promoted the standardisation of assays. New advancements and continuing debate led the Australasian Creatinine Consensus Working Group to reconvene in 2010. The working group recommends that the method of calculating eGFR should be changed to the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula, and that all laboratories should report eGFR values as a precise figure to at least 90 mL/min/1.73 m(2). Age-related decision points for eGFR in adults are not recommended, as although an eGFR < 60 mL/min/1.73 m(2) is very common in older people, it is nevertheless predictive of significantly increased risks of adverse clinical outcomes, and should not be considered a normal part of ageing.If using eGFR for drug dosing, body size should be considered, in addition to referring to the approved product information. For drugs with a narrow therapeutic index, therapeutic drug monitoring or a valid marker of drug effect should be used to individualise dosing. The CKD-EPI formula has been validated as a tool to estimate GFR in some populations of non-European ancestry living in Western countries. Pending publication of validation studies, the working group also recommends that Australasian laboratories continue to automatically report eGFR in Aboriginal and Torres Strait Islander peoples. The working group concluded that routine calculation of eGFR is not recommended in children and youth, or in pregnant women. Serum creatinine concentration (preferably using an enzymatic assay for paediatric patients) should remain as the standard test for kidney function in these populations.

BICEPP: an example-based statistical text mining method for predicting the binary characteristics of drugs.

BACKGROUND: The identification of drug characteristics is a clinically important task, but it requires much expert knowledge and consumes substantial resources. We have developed a statistical text-mining approach (BInary Characteristics Extractor and biomedical Properties Predictor: BICEPP) to help experts screen drugs that may have important clinical characteristics of interest. RESULTS: BICEPP first retrieves MEDLINE abstracts containing drug names, then selects tokens that best predict the list of drugs which represents the characteristic of interest. Machine learning is then used to classify drugs using a document frequency-based measure. Evaluation experiments were performed to validate BICEPP's performance on 484 characteristics of 857 drugs, identified from the Australian Medicines Handbook (AMH) and the PharmacoKinetic Interaction Screening (PKIS) database. Stratified cross-validations revealed that BICEPP was able to classify drugs into all 20 major therapeutic classes (100%) and 157 (of 197) minor drug classes (80%) with areas under the receiver operating characteristic curve (AUC) > 0.80. Similarly, AUC > 0.80 could be obtained in the classification of 173 (of 238) adverse events (73%), up to 12 (of 15) groups of clinically significant cytochrome P450 enzyme (CYP) inducers or inhibitors (80%), and up to 11 (of 14) groups of narrow therapeutic index drugs (79%). Interestingly, it was observed that the keywords used to describe a drug characteristic were not necessarily the most predictive ones for the classification task. CONCLUSIONS: BICEPP has sufficient classification power to automatically distinguish a wide range of clinical properties of drugs. This may be used in pharmacovigilance applications to assist with rapid screening of large drug databases to identify important characteristics for further evaluation.

Perpetrators of pharmacokinetic drug-drug interactions arising from altered cytochrome P450 activity: a criteria-based assessment.

AIMS: To catalogue the perpetrators of CYP-mediated pharmacokinetic drug-drug interactions (PK-DDIs) using clinically relevant criteria, and to compare this with an analogous catalogue. METHODS: Candidate inhibitors and inducers of CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A ('perpetrators') were evaluated using published clinical pharmacokinetic interaction studies. Studies were selected on the basis of ≥six human subjects, use of a validated in vivo probe substrate for the CYP enzyme, and clinically relevant dosing. Inhibitors were described according to the FDA classifications of strong, moderate or weak, whereas inducers were classified as major (≥twofold decrease in AUC) or weak (

Detecting undiagnosed diabetes using glycated haemoglobin: an automated screening test in hospitalised patients.

OBJECTIVE: To assess the utility of glycated haemoglobin (HbA(1c)) level as an automated screening test for undiagnosed diabetes among hospitalised patients and to estimate the prevalence of undiagnosed diabetes among hospitalised patients. DESIGN, PARTICIPANTS AND SETTING: A 3-month prospective study of all adult patients admitted to a tertiary hospital. An HbA(1c) test was automatically undertaken on admission for all patients with a random plasma glucose (RPG) level ≥ 5.5 mmol/L. Demographic, admission and biochemical data were obtained from hospital databases. A subset of patients was recruited for an oral glucose tolerance test (OGTT) after discharge. MAIN OUTCOME MEASURES: Prevalence of undiagnosed diabetes (defined as HbA(1c) ≥ 6.5% in accordance with International Expert Committee and American Diabetes Association recommendations) and utility of automated HbA(1c) testing. RESULTS: The prevalence of undiagnosed diabetes was 11% (95% CI, 9.8%-12.4%) (262/2360) during the study period. A further 312 patients with known diabetes were admitted. The prevalence of undiagnosed diabetes was highest in the 65-74-years age group. The HbA(1c) test cost was $152 per new diagnosis of diabetes. Conservatively assuming an annual incidence of undiagnosed diabetes of 0.8%, the ongoing cost of testing hospitalised patients would be $2100 per new diagnosis of diabetes. RPG testing was not sensitive or specific in diagnosing diabetes. Patients were poorly compliant with the post-discharge OGTT (27% completion rate). CONCLUSIONS: HbA(1c) is a simple, inexpensive screening test that can be automated using existing clinical blood samples. Hospital screening for diabetes needs to be coupled with resources for management in the community.

Influence of serum inflammatory cytokines on cytochrome P450 drug metabolising activity during breast cancer chemotherapy: a patient feasibility study.

Individual response to chemotherapy in patients with breast cancer is variable. Obesity and exercise are associated with better and worse outcomes, respectively, and it is known that both impact the systemic cytokine milieu. Cytochrome P450 (CYP) enzymes are responsible for the metabolism of many chemotherapy agents, and CYP enzyme activity has been shown to be modified by inflammatory cytokines in vitro and in vivo. Cytokine-associated changes in CYP metabolism may alter chemotherapy exposure, potentially affecting treatment response and patient survival. Therefore, better understanding of these biological relationships is required. This exploratory single arm open label trial investigated changes in in vivo CYP activity in twelve women treated for stage II or III breast cancer, and demonstrated for the first time the feasibility and safety of utilising the Inje phenotyping cocktail to measure CYP activity in cancer patients receiving chemotherapy. Relative CYP activity varied between participants, particularly for CYP2C9 and CYP2D6, and changes in serum concentrations of the inflammatory cytokine monocyte chemoattractant protein 1 inversely correlated to CYP3A4 activity during chemotherapy. Future use of phenotyping cocktails in a clinical oncology setting may help guide drug dosing and improve chemotherapy outcomes.Clinical Trial Registration: Trial was retrospectively registered to the Australia New Zealand Clinical Trial Registry (ANZCTR). ACTRN12620000832976, 21 Aug 2020, https://www.anzctr.org.au/ACTRN12620000832976.aspx .

A persuasive approach to antimicrobial stewardship in Christchurch hospitals produced a sustained decrease in intravenous clarithromycin dosing and expenditure via a switch to azithromycin orally.

AIMS: To assess a persuasive multimodel approach to decreasing unnecessary intravenous (IV) clarithromycin use for community-acquired pneumonia (CAP) in Canterbury District Health Board (CDHB) hospitals. METHODS: In December 2013, CDHB guidelines for empiric treatment of CAP changed to prioritise oral azithromycin over IV clarithromycin. The multimodel approach we used to implement this change included obtaining stakeholder agreement, improved guidelines access, education and pharmacist support. The impact of the intervention was evaluated by comparing macrolide usage and expenditure for the four years pre- and post-intervention. RESULTS: Mean annual clarithromycin IV use decreased by 72% from 6.4 to 1.8 defined daily doses (DDDs) per 1,000 occupied bed days (OBDs) post-intervention, while oral azithromycin increased by 833% (4.2 to 39.2 DDDs per 1,000 OBDs). Concurrently, oral clarithromycin use decreased by 91% (32.9 to 2.9 DDDs per 1,000 OBDs), and roxithromycin by 71% (17.0 to 5.0 DDDs per 1,000 OBDs). Mean annual total macrolide use decreased by 21% (68.2 to 53.9 DDDs per 1,000 OBDs), while expenditure decreased by 69% mainly through avoided IV administration. CONCLUSIONS: A persuasive multimodel approach to support adoption of CAP guidelines produced a sustained decrease in IV clarithromycin use, which may have clinical benefits such as reduced occurrence of catheter-related complications.

Metformin increases plasma ghrelin in Type 2 diabetes.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: * Metformin, unlike the other major antihyperglycaemic drugs, is not associated with weight gain. * Ghrelin is an appetite-stimulating hormone whose concentrations vary in relation to food, obesity and diabetes control. * Reports are conflicting about how metformin affects ghrelin concentrations, and this study was aimed at resolving this issue in patients with Type 2 diabetes. WHAT THIS STUDY ADDS: * In this study an increase in ghrelin concentrations was seen in response to metformin treatment in patients with Type 2 diabetes. * This effect was opposite to what might be expected if the effect of metformin on weight control was mediated via suppression of ghrelin. * It is likely that the ghrelin response was secondary to improved glycaemic control. * Meal time changes in appetite and satiety did not correlate with changes in ghrelin, which suggests ghrelin may not be important in meal initiation. AIMS: Metformin treatment of Type 2 diabetes is not usually associated with weight gain, and may assist with weight reduction. Plasma ghrelin concentrations are inversely associated with obesity and food intake. Metformin might therefore affect ghrelin concentrations, although previous studies have shown variable results in this regard. The primary aim of this study was to determine the effect of metformin on plasma ghrelin, appetite and satiety in patients with Type 2 diabetes. METHODS: Eighteen patients with Type 2 diabetes were studied before and after 6 weeks of metformin treatment, which was titrated to 1 g b.d. On the study days patients were fed standard meals of 390 kcal at 08.00 and 12.30 h, plasma samples were collected at 15- and 30-min intervals, and appetite and satiety were measured on visual analogue scales. Changes in the area under the concentration-time curves (AUCs) of plasma ghrelin, insulin, glucose, appetite and satiety were assessed and examined for correlations with metformin AUCs. Changes in fasting adiponectin and leptin were also measured. RESULTS: Treatment with metformin increased the mean AUC (07.30-16.30 h) of plasma ghrelin by 24% (P= 0.003), while decreasing those of glucose by 19% (P < 0.001) and insulin by 19% (P= 0.001). No changes were detected in hunger and satiety, or in fasting adiponectin or leptin concentrations. There were no clear correlations between metformin plasma concentrations (AUC) and changes in plasma glucose, insulin or ghrelin. CONCLUSIONS: Treatment of Type 2 diabetes with metformin was associated with increased plasma ghrelin concentrations, without associated changes in hunger and satiety.