Detecting of a Patient's Condition From Clinical Narratives Using Natural Language Representation

The rapid progress in clinical data management systems and artificial intelligence approaches enable the era of personalized medicine. Intensive care units (ICUs) are the ideal clinical research environment for such development because they collect many clinical data and are highly computerized environments. We designed a retrospective clinical study on a prospective ICU database using clinical natural language to help in the early diagnosis of heart failure in critically ill children. The methodology consisted of empirical experiments of a learning algorithm to learn the hidden interpretation and presentation of the French clinical note data. This study included 1386 patients' clinical notes with 5444 single lines of notes. There were 1941 positive cases (36 % of total) and 3503 negative cases classified by two independent physicians using a standardized approach. The multilayer perceptron neural network outperforms other discriminative and generative classifiers. Consequently, the proposed framework yields an overall classification performance with 89 % accuracy, 88 % recall, and 89 % precision. Furthermore, a generative autoencoder learning algorithm was proposed to leverage the sparsity reduction that achieved 91% accuracy, 91% recall, and 91% precision. This study successfully applied learning representation and machine learning algorithms to detect heart failure from clinical natural language in a single French institution. Further work is needed to use the same methodology in other institutions and other languages.Comment: Submitting to IEEE Transactions on Biomedical Engineering. arXiv admin note: text overlap with arXiv:2104.0393

Head and thorax elevation prevents the rise of intracranial pressure during extracorporeal resuscitation in swine

Aim: Head and thorax elevation during cardiopulmonary resuscitation improves cerebral hemodynamics and ultimate neurological outcome after cardiac arrest. Its effect during extracorporeal cardiopulmonary resuscitation (E-CPR) is unknown. We tested whether this procedure could improve hemodynamics in swine treated by E-CPR. Methods and Results: Pigs were anesthetized and submitted to 15 minutes of untreated ventricular fibrillation followed by E-CPR. Animals randomly remained in flat position (flat group) or underwent head and thorax elevation since E-CPR institution (head-up group). Electric shocks were delivered after 30 minutes until the return of spontaneous circulation (ROSC). They were followed during 120 minutes after ROSC. After 30 minutes of E-CPR, ROSC was achieved in all animals, with no difference regarding blood pressure, heart rate, and extracorporeal membrane of oxygenation flow among groups. The head-up group had an attenuated increase in ICP as compared with the flat group after cardiac arrest (13 ± 1 vs. 26 ± 2 mm Hg at the end of the follow-up, respectively). Cerebral perfusion pressure tended to be higher in the head-up versus flat group despite not achieving statistical difference (66 ± 1 vs 46 ± 1 mm Hg at the end of the follow-up). Carotid blood flow and cerebral oxygen saturation were not significantly different among groups. Conclusion: During E-CPR, head and thorax elevation prevents ICP increase. Whether it could improve the ultimate neurological outcome in this situation deserves further investigation.The study was supported by grants LIVE-RESP and AREG-SHOCK from Agence Nationale pour la Recherche. Y. Levy was supported by ADEREMVeterinari

Executive Summary of the Second International Guidelines for the Diagnosis and Management of Pediatric Acute Respiratory Distress Syndrome (PALICC-2)

OBJECTIVES: We sought to update our 2015 work in the Second Pediatric Acute Lung Injury Consensus Conference (PALICC-2) guidelines for the diagnosis and management of pediatric acute respiratory distress syndrome (PARDS), considering new evidence and topic areas that were not previously addressed. DESIGN: International consensus conference series involving 52 multidisciplinary international content experts in PARDS and four methodology experts from 15 countries, using consensus conference methodology, and implementation science. SETTING: Not applicable. PATIENTS: Patients with or at risk for PARDS. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Eleven subgroups conducted systematic or scoping reviews addressing 11 topic areas: 1) definition, incidence, and epidemiology; 2) pathobiology, severity, and risk stratification; 3) ventilatory support; 4) pulmonary-specific ancillary treatment; 5) nonpulmonary treatment; 6) monitoring; 7) noninvasive respiratory support; 8) extracorporeal support; 9) morbidity and long-term outcomes; 10) clinical informatics and data science; and 11) resource-limited settings. The search included MEDLINE, EMBASE, and CINAHL Complete (EBSCOhost) and was updated in March 2022. Grading of Recommendations, Assessment, Development, and Evaluation methodology was used to summarize evidence and develop the recommendations, which were discussed and voted on by all PALICC-2 experts. There were 146 recommendations and statements, including: 34 recommendations for clinical practice; 112 consensus-based statements with 18 on PARDS definition, 55 on good practice, seven on policy, and 32 on research. All recommendations and statements had agreement greater than 80%. CONCLUSIONS: PALICC-2 recommendations and consensus-based statements should facilitate the implementation and adherence to the best clinical practice in patients with PARDS. These results will also inform the development of future programs of research that are crucially needed to provide stronger evidence to guide the pediatric critical care teams managing these patients.</p

Planck pre-launch status : The Planck mission

Peer reviewe

Detection of nitrogen flow condensation onset in a hypersonic wind tunnel using a static pressure probe

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Experimental Characterization of Hypersonic Nozzle Boundary Layers and Free-Stream Noise Levels

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Design of static pressure probes for improved free-stream characterization in hypersonic wind tunnels

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