Critical care medicine
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Critical care medicine · Oct 2017
Multicenter Study Comparative StudyCritically Ill Patients With the Middle East Respiratory Syndrome: A Multicenter Retrospective Cohort Study.
To describe patient characteristics, clinical manifestations, disease course including viral replication patterns, and outcomes of critically ill patients with severe acute respiratory infection from the Middle East respiratory syndrome and to compare these features with patients with severe acute respiratory infection due to other etiologies. ⋯ Substantial overlap exists in the clinical presentation and comorbidities among patients with Middle East respiratory syndrome severe acute respiratory infection from other etiologies; therefore, a high index of suspicion combined with diagnostic testing is essential component of severe acute respiratory infection investigation for at-risk patients. The lack of distinguishing clinical features, the need to rely on real-time reverse transcription polymerase chain reaction from respiratory samples, variability in viral shedding duration, lack of effective therapy, and high mortality represent substantial clinical challenges and help guide ongoing clinical research efforts.
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Critical care medicine · Oct 2017
Neurobiologic Correlates of Attention and Memory Deficits Following Critical Illness in Early Life.
Survivors of critical illness in early life are at risk of long-term-memory and attention impairments. However, their neurobiologic substrates remain largely unknown. ⋯ Our findings indicate specific neurobiologic correlates of attention and memory deficits in school-age survivors of neonatal extracorporeal membrane oxygenation and congenital diaphragmatic hernia. A better understanding of the neurobiology following critical illness, both in early and in adult life, may lead to earlier identification of patients at risk for impaired neuropsychological outcome with the use of neurobiologic markers.
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Critical care medicine · Oct 2017
Observational StudyPatterns and Outcomes Associated With Timeliness of Initial Crystalloid Resuscitation in a Prospective Sepsis and Septic Shock Cohort.
The objectives of this study were to 1) assess patterns of early crystalloid resuscitation provided to sepsis and septic shock patients at initial presentation and 2) determine the association between time to initial crystalloid resuscitation with hospital mortality, mechanical ventilation, ICU utilization, and length of stay. ⋯ Crystalloid was initiated significantly later with comorbid heart failure and renal failure, with absence of fever or hypotension, and in inpatient-presenting sepsis. Earlier crystalloid initiation was associated with decreased mortality. Comorbidities and severity did not modify this effect.
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Sepsis hospitalizations are frequently followed by hospital readmissions, often for recurrent sepsis. However, it is unclear how often sepsis readmissions are for relapsed/recrudescent versus new infections. The aim of this study was to assess the extent to which 90-day readmissions for recurrent sepsis are due to infection of the same site and same pathogen as the initial episode. ⋯ Of the patients readmitted with sepsis within 90 days, two thirds had infection at the same site as their initial admission. Just 19% had infection confirmed to be from the same site and organism as the initial sepsis hospitalization. Half of readmissions were definitively for new infections, whereas an additional 34% were unclear since cultures were negative in one of the hospitalizations.
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Critical care medicine · Oct 2017
Identifying Distinct Subgroups of ICU Patients: A Machine Learning Approach.
Identifying subgroups of ICU patients with similar clinical needs and trajectories may provide a framework for more efficient ICU care through the design of care platforms tailored around patients' shared needs. However, objective methods for identifying these ICU patient subgroups are lacking. We used a machine learning approach to empirically identify ICU patient subgroups through clustering analysis and evaluate whether these groups might represent appropriate targets for care redesign efforts. ⋯ A machine learning approach revealed important differences between empirically derived subgroups of ICU patients that are not typically revealed by admitting diagnosis or severity of illness alone. Similar data-driven approaches may provide a framework for future organizational innovations in ICU care tailored around patients' shared needs.