I., Borobia Pérez AM., Carcas Sansuán AJ., Martí nez Ávila JC., Ramírez García E. Acute and chronic paracetamol overdose in paediatric populati on: Protocol of a prospecti ve study of cohort to evaluate clinic factor and biomarkers to predict development of hepatotoxicity. IBJ Clin Pharmacol 2017 1(1):e0007. Funding: The authors have no fi nancial relati onships relevant to this arti cle to disclose. Competi ng Interests:The authors declare no confl icts of interest. Background:In Spain, 30% of cases of acute liver failure remaining undetermined. Paracetamol is the main drug causing acute liver failure in children of some countries like the United States, UK and other European countries. The key factors to assess in paracetamol toxicity, the ingested dose and the ti me from the poisoning, are diffi cult to assess in children where accidental acute poisoning or medicati on errors are not rare. Metabolomics technology may be able to identi fy specifi c biomarkers of toxicity and adverse events in early stages. The identi fi cati on of paracetamol toxicity biomarkers could have important clinical implicati ons for pati ents who can not apply the Rumack-Matt hew nomogram and could be useful in the evaluati on of children with acute liver failure of unknown eti ology, and to predict liver damage before elevati on of transaminases. Methods and design:This is an observati onal prospecti ve study of case control. The protocol was approved by the Clinical Research Ethics Committ ee of the La Paz University Hospital. It will recruit pati ents who will be att ending in the emergency paediatric at La Paz University Hospital, at Niño Jesus University Hospital, and at Gregorio Marañón University hospital with suspected acute or chronic intake of paracetamol. Likewise, two cohorts of control will be recruited. It is expected to recruit at least 36 cases and 144 controls, matched for age and clinical characteristi cs. Peripheral blood, plasma, serum and urine samples will be collected, paracetamol serum concentrati ons, hepati c and renal functi on, coagulati on and metabolomic analysis. Discussion:It is important to determine the clinical factors and biomarkers that predict the development of hepatotoxicity in paediatric populati on following acute and chronic intake of paracetamol and develop a predicti ve model to assess the risk of hepatotoxicity in both type of intoxicati on by paracetamol suited to paediatric pati ents for use in clinical practi ce. Study registrati on: Editor: Jesús Frías IniestaCite as: Tong HY., Díaz García L., García García S., Ruiz Domínguez JA., Martí n Sánchez J., Storch de Gracias P., Rivas A., Muñoz M., Hernández Zabala R., García García I., Borobia Pérez AM., Carcas Sansuán AJ., Martí nez Ávila JC., Ramírez García E. Acute and chronic paracetamol overdose in paediatric populati on: Protocol of a prospecti ve study of cohort to evaluate clinic factor and biomarkers to predict development of hepatotoxicity. IBJ Clin Pharmacol 2017 1(1):e0007. Funding: The authors have no fi nancial relati onships...

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Conclusion FKplasm and IPV during induction are higher than in EM and LM. However, patients with CV >30% remain in the maintenance periods between 29.9% and 31.8%, and with values<5 ng/ml between 9.3% and 13.1% which would justify a greater need for pharmacokinetic monitoring and therapeutic control, in order to preserve a longer graft survival and to minimise the events of pharmacological adverse reactions.

Background: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. Methods: Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 Intensive Care Units(ICU) in Spain. The objective was to analyze patient’s factors associated with mortality risk and utilize a Machine Learning(ML) to derive clinical COVID-19 phenotypes. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. An unsupervised clustering analysis was applied to determine presence of phenotypes. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. Results: The database included a total of 2,022 patients (mean age 64[IQR5-71] years, 1423(70.4%) male, median APACHE II score (13[IQR10-17]) and SOFA score (5[IQR3-7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the C(severe) phenotype was the most common (857;42.5%) and was characterized by the interplay of older age (>65 years), high severity of illness and a higher likelihood of development shock. The A(mild) phenotype (537;26.7%) included older age (>65 years), fewer abnormal laboratory values and less development of complications and B (moderate) phenotype (623,30.8%) had similar characteristics of A phenotype but were more likely to present shock. Crude ICU mortality was 45.4%, 25.0% and 20.3% for the C, B and A phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications.Conclusion: The presented ML model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a “one-size-fits-all” model in practice. Funding: None