Performance of the Manchester Triage System in Adult Medical Emergency Patients: A Prospective Cohort Study.

BACKGROUND: Accurate initial patient triage in the emergency department (ED) is pivotal in reducing time to effective treatment by the medical team and in expediting patient flow. The Manchester Triage System (MTS) is widely implemented for this purpose. Yet the overall effectiveness of its performance remains unclear. OBJECTIVES: We investigated the ability of MTS to accurately assess high treatment priority and to predict adverse clinical outcomes in a large unselected population of medical ED patients. METHODS: We prospectively followed consecutive medical patients seeking ED care for 30 days. Triage nurses implemented MTS upon arrival of patients admitted to the ED. The primary endpoint was high initial treatment priority adjudicated by two independent physicians. Secondary endpoints were 30-day all-cause mortality, admission to the intensive care unit (ICU), and length of stay. We used regression models with area under the receiver operating characteristic curve (AUC) as a measure of discrimination. RESULTS: Of the 2407 patients, 524 (21.8%) included patients (60.5 years, 55.7% males) who were classified as high treatment priority; 3.9% (n = 93) were transferred to the ICU; and 5.7% (n = 136) died. The initial MTS showed fair prognostic accuracy in predicting treatment priority (AUC 0.71) and ICU admission (AUC 0.68), but not in predicting mortality (AUC 0.55). Results were robust across most predefined subgroups, including patients diagnosed with infections, or cardiovascular or gastrointestinal diseases. In the subgroup of neurological symptoms and disorders, the MTS showed the best performance. CONCLUSION: The MTS showed fair performance in predicting high treatment priority and adverse clinical outcomes across different medical ED patient populations. Future research should focus on further refinement of the MTS so that its performance can be improved. TRIAL REGISTRATION: Clinicaltrials.gov: NCT01768494.

Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections.

Metabolic profiling through targeted quantification of a predefined subset of metabolites, performed by mass spectrometric analytical techniques, allows detailed investigation of biological pathways and thus may provide information about the interaction of different organic systems, ultimately improving understanding of disease risk and prognosis in a variety of diseases. Early risk assessment, in turn, may improve patient management in regard to cite-of-care decisions and treatment modalities. Within this review, we focus on the potential of metabolic profiling to improve our pathophysiological understanding of disease and management of patients. We focus thereby on lower respiratory tract infections (LRTI) including community-acquired pneumonia (CAP) and chronic obstructive pulmonary disease (COPD), an important disease responsible for high mortality, morbidity and costs worldwide. Observational data from numerous clinical and experimental studies have provided convincing data linking metabolic blood biomarkers such as lactate, glucose or cortisol to patient outcomes. Also, identified through metabolomic studies, novel innovative metabolic markers such as steroid hormones, biogenic amines, members of the oxidative status, sphingo- and glycerophospholipids, and trimethylamine-N-oxide (TMAO) have shown promising results. Since many uncertainties remain in predicting mortality in these patients, further prospective and retrospective observational studies are needed to uncover metabolic pathways responsible for mortality associated with LRTI. Improved understanding of outcome-specific metabolite signatures in LRTIs may optimize patient management strategies, provide potential new targets for future individual therapy, and thereby improve patients' chances for survival.