Use of Distress and Depression Thermometers to Measure Psychosocial Morbidity Among Southern European Cancer Patients

GOALS OF WORK: Recent literature has indicated the need for rapid evaluation of psychosocial issues secondary to cancer. Because of the problems of routine use of psychometric instruments, short instruments such as visual analogue scales or one-item 0-10 scales have been developed as valid assessment alternatives. PATIENTS AND METHODS: A study was conducted to examine the role of two 0-10 scales in measuring emotional stress (distress thermometer, DT) and depressed mood (mood thermometer, MT), respectively, in a multicenter study carried out in southern European countries (Italy, Portugal, Spain, and Switzerland). A convenience sample of 312 cancer outpatients completed the DT and MT and the Hospital Anxiety Depression Scale (HADS). MAIN RESULTS: DT was more significantly associated HADS anxiety than HADS depression while MT was related both to HADS anxiety and depression. The correlation of MT with HADS was higher than DT. A cutoff point >4 on the DT maximized sensitivity (65%) and specificity (79%) for general psychosocial morbidity while a cutoff >5 identified more severe "caseness" (sensitivity=70%; specificity=73%). On the MT, sensitivity and specificity for general psychosocial morbidity were 85% and 72% by using the cutoff score >3. A score >4 on the MT was associated with a sensitivity of 78% and a specificity of 77% in detecting more severe caseness. CONCLUSIONS: Two simple instruments, the DT and the MT, were found to have acceptable levels of sensitivity and specificity in detecting psychosocial morbidity. Compared to the HADS, however, the mood MT performed better than the DT.

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.