Effects of prognosis, perceived benefit, and decision style on decision making and critical care on decision making in critical care

Derivation and Validation of a Prognostic Model to Predict 6-Month Mortality in an Intensive Care Unit Population

RATIONALE

Identification of terminally ill patients in the intensive care unit (ICU) would facilitate decision making and timely palliative care.

OBJECTIVES

To develop and validate a patient-specific integrated prognostic model to predict 6-month mortality in medical ICU patients.

METHODS

A longitudinal prospective cohort study of temporally split samples of 1,049 consecutive medical ICU patients in a tertiary care hospital was performed. For each patient, we collected demographic data, Acute Physiology and Chronic Health Evaluation III score, Charlson comorbidity index, intensivist response to a surprise question (SQ; "Would I be surprised if this patient died in the next 6 months?") on admission, and vital status at 6 months.

RESULTS

Between November 2013 and May 2015, derivation and validation cohorts of 500 and 549 consecutive patients were studied to develop a multivariate logistic regression model. In the multivariate logistic regression model, Charlson comorbidity index (P = 0.033), Acute Physiology and Chronic Health Evaluation III score (P < 0.001), and SQ response (P < 0.001) were predictors of vital status at 6 months. The odds of dying within 6 months were significantly higher when the SQ was answered "no" than when it was answered "yes" (odds ratio, 7.29; P < 0.001). The c-statistic for the derivation and validation cohorts were 0.832 (95% confidence interval, 0.795-0.870) and 0.84 (95% confidence interval, 0.806-0.875), respectively.

CONCLUSIONS

Our integrated prognostic model, which includes the SQ, has strong discrimination and calibration to predict 6-month mortality in medical ICU patients. This model can aid clinicians in identifying ICU patients who may benefit from the integration of palliative care into their treatment.

The conceptualisation of health-related quality of life in decision-making by intensive care physicians: A qualitative inquiry

OBJECTIVES

To explore how intensive care physicians conceptualise and prioritise patient health-related quality of life in their decision-making.

RESEARCH METHODOLOGY/DESIGN

General qualitative inquiry using elements of Grounded Theory. Six ICU physicians participated.

SETTING

A large, closed, mixed ICU at a university-affiliated hospital, Australia.

RESULTS

Three themes emerged: (1) Multi-dimensionality of HRQoL-HRQoL was described as difficult to understand; the patient was viewed as the best informant. Proxy information on HRQoL and health preferences was used to direct clinical care, despite not always being trusted. (2) Prioritisation of HRQoL within decision-making-this varied across the patient's health care trajectory. Premorbid HRQoL was prioritised when making admission decisions and used to predict future HRQoL. (3) Role of physician in decision-making-the physicians described their role as representing society with peers influencing their decision-making. All participants considered their practice to be similar to their peers, referring to their practice as the "middle of the road". This is a novel finding, emphasising other important influences in high-stakes decision-making.

CONCLUSION

Critical care physicians conceptualised HRQoL as a multi-dimensional subjective construct. Patient (or proxy) voice was integral in establishing patient HRQoL and future health preferences. HRQoL was important in high stakes decision-making including initiating invasive and burdensome therapies or in redirecting therapeutic goals.

Power and limitations of daily prognostications of death in the medical ICU for outcomes in the following 6 months

OBJECTIVES

We tested the power of clinicians' predictions that a medical ICU patient would "die before hospital discharge" for both survival to discharge and for outcomes at 6 months.

DESIGN

We restricted our analyses to patients who had been in the medical ICU at least 72 hours and for whom we had follow-up at 6 months after medical ICU admission. For 350 medical ICU patients, on each medical ICU day, we asked their attending physician, fellow, resident, and primary nurse one question-"do you think this patient will die in hospital or survive to be discharged"? We correlated these responses with 6-month outcomes (death and/or Barthel score for survivors).

RESULTS

We obtained over 6,000 predictions on 2,271 medical ICU patient-days. Of 350 medical ICU patients who stayed more than 72 hours, 143 patients (41%) had discordant predictions-that is, on the same medical ICU day, at least one provider predicted survival, whereas another predicted death before discharge. As we have shown previously, predictions of "death before discharge" were imperfect-only 104 of 187 of patients with a prediction of death (56%) actually died in hospital. However, this is the central finding of our study, and predictions of death before discharge were much more accurate for 6-month outcomes. Of 120 patients with a corroborated prediction of death before discharge (93%), 112 patients had died within 6 months of medical ICU discharge, and only 4% were functioning with a Barthel score more than 70. In contrast, 67 of 163 patients who did not have any prediction of death before discharge (41%) were alive with Barthel score more than 70 at 6 months.

CONCLUSIONS

Fewer than 4% of medical ICU patients who required 72 hours of medical ICU care and had a corroborated prediction of death before discharge were alive at 6 months and functioning with a Barthel score more than 70.

Uncertainty in end-of-life care

PURPOSE OF REVIEW

Uncertainty surrounding medical decision-making is particularly important during end-of-life decision-making. Doubts about the patient's best interests and prognostic accuracy may lead to conflict.

RECENT FINDINGS

Many authors have suggested recently that medical attitudes to uncertainty need review. It is inappropriate to avoid discussion of uncertainty during end-of-life care and American literature suggests that patients and families accept uncertainty in end-of-life discussions. Recently, authors have advocated the concept of 'Practical Certainty' accepting that absolute certainty is rarely possible in end-of-life decision-making and openly acknowledging that the physicians are as certain as they can be in the circumstances. Allowing time to provide acceptance of a palliative care pathway and using the collective wisdom of colleagues improves the accuracy of prediction and reduces conflict at the end of life.

SUMMARY

The implications of this review are that doctors should not avoid discussing uncertainty in end-of-life conversations and the article provides some recommendations for minimizing conflict arising from end-of-life discussion.

The prediction and cost of futility in the NICU

AIM

To quantify the cost and prediction of futile care in the Neonatal Intensive Care Unit (NICU).

METHODS

We observed 1813 infants on 100,000 NICU bed days between 1999 and 2008 at the University of Chicago. We determined costs and assessed predictions of futility for each day the infant required mechanical ventilation.

RESULTS

Only 6% of NICU expenses were spent on nonsurvivors, and in this sense, they were futile. If only money spent after predictions of death is considered, futile expenses fell to 4.5%. NICU care was preferentially directed to survivors for even the smallest infants, at the highest risk to die. Over 75% of ventilated NICU infants were correctly predicted to survive on every day of ventilation by every caretaker. However, predictions of 'die before discharge' were wrong more than one time in three. Attendings and neonatology fellows tended to be optimistic, while nurses and neonatal nurse practitioners tended to be pessimistic.

CONCLUSIONS

Criticisms of the expense of NICU care find little support in these data. Rather, NICU care is remarkably well targeted to patients who will survive, particularly when contrasted with care in adult ICUs. We continue to search for better prognostic tools for individual infants.

Comparison of physician prediction with 2 prognostic scoring systems in predicting 2-year mortality after intensive care admission: a linked-data cohort study

PURPOSE

Patients who survive an episode of critical illness continue to experience significant mortality after hospital discharge. This study assessed the accuracy of physician prediction of 2-year mortality and compared it with 2 objective prognostic models.

METHODS

Sensitivity (probability of a prediction of death in patients who died within 2 years) and specificity (probability of a prediction of survival in patients who survived at least 2 years) of physicians' 2-year prediction were compared with those from 2 objective prognostic models, Acute Physiology and Chronic Health Evaluation (APACHE) II and Predicted Risk Existing Disease Intensive Care Therapy (PREDICT).

RESULTS

Physician prediction of 2-year mortality was available for 2497 (94.8%) intensive care unit admissions. Specificity was high (85.2%; 95% confidence interval [CI], 83.7-86.4), but sensitivity (65.0%; 95% CI, 61.1-68.8) and positive predictive value (57.4%; 95% CI, 53.6-61.2) were relatively low, suggesting overpessimistic prediction of 2-year mortality. Age, Charlson comorbidity index, and APACHE score were independent risk factors for an inaccurate physician prediction. The diagnostic odds ratio for the physician predictions was at least comparable with the APACHE and PREDICT models, which both had very good discrimination of mortality at 2-year follow-up.

CONCLUSIONS

Physicians tended to overpredict the risk of 2-year mortality of critically ill patients, but accuracy was comparable with 2 objective prognostic models.

Estimating long-term survival of critically ill patients: the PREDICT model

Background

Long-term survival outcome of critically ill patients is important in assessing effectiveness of new treatments and making treatment decisions. We developed a prognostic model for estimation of long-term survival of critically ill patients.

Methodology and Principal Findings

This was a retrospective linked data cohort study involving 11,930 critically ill patients who survived more than 5 days in a university teaching hospital in Western Australia. Older age, male gender, co-morbidities, severe acute illness as measured by Acute Physiology and Chronic Health Evaluation II predicted mortality, and more days of vasopressor or inotropic support, mechanical ventilation, and hemofiltration within the first 5 days of intensive care unit admission were associated with a worse long-term survival up to 15 years after the onset of critical illness. Among these seven pre-selected predictors, age (explained 50% of the variability of the model, hazard ratio [HR] between 80 and 60 years old = 1.95) and co-morbidity (explained 27% of the variability, HR between Charlson co-morbidity index 5 and 0 = 2.15) were the most important determinants. A nomogram based on the pre-selected predictors is provided to allow estimation of the median survival time and also the 1-year, 3-year, 5-year, 10-year, and 15-year survival probabilities for a patient. The discrimination (adjusted c-index = 0.757, 95% confidence interval 0.745–0.769) and calibration of this prognostic model were acceptable.

Significance

Age, gender, co-morbidities, severity of acute illness, and the intensity and duration of intensive care therapy can be used to estimate long-term survival of critically ill patients. Age and co-morbidity are the most important determinants of long-term prognosis of critically ill patients.

Just, in time: ethical implications of serial predictions of death and morbidity for ventilated premature infants

OBJECTIVES

For a cohort of extremely premature, ventilated, newborn infants, we determined the power of either serial caretaker intuitions of "die before discharge" or serial illness severity scores to predict the outcomes of death in the NICU or neurologic performance at corrected age of 2 years.

METHODS

We identified 268 premature infants who were admitted to our NICU in 1999-2004 and required mechanical ventilation. For each infant on each day of mechanical ventilation, we asked nurses, residents, fellows, and attending physicians the following question: "Do you think this child is going to live to go home or die before hospital discharge?" In addition, we calculated illness severity scores until either death or extubation.

RESULTS

A total of 17,066 intuition profiles were obtained on 5609 days of mechanical ventilation in the NICU. One hundred (37%) of 268 profiled infants had > or = 1 intuition of die before discharge. Only 33 infants (33%) with an intuition of die actually died in the NICU. Of 48 infants with even 1 day of corroborated intuition of die in the NICU, only 7 (14%) were alive with both Mental Developmental Index and Psychomotor Developmental Index scores of > 69, and only 2 (4%) were alive with both Mental Developmental Index and Psychomotor Developmental Index Scores of > 79 at corrected age of 2 years. On day of life 1, the Score for Neonatal Acute Physiology II value for nonsurvivors (38.2 +/- 18.1) was significantly higher than that for survivors (26.3 +/- 12.7). However, this difference decreased steadily over time as scores improved for both groups.

CONCLUSIONS

Illness severity scores become progressively less helpful over time in distinguishing infants who will either die in the NICU or survive with low Mental Developmental Index/Psychomotor Developmental Index scores. Serial caretaker intuitions of die before discharge also fail to identify prospective nonsurviving infants. However, corroborated intuitions of die before discharge identify a subset of infants whose likelihood of surviving to 2 years with both MDI and PDI > 80 is approximately 4%.

Views and approaches toward risks and benefits among doctors who become patients

OBJECTIVE

To understand how views and approaches concerning risks and benefits may be affected by dynamic contexts and processes related to clinical roles and relationships.

METHODS

We conducted two in-depth, semi-structured interviews with 50 doctors who became patients due to serious illnesses, concerning their experiences before and after diagnosis.

RESULTS

As patients, these doctors gained critical new insights into the processes and contexts of communication about risks and benefits. Doctors and patients often varied in how they viewed and weighed risks and benefits (e.g., as "good' or "bad"). These data suggest a model in which patients undergo several dynamic processes: seeking statistics, accepting doctors' framing of statistics, being influenced by media hype, seeing statistics as relevant or not, over-valuing risks, weighing the importance of risks and benefits, interpreting statistics as good or bad, accepting or denying statistics and odds, and making treatment decisions. These processes are affected by external factors (e.g., doctors ordering tests, framing statistics, and often over- versus under-valuing risks), and internal factors (e.g., depression, denial of illness, optimism versus pessimism, magical thinking--that doctors are immune to disease--and rationalizations).

CONCLUSIONS

Doctors and patients are engaged in complex, dynamic processes that shape patients' approaches toward risks and benefits.

PRACTICE IMPLICATIONS

These data highlight the need for increased attention toward these issues in medical educational and care.

A comparative study examining the decision-making processes of medical and nursing staff in weaning patients from mechanical ventilation

A prolonged period of mechanical ventilation is costly for both the patient, in terms of the risk of complications such as ventilator-acquired pneumonia, and to the health service due to the high cost of maintaining a patient in intensive care. The recognition of the role nurses can play in the weaning process and the desire to try and reduce weaning times led to the introduction of nurse-managed weaning on the intensive care unit which is the focus of this study. This means that both doctors and nurses are now responsible for making decisions about weaning. Flexible guidelines for weaning were devised which still require a large element of individual, clinical decision-making during the process. At every stage in the weaning process clinicians are required to make judgments about patient responses, using these judgments as the basis for their decision-making. This study examined the ways doctors and nurses make these decisions. Semi-structured interviews were conducted with doctors and senior nurses. A grounded theory approach was used to analyse the results and the key themes of Treatment, Balance, Making Progress and The Individual were identified which were found to be linked with particular methods of decision-making.

Clinician discomfort with life support plans for mechanically ventilated patients

OBJECTIVE

To examine the incidence and predictors of clinician discomfort with life support plans for ICU patients.

DESIGN AND SETTING

Prospective cohort in 13 medical-surgical ICUs in four countries.

PATIENTS

657 mechanically ventilated adults expected to stay in ICU at least 72 h.

MEASUREMENTS AND RESULTS

Daily we documented the life support plan for mechanical ventilation, inotropes and dialysis, and clinician comfort with these plans. If uncomfortable, clinicians stated whether the plan was too technologically intense (the provision of too many life support modalities or the provision of any modality for too long) or not intense enough, and why. At least one clinician was uncomfortable at least once for 283 (43.1%) patients, primarily because plans were too technologically intense rather than not intense enough (93.9% vs. 6.1%). Predictors of discomfort because plans were too intense were: patient age, medical admission, APACHE II score, poor prior functional status, organ dysfunction, dialysis in ICU, plan to withhold dialysis, plan to withhold mechanical ventilation, first week in the ICU, clinician, and city.

CONCLUSIONS

Clinician discomfort with life support perceived as too technologically intense is common, experienced mostly by nurses, variable across centers, and is more likely for older, severely ill medical patients, those with acute renal failure, and patients lacking plans to forgo reintubation and ventilation. Acknowledging the sources of discomfort could improve communication and decision making.

Medical futility: predicting outcome of intensive care unit patients by nurses and doctors--a prospective comparative study

OBJECTIVE

First, to assess the pattern of the prediction of intensive care unit patients' outcome with regard to survival and quality of life by nurses and doctors and, second, to compare these predictions with the quality of life reported by the surviving patients.

DESIGN

Prospective opinion survey of critical care providers; comparison with follow-up for survival, functional status, and quality of life.

SETTING

Six-bed medical intensive care unit subunit of a 1,000-bed tertiary care, university hospital.

PATIENTS

All patients older than 18 yrs, admitted to the medical intensive care unit for >24 hrs over a 1-yr period (December 1997 to November 1998).

INTERVENTIONS

Daily judgment of eventual futility of medical interventions by nurses and doctors with respect to survival and future quality of life. Telephone interviews with discharged patients for quality of life and functional status 6 months after intensive care unit admission.

MEASUREMENTS AND MAIN RESULTS

Data regarding 521 patients including 1,932 daily judgments by nurses and doctors were analyzed. Disagreement on at least one of the daily judgments by nurses and doctors was found in 21% of all patients and in 63% of the dying patients. The disagreements more frequently concerned quality of life than survival. The higher the Simplified Acute Physiology Score and the longer the intensive care unit stay, the more divergent judgments were observed (p <.001). In surviving and dying patients, nurses gave more pessimistic judgment and considered withdrawal more often than did doctors (p <.001). Patients only rarely indicated bad quality of life (6%) and severe physical disability (2%) 6 months after intensive care unit admission. Compared with patients' own assessment, neither nurses nor doctors correctly predicted quality of life; false pessimistic and false optimistic appreciation was given.

CONCLUSIONS

Disagreement between nurses and doctors was frequent with respect to their judgment of futility of medical interventions. Disagreements most often concerned the most severely ill patients. Nurses, being more pessimistic in general, were more often correct than doctors in the judgment of dying patients but proposed treatment withdrawal in some very sick patients who survived. Future quality of life cannot reliably be predicted either by doctors or by nurses.

Serial assessment of mortality in the neonatal intensive care unit by algorithm and intuition: certainty, uncertainty, and informed consent

OBJECTIVES

Does predictive power for outcomes of neonatal intensive care unit (NICU) patients get better with time? Or does it get worse? We determined the predictive power of Score for Neonatal Acute Physiology (SNAP) scores and clinical intuitions as a function of day of life (DOL) for newborn infants admitted to our NICU.

METHODS

We identified 369 infants admitted to our NICU during 1996-1997 who required mechanical ventilation. We calculated SNAP scores on DOL 1, 3, 4, 5, 7, 10, 14, 21, 28, and weekly thereafter until either death or extubation. We also asked nurses, residents, fellows, and attendings on each day of mechanical ventilation: "Do you think this child is going to live to go home to their family, or die before hospital discharge?"

RESULTS

Two thousand twenty-eight SNAP scores were calculated for 285 infants. On DOL 1, SNAP for nonsurvivors (24 +/- 8.7 [standard deviation]) was significantly higher than SNAP for survivors (13 +/- 6.1). However, this difference diminished steadily and by DOL 10 was no longer statistically significant (12.7 +/- 4.9 vs 10.0 +/- 4.8). On each NICU day, at all ranges of SNAP scores, there were at least as many infants who would ultimately survive as would die. Consequently, the positive predictive value of any SNAP value for subsequent mortality was <0.5 on all NICU days. Prediction profiles were obtained for 230 ventilated infants reflecting over 11 000 intuitions obtained on 2867 patient days. One hundred fifty-seven (81%) of 192 survivor profiles displayed consistent accurate prediction profiles-at least 90% of their NICU ventilation days were characterized by 100% prediction of survival. Twenty-five (13%) of 192 surviving infants survived somewhat unexpectedly; that is, after at least 1 day characterized by at least 1 estimate of "death." Thirty-three (60%) of the 55 nonsurvivors died before DOL 10. Eighty-two percent of the prediction profiles for these early dying infants were homogeneous, dismal, and accurate. Twenty-two (40%) of the 55 nonsurvivors died after DOL 10. Seventeen (78%) of these 22 late-dying infants were predicted to live by many observers on many hospital days. Sixty-one (30%) of 230 profiled patients had at least 1 NICU day characterized by at least 1 prediction of death; 26/61 (43%) of these patients were incorrectly predicted; that is, they survived. Seventeen infants who were predicted to die during but survived nonetheless were assessed neurologically at 1 year. Fourteen (82%) of these 17 were not neurologically normal-8 were clearly abnormal, 1 suspicious, and 5 had died.

CONCLUSIONS

If absolute certainty about mortality is the only criterion that can justify a decision to withhold or withdraw life-sustaining treatment in the NICU, these data would make such decisions difficult on the first day of life, and increasingly problematic thereafter. However, if we acknowledge that medicine is inevitably an inexact science and that clinical predictions can never be perfect, we can ask the more interesting question of whether good but less-than-perfect predictions of imprecise but ethically relevant clinical outcomes can still be useful. We think that they can-and that they must.

What do physicians think about evidence-based antibiotic use in critical care? A survey of Australian intensivists and infectious disease practitioners

BACKGROUND

The analysis of factors that influence prescribing decisions is increasingly important. Antibiotic use is often based on limited evidence and lack of information about clinical decision-making processes is an important obstacle to improving antibiotic utilization.

AIMS

To compare the attitudes of intensive care unit practitioners (ICUP) and infectious disease practitioners (IDP) to antibiotic use and to the evidence-based information support.

METHOD

A postal survey conducted between March and July 2000 of ICUP and IDP representing all States and Territories in Australia.

RESULTS

One hundred and fifty-three of 224 clinicians returned the questionnaire (68.3% response rate). In choosing an antibiotic, IDP placed significantly more weight than ICUP on the in vitro susceptibility of the pathogen (P = 0.001), antibiotic cost (P = 0.05) and possible development of antibiotic resistance (P = 0.007). More than 95% of both groups believed that unit-specific antibiotic susceptibility of endemic pathogens was an essential factor in rational prescribing, but only 68.5% of IDP and 38.7% of ICUP use microbiology laboratory databases. When in doubt about appropriate antibiotic use, 63.8% of ICUP seek and 76.3% usually follow the advice of IDP. Both groups agree that published antibiotic guidelines are useful, but IDP were more likely to consult them. ICUP were more likely to believe that guidelines are used to control clinicians rather than to improve quality of care (P = 0.001). A greater proportion of IDP (71.2%) than ICUP (52.5%) believed that antibiotic prescribing in their intensive care unit (ICU) was evidence based but most (91.8% and 86.9%, respectively) agreed that it should be.

CONCLUSIONS

Australian clinicians have positive views about evidence-based prescribing and antibiotic guidelines. However, there are clinically significant differences in prescribing behaviour between ICUP and IDP. These may be explained by different disease spectra managed by each group or different cultures, training and/or cognitive styles. Improvements in the understanding of physicians' information and decision support needs are required to strengthen evidence-based prescribing.

Biomedical ethics and the withdrawal of advanced life support

It is common for health care providers to deal with the complex and difficult issue of withdrawing advanced life support. The patient is always the key source of authority in these decisions. The most important ingredient in end-of-life decision making is effective communication. It is important to try to ascertain what the patient thought about quality-of-life values before surrogate decisions can be made on the patient's behalf. The concepts of beneficence, nonmaleficence, autonomy, and justice are the foundation of ethical decision making. Numerous legal precedents have laid the groundwork for end-of-life decision making. Most state courts have supported withholding and withdrawing life support from patients who will not regain a reasonable quality of life. The recent Patient Self-Determination Act encourages patients to fill out advance directives that state their desires. When continued intensive care is futile, advanced life support should be withdrawn. However, a narrow definition of futility in this situation is the key, since the concept of futility could lead to inappropriate decisions. It is best to consider a situation futile when the patient is terminally ill, the condition is irreversible, and death is imminent. During the withdrawal of advanced life support, terminal or rapid weaning is preferable to extubation. Combinations of opiates, benzodiazepines, and other agents help provide comfort to patients who are suffering.