Routine Transthoracic Echocardiography in a General Intensive Care Unit: an 18 Month Survey in 704 Patients

The authors analyzed 704 transthoracic echocardiographic (TTE) examinations, performed routinely to all admitted patients to a general 16-bed Intensive Care Unit (ICU) during an 18-month period. Data acquisition and prevalence of abnormalities of cardiac structures and function were assessed, as well as the new, previously unknown severe diagnoses. A TTE was performed within the first 24 h of admission on 704 consecutive patients, with a mean age of 61.5+/-17.5 years, ICU stay of 10.6+/-17.1 days, APACHE II 22.6+/-8.9, and SAPS II 52.7+/-20.4. In four patients, TTE could not be performed. Left ventricular (LV) dimensions were quantified in 689 (97.8%) patients, and LV function in 670 (95.2%) patients. Cardiac output (CO) was determined in 610 (86.7%), and mitral E/A in 399 (85.9% of patients in sinus rhythm). Echocardiographic abnormalities were detected in 234 (33%) patients, the most common being left atrial (LA) enlargement (n=163), and LV dysfunction (n=132). Patients with these alterations were older (66+/-16.5 vs 58.1+/-17.4, p<0.001), presented a higher APACHE II score (24.4+/-8.7 vs 21.1+/-8.9, p<0.001), and had a higher mortality rate (40.1% vs 25.4%, p<0.001). Severe, previously unknown echocardiographic diagnoses were detected in 53 (7.5%) patients; the most frequent condition was severe LV dysfunction. Through a multivariate logistic regression analysis, it was determined that mortality was affected by tricuspid regurgitation (p=0.016, CI 1.007-1.016) and ICU stay (p<0.001, CI 1-1.019). We conclude that TTE can detect most cardiac structures in a general ICU. One-third of the patients studied presented cardiac structural or functional alterations and 7.5% severe previously unknown diagnoses.

Modeling in-Hospital Patient Survival During the First 28 Days After Intensive Care Unit Admission: a Prognostic Model for Clinical Trials in General Critically Ill Patients

OBJECTIVE: The objective of the study was to develop a model for estimating patient 28-day in-hospital mortality using 2 different statistical approaches. DESIGN: The study was designed to develop an outcome prediction model for 28-day in-hospital mortality using (a) logistic regression with random effects and (b) a multilevel Cox proportional hazards model. SETTING: The study involved 305 intensive care units (ICUs) from the basic Simplified Acute Physiology Score (SAPS) 3 cohort. PATIENTS AND PARTICIPANTS: Patients (n = 17138) were from the SAPS 3 database with follow-up data pertaining to the first 28 days in hospital after ICU admission. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The database was divided randomly into 5 roughly equal-sized parts (at the ICU level). It was thus possible to run the model-building procedure 5 times, each time taking four fifths of the sample as a development set and the remaining fifth as the validation set. At 28 days after ICU admission, 19.98% of the patients were still in the hospital. Because of the different sampling space and outcome variables, both models presented a better fit in this sample than did the SAPS 3 admission score calibrated to vital status at hospital discharge, both on the general population and in major subgroups. CONCLUSIONS: Both statistical methods can be used to model the 28-day in-hospital mortality better than the SAPS 3 admission model. However, because the logistic regression approach is specifically designed to forecast 28-day mortality, and given the high uncertainty associated with the assumption of the proportionality of risks in the Cox model, the logistic regression approach proved to be superior.

American Society of Anesthesiologists Score: Still Useful After 60 Years? Results of the EuSOS Study

OBJECTIVE: The European Surgical Outcomes Study described mortality following in-patient surgery. Several factors were identified that were able to predict poor outcomes in a multivariate analysis. These included age, procedure urgency, severity and type and the American Association of Anaesthesia score. This study describes in greater detail the relationship between the American Association of Anaesthesia score and postoperative mortality. METHODS: Patients in this 7-day cohort study were enrolled in April 2011. Consecutive patients aged 16 years and older undergoing inpatient non-cardiac surgery with a recorded American Association of Anaesthesia score in 498 hospitals across 28 European nations were included and followed up for a maximum of 60 days. The primary endpoint was in-hospital mortality. Decision tree analysis with the CHAID (SPSS) system was used to delineate nodes associated with mortality. RESULTS: The study enrolled 46,539 patients. Due to missing values, 873 patients were excluded, resulting in the analysis of 45,666 patients. Increasing American Association of Anaesthesia scores were associated with increased admission rates to intensive care and higher mortality rates. Despite a progressive relationship with mortality, discrimination was poor, with an area under the ROC curve of 0.658 (95% CI 0.642 - 0.6775). Using regression trees (CHAID), we identified four discrete American Association of Anaesthesia nodes associated with mortality, with American Association of Anaesthesia 1 and American Association of Anaesthesia 2 compressed into the same node. CONCLUSION: The American Association of Anaesthesia score can be used to determine higher risk groups of surgical patients, but clinicians cannot use the score to discriminate between grades 1 and 2. Overall, the discriminatory power of the model was less than acceptable for widespread use.