ObjectiveThe study purpose was to assess the usefulness of echocardiographic parameters of aortic stenosis (AS) severity and left ventricular (LV) systolic function to predict mortality in AS. The main hypothesis is that parameters of LV systolic function are the most important independent predictors of mortality, whereas parameters of stenosis severity are not.Methods1065 consecutive patients with AS referred to the echocardiography laboratory and meeting the inclusion/exclusion criteria were included and followed during 5.7 years. The end points were aortic valve replacement (AVR) (n=584), composite of AVR or death (n=932), all-cause mortality (n=550) and cardiovascular mortality (n=398).ResultsThe most powerful echocardiographic predictors of valve-related events were parameters of AS severity, such as peak aortic jet velocity (VPeak), mean gradient (MG) and aortic valve area (AVA) (all p<0.001). Regarding mortality, the main predictors were LV ejection fraction (LVEF) and stroke volume index (SVi) (p<0.05). After multivariable adjustment, LVEF (p<0.001) and SVi (p=0.02) remained the only echocardiographic predictors of mortality, even after adjustment for symptomatic status. AVA was also associated with mortality, whereas VPeak and MG were not.ConclusionsThe most powerful echocardiographic predictors of mortality are low LVEF and low flow, whereas AS severity parameters predict valve-related events but not overall mortality. Hence, low flow should be integrated in the risk stratification and therapeutic decision-making in patients with AS.

Background Drug-drug interactions of current medications could increase the incidence of adverse effects.1 Adverse drug interactions are the most frequent causes of drug iatrogenicity. Their incidence is proportional to drugs number and increases with a period extension of the prescription. Purpose To determine nature and number of potential adverse drug interactions in a surgical intensive care unit (SICU). Material and methods The pharmaceutical analysis was carried out over a 6 month period from September 2016 to March 2017 and involved patients hospitalised in a SICU. Using a written document, we gather patients' personal information and drug treatments: Number of patients. The epidemiological parameters (age, sex). Average length of stay. Number of drug interactions. Drug class according to the anatomical chemical therapeutic classification (ATC). The levels of identified drug interactions are based on 'Guideline on the Investigation of Drug Interactions' edited by the French National Agency for the Safety of Medicines and Health Products (ANSM): warnings, precautions, possible adverse, contraindications. Prescriptions are analysed using: THERIAQUE®, Thesaurus ANSM 2016. Averages and percentages were calculated using Microsoft Excel 2007. Results Drug treatment of 131 patients was analysed. Forty-seven per cent were females and 53% were males, with mean age of 50.21±17.21 years. Average length of stay: 8.18±14.79 days The 131 lines of prescriptions analysed averaged 11.31±3 drugs (range: 3–20) A total of 81 drug interactions was detected, 28% (n=23) pharmacokinetic and 72% (n=58) pharmacodynamic. The drug classes: Antiinfectives for systemic use 23.53%. Nervous system 22.55% – cardiovascular system 15.69%. Alimentary tract and metabolism 15.69%. Blood and blood–forming organs 14.7%. Musculo–skeletal system 3.92% – respiratory system 2.94%. Systemic hormonal preparations, excluding sex hormones and insulins 0.98%. The levels observed were eight warnings, 34 precautions, 35 possible adverse interactions and four contraindications. The actual interactions observed were related especially to thrombocytopaenia. Conclusion It seems important to maintain the vigilance of healthcare professionals in drug interactions and to integrate this risk into the assessment of the benefit/risk balance of drug treatments. Reference and/or Acknowledgements 1. Bellmann, R. Personalised pharmacotherapy in intensive care unit patients. Med. Klin. Intensivmed. Notfallmedizin2017. No conflict of interest

Background The hospital pharmacy is in charge of providing pharmaceutical products for 1200 hospital beds dispatched across more than 46 care units. It covers a large rank of references arranged arbitrarily. This lack of standardisation in the medical devices classification can cause sudden shortages and disturbances in space management. Purpose The aim was to implement progressively a quality management system by building storage mapping related to both risk based classification of medical devices and their medical specialty panels. Material and methods The superficies of storage stores were calculated through development plans. To classify and organise medical devices, two programmes were used: Microsoft Excel 2010 and ARCHICAD19. The dimensions of the secondary and tertiary packaging of each medical device, shelves and storage pallets were measured. Other parameters were also calculated: packaging volume, average monthly consumption, volume of average monthly storage and number of average monthly consumption in 1 year, and the effective storage capacity (ESC) of each storage store. Results The ESC of storage store were, respectively, 552.20 m3 for fungible, 227.68 m3 for products accessories for medicine and pharmacy (PAMP) and 38.80 m3 for surgical sutures. 14 medical specialty panels composed fungible storage store. Their distribution was as follows: Fungible 79%: Surgical panel 63%, including the following surgeries: general, thoracic, cardiovascular, surgical drainage, visceral, orthopaedic and traumatology and neurosurgery. Respiratory panel 16% Urogenital panel 6% Gastric panel 5% Parenteral panel 4% Spinal panel 1% Other accessories 5% (eg, review and monitoring–operating kits–accessories infusion and transfusion divers) PAMP 8% Surgical sutures 13%. These statistics are also converted in space occupancy percentage. Conclusion The new classification has helped to build storage mapping of medical devices, which has provided better product visual identification, has improved space management and will have a positive impact on performance indicators of the quality management system, such as decreased shortages. References and/or acknowledgements Article 4, Dahir No 1-13-90 du 22 chaoual 1434 (30August 2013) Law No. 84-12 related to devices medical. Article 7, Decree No 2-14-607 (18 September 2014) Law No. 84-12 related to devices medical. No conflict of interest

Objective Is to evaluate the nutritional status of preoperative patients in the visceral surgery department III of CHU Ibn Rushd of Casablanca and to correlate to postoperative length of stay. Patients and methods Prospective observational study of six months from February 2015 to late July 2015, in patients from being operated in the visceral surgery department II1. The nutritional status of 151 patients preoperatively was evaluated the correlation between the various diagnostic tests and clinical and biological parameters was investigated and postoperative length of stay was calculated. Results 151 patients predominantly female (72.84%1, reporting their consent, were selected for this study. 51.56% of patients had risk factors for undernutrition. The cholelithiasis was the most responded diagnosis (57.61%). The Nutritional Risk Index (NRII allowed to identify 13 low nutritional risk patients, 7 moderate-risk and 3 major risk. According to the Mini Nutritional Assessment (MNA two elderly people [over 70 years] were at risk of undernutrition and one person had a bad nutritional status. Nutritional risk stratification identified 19 patients with postoperative nutritional grade 3. The average length of stay was variable; it was not correlated with the nutritional status of patients against it is based on the type of surgery. Conclusion The risk of undernutrition was high; however, a single parameter is insufficient for the diagnosis of preoperative undernutrition, a combination of different parameters would be a more reliable method.