BACKGROUND: Early and accurate identification of patients who may benefit from aggressive optimal medical intervention is essential if improved outcomes in terms of survival are to be achieved. We studied the usefulness of routine clinical measurements and/or markers of metabolic abnormality in the early identification of those patients at greatest risk of deterioration on presentation to the accident and emergency department. METHODS: We conducted a prospective observational study in the accident and emergency department of a 602-bed district general hospital. Routine clinical measurements (heart rate, systolic blood pressure, temperature, oxygen saturation in room air, level of consciousness and ventilatory frequency) and venous blood analysis for metabolic markers (pH, bicarbonate, standard base excess, lactate, anion gap, strong ion difference, and strong ion gap) and biochemical markers (Na+, K+, Ca2+, Cl-, PO4- albumin, urea and creatinine) were recorded from unselected consecutive hospital admissions over two 3-month periods (September-November 2002 and February-April 2003). RESULTS: Logistic regression analysis showed that neither conventional clinical measurements upon presentation to the accident and emergency department nor venous biochemical and metabolic indices have good discriminatory ability when used as single predictors of either hospital mortality or length of hospital stay. Selecting variables from all the clinical and venous blood measurements gave a parsimonious model containing only age, heart rate, phosphate and albumin (area under the receiver operating characteristic curve, 0.82 [95% CI 0.76, 0.87]). CONCLUSIONS: A combination of clinical and venous biochemical measurements in the accident and emergency department proved the best predictors of hospital mortality. Consequently, they may be helpful as a triage tool in the accident and emergency department to help identify patients at risk of deterioration.
BACKGROUND: Early and accurate identification of patients who may benefit from aggressive optimal medical intervention is essential if improved outcomes in terms of survival are to be achieved. We studied the usefulness of routine clinical measurements and/or markers of metabolic abnormality in the early identification of those patients at greatest risk of deterioration on presentation to the accident and emergency department. METHODS: We conducted a prospective observational study in the accident and emergency department of a 602-bed district general hospital. Routine clinical measurements (heart rate, systolic blood pressure, temperature, oxygen saturation in room air, level of consciousness and ventilatory frequency) and venous blood analysis for metabolic markers (pH, bicarbonate, standard base excess, lactate, anion gap, strong ion difference, and strong ion gap) and biochemical markers (Na+, K+, Ca2+, Cl-, PO4- albumin, urea and creatinine) were recorded from unselected consecutive hospital admissions over two 3-month periods (September-November 2002 and February-April 2003). RESULTS: Logistic regression analysis showed that neither conventional clinical measurements upon presentation to the accident and emergency department nor venous biochemical and metabolic indices have good discriminatory ability when used as single predictors of either hospital mortality or length of hospital stay. Selecting variables from all the clinical and venous blood measurements gave a parsimonious model containing only age, heart rate, phosphate and albumin (area under the receiver operating characteristic curve, 0.82 [95% CI 0.76, 0.87]). CONCLUSIONS: A combination of clinical and venous biochemical measurements in the accident and emergency department proved the best predictors of hospital mortality. Consequently, they may be helpful as a triage tool in the accident and emergency department to help identify patients at risk of deterioration.
Authors: Matthew M Churpek; Trevor C Yuen; Michael T Huber; Seo Young Park; Jesse B Hall; Dana P Edelson Journal: Chest Date: 2011-11-03 Impact factor: 9.410
Authors: Mohammed A Mohammed; Gavin Rudge; Duncan Watson; Gordon Wood; Gary B Smith; David R Prytherch; Alan Girling; Andrew Stevens Journal: PLoS One Date: 2013-05-29 Impact factor: 3.240
Authors: Mohammed A Mohammed; Gavin Rudge; Gordon Wood; Gary Smith; Vishal Nangalia; David Prytherch; Roger Holder; Jim Briggs Journal: PLoS One Date: 2012-10-15 Impact factor: 3.240