BackgroundAlthough the weaning classification based on the difficulty and duration of the weaning process has been evaluated in the different type of intensive care units (ICUs), little is known about clinical outcomes and validity among the three groups in medical ICU. The objectives of this study were to evaluate the clinical relevance of weaning classification and its association with hospital mortality in a medical ICU with a protocol-based weaning program.MethodsAll consecutive patients admitted to the medical ICU and requiring mechanical ventilation (MV) for more than 24 hours were prospectively registered and screened for weaning readiness by a standardized weaning program between July 2010 and June 2013. Baseline characteristics and outcomes were compared across weaning classifications.ResultsDuring the study period, a total of 680 patients were weaned according to the standardized weaning protocol. Of these, 457 (67%) were classified as simple weaning, 136 (20%) as difficult weaning, and 87 (13%) as prolonged weaning. Ventilator-free days within 28 days decreased significantly from simple to difficult to prolonged weaning groups (P < 0.001, test for trends). In addition, reintubation within 48 hours after extubation (P < 0.001) and need for tracheostomy during the weaning process (P < 0.001) increased significantly across weaning groups. Finally, ICU (P < 0.001), post-ICU (P = 0.001), and hospital (P < 0.001) mortalities significantly increased across weaning groups. In a multiple logistic regression model, prolonged weaning but not difficult weaning was still independently associated with ICU (adjusted OR 8.265, 95% CI 3.484–19.605, P < 0.001), and post-ICU (adjusted OR 3.180, 95% CI 1.349–7.497, P = 0.005), and hospital (adjusted OR 5.528, 95% CI 2.801–10.910, P < 0.001) mortalities.ConclusionsWeaning classification based on the difficulty and duration of the weaning process may provide prognostic information for mechanically ventilated patients who undergo the weaning process.

17The U.S. Department of Energy Systems Biology Knowledgebase (KBase) is an open-source 18 software and data platform designed to meet the grand challenge of systems biology-19 predicting and designing biological function from the biomolecular (small scale) to the ecological 20 (large scale). KBase is available for anyone to use, and enables researchers to collaboratively 21 generate, test, compare, and share hypotheses about biological functions; perform large-scale 22 analyses on scalable computing infrastructure; and combine experimental evidence and 23conclusions that lead to accurate models of plant and microbial physiology and community 24 dynamics. The KBase platform has (1) extensible analytical capabilities that currently include 25 genome assembly, annotation, ontology assignment, comparative genomics, transcriptomics, 26 and metabolic modeling; (2) a web-browser-based user interface that supports building, sharing, 27and publishing reproducible and well-annotated analyses with integrated data; (3) access to 28 extensive computational resources; and (4) a software development kit allowing the community 29to add functionality to the system. 30

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The performances of PSI and CURB-65 for predicting 30-day mortality in patients with HCAP were comparable to those in patients with CAP. However, the discriminatory powers of PSI and CURB-65 for 30-day mortality were significantly lower in the HACP group than those in the CAP group.