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Derek C Angus

Publications and source records attributed to Derek C Angus.

At least 55 records · Page 3Linked to original sources
PubMed2005

Potential mechanisms and markers of critical illness-associated cognitive dysfunction.

PURPOSE OF REVIEW: To review the current understanding of the potential mechanisms of critical illness-associated cognitive dysfunction and to provide insight into markers that could be used to evaluate the influence of specific mechanisms in individual patients. RECENT FINDINGS: Cognitive dysfunction is common in critically ill patients, not only during the acute illness but also long after its resolution. Several pathophysiologic mechanisms are thought to underlie critical illness-associated cognitive dysfunction, including neurotransmitter abnormalities and occult diffuse brain injury. Markers that could be used to evaluate the influence of specific mechanisms in individual patients include serum anticholinergic activity, certain brain proteins, and tissue sodium concentration determination by way of high-resolution three-dimensional magnetic resonance imaging. SUMMARY: Although recent advances in this area are exciting, they are still too immature to influence patient care. Additional research is needed to provide a better understanding of the relative contribution of specific mechanisms to the development of critical illness-associated cognitive dysfunction and to determine whether these mechanisms might be amenable to treatment or prevention.

Biomarkers↗
PubMed2005

What's in a day?

Explore the source record for details and available documents.

Anti-Bacterial Agents↗
PubMed2004

Dynamic microsimulation to model multiple outcomes in cohorts of critically ill patients.

BACKGROUND: Existing intensive care unit (ICU) prediction tools forecast single outcomes, (e.g., risk of death) and do not provide information on timing. OBJECTIVE: To build a model that predicts the temporal patterns of multiple outcomes, such as survival, organ dysfunction, and ICU length of stay, from the profile of organ dysfunction observed on admission. DESIGN: Dynamic microsimulation of a cohort of ICU patients. SETTING: 49Forty-nine ICUs in 11 countries. PATIENTS: One thousand four hundred and forty-nine patients admitted to the ICU in May 1995. INTERVENTIONS: None. MODEL CONSTRUCTION: We developed the model on all patients (n=989) from 37 randomly-selected ICUs using daily Sequential Organ Function Assessment (SOFA) scores. We validated the model on all patients (n=460) from the remaining 12 ICUs, comparing predicted-to-actual ICU mortality, SOFA scores, and ICU length of stay (LOS). MAIN RESULTS: In the validation cohort, the predicted and actual mortality were 20.1% (95%CI: 16.2%-24.0%) and 19.9% at 30 days. The predicted and actual mean ICU LOS were 7.7 (7.0-8.3) and 8.1 (7.4-8.8) days, leading to a 5.5% underestimation of total ICU bed-days. The predicted and actual cumulative SOFA scores per patient were 45.2 (39.8-50.6) and 48.2 (41.6-54.8). Predicted and actual mean daily SOFA scores were close (5.1 vs 5.5, P=0.32). Several organ-organ interactions were significant. Cardiovascular dysfunction was most, and neurological dysfunction was least, linked to scores in other organ systems. CONCLUSIONS: Dynamic microsimulation can predict the time course of multiple short-term outcomes in cohorts of critical illness from the profile of organ dysfunction observed on admission. Such a technique may prove practical as a prediction tool that evaluates ICU performance on additional dimensions besides the risk of death.

Cohort Studies↗
PubMed2004

Severe sepsis epidemiology: sampling, selection, and society.

Three new articles in Critical Care add to an expanding body of information on the epidemiology of severe sepsis. Although there have been a range of approaches to estimate the incidence of severe sepsis, most studies report severe sepsis in about 10 +/- 4% of ICU patients with a population incidence of 1 +/- 0.5 cases per 1000. Importantly, the availability of ICU services may well determine the number of treated cases of severe sepsis, and it seems clear that these studies are reporting the treated incidence, not the incidence, of severe sepsis. In the future, we must focus on whether all severe sepsis should be treated, and, consequently, what level of ICU services is optimal.

Consensus↗
PubMed2004

Improving care of the critically ill: institutional and health-care system approaches.

Institutional and health-care system approaches complement bedside strategies to improve care of the critically ill. Focusing on the USA and the UK, we discuss seven approaches: education (especially of non-clinical managers, policy-makers, and the public), organisational guidelines, performance reporting, financial and sociobehavioural incentives to health-care professionals and institutions, regulation, legal requirements, and health-care system reorganisation. No single action is likely to have sustained effect and we recommend a combination of approaches. Several recent initiatives that hold promise tie performance reporting to financial incentives. Though performance reporting has been hampered by concerns over cost and accuracy, it remains an essential component and we recommend continued effort in this area. We also recommend more public education and use of organisational guidelines, such as admission criteria and staffing levels in intensive care units. Even if these endeavours are successful, with rising demand for services and continuing pressure to control costs, optimum care of the critically ill will not be realised without a fundamental reorganisation of services. In both the USA and UK, we recommend exploration of regionalised care, akin to US state trauma systems, and greater use of physician-extenders, such as nurse practitioners, to provide enhanced access to specialist care for critical illness.

Critical Care↗
PubMed2004

Understanding the lingering consequences of what we treat and what we do.

Granja and colleagues have helped us by showing that long-term follow-up is feasible and by trying to tease out whether select intensive care unit patient populations are at particular risk of adverse outcomes. This work gives us clues for future investigations which will hopefully interrogate further the potential mechanisms of action that underlie poor long-term outcomes. In the meantime, we can hope that this quality of follow-up will move from the research arena to become a part of routine clinical care.

Critical Illness↗
PubMed2004

Survival after liver transplantation in the United States: a disease-specific analysis of the UNOS database.

Our goal was to describe disease-specific survival and the clinical variables that predict survival in a large national cohort of adult liver transplant recipients. Data on 17,044 adult patients who received an initial orthotopic liver transplant between 1990 and 1996 with follow-up through 1999 was obtained from the United Network for Organ Sharing (UNOS). Disease-specific Kaplan-Meier survival plots and Cox Proportional Hazards models were estimated, and differences in the clinical characteristics of patients at the time of transplantation by disease were examined. Overall posttransplant survival currently exceeds 85% in the first year and is approaching 75% at 5 years. Unadjusted Kaplan-Meier survival is improved for recipients who are younger, female, and in better clinical condition. Survival is a function of disease and level of illness: cancer, fulminant liver failure, alcoholic liver disease, and the hepatitidies have the poorest prognosis, while primary billiary cirrohsis and sclerosing cholangitis have the best. Recipients who were outpatients before transplantation have longer survival than those transplanted from the hospital or intensive care unit. Although the model for end-stage liver disease (MELD) score was designed to predict pretransplant survival, patients with higher MELD scores have poorer posttransplant survival, but the MELD score is less predictive than the specific disease. Differences in disease-specific survival are partially explained by differences in disease severity at the time of transplantation. In conclusion, Disease-specific survival models indicate that there remains tremendous variability in survival as a function of underlying liver disease. However, a significant portion of the difference in survival between diseases arises from differences in clinical characteristics at the time of transplantation.

Adolescent↗
PubMed2004

Value and role of intensive care unit outcome prediction models in end-of-life decision making.

In the United States, intensive care unit (ICU) admission at the end of life is commonplace. What is the value and role of ICU mortality prediction models for informing the utility of ICU care?In this article, we review the history, statistical underpinnings,and current deployment of these models in clinical care. We conclude that the use of outcome prediction models to ration care that is unlikely to provide an expected benefit is hampered by imperfect performance, the lack of real-time availability, failure to consider functional outcomes beyond survival, and physician resistance to the use of probabilistic information when death is guaranteed by the decision it informs. Among these barriers, the most important technical deficiency is the lack of automated information systems to provide outcome predictions to decision makers, and the most important research and policy agenda is to understand and address our national ambivalence toward rationing care based on any criterion.

Advance Care Planning↗
PubMed2004

Health status versus utilities of patients with end-stage liver disease.

BACKGROUND: Health-related quality of life (HRQL) in patients with end-stage liver disease (ESLD) can be evaluated using either health-status questionnaires or utility assessment techniques. The two approaches have never been compared in terms of the values they assign to health prior to liver transplantation. STUDY DESIGN: We assessed health status of patients with ESLD using validated disease-specific instruments covering multiple domains (measures of disease, psychological status, personal function, social/role function, and general health perception). We also elicited utilities using formal approaches (standard gamble [SG] and time tradeoff [TTO]) and a simpler alternative (visual analog scale [VAS]). PATIENTS: Outpatients and inpatients at a single center prior to liver transplantation (n = 78). PRINCIPAL FINDINGS: Health status was generally poor (median physical symptoms score on a 0-1 [worst to best] scale, 0.33; psychological symptoms, 0; happiness, 0.50; personal function, 0; social/role function, 0.40; and general health perception, 0.40). The median VAS score was 0.50. The median TTO was 0.79, indicating that half of the patients in our sample chose healthier life in return for a 21% shorter life expectancy. The median SG score was 0.50, indicating that half of the patients were willing to take up to a 50% risk of death in exchange for perfect health. CONCLUSIONS: Both health status measures and utility assessments indicate that HRQL is compromised in patients awaiting liver transplantation. Despite the overall consistency between the two approaches, however, health status measures do not serve as reasonable proxies for utilities. For formal economic evaluations such as cost effectiveness analyses, only direct measures of utility can be used to quantify health states.

Adult↗
PubMed2004

Genetic epidemiology of sepsis and septic shock.

Sepsis affects more than 750,000 people each year in the United States alone, with a mortality rate of over 35% making it one of the leading causes of death in developed countries. Recent genetic analysis has provided us with several candidate genes, which have become the focus of genetic research in sepsis. The analysis of single nucleotide polymorphisms among various genes, such as those coding for pro- and antiinflammatory mediators, in the septic response has the potential to develop into prediction tools that will permit the clinician to more precisely determine the type of therapy that a particular patient should receive. However, unraveling the genetic variation in sepsis is complicated, and close attention must be paid to study design issues, including the selection of an appropriate study population and sample size and understanding gene-environment interactions. We must anticipate that future implementation of genetic information will lend itself to additional ethical dilemmas when we are faced with allocation of resources.

Journal Article↗
PubMed2004

Guidelines for critical care medicine training and continuing medical education.

OBJECTIVE: Critical care medicine trainees and faculty must acquire and maintain the skills necessary to provide state-of-the art clinical care to critically ill patients, to improve patient outcomes, optimize intensive care unit utilization, and continue to advance the theory and practice of critical care medicine. This should be accomplished in an environment dedicated to compassionate and ethical care. PARTICIPANTS: A multidisciplinary panel of professionals with expertise in critical care education and the practice of critical care medicine under the direction of the American College of Critical Care Medicine. SCOPE: Physician education in critical care medicine in the United States should encompass all disciplines that provide care in the intensive care unit and all levels of training: from medical students through all levels of postgraduate training and continuing medical education for all providers of clinical critical care. The scope of this guideline includes physician education in the United States from residency through ongoing practice after subspecialization. DATA SOURCES AND SYNTHESIS: Relevant literature was accessed via a systematic Medline search as well as by requesting references from all panel members. Subsequently, the bibliographies of obtained literature were reviewed for additional references. In addition, a search of organization-based published material was conducted via the Internet. This included but was not limited to material published by the American College of Critical Care Medicine, Accreditation Council for Graduate Medical Education, Accreditation Council for Continuing Medical Education, and other primary and specialty organizations. Collaboratively and iteratively, the task force met, by conference call and in person, to construct the tenets and ultimately the substance of this guideline. CONCLUSIONS: Guidelines for the continuum of education in critical care medicine from residency through specialty training and ongoing throughout practice will facilitate standardization of physician education in critical care medicine.

Clinical Competence↗
PubMed2004

Use of intensive care at the end of life in the United States: an epidemiologic study.

OBJECTIVE: Despite concern over the appropriateness and quality of care provided in an intensive care unit (ICU) at the end of life, the number of Americans who receive ICU care at the end of life is unknown. We sought to describe the use of ICU care at the end of life in the United States using hospital discharge data from 1999 for six states and the National Death Index. DESIGN: Retrospective analysis of administrative data to calculate age-specific rates of hospitalization with and without ICU use at the end of life, to generate national estimates of end-of-life hospital and ICU use, and to characterize age-specific case mix of ICU decedents. SETTING: All nonfederal hospitals in the states of Florida, Massachusetts, New Jersey, New York, Virginia, and Washington. PATIENTS: All inpatients in nonfederal hospitals in the six states in 1999. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: We found that there were 552,157 deaths in the six states in 1999, of which 38.3% occurred in hospital and 22.4% occurred after ICU admission. Using these data to project nationwide estimates, 540,000 people die after ICU admission each year. The age-specific rate of ICU use at the end of life was highest for infants (43%), ranged from 18% to 26% among older children and adults, and fell to 14% for those >85 yrs. Average length of stay and costs were 12.9 days and $24,541 for terminal ICU hospitalizations and 8.9 days and $8,548 for non-ICU terminal hospitalizations. CONCLUSIONS: One in five Americans die using ICU services. The doubling of persons over the age of 65 yrs by 2030 will require a system-wide expansion in ICU care for dying patients unless the healthcare system pursues rationing, more effective advanced care planning, and augmented capacity to care for dying patients in other settings.

Adolescent↗
PubMed2004

Comparison of Cox and Gray's survival models in severe sepsis.

BACKGROUND: Although survival is traditionally modeled using Cox proportional hazards modeling, this approach may be inappropriate in sepsis, in which the proportional hazards assumption does not hold. Newer, more flexible models, such as Gray's model, may be more appropriate. OBJECTIVES: To construct and compare Gray's model and two different Cox models in a large sepsis cohort. To determine whether hazards for death after sepsis were nonproportional. To explore how well the different survival modeling approaches describe these data. DESIGN: Analysis of combined data from the treatment and placebo arms of a large, negative, sepsis trial. SETTING: Intensive care units at 136 U.S. medical centers. SUBJECTS: A total of 1090 adults aged 18 yrs or older with signs and symptoms of severe sepsis and documented or probable Gram-negative infection. MEASUREMENTS: We considered 27 potential baseline risk factors and modeled survival over the 28 days after the onset of sepsis. We tested proportionality in single-variable Cox analysis using Schoenfeld residuals and log-log plots. We constructed a traditional multivariable Cox model, a multivariable Cox model with time-varying covariates, and a multivariable Gray's model. RESULTS: In single-variable analyses, 20 of the 27 potential factors were significantly associated with mortality, and 10 of 20 had nonproportional hazards. In multivariate analysis, all three models retained a very similar set of significant covariates (two models retained the identical set of nine variables, and the third differed only in that it retained the same nine plus a tenth variable). Four of the nine common covariates had nonproportional hazards. Of the three models, Gray's model best captured these changing hazard ratios over time. CONCLUSION: We confirm that many of the important predictors of mortality in severe sepsis are nonproportional and find that Gray's model seems best suited for modeling survival in this condition.

Adult↗
PubMed2004

The effect of drotrecogin alfa (activated) on long-term survival after severe sepsis.

OBJECTIVE: To determine long-term survival for subjects with severe sepsis enrolled in the previous multiple-center trial (PROWESS) of drotrecogin alfa (activated) (DrotAA) vs. placebo. DESIGN: Retrospective, cross-sectional, blinded follow-up of subjects enrolled in a previous randomized, controlled trial. SETTING: One hundred sixty-four tertiary care institutions in 11 countries. PARTICIPANTS: The 1,690 subjects with severe sepsis enrolled and treated with study drug in PROWESS, of whom 1,220 were alive at 28 days (the end of the original PROWESS follow-up). INTERVENTIONS: DrotAA (n = 850), 24 mug/kg/hr for 96 hrs, or placebo (n = 840). MEASUREMENTS AND MAIN RESULTS: Long-term survival data were collected. We had follow-up information on 100% of subjects at 28 days, 98% at hospital discharge, 94% at 3 months, and 93% at 1 yr. The longest follow-up was 3.6 yrs. Hospital survival was higher with DrotAA vs. placebo (70.3% vs. 65.1%, p = .03). There was no statistically significant difference in duration of survival time or in landmark survival rates in subjects who received DrotAA compared with those who received placebo (median duration of survival = 1113 days vs. 846 days for DrotAA vs. placebo, p = .10; landmark survival rates for DrotAA vs. placebo, 66.1% vs. 62.4% at 3 months [p = .11], 62.2% vs. 60.3% at 6 months [p = .44], 58.9% vs. 57.2% at 1 yr [p = .49], and 52.6% vs. 49.3% at 2(1/2) yrs [p = .21]). There was a significant interaction (p = .0008) between treatment assignment and baseline Acute Physiology and Chronic Health Evaluation (APACHE) II scores, suggesting qualitative differences in treatment effect with severity of illness. Subjects with APACHE II >/=25 had better survival time with DrotAA (median duration of survival: 450 vs. 71 days, p =.0005). Survival rates were also higher at landmark time points (DrotAA vs. placebo, 58.9% vs. 48.4% at 3 months [p = .003], 55.2% vs. 45.3% at 6 months [p = .005], 52.1% vs. 41.3% at 1 yr [p = .002], and 45.6% vs. 33.8% at 2(1/2) yrs [p = .001]). In the APACHE II <25 group there was no significant difference in survival time or survival rates at landmark time points except at 1 yr (DrotAA vs. placebo, 65.5% vs. 72.0% at 1 yr, p = .04). CONCLUSIONS: The acute survival benefit observed in subjects with severe sepsis who received DrotAA persists to hospital discharge. The survival benefit loses statistical significance thereafter. Post hoc analysis suggests the effect of DrotAA varies by APACHE II score with improved long-term survival in subjects with APACHE II scores >/=25 but no benefit in those with lower scores.

APACHE↗
PubMed2004

Hospital mortality and resource use in subgroups of the Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis (PROWESS) trial.

OBJECTIVE: To compare differences in hospital mortality and resource use in adult severe sepsis subjects randomized to receive drotrecogin alfa (activated) (DrotAA) or placebo in the PROWESS trial. DESIGN: Retrospective, cross-sectional, blinded follow-up of subjects enrolled in a previous randomized, controlled trial. SETTING: One hundred sixty-four tertiary care institutions in 11 countries. PARTICIPANTS: The 1,690 subjects with severe sepsis enrolled and treated with study drug in PROWESS, of whom 1,220 were alive at 28 days (the end of the original PROWESS follow-up). INTERVENTIONS: DrotAA (n = 850), 24 microg/kg/hr for 96 hrs, or placebo (n = 840). MEASUREMENTS AND MAIN RESULTS: New follow-up data through hospital discharge were merged with existing 28-day follow-up data. Hospital mortality was calculated for designated subgroups. Intensive care unit and hospital length of stay and Simplified Therapeutic Intervention Scoring System-28 (TISS-28) scores were calculated overall and in designated subgroups. Hospital discharge location was recorded. The 95% confidence interval of most subgroups contained the relative risk estimate for overall 28-day and hospital mortality. Median hospital length of stay and intensive care unit length of stay were similar in both treatment groups: 16 vs. 17 days (p = .22) and 9 vs. 9 days (p = .7) for placebo vs. DrotAA. No significant difference in TISS-28 scores was observed between treatment groups overall or in subgroups of disease severity. In subjects for whom discharge destination was reported, 42.8% of placebo subjects and 46.8% of DrotAA subjects (two thirds of survivors in each group) were discharged directly to home. CONCLUSIONS: Reduction in hospital mortality with DrotAA in most of the subgroups of PROWESS is consistent with the reduction in 28-day and hospital mortality observed in the overall PROWESS population. Additional survivors created with DrotAA treatment did not increase per-patient resource use or intensive care unit or hospital length of stay.

APACHE↗
PubMed2004

Quality of death: assessing the importance placed on end-of-life treatment in the intensive-care unit.

CONTEXT: The value of good end-of-life (EOL) care could be underestimated if its effects are assessed using the standard metric of quality-adjusted survival, especially if the time horizon is limited to the duration of the EOL care. This issue is particularly problematic in the intensive-care unit (ICU) where death is frequent, care is difficult, and costs are high. OBJECTIVES: The objectives of this study were to test whether people would trade healthy life expectancy for better EOL care, to understand how much life expectancy they would trade relative to domains of good care, and to determine the association of respondent characteristics to time traded. DESIGN AND SUBJECTS: We used a computerized survey instrument describing hypothetical patient experiences in the ICU used to assess attitudes of a general population sample (n = 104) recruited in Pittsburgh, Pennsylvania. MEASURES: We used life expectancy traded (from a baseline of 80 healthy years followed by a 1-month fatal ICU stay) for improving ICU care in 4 domains: pain and discomfort, daily surroundings, treatment decisions, and family support. RESULTS: Three fourths of respondents (n = 78) were prepared to shorten healthy life for better EOL care. Median time traded in individual domains ranged from 7.2 to 7.7 months overall and 9.6 to 11.4 months when restricted to those willing to trade. Median time traded for improvement in all domains was 8.3 months overall and 24.0 months by those willing to trade. In multivariable analyses, respondents who were older, nonwhite, or had children traded significantly less time, whereas those who did not perceive the ICU to be a caring environment traded more time. CONCLUSIONS: Good EOL care is highly valued, both in terms of medical and nonmedical domains, as suggested by previous work and confirmed by our data showing respondents trading quantities of healthy life several times longer than the duration of the EOL period itself. The considerable interperson variation highlights the importance of soliciting individual preferences about EOL care.

Adult↗