ABSTRACT
The introduction of clinical information systems (CIS) in Intensive Care Units (ICUs) offers the possibility of storing a huge amount of machine-ready clinical data that can be used to improve patient outcomes and the allocation of resources, as well as suggest topics for randomized clinical trials. Clinicians, however, usually lack the necessary training for the analysis of large databases. In addition, there are issues referred to patient privacy and consent, and data quality. Multidisciplinary collaboration among clinicians, data engineers, machine-learning experts, statisticians, epidemiologists and other information scientists may overcome these problems. A multidisciplinary event (Critical Care Datathon) was held in Madrid (Spain) from 1 to 3 December 2017. Under the auspices of the Spanish Critical Care Society (SEMICYUC), the event was organized by the Massachusetts Institute of Technology (MIT) Critical Data Group (Cambridge, MA, USA), the Innovation Unit and Critical Care Department of San Carlos Clinic Hospital, and the Life Supporting Technologies group of Madrid Polytechnic University. After presentations referred to big data in the critical care environment, clinicians, data scientists and other health data science enthusiasts and lawyers worked in collaboration using an anonymized database (MIMIC III). Eight groups were formed to answer different clinical research questions elaborated prior to the meeting. The event produced analyses for the questions posed and outlined several future clinical research opportunities. Foundations were laid to enable future use of ICU databases in Spain, and a timeline was established for future meetings, as an example of how big data analysis tools have tremendous potential in our field.
Subject(s)
Big Data , Critical Care/methods , Critical Illness , Interdisciplinary Research/methods , Machine Learning , Databases, Factual , Humans , Interdisciplinary Research/organization & administration , SpainABSTRACT
BACKGROUND: Catheter suctioning of respiratory secretions in intubated subjects is limited to the proximal airway and associated with traumatic lesions to the mucosa and poor tolerance. "Mechanical insufflation-exsufflation" exerts positive pressure, followed by an abrupt drop to negative pressure. Potential advantages of this technique are aspiration of distal airway secretions, avoiding trauma, and improving tolerance. METHODS: We applied insufflation of 50 cmH2O for 3 s and exsufflation of - 45 cmH2O for 4 s in patients with an endotracheal tube or tracheostomy cannula requiring secretion suctioning. Cycles of 10 to 12 insufflations-exsufflations were performed and repeated if secretions were aspirated and visible in the proximal artificial airway. Clinical and laboratory parameters were collected before and 5 and 60 min after the procedure. Subjects were followed during their ICU stay until discharge or death. RESULTS: Mechanical insufflation-exsufflation was applied 26 times to 7 male and 6 female subjects requiring suctioning. Mean age was 62.6 ± 20 years and mean Apache II score 23.3 ± 7.4 points. At each session, a median of 2 (IQR 1; 2) cycles on median day of intubation 11.5 (IQR 6.25; 25.75) were performed. Mean insufflation tidal volume was 1043.6 ± 649.9 ml. No statistically significant differences were identified between baseline and post-procedure time points. Barotrauma, desaturation, atelectasis, hemoptysis, or other airway complication and hemodynamic complications were not detected. All, except one, of the mechanical insufflation-exsufflation sessions were productive, showing secretions in the proximal artificial airway, and were well tolerated. CONCLUSIONS: Our preliminary data suggest that mechanical insufflation-exsufflation may be safe and effective in patients with artificial airway. Safety and efficacy need to be confirmed in larger studies with different patient populations. TRIAL REGISTRATION: EudraCT 2017-005201-13 (EU Clinical Trials Register).
