BACKGROUND: Emergency response systems (ERS) are based on a set of triggers used to identify patients "at risk". This study aimed to establish the association between recordings of disturbed physiological variables and adverse events. METHODS: A cross-sectional survey of 3,046 non Do Not Attempt Resuscitation (non DNAR) adult admissions in five hospitals over 14 days. Medical records were reviewed for 26 early signs (ES) and 21 late signs (LS) of critical conditions and serious adverse events (SAE): death, cardiac arrest, severe respiratory problems, or transfer to a critical care area. The LS included published medical emergency team (MET) call criteria. FINDINGS: There were 12,384 ES and 1,410 LS. The 'top five' ES and the odds (OR) for death were: base deficit -5 to -8 mmol/L=40.2 (95% C.I. 7.7-208.8), partial airway obstruction OR=38.7 (3.9-64.4), poor peripheral circulation OR=34.4 (6.8-174.0), >expected drain fluid loss OR=30.1 (6.1-148.9), pH <7.3 >7.2 OR=29.0 (3.1-268.3). For LS: urine output <200 mL in 24 h OR=188.6 (95% C.I. 30.1-1179.8), pH <7.2 OR=116.1 (7.1-1906.1), unresponsive to voice OR=34.8 (10.7-113.0), anuric OR=29.0 (3.1-268.3), base deficit <-8.0 mmol/L OR=29.0 (3.1-268.3). OR for the other SAE were similar. Pulse oximetry abnormalities were associated with all SAE. The risk for death for ES: SpO2 90-95% OR=8.1 (3.0-21.3) and LS: SpO2 <90% OR=9.0 (4.2-19.4). INTERPRETATION: Both ES and LS were associated with adverse events. This study confirms the validity of current MET call criteria but points to the need to expand them. It provides a possible explanation for the failure to demonstrate efficacy of a MET in some trials because current call criteria maybe too late in the progress of the patient's critical condition. It allows the modelling of ERS and education programmes focused on signs of critical conditions. It potentially brings together ICU outreach and ward based responses. Broader use of clinical signs, monitoring such as pulse oximetry and objective data such as blood gas results may assist early intervention and help prevent loss of life.
BACKGROUND: Emergency response systems (ERS) are based on a set of triggers used to identify patients "at risk". This study aimed to establish the association between recordings of disturbed physiological variables and adverse events. METHODS: A cross-sectional survey of 3,046 non Do Not Attempt Resuscitation (non DNAR) adult admissions in five hospitals over 14 days. Medical records were reviewed for 26 early signs (ES) and 21 late signs (LS) of critical conditions and serious adverse events (SAE): death, cardiac arrest, severe respiratory problems, or transfer to a critical care area. The LS included published medical emergency team (MET) call criteria. FINDINGS: There were 12,384 ES and 1,410 LS. The 'top five' ES and the odds (OR) for death were: base deficit -5 to -8 mmol/L=40.2 (95% C.I. 7.7-208.8), partial airway obstruction OR=38.7 (3.9-64.4), poor peripheral circulation OR=34.4 (6.8-174.0), >expected drain fluid loss OR=30.1 (6.1-148.9), pH <7.3 >7.2 OR=29.0 (3.1-268.3). For LS: urine output <200 mL in 24 h OR=188.6 (95% C.I. 30.1-1179.8), pH <7.2 OR=116.1 (7.1-1906.1), unresponsive to voice OR=34.8 (10.7-113.0), anuric OR=29.0 (3.1-268.3), base deficit <-8.0 mmol/L OR=29.0 (3.1-268.3). OR for the other SAE were similar. Pulse oximetry abnormalities were associated with all SAE. The risk for death for ES: SpO2 90-95% OR=8.1 (3.0-21.3) and LS: SpO2 <90% OR=9.0 (4.2-19.4). INTERPRETATION: Both ES and LS were associated with adverse events. This study confirms the validity of current MET call criteria but points to the need to expand them. It provides a possible explanation for the failure to demonstrate efficacy of a MET in some trials because current call criteria maybe too late in the progress of the patient's critical condition. It allows the modelling of ERS and education programmes focused on signs of critical conditions. It potentially brings together ICU outreach and ward based responses. Broader use of clinical signs, monitoring such as pulse oximetry and objective data such as blood gas results may assist early intervention and help prevent loss of life.
Authors: Jasmeet Soar; Mary E Mancini; Farhan Bhanji; John E Billi; Jennifer Dennett; Judith Finn; Matthew Huei-Ming Ma; Gavin D Perkins; David L Rodgers; Mary Fran Hazinski; Ian Jacobs; Peter T Morley Journal: Resuscitation Date: 2010-10 Impact factor: 5.262
Authors: Gooske Douw; Lisette Schoonhoven; Tineke Holwerda; Getty Huisman-de Waal; Arthur R H van Zanten; Theo van Achterberg; Johannes G van der Hoeven Journal: Crit Care Date: 2015-05-20 Impact factor: 9.097
Authors: John Rihari-Thomas; Michelle DiGiacomo; Jane Phillips; Phillip Newton; Patricia M Davidson Journal: Int J Health Policy Manag Date: 2017-08-01