Articles: sepsis.
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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 (PAFARDS) in hypoinflammatory and hyperinflammatory sepsis, and to determine the primary cause of death within each phenotype. ⋯ The PAFARDS is modest in both phenotypes whereas primary cause of death among patients with sepsis differed substantially by phenotype. This study identifies challenges in powering future clinical trials to detect changes in mortality outcomes among patients with sepsis and ARDS.
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Current classification for acute kidney injury (AKI) in critically ill patients with sepsis relies only on its severity-measured by maximum creatinine which overlooks inherent complexities and longitudinal evaluation of this heterogenous syndrome. The role of classification of AKI based on early creatinine trajectories is unclear. ⋯ These 8 classes of AKI in critically ill patients with sepsis, stratified by early creatinine trajectories, were good predictors for key outcomes in patients with AKI in critically ill patients with sepsis independent of their AKI staging.
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Sepsis occurs in 12-27% of patients with haematological malignancy within a year of diagnosis. Sepsis mortality has improved in non-cancer patients in the last two decades, but longitudinal trends in patients with haematological malignancy are not well characterised. We aimed to compare outcomes, including temporal changes, in patients with and without a haematological malignancy admitted to ICU with a primary diagnosis of sepsis in Australia and New Zealand over the past two decades. ⋯ Sepsis mortality has improved in patients with haematological malignancy admitted to ICU. However, mortality remains higher in patients with haematological malignancy than those without.
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J. Korean Med. Sci. · May 2024
Rapid Direct Identification of Microbial Pathogens and Antimicrobial Resistance Genes in Positive Blood Cultures Using a Fully Automated Multiplex PCR Assay.
This study assessed the performance of the BioFire Blood Culture Identification 2 (BCID2) panel in identifying microorganisms and antimicrobial resistance (AMR) profiles in positive blood cultures (BCs) and its influence on turnaround time (TAT) compared with conventional culture methods. We obtained 117 positive BCs, of these, 102 (87.2%) were correctly identified using BCID2. The discordance was due to off-panel pathogens detected by culture (n = 13), and additional pathogens identified by BCID2 (n = 2). ⋯ BCID2 correctly predicted 53 (96.4%) of 55 phenotypic resistance patterns by detecting AMR genes. The TAT for BCID2 was significantly lower than that for the conventional method. BCID2 rapidly identifies pathogens and AMR genes in positive BCs.