04 Sep 09
Posted in Sepsis at 1:01 by Laci
By C Adrie, A Francais, A Alvarez-Gonzalez, R Mounier, E Azoulay et al for the Outcomerea Study Group
Critical Care 2009, 13:R72
To establish a prognostic model for predicting 14-day mortality in ICU patients with severe sepsis overall and according to place of infection acquisition and to sepsis episode number.
Methods
In this prospective multicentre observational study on a multicentre database (OUTCOMEREA) including data from 12 ICUs, 2268 patients with 2737 episodes of severe sepsis were randomly divided into a training cohort (n = 1458) and a validation cohort (n = 810). Up to four consecutive severe sepsis episodes per patient occurring within the first 28 ICU days were included. We developed a prognostic model for predicting death within 14 days after each episode, based on patient data available at sepsis onset.
Results
Independent predictors of death were logistic organ dysfunction (odds ratio (OR), 1.22 per point, P < 10-4), septic shock (OR, 1.40; P = 0.01), rank of severe sepsis episode (1 reference, 2: OR, 1.26; P = 0.10 ≥ 3: OR, 2.64; P < 10-3), multiple sources of infection (OR; 1.45, P = 0.03), simplified acute physiology score II (OR, 1.02 per point; P < 10-4), McCabe score ([greater than or equal to]2) (OR, 1.96; P < 10-4), and number of chronic co-morbidities (1: OR, 1.75; P < 10-3, ≥ 2: OR, 2.24, P < 10-3). Validity of the model was good in whole cohorts (AUC-ROC, 0.76; 95%CI, 0.74 to 0.79; and HL Chi-square: 15.3 (P = 0.06) for all episodes pooled).
Conclusions
In ICU patients, a prognostic model based on a few easily obtained variables is effective in predicting death within 14 days after the first to fourth episode of severe sepsis complicating community-, hospital-, or ICU-acquired infection.
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02 Sep 09
Posted in Monitoring at 0:01 by Laci
By S Marqué, A Cariou, J-D Chiche and Pierre Squara
Critical Care 2009, 13:R73
This study was designed to compare the clinical acceptability of two cardiac output (CO) monitoring systems: a pulse wave contour-based system (FloTrac-Vigileo) and a bioreactance-based system (NICOM), using continuous thermodilution (PAC-CCO) as a reference method.
Methods
Consecutive patients, requiring PAC-CCO monitoring following cardiac surgery, were also monitored by the two other devices. CO values obtained simultaneously by the three systems were recorded continuously on a minute-by-minute basis.
Results
Continuous recording was performed on 29 patients, providing 12,099 simultaneous measurements for each device (417 ± 107 per patient). In stable conditions, correlations of NICOM and Vigileo with PAC-CCO were 0.77 and 0.69, respectively. The bias was -0.01 ± 0.84 for NICOM and -0.01 ± 0.81 for Vigileo (NS). NICOM relative error was less than 30% in 94% of the patients and less than 20% in 79% vs. 91% and 79% for the Vigileo, respectively (NS). The variability of measurements around the trend line (precision) was not different between the three methods: 8 ± 3%, 8 ± 4% and 8 ± 3% for PAC-CCO, NICOM and Vigileo, respectively. CO changes were 7.2 minutes faster with Vigileo and 6.9 minutes faster with NICOM (P < 0.05 both systems vs. PAC-CCO, NS). Amplitude of changes was not significantly different than thermodilution. Finally, the sensitivity and specificity for predicting significant CO changes were 0.91 and 0.95 respectively for the NICOM and 0.86 and 0.92 respectively for the Vigileo.
Conclusions
This study showed that the NICOM and Vigileo devices have similar monitoring capabilities in post-operative cardiac surgery patients.
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