Critical care medicine
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Critical care medicine · Jun 2018
Comparative StudyLactate Level Versus Lactate Clearance for Predicting Mortality in Patients With Septic Shock Defined by Sepsis-3.
This study aimed to compare the prognostic value of lactate level and lactate clearance at 6 hours after septic shock recognition. And, we performed it to determine lactate kinetics in the Sepsis-3 defined septic shock. ⋯ Our findings indicate lactate and lactate clearance are both useful targets in patients with septic shock defined by Sepsis-3. Serum lactate level at 6-hour can be an easier and more effective tool for prognosis of septic shock patients who were treated with protocol-driven resuscitation bundle therapy.
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Critical care medicine · Jun 2018
Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters.
To find and validate generalizable sepsis subtypes using data-driven clustering. ⋯ The three sepsis subtypes may represent a unifying framework for understanding the molecular heterogeneity of the sepsis syndrome. Further study could potentially enable a precision medicine approach of matching novel immunomodulatory therapies with septic patients most likely to benefit.
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Critical care medicine · Jun 2018
Presepsin and Inflammatory Markers Correlate With Occurrence and Severity of Nonocclusive Mesenteric Ischemia After Cardiovascular Surgery.
To prospectively evaluate the relationship of established inflammatory markers and presepsin on nonocclusive mesenteric ischemia and to correlate presepsin levels to the occurrence and severity of nonocclusive mesenteric ischemia. ⋯ Elevated postoperative plasma presepsin concentrations are an independent predictor of mild and severe nonocclusive mesenteric ischemia. The established inflammatory blood markers significantly correlate with the development and severity of nonocclusive mesenteric ischemia.
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Critical care medicine · Jun 2018
Survival and Safety Outcomes of ICU Patients Discharged Directly Home-A Direct From ICU Sent Home Study.
Evaluate outcomes (mortality, morbidity, unplanned return visits) of patients who are discharged directly to home from the ICU. ⋯ Recruited discharged directly to home patients experienced very good 8-week postdischarge outcomes with 0% mortality and a low rate of ICU readmission (1%) or ward readmission (4%), but not an insignificant rate of emergency department visits (18%). Recruited discharged directly to home patients had better outcomes compared with nonrecruited discharged directly to home patients and patients transferred briefly to the ward prior to discharge home. Future work should include derivation of a clinical prediction tool to identify patient characteristics that make discharged directly to home safe and a randomized control trial to compare discharged directly to home with short stay ward transfers.
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Critical care medicine · Jun 2018
Development and Evaluation of an Automated Machine Learning Algorithm for In-Hospital Mortality Risk Adjustment Among Critical Care Patients.
Risk adjustment algorithms for ICU mortality are necessary for measuring and improving ICU performance. Existing risk adjustment algorithms are not widely adopted. Key barriers to adoption include licensing and implementation costs as well as labor costs associated with human-intensive data collection. Widespread adoption of electronic health records makes automated risk adjustment feasible. Using modern machine learning methods and open source tools, we developed and evaluated a retrospective risk adjustment algorithm for in-hospital mortality among ICU patients. The Risk of Inpatient Death score can be fully automated and is reliant upon data elements that are generated in the course of usual hospital processes. ⋯ Low adoption of ICU mortality risk adjustment algorithms impedes progress toward increasing the value of the healthcare delivered in ICUs. The Risk of Inpatient Death score has many attractive attributes that address the key barriers to adoption of ICU risk adjustment algorithms and performs comparably to existing human-intensive algorithms. Automated risk adjustment algorithms have the potential to obviate known barriers to adoption such as cost-prohibitive licensing fees and significant direct labor costs. Further evaluation is needed to ensure that the level of performance observed in this study could be achieved at independent sites.