Communication of end-of-life decisions in European intensive care units

Objective To examine end-of-life (EOL) practices in European ICUs: who makes these decisions, how they are made, communication of these decisions and questions on communication between the physicians, nurses, patients and families.Design Data collected prospectively on EOL decisions facilitated by a questionnaire including EOL decision categories, geographical regions, mental competency, information about patient wishes, and discussions with patients, families and health care professionals.Setting 37 European ICUs in 17 countriesPatients ICU physicians collected data on 4,248 patients.Results 95% of patients lacked decision making capacity at the time of EOL decision and patients wishes were known in only 20% of cases. EOL decisions were discussed with the family in 68% of cases. Physicians reported having more information about patients wishes and discussions in the northern countries (31%, 88%) than central (16%, 70%) or southern (13%, 48%) countries. The family was more often told (88%) than asked (38%) about EOL decisions. Physicians reasons for not discussing EOL care with the family included the fact that the patient was unresponsive to therapy (39%), the family was unavailable (28%), and the family was thought not to understand (25%).Conclusions ICU patients typically lack decision-making capacity, and physicians know patients wishes in only 20% of EOL decisions. There were regional differences in discussions of EOL decisions with families and other physicians. In European ICUs there seems to be a need to improve communicationP. Sjokvist died in December 2003Funding was provided by the European Concerted Action project and by the European Commission (contract PL963733), the Chief Scientists Office of the Ministry of Health, Israel (grant no. 4226), the European Society of Intensive Care Medicine (ESICM) and by OFES Switzerland (Biomed, no. 980271)     

Intensive care physicians’ attitudes concerning distribution of intensive care resources

Objective To evaluate the attitudes of Israeli intensive care physicians regarding intensive care unit (ICU) triage issues.Design An opinion survey using questionnaires similar to those used in a previous study in the United States.Setting and participants Forty-three physicians, members of the Israel Society of Critical Care Medicine (45%).Results Important factors for admission to the last ICU bed were: small likelihood of surviving hospitalization, irreversibility of acute disorder, nature of chronic disorders and the physicians personal attitude. Most respondents would admit a patient with a predicted survival of a few weeks (70%) or a patient whose quality of life would be poor according to the physicians (98%) or patients (77%) definition, to the last ICU bed. The personal attitude of the respondents and their own view of the patients quality of life were considered as important as the quality of life as viewed by the patient. Israeli physicians tended to refuse patient admission into the ICU more than their US counterparts. Most Israeli physicians refused to discharge an ICU patient in order to admit another, despite bed shortage.Conclusions The attitudes of Israeli intensive care physicians towards distribution of ICU resources differ from those of their United States counterparts; they are more paternalistic and comply less with requests for admission. Such attitudes are comparable to those expressed by some European intensive care physicians, highlighting the existence of diversity in the factors important to physicians decision-making.     

Early evaluation of coagulase negative staphylococcus in blood samples of intensive care unit patients

Of 2160 intensive care unit patients, 36 patients with positive blood cultures had coagulasenegative staphylococcus in one blood bottle, whereas the organism was present in two or more bottles in 38 cases. The groups were not significantly different in 27 clinical variables, obtained at the time of their first positive blood culture. There was also no significant difference in the antimicrobial sensitivities. No initial clinical data supported the classification of coagulase-negative staphylococcus as either pathogen or contaminant.When the 74 patients with blood culture positive coagulase-negative staphylococcus were compared with three control groups (absent septicemia, probable septicemia and proven septicemia) they were not different from those with probable septicemia. A discriminant analysis was performed comparing patients with absent septicemia and with proven septicemia in an attempt to classify patients with isolates of coagulase-negative staphylococcus in one of these groups at an early stage. Patients with two or more positive blood cultures were not statistically classified more frequently as septicemic than patients with one blood bottle positive for this organism. However, patients categorized as septicemic had a significantly higher mortality (59%) than those classified as non-septicemic (35%) (p<0.05).     

Informatics Infrastructure for Syndrome Surveillance, Decision Support, Reporting, and Modeling of Critical Illness

OBJECTIVE: To develop and validate an informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness.METHODS: Using open-schema data feeds imported from electronic medical records (EMRs), we developed a near-real-time relational database (Multidisciplinary Epidemiology and Translational Research in Intensive Care Data Mart). Imported data domains included physiologic monitoring, medication orders, laboratory and radiologic investigations, and physician and nursing notes. Open database connectivity supported the use of Boolean combinations of data that allowed authorized users to develop syndrome surveillance, decision support, and reporting (data “sniffers”) routines. Random samples of database entries in each category were validated against corresponding independent manual reviews.RESULTS: The Multidisciplinary Epidemiology and Translational Research in Intensive Care Data Mart accommodates, on average, 15,000 admissions to the intensive care unit (ICU) per year and 200,000 vital records per day. Agreement between database entries and manual EMR audits was high for sex, mortality, and use of mechanical ventilation (κ, 1.0 for all) and for age and laboratory and monitored data (Bland-Altman mean difference ± SD, 1(0) for all). Agreement was lower for interpreted or calculated variables, such as specific syndrome diagnoses (κ, 0.5 for acute lung injury), duration of ICU stay (mean difference ± SD, 0.43±0.2), or duration of mechanical ventilation (mean difference ± SD, 0.2±0.9).CONCLUSION: Extraction of essential ICU data from a hospital EMR into an open, integrative database facilitates process control, reporting, syndrome surveillance, decision support, and outcome research in the ICU.EMR = electronic medical record; ICU = intensive care unit; IRB = Institutional Review Board; METRIC = Multidisciplinary Epidemiology and Translational Research in Intensive Care; SQL = structured query languageThe relevance of care in the intensive care unit (ICU) to public health in the United States is reflected in annual figures of 4.4 million ICU admissions, 500,000 deaths, 13.3% of hospital costs, 4.2% of national health expenditures, and 0.56% of the gross domestic product.^1,2 This demand is expected to increase as the US population ages; patients older than 65 years currently account for more than 55% of all ICU days.^3,4 Unmeasured burdens include the high degree of disability and loss of productivity for both ICU survivors and their caregivers.^5-7The complexity of the ICU environment, characterized by a vast amount of information and the critical importance of timing of interventions, presents a major barrier to safe and efficient care delivery.^8,9 Recent advances in medical informatics and the anticipated widespread implementation of electronic medical records (EMRs) combine to provide an opportunity to facilitate processes for delivery of safe, high-quality care in the ICU.This article describes the development and implementation of the Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC) Data Mart, an informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness at Mayo Clinic.     

Decisions to limit life-sustaining treatment for critically ill patients who lack both decision-making capacity and surrogate decision-makers

OBJECTIVE: Many intensive care unit (ICU) physicians have withdrawn life-support from a patient who lacked decision-making capacity and a surrogate decision-maker, yet little is known about the decision-making practices for these patients. We sought to determine how often such patients are admitted to the ICU of a metropolitan hospital and how end-of-life decisions are made for them. DESIGN: Prospective, observational cohort study. PATIENTS AND SETTING: Consecutive adult patients admitted to the medical ICU of a metropolitan West Coast hospital during a 7-month period in 2003 to 2004. MEASUREMENTS: Attending physicians completed a questionnaire about the decision-making process for each patient for whom they considered limiting life-support who lacked decisional capacity and a legally recognized surrogate decision-maker. MAIN RESULTS: Of the 303 patients admitted during the study period, 49 (16%; 95% confidence interval [CI], 12-21%) lacked decision-making capacity and a surrogate during the entire ICU stay. Compared with all other ICU patients, these patients were more likely to be male (88% vs. 69%; p = .002), white (42% vs. 23%; p = .028), and > or =65 yrs old (29% vs. 13%; p = .007). Physicians considered withholding or withdrawing treatment from 37% (18) of the 49 patients who lacked both decision-making capacity and a surrogate decision-maker. For 56% (10) of these 18 patients, the opinion of another attending physician was obtained; for 33% (6 of 18), the ICU team made the decision independently, and for 11% (2 of 18), the input of the courts or the hospital ethics committee was obtained. Overall, 27% of deaths (13 of 49) during the study period were in incapacitated patients who lacked a surrogate (95% CI, 15-41%). CONCLUSIONS: Sixteen percent of patients admitted to the medical ICU of this hospital lacked both decision-making capacity and a surrogate decision-maker. Decisions to limit life support were generally made by physicians without judicial or institutional review. Further research and debate are needed to develop optimal decision-making strategies for these difficult cases.     

Can a clinician predict the technical equipment a patient will need during intensive care unit treatment? An approach to standardize and redesign the intensive care unit workstation

The technical equipment of today's intensive care unit (ICU) workstation has been characterized by a gradual, incremental accumulation of individual devices, whose presence is dictated by patient needs. These devices usually present differently designed controls, operate under different alarm philosophies, and cannot communicate with each other. By contrast, ICU workstations could be equipped permanently and in a standardized manner with electronically linked modules if the attending physicians could reliably predict, at the time of admission, the patient's equipment needs. Over a period of 3 1/2 months, the doctors working in our 20-bed surgical ICU made 1,000 predictions concerning outcome, equipment need, duration of artificial ventilation, and duration of hospitalization for 300 recently admitted patients. The interviews were made within the first 24 hours after admission. The doctors being interviewed were usually (i.e., in over 90% of cases) unfamiliar with the patient. Information concerning the patient's general state of health, special pre-ICU events, and complications was offered to the interviewed clinician because this information represents standard admission data. It was found that the equipment need (represented by two different setups, high tech and low tech) could be predicted most reliably (96.4% correct predictions) compared with a prediction on outcome of ICU treatment (94.5%), on duration of artificial ventilation (75.4%), and on duration of stay (43.4%). There was no significant (p>0.05) difference in the reliability of predictions between residents and consultants. Factors influencing the postoperative equipment need varied with surgical specialty. The general state of health, as indicated by the ASA classification (p<0.001), and the specific intervention (all multiple-valve replacements needed the high-level equipment standard) appeared to be most important in cardiac surgery, while a state of septicemia was important in general surgery (p<0.001). Our findings suggest that ICU workstations may be standardized into at least two types.     

Increased nonbeneficial care in patients spending their birthday in the ICU

Objective

End-of-life decisions are based on objective and subjective criteria. Previous studies identified substantial subjective biases during end-of-life decision-making. We evaluated whether in-ICU patient’s birthday influenced management decisions.

Design

We used a case–control design in which patients spending their birthday in the ICU (cases) were matched to controls on center, gender, age, severity, type of admission, and length of ICU stay before birthday.

Setting

12 ICUs in French hospitals.

Patients

The cases and controls were patients with ICU admissions >48?h over a 10-year period.

Interventions

None.

Measurements and main results

Compared with the 1,042 controls, the 223 cases were more often trauma patients and received a larger number and longer durations of life-sustaining interventions. This increased intensity of life support occurred after, but not before, the birthday. The cases had longer ICU stay lengths. ICU and hospital mortality were not different between the two groups. End-of-life decisions were made in 22% and 24% of cases and controls, respectively. However, these decisions were made later in the cases than in the controls (18 [5–33] versus 9 [3–19]?days).

Conclusions

Our finding that patients who spent their birthday in the ICU received a higher intensity of life-sustaining care and had longer ICU stays but did not have significantly different mortality rates compared with the controls suggests the use of nonbeneficial interventions. Staff members caring for patients whose birthdays fall during the ICU stay should be aware that this feature can bias end-of-life decisions, leading to an inappropriate level of care.     

AKIpredictor,an online prognostic calculator for acute kidney injury in adult critically ill patients: development,validation and comparison to serum neutrophil gelatinase-associated lipocalin

Purpose

Early diagnosis of acute kidney injury (AKI) remains a major challenge. We developed and validated AKI prediction models in adult ICU patients and made these models available via an online prognostic calculator. We compared predictive performance against serum neutrophil gelatinase-associated lipocalin (NGAL) levels at ICU admission.

Methods

Analysis of the large multicenter EPaNIC database. Model development (n = 2123) and validation (n = 2367) were based on clinical information available (1) before and (2) upon ICU admission, (3) after 1 day in ICU and (4) including additional monitoring data from the first 24 h. The primary outcome was a comparison of the predictive performance between models and NGAL for the development of any AKI (AKI-123) and AKI stages 2 or 3 (AKI-23) during the first week of ICU stay.

Results

Validation cohort prevalence was 29% for AKI-123 and 15% for AKI-23. The AKI-123 model before ICU admission included age, baseline serum creatinine, diabetes and type of admission (medical/surgical, emergency/planned) and had an AUC of 0.75 (95% CI 0.75–0.75). The AKI-23 model additionally included height and weight (AUC 0.77 (95% CI 0.77–0.77)). Performance consistently improved with progressive data availability to AUCs of 0.82 (95% CI 0.82–0.82) for AKI-123 and 0.84 (95% CI 0.83–0.84) for AKI-23 after 24 h. NGAL was less discriminant with AUCs of 0.74 (95% CI 0.74–0.74) for AKI-123 and 0.79 (95% CI 0.79–0.79) for AKI-23.

Conclusions

AKI can be predicted early with models that only use routinely collected clinical information and outperform NGAL measured at ICU admission. The AKI-123 models are available at http://akipredictor.com/. Trial registration Clinical Trials.gov NCT00512122

     

Reliability of intensive care unit admitting and comorbid diagnoses, race, elements of Acute Physiology and Chronic Health Evaluation II score, and predicted probability of mortality in an electronic intensive care unit database

Background

Although reliability of severity of illness and predicted probability of hospital mortality have been assessed, interrater reliability of the abstraction of primary and other intensive care unit (ICU) admitting diagnoses and underlying comorbidities has not been studied.

Methods

Patient data from one ICU were originally abstracted and entered into an electronic database by an ICU nurse. A research assistant reabstracted patient demographics, ICU admitting diagnoses and underlying comorbidities, and elements of Acute Physiology and Chronic Health Evaluation II (APACHE II) score from 100 random patients of 474 admitted during 2005 using an identical electronic database. Chamberlain's percent positive agreement was used to compare diagnoses and comorbidities between the 2 data abstractors. A κ statistic was calculated for demographic variables, Glasgow Coma Score, APACHE II chronic health points, and HIV status. Intraclass correlation was calculated for acute physiology points and predicted probability of hospital mortality.

Results

Percent positive agreement for ICU primary and other admitting diagnoses ranged from 0% (primary brain injury) to 71% (sepsis), and for underlying comorbidities, from 40% (coronary artery bypass graft) to 100% (HIV). Agreement as measured by κ statistic was strong for race (0.81) and age points (0.95), moderate for chronic health points (0.50) and HIV (0.66), and poor for Glasgow Coma Score (0.36). Intraclass correlation showed a moderate-high agreement for acute physiology points (0.88) and predicted probability of hospital mortality (0.71).

Conclusion

Reliability for ICU diagnoses and elements of the APACHE II score is related to the objectivity of primary data in the medical charts.     

Octogenarians in the ICU: are you ever too old?

Long-term morbidity and mortality rates for older patients admitted to the ICU remain substantial. In this issue of Critical Care, Roch and colleagues describe a retrospective study evaluating factors associated with survival and quality-of-life of octogenarians (aged ≥80 years) admitted to a medical ICU. This study proposes to address a highly relevant and increasingly encountered scenario in ICUs - what factors can best estimate prognosis for elderly patients at the time of evaluation for ICU admission? While perhaps not unique to octogenarians, such data have the potential to better inform on decision-making regarding advanced life support along with facilitating discussion on the perceived benefit and on patient treatment preferences concerning intensive care.Despite advances in the support for older critically ill patients, the long- term morbidity and mortality rates remain substantial. In this issue of Critical Care, Roch and colleagues [1] present a retrospective cohort study evaluating the long-term survival and quality of life of 299 octogenarians (aged ≥80 years) admitted to a single French medical ICU over a 6-year period. The authors describe hospital and 2-year mortality rates of 55% and 79%, respectively. This observed mortality was significantly higher than the age and sex-matched general population. While higher illness severity score (Simplified Acute Physiology Score (SAPS) II) and the presence of fatal disease (McCabe score) were independently associated with in-hospital and 2-year mortality, surprisingly, the presence of pre-morbid functional limitation, though present in 85% of patients, was found to have little association. Of 133 surviving the index hospitalization, quality of life was prospectively assessed in 24 patients (18.0%) a median 5.3 years after hospital discharge, where overall scores for physical function were greatly reduced.While these findings are provocative and extend our knowledge of the outcomes for elderly patients suffering an episode of critical illness, this study also has important limitations that challenge its inferences and overall generalizability. First, it reflects a relatively small cohort of elderly patients admitted to a single tertiary medical ICU in France. Second, this study does not directly provide insight on the prognostic impact of age alone on long-term outcome after critical illness, due to lack of controls for comparison. Third, while 12.4% of all admissions to this ICU were aged ≥80 years, we do not know the prevalence of age-matched patients referred to, but not admitted to ICU, thus making these observations potentially susceptible to selection bias. In total, 23% of patients were classified as having treatment limitations, in terms of not being offered mechanical ventilation or renal replacement therapy; however, there is no clear information on other aspects of advanced care and/or end-of-life planning. Fourth, the intent of determining prognostic factors for long-term quality-adjusted survival at the time of evaluation for ICU admission is unmistakably important. However, it is made difficult in this study by omitting potentially important time-varying factors or other significant events that may have occurred after hospital discharge, such as repeated episodes of critical illness, hospitalization, or institutionalization. Finally, interpretation of the quality-of-life data is challenging due to the variable follow-up duration and the susceptibility to selection and recall bias.Despite these limitations, these data do provide further insight into the survival experience of critically ill octogenarians supported in an ICU [1]. One implication of these findings is that selected clinical factors at the time of evaluation for ICU admission may be able to provide a glimpse of short- and long-term prognosis for sick elderly patients and allow for better informed decision-making on advanced life support in the ICU. These were largely based on illness severity scores and advanced chronic illness.Patient severity of illness has been shown to be an important determinant of outcome of critically ill patients, including in the elderly [2-4]. However, elderly patients have generally been under-represented in the development and validation of illness severity scoring systems. Likewise, the attributable mortality for age alone has been inconsistent and appears to have diminished discriminatory power after adjustment for other clinical factors such as primary diagnosis, illness severity, co-morbidity and functional status [3].Prior investigations have found one of the strongest predictors of survival and functional recovery after critical illness in octogenarians is a patient''s pre-morbid functional status and/or disposition (that is, chronic care facility) [2,5]. One explanation may be that pre-existing functional impairment reflects a diminished repertoire of homeostatic responses to environmental stressors due to loss of physiologic reserve. Consequently, an episode of critical illness occurring in the frail elderly patient may be more likely to culminate in prolonged hospitalization, need for long-term institutionalization or death [6].In the current study, the observed association between pre-morbid status and outcome may have been negatively influenced by the high prevalence of functional limitation and pre-existing fatal disease, as assessed by the Knaus and McCabe scores, respectively. For example, 57% of the patients had diseases associated with survival of less than 5 years, and 85% had some functional limitation, with 44% classified as either severe or bedridden [1]. These factors may have also influenced the higher observed mortality at 2 years when compared to other similar studies [3,5,7]. The cumulative and subtle losses to independence and vulnerability to adverse event reflecting the loss of reserve can have a powerful impact on ICU outcome, as has been seen in the geriatric outpatient population [8,9].Unfortunately, the available literature does not provide for clear discrimination between elderly patients who will survive with a satisfactory quality of life or will either die or have severe functional limitations and reduced quality of life. Determination of prognosis early in the course of a patient presenting with critical illness is challenging and there are no reliable markers that distinguish survivors from non-survivors at the time of ICU admission [4]. Consequently, in the absence of highly specific predictors of poor outcome that could better inform decision-making on the suitability of ICU admission, it is ethically challenging to deny the potential benefits of ICU support on the basis of medical futility, poor outcome or non-maleficence. The observations in this study would appear to support this notion [1].Alternatively, observational data have suggested physician perception strongly influences patient out-come. Physician belief that life support is not wanted or that survival is unlikely is strongly associated with death and may have enormous effects on the decision-making around limitation or withdrawal of support [10]. Unfortunately, these influences are often difficult to elicit and adjust for in observational studies and have the potential to introduce bias. Notably, in this study, 23% had some limitation on support while in the ICU; however, no specific data were available on advanced or end-of-life care directives [1].Interestingly, in those studies reporting on the quality of life of octogenarians following recovery from critical illness, at least in highly selected groups, most report a perceived quality of life similar to the age-matched general population, often describe themselves as ''happy'' and would accept further ICU treatment if it was required, despite some limitations in physical function and worsening levels of dependence [7,11,12]. Indeed, while the quality-of-life assessment in this study found deficits in physical function, the scores for emotional and social well-being were relatively preserved and encouraging [1].Two large multi-center prospective observational studies will certainly add to our understanding of the quality-adjusted survival and decision-making process for critically ill octogenarians confronted with ICU admission. The French Intensive Care Unit Admission Decisions in the Elderly (ICE-CUB) trial has recently completed enrollment (n = 2,643) and will provide important insights into the decision-making processes for appropriateness of ICU admission and short- and long-term functional outcomes for critically ill octogenarians presenting to the emergency department [13]. The Canadian multi-center prospective Realities, Expectations and Attitudes to Life Support Technologies in Intensive Care for Octogenarians (REALISTIC-80) study is ongoing and will also provide significant insight into the long-term survival and quality of life of patients along with attain family caregivers'' perspective on the quality of care [14].The relevance of prognostication at the time of ICU admission for elderly patients will increasingly become more apparent, as ICUs are confronted with an aging population coupled with high societal expectations of the health care system, and data demonstrating the recent increase in utilization of critical care resources by the elderly [2,15,16]. Importantly, these data should also serve to underscore the critical importance of advanced care planning for elderly patients, including open discussion of the risk/benefit profile of ICU support in the context of perceived benefit and treatment preferences [17].