A Scenario-Based, Randomized Trial of Patient Values and Functional Prognosis on Intensivist Intent to Discuss Withdrawing Life Support*

Turnbull, Alison E.; Krall, Jenna R.; Ruhl, A. Parker; Curtis, J. Randall; Halpern, Scott D.; Lau, Bryan; Needham, Dale M.

doi:10.1097/ccm.0000000000000227

Cited by 44 publications

(37 citation statements)

References 29 publications

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“…Academic intensivists were identified from a database of academic critical care physicians in critical care fellowship programs that was first developed in 2006 22 and updated in 2012. 23 After distributing the e-mail invitations, we conducted a manual search of the internet using the Google search engine to find updated e-mail addresses for intensivists whose invitations bounced back.…”

Section: Methodsmentioning

confidence: 99%

ICU Attending Handoff Practices

Lane‐Fall

Collard

Turnbull

et al. 2016

Critical Care Medicine

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Objective To characterize intensivist handoff practices and expectations and to explore perceptions of the patient safety implications of attending handoffs. Design Cross-sectional electronic survey administered in 2014. Setting One hundred sixty nine U.S. hospitals with critical care training programs accredited by the Accreditation Council for Graduate Medical Education. Subjects Academic intensivists recruited via e-mail invitation from a database of 1,712 eligible academic intensivists. Interventions None. Measurements and Main Results 661 intensivists completed the survey (completion rate 38.6%). Responses were received from at least one individual at 147 of 169 (87.0%) unique hospitals represented in the study database. 573 (87%) respondents reported participating in handoffs at the end of each ICU rotation. A variety of communication methods were used for end-of-rotation handoffs including in-person discussion (92.9%), telephone calls (83.9%), e-mail messages (69.0%), computer-generated documents (64.6%), and text messages (23.6%). Mean satisfaction with current handoff process was rated as 68.4 on a scale from 0-100 (SD 22.6). 55.4% of respondents said that attending handoffs should be standardized, but only 13.3% (76/572) of those participating in end-of-rotation handoffs reported using a standardized process. Specific handoff topics, including active clinical issues and resuscitation status, were reportedly discussed less frequently than would be ideal (p < 0.001 for the difference between reported frequency and ideal frequency). In free-text comments, 76 (11.5%) respondents expressed skepticism that attending handoffs were necessary given the presence of residents and fellows and given a lack of agreement about necessary content. 200 respondents (30.8%) reported knowing of an adverse event (inappropriate treatment, cardiac arrest, death) attributable to inadequate attending handoffs. Conclusions ICU attending handoffs in the United States exhibit marked heterogeneity, and intensivists do not agree about the value of attending handoffs. Additionally, some intensivists perceive a link between suboptimal attending handoffs, inappropriate treatment, and serious adverse events that warrants further study.

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Section: Methodsmentioning

confidence: 99%

ICU Attending Handoff Practices

Lane‐Fall

Collard

Turnbull

et al. 2016

Critical Care Medicine

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“…It is possible that inclusion of additional variables could have improved the discrimination of the model, but this would be a subject for future prospective studies. Finally, the ProVent 14 model predicts one-year mortality, but it does not provide information on long-term physical or cognitive function, which would also be of significant importance in decision making and should be an objective of future research 41 .…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Mortality Prediction Model for Patients Receiving 14 Days of Mechanical Ventilation

Hough

Caldwell

Cox

et al. 2016

Survey of Anesthesiology

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Objectives-The existing risk prediction model for patients requiring prolonged mechanical ventilation is not applicable until after 21 days of mechanical ventilation. We sought to develop and validate a mortality prediction model for patients earlier in the ICU course using data from day 14 of mechanical ventilation.Study Design-Multi-center retrospective cohort study.Patients-Adult patients receiving at least 14 days of mechanical ventilation at 5 medical centers (development cohort) or enrolled in the ARDS Network FACTT trial (validation cohort). HHS Public Access Author Manuscript Author ManuscriptAuthor Manuscript Author ManuscriptMeasurements and Main Results-Predictor variables were measured on day 14 of mechanical ventilation in the development cohort and included in a logistic regression model with one-year mortality as the outcome. Variables were sequentially eliminated to develop the ProVent 14 model. This model was then generated in the validation cohort. A simplified prognostic scoring rule (ProVent 14 Score) using categorical variables was created in the development cohort and then tested in the validation cohort. Model discrimination was assessed by the area under the receiver-operator characteristic curve (AUC).491 patients and 245 patients were included in the development and validation cohorts, respectively. The most parsimonious model included age, platelet count, requirement for vasopressors, requirement for hemodialysis, and non-trauma admission. The AUC for the ProVent 14 model using continuous variables was 0.80 (95% CI, 0.76-0.83) in the development cohort and 0.78 (95% CI, 0.72-0.83) in the validation cohort. The ProVent 14 Score categorized age at 50 and 65 years old, and categorized platelet count at 100 × 10 9 /L, and had similar discrimination as the ProVent 14 model in both cohorts.Conclusion-Using clinical variables available on day 14 of mechanical ventilation, the ProVent14 model can identify patients receiving prolonged mechanical ventilation with a high risk of mortality within one year. KeywordsProlonged mechanical ventilation; outcomes; prognosis; critical care; communication; multiple organ failure; decision makingFor an increasing number of patients, critical illness or injury is neither self-limited nor imminently fatal 1 . As survival from life-threatening illness improves, pre-existing disease and newly-acquired organ dysfunction may conspire against recovery, leaving patients dependent on life supporting therapies for extended time periods. This syndrome, termed "chronic critical illness", is commonly typified by persistent respiratory failure that requires prolonged mechanical ventilation (PMV). Long-term mortality is high, approaching rates of 40% to 60% at one-year in inclusive cohorts [2][3][4][5][6][7][8][9][10] . Patients have a very high symptom burden during the weeks of prolonged ventilation 11,12 and chances of living at home with functional independence at the end of the year are as low as 10% 9,13 .Most PMV patients are unable to participate in thei...

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“…Additionally, this population is particularly prone to withdrawal of care in the ICU, a decision that may be motivated in part by concerns that survival would be associated with intolerable long-term functional outcomes. (12)…”

Section: Introductionmentioning

confidence: 99%

Long-Term Outcomes After Severe Shock

Pratt¹,

Jones²,

Kuttler³

et al. 2015

Shock

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Background Severe shock is a life-threatening condition with very high short-term mortality. Whether the long-term outcomes among survivors of severe shock are similar to long-term outcomes of other critical illness survivors is unknown. We therefore sought to assess long-term survival and functional outcomes among 90-day survivors of severe shock and determine whether clinical predictors were associated with outcomes. Methods Seventy-six patients who were alive 90 days after severe shock (received ≥1 mcg/kg/min of norepinephrine equivalent) were eligible for the study. We measured three-year survival and long-term functional outcomes using the Medical Outcomes Study 36-Item Short-Form Health Survey, the EuroQOL 5-D-3L, the Hospital Anxiety and Depression Scale, the Impact of Event Scale-Revised and an employment instrument. We also assessed the relationship between in-hospital predictors and long-term outcomes. Results The mean long-term survival was 5.1 years: 82% (62/76) of patients survived, of whom 49 were eligible for follow-up. Patients who died were older than patients who survived. Thirty-six patients completed a telephone interview a mean of five years after hospital admission. The patients’ Physical Functioning scores were below US population norms (p<0.001), whereas mental health scores were similar to population norms. Nineteen percent of the patients had symptoms of depression, 39% had symptoms of anxiety and 8% had symptoms of posttraumatic stress disorder. Thirty-six percent were disabled, and 17% were working full time. Conclusions Early survivors of severe shock had a high three-year survival rate. Patients’ long term physical and psychological outcomes were similar to those reported for cohorts of less severely ill ICU survivors. Anxiety and depression were relatively common, but only a few patients had symptoms of posttraumatic stress disorder. This study supports the observation that acute illness severity does not determine long-term outcomes. Even extremely critically ill patients have similar outcome to general ICU survivor populations.

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A Scenario-Based, Randomized Trial of Patient Values and Functional Prognosis on Intensivist Intent to Discuss Withdrawing Life Support*

Cited by 44 publications

References 29 publications

ICU Attending Handoff Practices

ICU Attending Handoff Practices

Development and Validation of a Mortality Prediction Model for Patients Receiving 14 Days of Mechanical Ventilation

Long-Term Outcomes After Severe Shock

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