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OBJECTIVE: To determine the impact of point-of-care ultrasound (POCUS)-guided resuscitation on clinical outcomes in adult patients with shock. DATA SOURCE: We searched MEDLINE, Embase, and unpublished sources from inception to December 2023. STUDY SELECTION: We included randomized controlled trials (RCTs) that examined the use of POCUS to guide resuscitation in patients with shock. DATA EXTRACTION: We collected data regarding study and patient characteristics, POCUS protocol, control group interventions, and outcomes. DATA SYNTHESIS: We identified 18 eligible RCTs. POCUS slightly influences physicians' plans for IV fluid (IVF) and vasoactive medication prescription (moderate certainty), but results in little to no changes in the administration of IVF (low to high certainty) or inotropes (high certainty). POCUS may result in no change in the number of CT scans performed (low certainty) but probably reduces the number of diagnostic echocardiograms performed (moderate certainty). POCUS-guided resuscitation probably reduces 28-day mortality (relative risk [RR] 0.88; 95% CI, 0.78-0.99), the duration of vasoactive medication (mean difference -0.73 d; 95% CI, -1.16 to -0.30), and the need for renal replacement therapy (RRT) (RR 0.80; 95% CI, 0.63-1.02) (low to moderate certainty evidence), and lactate clearance (high certainty evidence). POCUS-guided resuscitation may results in little to no difference in ICU or hospital admissions, ICU and hospital length of stay, and the need for mechanical ventilation (MV) (low to moderate certainty evidence). There is an uncertain effect on the risk of acute kidney injury and the duration of MV or RRT (very low certainty evidence). CONCLUSIONS: POCUS-guided resuscitation in shock may yield important patient and health system benefits. Due to lack of sufficient evidence, we were unable to explore how the thresholds of operator competency, frequency, and timing of POCUS scans impact patient outcomes.
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BACKGROUND: Despite the high morbidity and mortality associated with sepsis, the relationship between the plasma proteome and clinical outcome is poorly understood. In this study, we used targeted plasma proteomics to identify novel biomarkers of sepsis in critically ill patients. METHODS: Blood was obtained from 15 critically ill patients with suspected/confirmed sepsis (Sepsis-3.0 criteria) on intensive care unit (ICU) Day-1 and Day-3, as well as age- and sex-matched 15 healthy control subjects. A total of 1161 plasma proteins were measured with proximal extension assays. Promising sepsis biomarkers were narrowed with machine learning and then correlated with relevant clinical and laboratory variables. RESULTS: The median age for critically ill sepsis patients was 56 (IQR 51-61) years. The median MODS and SOFA values were 7 (IQR 5.0-8.0) and 7 (IQR 5.0-9.0) on ICU Day-1, and 4 (IQR 3.5-7.0) and 6 (IQR 3.5-7.0) on ICU Day-3, respectively. Targeted proteomics, together with feature selection, identified the leading proteins that distinguished sepsis patients from healthy control subjects with ≥ 90% classification accuracy; 25 proteins on ICU Day-1 and 26 proteins on ICU Day-3 (6 proteins overlapped both ICU days; PRTN3, UPAR, GDF8, NTRK3, WFDC2 and CXCL13). Only 7 of the leading proteins changed significantly between ICU Day-1 and Day-3 (IL10, CCL23, TGFα1, ST2, VSIG4, CNTN5, and ITGAV; P < 0.01). Significant correlations were observed between a variety of patient clinical/laboratory variables and the expression of 15 proteins on ICU Day-1 and 14 proteins on ICU Day-3 (P < 0.05). CONCLUSIONS: Targeted proteomics with feature selection identified proteins altered in critically ill sepsis patients relative to healthy control subjects. Correlations between protein expression and clinical/laboratory variables were identified, each providing pathophysiological insight. Our exploratory data provide a rationale for further hypothesis-driven sepsis research.