Long-term consequences of an intensive care unit stay in older critically ill patients: design of a longitudinal study

Background Modern methods in intensive care medicine often enable the survival of older critically ill patients. The short-term outcomes for patients treated in intensive care units (ICUs), such as survival to hospital discharge, are well documented. However, relatively little is known about subsequent long-term outcomes. Pain, anxiety and agitation are important stress factors for many critically ill patients. There are very few studies concerned with pain, anxiety and agitation and the consequences in older critically ill patients. The overall aim of this study is to identify how an ICU stay influences an older person's experiences later in life. More specific, this study has the following objectives: (1) to explore the relationship between pain, anxiety and agitation during ICU stays and experiences of the same symptoms in later life; and (2) to explore the associations between pain, anxiety and agitation experienced during ICU stays and their effect on subsequent health-related quality of life, use of the health care system (readmissions, doctor visits, rehabilitation, medication use), living situation, and survival after discharge and at 6 and 12 months of follow-up. Methods/Design A prospective, longitudinal study will be used for this study. A total of 150 older critically ill patients in the ICU will participate (ICU group). Pain, anxiety, agitation, morbidity, mortality, use of the health care system, and health-related quality of life will be measured at 3 intervals after a baseline assessment. Baseline measurements will be taken 48 hours after ICU admission and one week thereafter. Follow-up measurements will take place 6 months and 12 months after discharge from the ICU. To be able to interpret trends in scores on outcome variables in the ICU group, a comparison group of 150 participants, matched by age and gender, recruited from the Swiss population, will be interviewed at the same intervals as the ICU group. Discussion Little research has focused on long term consequences after ICU admission in older critically ill patients. The present study is specifically focussing on long term consequences of stress factors experienced during ICU admission.

Family satisfaction in the intensive care unit: what makes the difference?

PURPOSE: To assess family satisfaction in the ICU and to identify parameters for improvement. METHODS: Multicenter study in Swiss ICUs. Families were given a questionnaire covering overall satisfaction, satisfaction with care and satisfaction with information/decision-making. Demographic, medical and institutional data were gathered from patients, visitors and ICUs. RESULTS: A total of 996 questionnaires from family members were analyzed. Individual questions were assessed, and summary measures (range 0-100) were calculated, with higher scores indicating greater satisfaction. Summary score was 78 +/- 14 (mean +/- SD) for overall satisfaction, 79 +/- 14 for care and 77 +/- 15 for information/decision-making. In multivariable multilevel linear regression analyses, higher severity of illness was associated with higher satisfaction, while a higher patient:nurse ratio and written admission/discharge criteria were associated with lower overall satisfaction. Using performance-importance plots, items with high impact on overall satisfaction but low satisfaction were identified. They included: emotional support, providing understandable, complete, consistent information and coordination of care. CONCLUSIONS: Overall, proxies were satisfied with care and with information/decision-making. Still, several factors, such as emotional support, coordination of care and communication, are associated with poor satisfaction, suggesting the need for improvement. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00134-009-1611-4) contains supplementary material, which is available to authorized users.

Prospective population-based study of RSV-related intermediate care and intensive care unit admissions in Switzerland over a 4-year period (2001-2005)

OBJECTIVES: Respiratory syncytial virus (RSV) infections are a leading cause of hospital admissions in small children. A substantial proportion of these patients require medical and nursing care, which can only be provided in intermediate (IMC) or intensive care units (ICU). This article reports on all children aged < 3 years who required admission to IMC and/or ICU between October 1, 2001 and September 30, 2005 in Switzerland. PATIENTS AND METHODS: We prospectively collected data on all children aged < 3 years who were admitted to an IMC or ICU for an RSV-related illness. Using a detailed questionnaire, we collected information on risk factors, therapy requirements, length of stay in the IMC/ICU and hospital, and outcome. RESULTS: Of the 577 cases reported during the study period, 90 were excluded because the patients did not fulfill the inclusion criteria; data were incomplete in another 25 cases (5%). Therefore, a total of 462 verified cases were eligible for analysis. At the time of hospital admission, only 31 patients (11%) were older than 12 months. Since RSV infection was not the main reason for IMC/ICU admission in 52% of these patients, we chose to exclude this subgroup from further analyses. Among the 431 infants aged < 12 months, the majority (77%) were former near term or full term (NT/FT) infants with a gestational age > or = 35 weeks without additional risk factors who were hospitalized at a median age of 1.5 months. Gestational age (GA) < 32 weeks, moderate to severe bronchopulmonary dysplasia (BPD), and congenital heart disease (CHD) were all associated with a significant risk increase for IMC/ICU admission (relative risk 14, 56, and 10, for GA < or = 32 weeks, BPD, and CHD, respectively). Compared with NT/FT infants, high-risk infants were hospitalized at an older age (except for infants with CHD), required more invasive and longer respiratory support, and had longer stays in the IMC/ICU and hospital. CONCLUSIONS: In Switzerland, RSV infections lead to the IMC/ICU admission of approximately 1%-2% of each annual birth cohort. Although prematurity, BPD, and CHD are significant risk factors, non-pharmacological preventive strategies should not be restricted to these high-risk patients but also target young NT/FT infants since they constitute 77% of infants requiring IMC/ICU admission.

Study of length of stay in the cardiovascular intensive care unit

Coronary artery bypass graft (CABG) surgery is among the most common operations performed in the United States and accounts for more resources expended in cardiovascular medicine than any other single procedure. CABG surgery patients initially recover in the Cardiovascular Intensive Care Unit (CVICU). The post-procedure CVICU length of stay (LOS) goal is two days or less. A longer ICU LOS is associated with a prolonged hospital LOS, poor health outcomes, greater use of limited resources, and increased medical costs. ^ Research has shown that experienced clinicians can predict LOS no better than chance. Current CABG surgery LOS risk models differ greatly in generalizability and ease of use in the clinical setting. A predictive model that identified modifiable pre- and intra-operative risk factors for CVICU LOS greater than two days could have major public health implications as modification of these identified factors could decrease CVICU LOS and potentially minimize morbidity and mortality, optimize use of limited health care resources, and decrease medical costs. ^ The primary aim of this study was to identify modifiable pre-and intra-operative predictors of CVICU LOS greater than two days for CABG surgery patients with cardiopulmonary bypass (CPB). A secondary aim was to build a probability equation for CVICU LOS greater than two days. Data were extracted from 416 medical records of CABG surgery patients with CPB, 50 to 80 years of age, recovered in the CVICU of a large teaching, referral hospital in southeastern Texas, during the calendar year 2004 and the first quarter of 2005. Exclusion criteria included Diagnosis Related Group (DRG) 106, CABG surgery without CPB, CABG surgery with other procedures, and operative deaths. The data were analyzed using multivariate logistic regression for an alpha=0.05, power=0.80, and correlation=0.26. ^ This study found age, history of peripheral arterial disease, and total operative time equal to and greater than four hours to be independent predictors of CVICU LOS greater than two days. The probability of CVICU LOS greater than two days can be calculated by the following equation: -2.872941 +.0323081 (age in years) + .8177223 (history of peripheral arterial disease) + .70379 (operative time). ^

Nosocomial infections and their relationship to non-traditional risk factors in a medical intensive care unit

Background. Nosocomial infections are a source of concern for many hospitals in the United States and worldwide. These infections are associated with increased morbidity, mortality and hospital costs. Nosocomial infections occur in ICUs at a rate which is five times greater than those in general wards. Understanding the reasons for the higher rates can ultimately help reduce these infections. The literature has been weak in documenting a direct relationship between nosocomial infections and non-traditional risk factors, such as unit staffing or patient acuity.^ Objective. To examine the relationship, if any, between nosocomial infections and non-traditional risk factors. The potential non-traditional risk factors we studied were the patient acuity (which comprised of the mortality and illness rating of the patient), patient days for patients hospitalized in the ICU, and the patient to nurse ratio.^ Method. We conducted a secondary data analysis on patients hospitalized in the Medical Intensive Care Unit (MICU) of the Memorial Hermann- Texas Medical Center in Houston during the months of March 2008- May 2009. The average monthly values for the patient acuity (mortality and illness Diagnostic Related Group (DRG) scores), patient days for patients hospitalized in the ICU and average patient to nurse ratio were calculated during this time period. Active surveillance of Bloodstream Infections (BSIs), Urinary Tract Infections (UTIs) and Ventilator Associated Pneumonias (VAPs) was performed by Infection Control practitioners, who visited the MICU and performed a personal infection record for each patient. Spearman's rank correlation was performed to determine the relationship between these nosocomial infections and the non-traditional risk factors.^ Results. We found weak negative correlations between BSIs and two measures (illness and mortality DRG). We also found a weak negative correlation between UTI and unit staffing (patient to nurse ratio). The strongest positive correlation was found between illness DRG and mortality DRG, validating our methodology.^ Conclusion. From this analysis, we were able to infer that non-traditional risk factors do not appear to play a significant role in transmission of infection in the units we evaluated.^

Development of a standard sign-out procedure for clinicians in a pediatric intensive care unit

Background: Poor communication among health care providers is cited as the most common cause of sentinel events involving patients. Sign-out of patient data at the change of clinician shifts is a component of communication that is especially vulnerable to errors. Sign-outs are particularly extensive and complex in intensive care units (ICUs). There is a paucity of validated tools to assess ICU sign-outs. ^ Objective: To design a valid and reliable survey tool to assess the perceptions of Pediatric ICU (PICU) clinicians about sign-out. ^ Design: Cross-sectional, web-based survey ^ Setting: Academic hospital, 31-bed PICU ^ Subjects: Attending faculty, fellows, nurse practitioners and physician assistants. ^ Interventions: A survey was designed with input from a focus group and administered to PICU clinicians. Test-retest reliability, internal consistency and validity of the survey tool were assessed. ^ Measurements and Main Results: Forty-eight PICU clinicians agreed to participate. We had 42(88%) and 40(83%) responses in the test and retest phases. The mean scores for the ten survey items ranged from 2.79 to 3.67 on a five point Likert scale with no significant test-retest difference and a Pearson correlation between pre and post answers of 0.65. The survey item scores showed internal consistency with a Cronbach's Alpha of 0.85. Exploratory factor analysis revealed three constructs: efficacy of sign-out process, recipient satisfaction and content applicability. Seventy eight % clinicians affirmed the need for improvement of the sign-out process and 83% confirmed the need for face- to-face verbal sign-out. A system-based sign-out format was favored by fellows and advanced level practitioners while attendings preferred a problem-based format (p=0.003). ^ Conclusions: We developed a valid and reliable survey to assess clinician perceptions about the ICU sign-out process. These results can be used to design a verbal template to improve and standardize the sign-out process.^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Dysfunction of respiratory muscles in critically ill patients on the intensive care unit.

Muscular weakness and muscle wasting may often be observed in critically ill patients on intensive care units (ICUs) and may present as failure to wean from mechanical ventilation. Importantly, mounting data demonstrate that mechanical ventilation itself may induce progressive dysfunction of the main respiratory muscle, i.e. the diaphragm. The respective condition was termed 'ventilator-induced diaphragmatic dysfunction' (VIDD) and should be distinguished from peripheral muscular weakness as observed in 'ICU-acquired weakness (ICU-AW)'. Interestingly, VIDD and ICU-AW may often be observed in critically ill patients with, e.g. severe sepsis or septic shock, and recent data demonstrate that the pathophysiology of these conditions may overlap. VIDD may mainly be characterized on a histopathological level as disuse muscular atrophy, and data demonstrate increased proteolysis and decreased protein synthesis as important underlying pathomechanisms. However, atrophy alone does not explain the observed loss of muscular force. When, e.g. isolated muscle strips are examined and force is normalized for cross-sectional fibre area, the loss is disproportionally larger than would be expected by atrophy alone. Nevertheless, although the exact molecular pathways for the induction of proteolytic systems remain incompletely understood, data now suggest that VIDD may also be triggered by mechanisms including decreased diaphragmatic blood flow or increased oxidative stress. Here we provide a concise review on the available literature on respiratory muscle weakness and VIDD in the critically ill. Potential underlying pathomechanisms will be discussed before the background of current diagnostic options. Furthermore, we will elucidate and speculate on potential novel future therapeutic avenues.

Adoption of a sedation scoring system and sedation guideline in an intensive care unit

Aim. The paper presents a study assessing the rate of adoption of a sedation scoring system and sedation guideline. Background. Clinical practice guidelines including sedation guidelines have been shown to improve patient outcomes by standardizing care. In particular sedation guidelines have been shown to be beneficial for intensive care patients by reducing the duration of ventilation. Despite the acceptance that clinical practice guidelines are beneficial, adoption rates are rarely measured. Adoption data may reveal other factors which contribute to improved outcomes. Therefore, the usefulness of the guideline may be more appropriately assessed by collecting adoption data. Method. A quasi-experimental pre-intervention and postintervention quality improvement design was used. Adoption was operationalized as documentation of sedation score every 4 hours and use of the sedation and analgesic medications suggested in the guideline. Adoption data were collected from patients' charts on a random day of the month; all patients in the intensive care unit on that day were assigned an adoption category. Sedation scoring system adoption data were collected before implementation of a sedation guideline, which was implemented using an intensive information-giving strategy, and guideline adoption data were fed back to bedside nurses. After implementation of the guideline, adoption data were collected for both the sedation scoring system and the guideline. The data were collected in the years 2002-2004. Findings. The sedation scoring system was not used extensively in the pre-intervention phase of the study; however, this improved in the postintervention phase. The findings suggest that the sedation guideline was gradually adopted following implementation in the postintervention phase of the study. Field notes taken during the implementation of the sedation scoring system and the guideline reveal widespread acceptance of both. Conclusion. Measurement of adoption is a complex process. Appropriate operationalization contributes to greater accuracy. Further investigation is warranted to establish the intensity and extent of implementation required to positively affect patient outcomes.

The effects of advanced practice nurses (APNs) as intensivists in a surgical intensive care unit (SICU) on patient outcomes, healthcare charges, and apn intensivist services in the SICU

Intensive Care Units (ICUs) account for over 10 percent of all US hospital beds, have over 4.4 million patient admissions yearly, approximately 360,000 deaths, and account for close to 30% of acute care hospital costs. The need for critical care services has increased due to an aging population and medical advances that extend life. The result is efforts to improve patient outcomes, optimize financial performance, and implement models of ICU care that enhance quality of care and reduce health care costs. This retrospective chart review study examined the dose effect of APN Intensivists in a surgical intensive care unit (SICU) on differences in patient outcomes, healthcare charges, SICU length of stay, charges for APN intensivist services, and frequency of APNs special initiatives when the SICU was staffed by differing levels of APN Intensivist staffing over four time periods (T1-T4) between 2009 and 2011. The sample consisted of 816 randomly selected (204 per T1-T4) patient chart data. Study findings indicated reported ventilator associated pneumonia (VAP) rates, ventilator days, catheter days and catheter associated urinary tract infection (CAUTI) rates increased at T4 (when there was the lowest number of APN Intensivists), and there was increased pressure ulcer incidence in first two quarters of T4. There was no statistically significant difference in post-surgical glycemic control (M = 142.84, SD = 40.00), t (223) = 1.40, p = .17, and no statistically significant difference in the SICU length of stay among the time-periods (M = 3.27, SD = 3.32), t (202) = 1.02, p = .31. Charges for APN services increased over the 4 time periods from $11,268 at T1 to $51,727 at T4 when a system to capture APN billing was put into place. The number of new APN initiatives declined in T4 as the number of APN Intensivists declined. Study results suggest a dose effect of APN Intensivists on important patient health outcomes and on the number of APNs initiatives to prevent health complications in the SICU. ^

The Effects of Advanced Practice Nurses (APNs) as Intensivists in a Surgical Intensive Care Unit (SICU) on Patient Outcomes, Healthcare Charges, and APN Intensivist Services in the SICU

Intensive Care Units (ICUs) account for over 10 percent of all US hospital beds, have over 4.4 million patient admissions yearly, approximately 360,000 deaths, and account for close to 30% of acute care hospital costs. The need for critical care services has increased due to an aging population and medical advances that extend life. The result is efforts to improve patient outcomes, optimize financial performance, and implement models of ICU care that enhance quality of care and reduce health care costs. This retrospective chart review study examined the dose effect of APN Intensivists in a surgical intensive care unit (SICU) on differences in patient outcomes, healthcare charges, SICU length of stay, charges for APN intensivist services, and frequency of APNs special initiatives when the SICU was staffed by differing levels of APN Intensivist staffing over four time periods (T1-T4) between 2009 and 2011. The sample consisted of 816 randomly selected (204 per T1-T4) patient chart data. Study findings indicated reported ventilator associated pneumonia (VAP) rates, ventilator days, catheter days and catheter associated urinary tract infection (CAUTI) rates increased at T4 (when there was the lowest number of APN Intensivists), and there was increased pressure ulcer incidence in first two quarters of T4. There was no statistically significant difference in post-surgical glycemic control (M = 142.84, SD= 40.00), t (223) = 1.40, p = .17, and no statistically significant difference in the SICU length of stay among the time-periods (M= 3.27, SD = 3.32), t (202) = 1.02, p= .31. Charges for APN services increased over the 4 time periods from $11,268 at T1 to $51,727 at T4 when a system to capture APN billing was put into place. The number of new APN initiatives declined in T4 as the number of APN Intensivists declined. Study results suggest a dose effect of APN Intensivists on important patient health outcomes and on the number of APNs initiatives to prevent health complications in the SICU.

Increased hospital-based physical rehabilitation and information provision after intensive care unit discharge: the RECOVER randomized clinical trial.

Importance: critical illness results in disability and reduced health-related quality of life (HRQOL), but the optimum timing and components of rehabilitation are uncertain. Objective: to evaluate the effect of increasing physical and nutritional rehabilitation plus information delivered during the post–intensive care unit (ICU) acute hospital stay by dedicated rehabilitation assistants on subsequent mobility, HRQOL, and prevalent disabilities. Design, Setting, and Participants: a parallel group, randomized clinical trial with blinded outcome assessment at 2 hospitals in Edinburgh, Scotland, of 240 patients discharged from the ICU between December 1, 2010, and January 31, 2013, who required at least 48 hours of mechanical ventilation. Analysis for the primary outcome and other 3-month outcomes was performed between June and August 2013; for the 6- and 12-month outcomes and the health economic evaluation, between March and April 2014. Interventions: during the post-ICU hospital stay, both groups received physiotherapy and dietetic, occupational, and speech/language therapy, but patients in the intervention group received rehabilitation that typically increased the frequency of mobility and exercise therapies 2- to 3-fold, increased dietetic assessment and treatment, used individualized goal setting, and provided greater illness-specific information. Intervention group therapy was coordinated and delivered by a dedicated rehabilitation practitioner. Main Outcomes and Measures: the Rivermead Mobility Index (RMI) (range 0-15) at 3 months; higher scores indicate greater mobility. Secondary outcomes included HRQOL, psychological outcomes, self-reported symptoms, patient experience, and cost-effectiveness during a 12-month follow-up (completed in February 2014). Results: median RMI at randomization was 3 (interquartile range [IQR], 1-6) and at 3 months was 13 (IQR, 10-14) for the intervention and usual care groups (mean difference, −0.2 [95% CI, −1.3 to 0.9; P = .71]). The HRQOL scores were unchanged by the intervention (mean difference in the Physical Component Summary score, −0.1 [95% CI, −3.3 to 3.1; P = .96]; and in the Mental Component Summary score, 0.2 [95% CI, −3.4 to 3.8; P = .91]). No differences were found for self-reported symptoms of fatigue, pain, appetite, joint stiffness, or breathlessness. Levels of anxiety, depression, and posttraumatic stress were similar, as were hand grip strength and the timed Up & Go test. No differences were found at the 6- or 12-month follow-up for any outcome measures. However, patients in the intervention group reported greater satisfaction with physiotherapy, nutritional support, coordination of care, and information provision. Conclusions and Relevance: post-ICU hospital-based rehabilitation, including increased physical and nutritional therapy plus information provision, did not improve physical recovery or HRQOL, but improved patient satisfaction with many aspects of recovery.

Fatal adenoviral necrotizing bronchiolitis case in a post-cardiac surgery intensive care unit

We report a case of a 67 year-old-male patient admitted to the intensive care unit in the post-coronary bypass surgery period who presented cardiogenic shock, acute renal failure and three episodes of sepsis, the latter with pulmonary distress at the 30th post-operative day. The patient expired within five days in spite of treatment with vancomycin, imipenem, colistimethate and amphotericin B. At autopsy severe adenovirus pneumonia was found. Viral pulmonary infections following cardiovascular surgery are uncommon. We highlight the importance of etiological diagnosis to a correct treatment approach.

Constipation in intensive care unit: Incidence and risk factors

Purpose: Although gastrointestinal motility disorders are common in critically ill patients, constipation and its implications have received very little attention. We aimed to determine the incidence of constipation to find risk factors and its implications in critically ill patients Materials and Methods: During a 6-month period, we enrolled all patients admitted to an intensive care unit from an universitary hospital who stayed 3 or more days. Patients submitted to bowel surgery were excluded. Results: Constipation occurred in 69.9% of the patients. There was no difference between constipated and not constipated in terms of sex, age, Acute Physiology and Chronic Health Evaluation II, type of admission (surgical, clinical, or trauma), opiate use, antibiotic therapy, and mechanical ventilation. Early (<24 hours) enteral nutrition was associated with less constipation, a finding that persisted at multivariable analysis (P < .01). Constipation was not associated with greater intensive care unit or mortality, length of stay, or days free from mechanical ventilation. Conclusions: Constipation is very common among critically ill patients. Early enteral nutrition is associated with earlier return of bowel function. (C) 2009 Elsevier Inc. All rights reserved.