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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, METHODS, RESULTS. Meshes: Adult, Aged, Aged, 80 and over, Critical Illness, Health Status Indicators, Hemodynamics, Hospital Mortality, Hospitalization, Humans, Length of Stay, Logistic Models, Middle Aged, Monitoring, Physiologic, Prognosis, Respiration, Risk Assessment, Risk Factors.
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Are physiological abnormalities in early warning scores related to mortality in adult inpatients? Context: Early warning scores using physiological measurements may help identify ward patients who are, or who may become, critically ill. We studied the value of abnormal physiology scores to identify high-risk hospital patients. On a single day we recorded the following data from 433 adult non-obstetric inpatients: respiratory rate, heart rate, systolic pressure, temperature, oxygen saturation, level of consciousness, urine output for catheterized patients, age and inspired oxygen. We also noted the care required and given. Twenty-six patients (6%) died within 30 days. They were significantly older than survivors (P<0.001). Their median hospital stay was 26 days (interquartile range 16-39). Mortality increased with the number of physiological abnormalities (P<0.001), being 0.7% with no abnormalities, 4.4% with one, 9.2% with two and 21.3% with three or more. Patients receiving a lower level of care than desirable also had an increased mortality (P<0.01). Logistic regression modelling identified level of consciousness, heart rate, age, systolic pressure and respiratory rate as important variables in predicting outcome.
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Simple physiological observations identify high-risk hospital inpatients. Those who die are often inpatients for days or weeks before death, allowing time for clinicians to intervene and potentially change outcome. Access to critical care beds could decrease mortality. Final Decision: yes