Machine learning predicts lung recruitment in acute respiratory distress syndrome using single lung CT scan

Background: To develop and validate classifier models that could be used to identify patients with a high percentage of potentially recruitable lung from readily available clinical data and from single CT scan quantitative analysis at intensive care unit admission. 221 retrospectively enrolled mechanically ventilated, sedated and paralyzed patients with acute respiratory distress syndrome (ARDS) underwent a PEEP trial at 5 and 15 cmH2O of PEEP and two lung CT scans performed at 5 and 45 cmH2O of airway pressure. Lung recruitability was defined at first as percent change in not aerated tissue between 5 and 45 cmH2O (radiologically defined; recruiters: Δ45-5non-aerated tissue > 15%) and secondly as change in PaO2 between 5 and 15 cmH2O (gas exchange-defined; recruiters: Δ15-5PaO2 > 24 mmHg). Four machine learning (ML) algorithms were evaluated as classifiers of radiologically defined and gas exchange-defined lung recruiters using different models including different variables, separately or combined, of lung mechanics, gas exchange and CT data. Results: ML algorithms based on CT scan data at 5 cmH2O classified radiologically defined lung recruiters with similar AUC as ML based on the combination of lung mechanics, gas exchange and CT data. ML algorithm based on CT scan data classified gas exchange-defined lung recruiters with the highest AUC. Conclusions: ML based on a single CT data at 5 cmH2O represented an easy-to-apply tool to classify ARDS patients in recruiters and non-recruiters according to both radiologically defined and gas exchange-defined lung recruitment within the first 48 h from the start of mechanical ventilation

Lung volume calculated from electrical impedance tomography in ICU patients at different PEEP levels

Purpose: To study and compare the relationship between end-expiratory lung volume (EELV) and changes in end-expiratory lung impedance (EELI) measured with electrical impedance tomography (EIT) at the basal part of the lung at different PEEP levels in a mixed ICU population. Methods: End-expiratory lung volume, EELI and tidal impedance variation were determined at four PEEP levels (15-10-5-0 cm H2O) in 25 ventilated ICU patients. The tidal impedance variation and tidal volume at 5 cm H2O PEEP were used to calculate change in impedance per ml; this ratio was then used to calculate change in lung volume from change in EELI. To evaluate repeatability, EELV was measured in quadruplicate in five additional patients. Results: There was a significant but relatively low correlation (r = 0.79; R2= 0.62) and moderate agreement (bias 194 ml, SD 323 ml) between ΔEELV and change in lung volume calculated from the ΔEELI. The ratio of tidal impedance variation and tidal volume differed between patients and also varied at different PEEP levels. Good agreement was found between repeated EELV measurements and washin/washout of a simulated nitrogen washout technique. Conclusion: During a PEEP trial, the assumption of a linear relationship between change in global tidal impedance and tidal volume cannot be used to calculate EELV when impedance is measured at only one thoracic level just above the diaphragm

The Italian National Register of infants with congenital hypothyroidism: twenty years of surveillance and study of congenital hypothyroidism

All the Italian Centres in charge of screening, diagnosis, and follow-up of infants with congenital hypothyroidism participate in the Italian National Registry of affected infants, which performs the nationwide surveillance of the disease. It was established in 1987 as a program of the Health Ministry and is coordinated by the Istituto Superiore di Sanità. The early diagnosis performed by the nationwide newborn screening programme, the prompt treatment and the appropriate clinical management of the patients carried out by the Follow-up Centres, and the surveillance of the disease performed by the National Register of infants with congenital hypothyroidism are the components of an integrated approach to the disease which has been successfully established in our country

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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