ObjectiveTo develop a model to assess severity of illness and predict vital status at hospital discharge based on ICU admission data.DesignProspective multicentre, multinational cohort study.Patients and settingA total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002.Measurements and resultsICU admission data (recorded within ±1 h) were used, describing: prior chronic conditions and diseases; circumstances related to and physiologic derangement at ICU admission. Selection of variables for inclusion into the model used different complementary strategies. For cross-validation, the model-building procedure was run five times, using randomly selected four fifths of the sample as a development- and the remaining fifth as validation-set. Logistic regression methods were then used to reduce complexity of the model. Final estimates of regression coefficients were determined by use of multilevel logistic regression. Variables selection and weighting were further checked by bootstraping (at patient level and at ICU level). Twenty variables were selected for the final model, which exhibited good discrimination (aROC curve 0.848), without major differences across patient typologies. Calibration was also satisfactory (Hosmer-Lemeshow goodness-of-fit test Ĥ=10.56, p=0.39, Ĉ=14.29, p=0.16). Customised equations for major areas of the world were computed and demonstrate a good overall goodness-of-fit.ConclusionsThe SAPS 3 admission score is able to predict vital status at hospital discharge with use of data recorded at ICU admission. Furthermore, SAPS 3 conceptually dissociates evaluation of the individual patient from evaluation of the ICU and thus allows them to be assessed at their respective reference levels.Electronic Supplementary MaterialElectronic supplementary material is included in the online fulltext version of this article and accessible for authorised users: http://dx.doi.org/10.1007/s00134-005-2763-5

ObjectiveRisk adjustment systems now in use were developed more than a decade ago and lack prognostic performance. Objective of the SAPS 3 study was to collect data about risk factors and outcomes in a heterogeneous cohort of intensive care unit (ICU) patients, in order to develop a new, improved model for risk adjustment.DesignProspective multicentre, multinational cohort study.Patients and settingA total of 19,577 patients consecutively admitted to 307 ICUs from 14 October to 15 December 2002.Measurements and resultsData were collected at ICU admission, on days 1, 2 and 3, and the last day of the ICU stay. Data included sociodemographics, chronic conditions, diagnostic information, physiological derangement at ICU admission, number and severity of organ dysfunctions, length of ICU and hospital stay, and vital status at ICU and hospital discharge. Data reliability was tested with use of kappa statistics and intraclass-correlation coefficients, which were >0.85 for the majority of variables. Completeness of the data was also satisfactory, with 1 [0–3] SAPS II parameter missing per patient. Prognostic performance of the SAPS II was poor, with significant differences between observed and expected mortality rates for the overall cohort and four (of seven) defined regions, and poor calibration for most tested subgroups.ConclusionsThe SAPS 3 study was able to provide a high-quality multinational database, reflecting heterogeneity of current ICU case-mix and typology. The poor performance of SAPS II in this cohort underscores the need for development of a new risk adjustment system for critically ill patients.Electronic Supplementary MaterialElectronic supplementary material is included in the online fulltext version of this article and accessible for authorised users: http://dx.doi.org/10.1007/s00134-005-2762-6

A prospective, observational study was conducted in a medico-surgical intensive care unit to assess the value of C-reactive protein (CRP), temperature and white cell count (WCC) measurements for the diagnosis of infection in critically ill patients. CRP, temperature and WCC were monitored daily in 76 infected and 36 non-infected patients. Multiple receiver-operating characteristics (ROC) curves were used to compare each parameter for infection diagnosis. The area under the curve (AUC) of CRP was significantly higher than that of temperature (0.93 and 0.75, respectively; p < 0.001). A CRP concentration of >8.7 mg/dL and a temperature of >38.2 degrees C were associated with infection, with a sensitivity of 93.4% and 54.8%, and a specificity of 86.1% and 88.9%, respectively. The ROC curve of WCC showed a poor diagnostic performance. The combination of CRP and temperature increased the specificity for infection diagnosis to 100%. In the subgroup of patients with ventilator-associated pneumonia (n = 48), CRP measurements were more reliable than temperature (AUC 0.92 and 0.78, respectively; p 0.006). The CRP levels in infected patients with sepsis, severe sepsis and septic shock were 15.2 +/- 8.2, 20.3 +/- 10.9 and 23.3 +/- 8.7 mg/dL, respectively (p 0.044). It was concluded that CRP was a better marker of infection than temperature. However, the combination of CRP and temperature measurements further increased the specificity for infection diagnosis, even in the subgroup of patients with VAP.

Daily measurement of CRP is useful in the detection of sepsis and it is more sensitive than the currently used markers, such as BT and WBC.

Background The aim of the present study was to evaluate the C-reactive protein level, the body temperature and the white cell count in patients after prescription of antibiotics in order to describe the clinical resolution of severe community-acquired pneumonia.