Publications by authors named "K L Delucchi"
Article Synopsis
- Automated analysis of lung CT scans can help classify different subphenotypes of acute respiratory illness in COVID-19 patients by combining CT features with clinical and lab data.
- A study of 559 spontaneously breathing COVID-19 patients identified two subphenotypes: one with older patients, higher inflammation, more severe hypoxemia, and a higher mortality rate, while the other had distinct lung imaging features and lower mortality.
- The findings emphasize the potential of using machine learning and lung-CT imaging to improve the understanding and treatment of respiratory failure in COVID-19 patients.
Background: Recent insights into substance use cessation suggest that outcomes short of long-term abstinence are clinically meaningful and may offer more realistic incremental goals, particularly for highly vulnerable individuals. With the goal of informing tobacco treatment programs, we examined distinct patterns of cigarette smoking and their association with the ongoing use of other substances in women who experience housing instability.
Methods: We recruited participants from a longitudinal study of women experiencing housing instability.
Background: Hypoinflammatory and hyperinflammatory phenotypes have been identified in both Acute Respiratory Distress Syndrome (ARDS) and sepsis. Attributable mortality of ARDS in each phenotype of sepsis is yet to be determined. We aimed to estimate the population attributable fraction of death from ARDS (PAF) in hypoinflammatory and hyperinflammatory sepsis, and to determine the primary cause of death within each phenotype.
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