cohort (p=0.273). Patients were classified into three risk categories (high, medium and low) and had the following rates of risk: 11.1% (0-6 points), 20.0% (8-13 points) and 39.5% (>13 points). Findings were similar in the validation cohort. The optimal cutoff point in the model was 9, having a sensitive of 67.09%, a specificity of 69.06%, a positive predictive value of 36.78%, and a negative predictive value of 87.61%. Conclusion and relevance This score could be used by clinicians from the ED to identify those patients at high risk of 30 day revisits, and could be useful to design specific interventions at discharge in this group of patients.

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Aim and objectives The objective of this study was to perform a preliminary pharmacokinetic (PK) model of adalimumab to evaluate covariates potentially responsible for the PK variability in paediatric patients with IBD. Material and methods A 3 year retrospective multicentre study was performed including children and adolescent (£ 18 years) diagnosed with IBD and treated with adalimumab. Demographic and clinical data were collected, including serum albumin, C reactive protein and faecal calprotectin. Pre-dose serum samples were carried out before administration. Adalimumab concentrations and anti-adalimumab antibodies (AAA) were determined by ELISA. The model was developed in NONMEM V.7.4 by approximating the non-linear mixed effects models. The first order conditional estimation method with interaction (FOCEI) was used for model building. Concentrations below the lower limit of quantification (LLOQ) were set to LLOQ/2. Body weight (WGT) was included in the PK parameters following an allometric relationship. Results Twenty-three paediatric patients (10 women) were included, 3 were diagnosed with ulcerative colitis and 20 with Crohn disease. Median age (range) was 14.0 (5-18) years and weight 55.9 (20.4-80) kg. A total of 75 concentrations (2< LLOQ) were determined, with a medium concentration of 10.72 (0.1-24.7) mg/mL. Median (range) serum albumin level was 4.0 (2.8-5.0) g/dL. Only one patient developed AAA. Population PK model (PopPK): a one compartment with first order absorption and elimination described adequately the serum adalimumab concentration-time data. The absorption rate constant was fixed (Ka=0.008/hour) according to Sharma et al. Among the clinical variables analysed, only albumin was significant on the apparent clearance (CL/F). The final PopPK model in the absence of AAA was as defined as: V/ F=11.30×(WGT/56 kg) and CL/F (L/day)=0.42×(albumin/4 g/ dL)-2.32 × (WGT/56 kg) 0.75. Covariate analysis reduced the interindividual variability associated with CL (IIVCL) from 34.1% to 21.3%. Proportional residual error estimated was 28.4%. Conclusion and relevance Adalimumab PK in paediatric patients with IBD was best described by a one compartment model with first order absorption and elimination. WGT was included in the PK parameters following an allometric relationship. Albumin showed statistically significant differences on adalimumab CL/F, explaining 62.5% of its variability.

methods A preliminary risk analysis was chosen to carry out the risk mapping. The working group included a doctor, a pharmacist, a nurse, a PT, a health framework and a manager responsible for risk management. Results The risk mapping concerned the stages of preparation and delivery of drugs. The initial criticalities of the scenarios were distributed as follows: 46.5% unacceptable (C1), 37.2% tolerable under control (C2) and 16.3% unacceptable (C3). After the implementation of corrective actions, the residual criticalities were distributed as follows: 97.7% C1 criticality and 2.3% C2 criticality. Ten corrective actions were identified by the working group, for example, the computerisation of prescriptions and the over-labelling of non-unit drug blisters. Conclusion and relevanceThe preparation step is considered more risky. For the preparation stage 76% of the scenarios were classified as very vulnerable versus 58% for the delivery stage. The realisation of the risk mapping of drug management at prison made it possible to identify the potential dangers. The weekly nominative automated preparation of drugs by the pharmacy represents a major challenge.