Predictors of time to death after terminal withdrawal of mechanical ventilation in the ICU

Predicting time to asystole following withdrawal of life-sustaining treatment: a systematic review

The planned withdrawal of life-sustaining treatment is a common practice in the intensive care unit for patients where ongoing organ support is recognised to be futile. Predicting the time to asystole following withdrawal of life-sustaining treatment is crucial for setting expectations, resource utilisation and identifying patients suitable for organ donation after circulatory death. This systematic review evaluates the literature for variables associated with, and predictive models for, time to asystole in patients managed on intensive care units. We conducted a comprehensive structured search of the MEDLINE and Embase databases. Studies evaluating patients managed on adult intensive care units undergoing withdrawal of life-sustaining treatment with recorded time to asystole were included. Data extraction and PROBAST quality assessment were performed and a narrative summary of the literature was provided. Twenty-three studies (7387 patients) met the inclusion criteria. Variables associated with imminent asystole (<60 min) included: deteriorating oxygenation; absence of corneal reflexes; absence of a cough reflex; blood pressure; use of vasopressors; and use of comfort medications. We identified a total of 20 unique predictive models using a wide range of variables and techniques. Many of these models also underwent secondary validation in further studies or were adapted to develop new models. This review identifies variables associated with time to asystole following withdrawal of life-sustaining treatment and summarises existing predictive models. Although several predictive models have been developed, their generalisability and performance varied. Further research and validation are needed to improve the accuracy and widespread adoption of predictive models for patients managed in intensive care units who may be eligible to donate organs following their diagnosis of death by circulatory criteria.

Effectiveness of an Algorithmic Approach to Ventilator Withdrawal at the End of Life: A Stepped Wedge Cluster Randomized Trial

Background: The transition to spontaneous breathing puts patients who are undergoing ventilator withdrawal at high risk for developing respiratory distress. A patient-centered algorithmic approach could standardize this process and meet unique patient needs because a single approach (weaning vs. one-step extubation) does not capture the needs of a heterogenous population undergoing this palliative procedure. Objectives: (1) Demonstrate that the algorithmic approach can be effective to ensure greater patient respiratory comfort compared to usual care; (2) determine differences in opioid or benzodiazepine use; (3) predict factors associated with duration of survival. Design/Settings/Measures: A stepped-wedge cluster randomized design at five sites was used. Sites crossed over to the algorithm in random order after usual care data were obtained. Patient comfort was measured with the Respiratory Distress Observation Scale© (RDOS) at baseline, at ventilator off, and every 15-minutes for an hour. Parenteral morphine and lorazepam equivalents from the onset of the process until patient death were calculated. Results: Usual care data n = 120, algorithm data n = 48. Gender and race were evenly distributed. All patients in the usual care arm underwent a one-step ventilator cessation; 58% of patients in the algorithm arm were weaned over an average of 18 ± 27 minutes as prescribed in the algorithm. Patients had significantly less respiratory distress in the intervention arm (F = 10.41, p = 0.0013, effective size [es] = 0.49). More opioids (t = -2.30, p = 0.023) and benzodiazepines (t = -2.08, p = 0.040) were given in the control arm. Conclusions: The algorithm was effective in ensuring patient respiratory comfort. Surprisingly, more medication was given in the usual care arm; however, less may be needed when distress is objectively measured (RDOS), and treatment is initiated as soon as distress develops as in the algorithm. Clinical Trial Registration number: NCT03121391.

Analgesia and Sedation at Terminal Extubation: A Secondary Analysis From Death One Hour After Terminal Extubation Study Data

OBJECTIVES

To describe the doses of opioids and benzodiazepines administered around the time of terminal extubation (TE) to children who died within 1 hour of TE and to identify their association with the time to death (TTD).

DESIGN

Secondary analysis of data collected for the Death One Hour After Terminal Extubation study.

SETTING

Nine U.S. hospitals.

PATIENTS

Six hundred eighty patients between 0 and 21 years who died within 1 hour after TE (2010-2021).

MEASUREMENTS AND MAIN RESULTS

Medications included total doses of opioids and benzodiazepines 24 hours before and 1 hour after TE. Correlations between drug doses and TTD in minutes were calculated, and multivariable linear regression performed to determine their association with TTD after adjusting for age, sex, last recorded oxygen saturation/F io2 ratio and Glasgow Coma Scale score, inotrope requirement in the last 24 hours, and use of muscle relaxants within 1 hour of TE. Median age of the study population was 2.1 years (interquartile range [IQR], 0.4-11.0 yr). The median TTD was 15 minutes (IQR, 8-23 min). Forty percent patients (278/680) received either opioids or benzodiazepines within 1 hour after TE, with the largest proportion receiving opioids only (23%, 159/680). Among patients who received medications, the median IV morphine equivalent within 1 hour after TE was 0.75 mg/kg/hr (IQR, 0.3-1.8 mg/kg/hr) ( n = 263), and median lorazepam equivalent was 0.22 mg/kg/hr (IQR, 0.11-0.44 mg/kg/hr) ( n = 118). The median morphine equivalent and lorazepam equivalent rates after TE were 7.5-fold and 22-fold greater than the median pre-extubation rates, respectively. No significant direct correlation was observed between either opioid or benzodiazepine doses before or after TE and TTD. After adjusting for confounding variables, regression analysis also failed to show any association between drug dose and TTD.

CONCLUSIONS

Children after TE are often prescribed opioids and benzodiazepines. For patients dying within 1 hour of TE, TTD is not associated with the dose of medication administered as part of comfort care.

Breaking bad news in the era of artificial intelligence and algorithmic medicine: an exploration of disclosure and its ethical justification using the hedonic calculus

An appropriate ethical framework around the use of Artificial Intelligence (AI) in healthcare has become a key desirable with the increasingly widespread deployment of this technology. Advances in AI hold the promise of improving the precision of outcome prediction at the level of the individual. However, the addition of these technologies to patient-clinician interactions, as with any complex human interaction, has potential pitfalls. While physicians have always had to carefully consider the ethical background and implications of their actions, detailed deliberations around fast-moving technological progress may not have kept up. We use a common but key challenge in healthcare interactions, the disclosure of bad news (likely imminent death), to illustrate how the philosophical framework of the 'Felicific Calculus' developed in the eighteenth century by Jeremy Bentham, may have a timely quasi-quantitative application in the age of AI. We show how this ethical algorithm can be used to assess, across seven mutually exclusive and exhaustive domains, whether an AI-supported action can be morally justified.

Palliative Ventilator Withdrawal Practices in an Inpatient Hospice Unit

Background

Palliative ventilator withdrawal (PVW) involves removal of mechanical ventilation in patients not expected to survive to allow a peaceful death. This process traditionally occurs in Intensive Care Units (ICU) and recently has evolved to occur in Inpatient Hospice and Palliative Care Units (IPU).

Objectives

To describe the process and response of patients undergoing PVW in an IPU setting.

Methods

This is a longitudinal observational cohort study of adult patients who underwent PVW in an IPU from January 2021 through March 2022.

Results

Among 25 enrolled subjects, median age was 68 (IQR 62.5-76.5) years and 14 (56%) were females. Median time from PVW to death was 16.8 (IQR 2.6-100) hours. A registered nurse and attending physician were present in all the cases, while a respiratory therapist was present in 20 (80%) and chaplain in 9 (36%) of the cases. Before PVW, opioids and benzodiazepines were administered to 24 (96%) patients. Post PVW, respiratory distress was noted among 16 (64%) patients and medication was given to 15 (60%) patients for respiratory distress. There was a significant association between the presence of respiratory distress and administration of medication within 30 minutes after PVW ( P = .009). The rituals performed during PVW were reciting prayers for 11 (44%), playing music for 8 (32%), and observing silence for 6 (24%) of the patients.

Conclusion

This study describes the PVW practices in an IPU setting where a multidisciplinary team was present during PVW for most of the cases and two-third of the patients undergoing PVW experienced respiratory distress immediately after PVW.

Predicting Time to Death After Withdrawal of Life-Sustaining Treatment in Children

Accurately predicting time to death after withdrawal of life-sustaining treatment is valuable for family counseling and for identifying candidates for organ donation after cardiac death. This topic has been well studied in adults, but literature is scant in pediatrics. The purpose of this report is to assess the performance and clinical utility of the available tools for predicting time to death after treatment withdrawal in children.

Evolution of Investigating Informed Assent Discussions about CPR in Seriously Ill Patients

CONTEXT

Outcomes after cardiopulmonary resuscitation (CPR) remain poor. We have spent 10 years investigating an "informed assent" (IA) approach to discussing CPR with chronically ill patients/families. IA is a discussion framework whereby patients extremely unlikely to benefit from CPR are informed that unless they disagree, CPR will not be performed because it will not help achieve their goals, thus removing the burden of decision-making from the patient/family, while they retain an opportunity to disagree.

OBJECTIVES

Determine the acceptability and efficacy of IA discussions about CPR with older chronically ill patients/families.

METHODS

This multi-site research occurred in three stages. Stage I determined acceptability of the intervention through focus groups of patients with advanced COPD or malignancy, family members, and physicians. Stage II was an ambulatory pilot randomized controlled trial (RCT) of the IA discussion. Stage III is an ongoing phase 2 RCT of IA versus attention control in in patients with advanced chronic illness.

RESULTS

Our qualitative work found the IA approach was acceptable to most patients, families, and physicians. The pilot RCT demonstrated feasibility and showed an increase in participants in the intervention group changing from "full code" to "do not resuscitate" within two weeks after the intervention. However, Stages I and II found that IA is best suited to inpatients. Our phase 2 RCT in older hospitalized seriously ill patients is ongoing; results are pending.

CONCLUSIONS

IA is a feasible and reasonable approach to CPR discussions in selected patient populations.

Discordances Between Factors Associated With Withholding Extubation and Extubation Failure After a Successful Spontaneous Breathing Trial

OBJECTIVES

To identify whether factors associated with withholding extubation in the ICU also predict the risk of extubation failure.

DESIGN

Retrospective cohort study.

SETTING

Eight medical-surgical ICUs in Toronto.

PATIENTS

Adult patients receiving invasive mechanical ventilation, with a first successful spontaneous breathing trial within 28 days of initial ICU admission.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The primary end point had three mutually exclusive levels, including: 1) withholding extubation after a successful spontaneous breathing trial, 2) extubation failure within 48 hours, and 3) successful extubation. Among 9,910 patients, 38% of patients were not extubated within 24 hours of their first successful spontaneous breathing trial. A total of 12.9% of patients who were promptly extubated failed within the next 48 hours. Several discrepancies were evident in the association of factors with risk of withholding extubation and extubation failure. Specifically, both age and female sex were associated with withholding extubation (odds ratio, 1.07; 95% CI, 1.03-1.11; and odds ratio, 1.13; 95% CI, 1.02-1.26, respectively) but not a higher risk of failed extubation (odds ratio, 0.99; 95% CI, 0.93-1.05; and odds ratio, 0.93; 95% CI, 0.77-1.11, respectively). Conversely, both acute cardiovascular conditions and intubation for hypoxemic respiratory failure were associated with a higher risk of failed extubation (odds ratio, 1.32; 95% CI, 1.06-1.66; and odds ratio, 1.46; 95% CI, 1.16-1.82, respectively) but not a higher odds of a withheld extubation attempt (odds ratio, 0.79; 95% CI, 0.68-0.91; and odds ratio, 1.07; 95% CI, 0.93-1.23, respectively).

CONCLUSIONS

Several factors showed discordance between the decision to withhold extubation and the risk of extubation failure. This discordance may lead to longer duration of mechanical ventilation or higher reintubation rates. Improving the decision-making behind extubation may help to reduce both exposure to invasive mechanical ventilation and extubation failure.

Machine Learning to Predict Cardiac Death Within 1 Hour After Terminal Extubation

OBJECTIVES

Accurate prediction of time to death after withdrawal of life-sustaining therapies may improve counseling for families and help identify candidates for organ donation after cardiac death. The study objectives were to: 1) train a long short-term memory model to predict cardiac death within 1 hour after terminal extubation, 2) calculate the positive predictive value of the model and the number needed to alert among potential organ donors, and 3) examine associations between time to cardiac death and the patient's characteristics and physiologic variables using Cox regression.

DESIGN

Retrospective cohort study.

SETTING

PICU and cardiothoracic ICU in a tertiary-care academic children's hospital.

PATIENTS

Patients 0-21 years old who died after terminal extubation from 2011 to 2018 (n = 237).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The median time to death for the cohort was 0.3 hours after terminal extubation (interquartile range, 0.16-1.6 hr); 70% of patients died within 1 hour. The long short-term memory model had an area under the receiver operating characteristic curve of 0.85 and a positive predictive value of 0.81 at a sensitivity of 94% when predicting death within 1 hour of terminal extubation. About 39% of patients who died within 1 hour met organ procurement and transplantation network criteria for liver and kidney donors. The long short-term memory identified 93% of potential organ donors with a number needed to alert of 1.08, meaning that 13 of 14 prepared operating rooms would have yielded a viable organ. A Cox proportional hazard model identified independent predictors of shorter time to death including low Glasgow Coma Score, high Pao2-to-Fio2 ratio, low-pulse oximetry, and low serum bicarbonate.

CONCLUSIONS

Our long short-term memory model accurately predicted whether a child will die within 1 hour of terminal extubation and may improve counseling for families. Our model can identify potential candidates for donation after cardiac death while minimizing unnecessarily prepared operating rooms.

Terminal withdrawal of mechanical ventilation in adult intensive care units: A systematic review and narrative synthesis of perceptions, experiences and practices

BACKGROUND

During the terminal withdrawal of life-sustaining measures for intensive care patients, the removal of respiratory support remains an ambiguous practice. Globally, perceptions and experiences of best practice vary due to the limited evidence in this area.

AIM

To identify, appraise and synthesise the latest evidence around terminal withdrawal of mechanical ventilation in adult intensive care units specific to perceptions, experiences and practices.

DESIGN

Mixed methods systematic review and narrative synthesis. A review protocol was registered on PROSPERO (CRD42018086495).

DATA SOURCES

Four electronic databases were systematically searched (Medline, Embase, CENTRAL and CINAHL). Obtained articles published between January 2008 and January 2020 were screened for eligibility. All included papers were appraised using relevant appraisal tools.

RESULTS

Twenty-five papers were included in the review. Findings from the included papers were synthesised into four themes: 'clinicians' perceptions and practices'; 'time to death and predictors'; 'analgesia and sedation practices'; 'physiological and psychological impact'.

CONCLUSIONS

Perceptions, experiences and practices of terminal withdrawal of mechanical ventilation vary significantly across the globe. Current knowledge highlights that the time to death after withdrawal of mechanical ventilation is very short. Predictors for shorter duration could be considered by clinicians and guide the choice of pharmacological interventions to address distressing symptoms that patients may experience. Clinicians ought to prepare patients, families and relatives for the withdrawal process and the expected progression and provide them with immediate and long-term support following withdrawal. Further research is needed to improve current evidence and better inform practice guidelines.

Mechanical ventilation withdrawal as a palliative procedure in a Brazilian intensive care unit

Objective

To describe the characteristics and outcomes of patients undergoing mechanical ventilation withdrawal and to compare them to mechanically ventilated patients with limitations (withhold or withdrawal) of life-sustaining therapies but who did not undergo mechanical ventilation withdrawal.

Methods

This was a retrospective cohort study from January 2014 to December 2018 of mechanically ventilated patients with any organ support limitation admitted to a single intensive care unit. We compared patients who underwent mechanical ventilation withdrawal and those who did not regarding intensive care unit and hospital mortality and length of stay in both an unadjusted analysis and a propensity score matched subsample. We also analyzed the time from mechanical ventilation withdrawal to death.

Results

Out of 282 patients with life-sustaining therapy limitations, 31 (11%) underwent mechanical ventilation withdrawal. There was no baseline difference between groups. Intensive care unit and hospital mortality rates were 71% versus 57% and 93% versus 80%, respectively, among patients who underwent mechanical ventilation withdrawal and those who did not. The median intensive care unit length of stay was 7 versus 8 days (p = 0.6), and the hospital length of stay was 9 versus 15 days (p = 0.015). Hospital mortality was not significantly different (25/31; 81% versus 29/31; 93%; p = 0.26) after matching. The median time from mechanical ventilation withdrawal until death was 2 days [0 - 5], and 10/31 (32%) patients died within 24 hours after mechanical ventilation withdrawal.

Conclusion

In this Brazilian report, mechanical ventilation withdrawal represented 11% of all patients with treatment limitations and was not associated with increased hospital mortality after propensity score matching on relevant covariates.

Palliative extubation: five-year experience in a pediatric hospital

OBJECTIVE

To present the characteristics of pediatric patients with chronic and irreversible diseases submitted to palliative extubation.

METHOD

This is a descriptive analysis of a series of patients admitted to a public pediatric hospital, with chronic and irreversible diseases, permanently dependent on ventilatory support, who underwent palliative extubation between April 2014 and May 2019. The following information was collected from the medical records: demographic data, diagnosis, duration and type of mechanical ventilation; date, time, and place of palliative extubation; medications used; symptoms observed; and hospital outcome.

RESULTS

A total of 19 patients with a mean age of 2.2 years were submitted to palliative extubation. 68.4% of extubations were performed in the ICU; 11 patients (57.9%) died in the hospital. The time between mechanical ventilation withdrawal and in-hospital death ranged from 15minutes to five days. Thirteen patients used an orotracheal tube and the others used tracheostomy. The main symptoms were dyspnea and pain, and the main drugs used to control symptoms were opioids and benzodiazepines.

CONCLUSIONS

It was not possible to identify predictors of in-hospital death after ventilatory support withdrawal. Palliative extubation requires specialized care, with the presence and availability of a multidisciplinary team with adequate training in symptom control and palliative care.

Ventilator Withdrawal in Anticipation of Death: The Simulation Lab as an Educational Tool in Palliative Medicine

Simulation is a growing model of education in many medical disciplines. Withdrawal of mechanical ventilation is an important skill set for palliative medicine practitioners who must be facile with a variety of end-of-life scenarios and is well suited to the simulation laboratory. We describe a novel approach using high-fidelity simulation to design a curriculum to teach Hospice & Palliative Medicine fellows the practical aspects of managing a compassionate terminal extubation. This simulation session aims to equip palliative fellows with a knowledge base of respiratory physiology and mechanical ventilation as well as the practical experience of performing a terminal extubation. We designed a three-hour simulation session which includes a one-hour didactic followed by two hours of simulation, with four cases that focus on different teaching points regarding symptom management and practical aspects of removing the endotracheal tube. The session was designed as an annual session for Hospice & Palliative Medicine fellows in our region during a collaborative educational conference. Based on feedback, the session is scheduled for the beginning of the academic year and each fellow is given the opportunity to physically remove the endotracheal tube. Simulation can be effectively used to teach practical and complex bedside skills such as withdrawal of mechanical ventilation to palliative medicine trainees. This method of teaching could be expanded to teach other advanced hospice and palliative care skills.

Death, unity, and the brain

The dead donor rule holds that removing organs from living human beings without their consent is wrongful killing. The rule still prevails in most countries, and I assume it without argument in order to pose the question: is it possible to have a metaphysically correct, clinically relevant analysis of human death that makes organ donation ethically permissible? I argue that the two dominant criteria of death-brain death and circulatory death-are both empirically and metaphysically inadequate as definitions of human death and therefore hold no epistemic value in themselves. I first set out a neo-Aristotelian theory of death as separation of soul (understood as organising principle) and body, which is then fleshed out as loss of organismic integrity. The brain and circulatory criteria are shown to have severe weaknesses as physiological manifestations of loss of integrity. Given the mismatch between what death is, metaphysically speaking, and the dominant criteria accepted by clinicians and philosophers, it turns out that only actual bodily decomposition is a sure sign of death. In this I differ from Alan Shewmon, whose important work I discuss in detail.

Predictors of withdrawal of life support after burn injury

INTRODUCTION

Discussions regarding withdrawal of life support after burn injury are challenging and complex. Often, providers may facilitate this discussion when the extent of injury makes survival highly unlikely or when the patient's condition deteriorates during resuscitation. Few papers have evaluated withdrawal of life support in burn patients. We therefore sought to determine the predictor of withdrawal of life support (WLS) in a regional burn center.

METHODS

We conducted a retrospective analysis of all burn patients from 2002 to 2012. Patient characteristics included age, gender, burn mechanism, percentage total body surface area (%TBSA) burned, presence of inhalation injury, hospital length of stay, and pre-existing comorbidities. Patients <17years of age and patients with unknown disposition were excluded. Patients were categorized into three cohorts: Alive till discharge (Alive), death by withdrawal of life support (WLS), or death despite ongoing life support (DLS). DLS patients were then excluded from the study population. Multivariate logistic regression was used to estimate predictors of WLS.

RESULTS

8,371 patients were included for analysis: 8134 Alive, 237 WLS. Females had an increased odd of WLS compared to males (OR 2.03, 95% CI 1.18-3.48; p=0.010). Based on higher CCI, patients with pre-existing comorbidities had an increased odd of WLS (OR 1.28, 95% CI 1.08-1.52; p=0.005). There was a significantly increased odds for WLS (OR 1.09, 95% CI 1.06-1.12; p<0.001) with increasing age. Similarly, there was an increased odd for WLS (OR 1.08, 95% CI 1.07-1.51; p<0.001) with increasing %TBSA. An increased odd of WLS (OR 2.47, 95% CI 1.05-5.78; p=0.038) was also found in patients with inhalation injury.

CONCLUSION

The decision to withdraw life support is a complex and difficult decision. Our current understanding of predictors of withdrawal of life support suggests that they mirror those factors which increase a patient's risk of mortality. Further research is needed to fully explore end-of-life decision making in regards to burn patients. The role of patient's sex, particularly women, in WLS decision making needs to be further explored.

Ensuring Breathing Comfort at the End of Life: The Integral Role of the Critical Care Nurse

This article describes the author's program of clinical research focused on assessment and treatment of respiratory distress among critically ill patients at the end of life. Dyspnea is a subjective experience of breathing discomfort that occurs in the presence of cardiopulmonary and neuromuscular diseases. Dyspnea is one of the most common and most distressing symptoms experienced by critically ill patients. Many critically ill patients, particularly those not expected to survive, become cognitively impaired or unconscious and lose the ability to report symptoms, although dyspnea can be known only from a patient's report. When self-reporting ability is lost, the critical care nurse must rely on signs indicative of a patient's respiratory distress. The critically ill patient unable to self-report is vulnerable to under-recognition of symptom distress and subsequent over-treatment or undertreatment. When the patient is dying, there is only 1 chance to optimize the assessment and treatment of symptoms.

A few realistic questions raised by organ retrieval in the intensive care unit

Organ transplantation saves the lives of many persons who would otherwise die from end-stage organ disease. The increasing demand for donated organs has led to a renewed interest in donation after circulatory determination of death (CDD). In many countries (including France), terminally ill patients who die of circulatory arrest after a planned withdrawal of life support may be considered as organ donors under certain conditions. While having equal responsibility towards the potential donor and the persons awaiting a transplant, caregivers may experience an ethical dilemma between the responsibility to deliver the best care to the dying, and the need to retrieve the organs. Once it has been established that the patient wishes to be a donor, we assume that end-of-life care and organ donation may have convergent goals when they contribute to transforming a comfortable death into a chance of life for others in need.

Clinical characteristics and survival outcomes of terminally ill patients undergoing withdrawal of mechanical ventilation

BACKGROUND

Withdrawal of mechanical ventilation is an important, but rarely explored issue in Asia during end-of-life care. This study aimed to describe the clinical characteristics and survival outcomes of terminally ill patients undergoing withdrawal of mechanical ventilation in Taiwan.

METHODS

One-hundred-thirty-five terminally ill patients who had mechanical ventilation withdrawn between 2013 and 2016, from a medical center in Taiwan, were enrolled. Patients' clinical characteristics and survival outcomes after withdrawal of mechanical ventilation were analyzed.

RESULTS

The three most common diagnoses were organic brain lesion, advanced cancer, and newborn sequelae. The initiator of the withdrawal process was family, medical personnel, and patient him/herself. The median survival time was 45 min (95% confidence interval, 33-57 min) after the withdrawal of mechanical ventilation, and 102 patients (75.6%) died within one day after extubation. The median time from diagnosis of disease to receiving life-sustaining treatment and artificial ventilation support, receiving life-sustaining treatment and artificial ventilation support to "Withdrawal meeting," "Withdrawal meeting" to ventilator withdrawn, and ventilator withdrawn to death was 12.1 months, 19 days, 1 day, and 0 days, respectively. Patients with a diagnosis of advanced cancer and withdrawal initiation by the patients themselves had a significantly shorter time interval between receiving life-sustaining treatment and artificial ventilation support to "Withdrawal meeting" compared to those with non-cancer diseases and withdrawal initiation by family or medical personnel.

CONCLUSION

This study is the first observational study to describe the patients' characteristics and elaborate on the survival outcome of withdrawal of mechanical ventilation in patients who are terminally ill in an Asian population. Understanding the clinical characteristics and survival outcomes of mechanical ventilation withdrawal might help medical personnel provide appropriate end-of-life care and help patients/families decide about the withdrawal process earlier.

How Long Does (S)He Have? Retrospective Analysis of Outcomes After Palliative Extubation in Elderly, Chronically Critically Ill Patients

OBJECTIVE

For chronically critically ill elderly patients on mechanical ventilation, prognosis for significant recovery may be minimal. These individuals, or their surrogates, may decide for "palliative extubation." A common prognostic question arises: "How long does she/he have?" This study describes demographics, mortality, time to death, and factors associated with death after palliative extubation.

DESIGN, SETTING, AND PATIENTS

Retrospective 3-year study in community hospital with ethnically diverse elderly population. Chronically critically ill patients followed from palliative extubation to death or survival to discharge.

MEASURES

Mortality/survival following palliative extubation, time to death or discharge, factors associated with death.

RESULTS

Hundred and forty-eight subjects underwent palliative extubation. Mean age: 78 years, 60% female, ethnically diverse with 46% white, and 54% others. Top diagnostic categories: sepsis (47%) and respiratory failure (22%). After extubation, 114 patients (77%) died in hospital and 34 (23%) were discharged. Of those who died, median time to death 8.9 hours (range, 4 min to 7 d). Mortality proportion was 56% at 24 hours and increased with time. Factors associated with early death: Systolic blood pressure less than 90 (p = 0.002) and Charlson Comorbidity Index that is above 6 or 0 (p = 0.002).

CONCLUSIONS

Palliative extubation at end of life was an option selected by an ethnically diverse elderly population. Approximately three-fourths of subjects died in hospital, and one-fourth was discharged alive. Over 50% who died did so within 24 hours, making this useful information for counseling and anticipatory planning. Subjects with systolic blood pressure less than 90 and Charlson Comorbidity Index that is very low or very high had higher mortality.

Mechanical Ventilator Discontinuation Process

The goal of this article is to discuss approaches to discontinuing invasive mechanical ventilation in a general intensive care unit (ICU) population. It considers approaches in which the clinician expects patient survival, as well as those that do not. Additionally, approaches to acute and chronic critical illness are included.

Outcomes following out-of-hospital cardiac arrest: What is the potential for donation after circulatory death?

We conducted a prospective observational study on 100 consecutive patients admitted to intensive care units at Leeds General Infirmary following out-of-hospital cardiac arrest. In the non-survivors, we reviewed their potential for organ donation via donation after circulatory death. Out of the 100 patients, 53 did not survive to hospital discharge. Out of these non-survivors, 13 died very suddenly within the intensive care unit and 3 other patients subsequently died in a general ward following discharge from the intensive care unit. One patient became brainstem dead, with out-of-hospital cardiac arrest secondary to a subarachnoid haemorrhage, rather than a primary cardiac cause. This patient went on to donate via the brain death mode. The remaining 36 patients had treatment withdrawn in the intensive care unit. Of these, 29 were referred to the transplant team for potential donation after circulatory death, and 14 were deemed to be medically suitable for organ donation. However, the families of only seven agreed to proceed with the donation process. Of these seven, only one went on to donate, primarily because the majority did not die within the 3-h window for acceptable warm ischaemia. In this series, the potential for donation after circulatory death following out-of-hospital cardiac arrest was limited. We would suggest an open dialogue between intensive care unit staff and transplant teams about the realistic potential for organ donation in each case. When clinicians believe it is unlikely that donation after circulatory death will proceed due to a failure to die within the pre-requisite time, then not starting with the donation after circulatory death process should be seriously considered.

Time to Death after Terminal Withdrawal of Mechanical Ventilation: Specific Respiratory and Physiologic Parameters May Inform Physician Predictions

BACKGROUND

Discussions about withdrawal of life-sustaining therapies often include family members of critically ill patients. These conversations should address essential components of the dying process, including expected time to death after withdrawal.

OBJECTIVES

The study objective was to aid physician communication about the dying process by identifying predictors of time to death after terminal withdrawal of mechanical ventilation.

METHODS

We conducted an observational analysis from a single-center, before-after evaluation of an intervention to improve palliative care. We studied 330 patients who died after terminal withdrawal of mechanical ventilation. Predictors included patient demographics, laboratory, respiratory, and physiologic variables, and medication use.

RESULTS

The median time to death for the entire cohort was 0.58 hours (interquartile range (IQR) 0.22-2.25 hours) after withdrawal of mechanical ventilation. Using Cox regression, independent predictors of shorter time to death included higher positive end-expiratory pressure (per 1 cm H2O hazard ratio [HR], 1.07; 95% CI 1.04-1.11); higher static pressure (per 1 cm H2O HR, 1.03; 95% CI 1.01-1.04); extubation prior to death (HR, 1.41; 95% CI 1.06-1.86); and presence of diabetes (HR, 1.75; 95% CI 1.25-2.44). Higher noninvasive mean arterial pressure predicted longer time to death (per 1 mmHg HR, 0.98; 95% CI 0.97-0.99).

CONCLUSIONS

Comorbid illness and key respiratory and physiologic parameters may inform physician predictions of time to death after withdrawal of mechanical ventilation. An understanding of the predictors of time to death may facilitate discussions with family members of dying patients and improve communication about end-of-life care.

An Observational Study on a Protocol for Withdrawal of Life-Sustaining Measures on Two Non-Academic Intensive Care Units in The Netherlands: Few Signs of Distress, No Suffering?

CONTEXT

Because anticipation of death is common within the intensive care unit, attention must be paid to the prevention of distressing signs and symptoms, enabling the patient to die peacefully. In the relevant studies on this subject, there has been a lack of focus on measuring determinants of comfort in this population.

OBJECTIVES

To evaluate whether dying without distressing signs after the withdrawal of life-sustaining measures is possible using a newly introduced protocol and to analyze the potential influence of opioids and sedatives on time till death.

METHODS

This was a prospective observational study, in two nonacademic Dutch intensive care units after the introduction of a national protocol for end-of-life care. The study lasted two years and included adult patients in whom mechanical ventilation and/or vasoactive medication was withdrawn. Exclusion criteria included all other causes of death.

RESULTS

During the study period, 450 patients died; of these, 305 patients were eligible, and 241 were included. Ninety percent of patients were well sedated before and after withdrawal. Severe terminal restlessness, death rattle, or stridor was seen in less than 6%. Dosages of opioids and sedatives increased significantly after withdrawal, but did not contribute to a shorter time till death according the regression analysis.

CONCLUSION

The end-of-life protocol seems effective in realizing adequate patient comfort. Most patients in whom life-sustaining measures are withdrawn are well sedated and show few signs of distress. Dosages of opioids and sedatives increase significantly during treatment withdrawal but do not contribute to time until death. Dying with a minimum of distressing signs is thus practically possible and ethically feasible.

Predicting time to death after withdrawal of life-sustaining therapy

PURPOSE

Predicting time to death following the withdrawal of life-sustaining therapy is difficult. Accurate predictions may better prepare families and improve the process of donation after circulatory death.

METHODS

We systematically reviewed any predictive factors for time to death after withdrawal of life support therapy.

RESULTS

Fifteen observational studies met our inclusion criteria. The primary outcome was time to death, which was evaluated to be within 60 min in the majority of studies (13/15). Additional time endpoints evaluated included time to death within 30, 120 min, and 10 h, respectively. While most studies evaluated risk factors associated with time to death, a few derived or validated prediction tools. Consistent predictors of time to death that were identified in five or more studies included the following risk factors: controlled ventilation, oxygenation, vasopressor use, Glasgow Coma Scale/Score, and brain stem reflexes. Seven unique prediction tools were derived, validated, or both across some of the studies. These tools, at best, had only moderate sensitivity to predicting the time to death. Simultaneous withdrawal of all support and physician opinion were only evaluated in more recent studies and demonstrated promising predictor capabilities.

CONCLUSIONS

While the risk factors controlled ventilation, oxygenation, vasopressors, level of consciousness, and brainstem reflexes have been most consistently found to be associated with time to death, the addition of novel predictors, such as physician opinion and simultaneous withdrawal of all support, warrant further investigation. The currently existing prediction tools are not highly sensitive. A more accurate and generalizable tool is needed to inform end-of-life care and enhance the predictions of donation after circulatory death eligibility.

Caring for Dying Patients in the Intensive Care Unit

Critically ill patients receiving palliative care at the end of life are at high risk for experiencing pain, dyspnea, and death rattle. Nearly all these patients are at risk for the development of delirium. Patients who are alert may experience anxiety. Advanced practice nurses and staff nurses are integral to detecting and treating these symptoms. Pain, dyspnea, and anxiety should be routinely assessed by patient self-report when possible. Routine behavioral screening for delirium is recommended. Behavioral observation tools to detect pain and dyspnea and proxy assessments guide symptom identification when the patient cannot provide a self-report. Evidence-based interventions are offered for both prevention and treatment of pain, dyspnea, anxiety, and delirium. Death rattle does not produce patient distress, and current pharmacological treatment lacks an evidence base. Pain management has a robust evidence base compared to management of dyspnea, anxiety, and delirium among this population; well-designed, adequately powered studies are needed.

Decisions to withhold or withdraw life-sustaining treatment in a Norwegian intensive care unit

BACKGROUND

To withhold and withdraw treatment are important and difficult decisions made in the intensive care unit (ICU). The aim of this study was to investigate the incidence of withholding or withdrawing treatment, characteristics of the patients, and how these decision processes were handled and documented in a general ICU from 2007 to 2009 in a university hospital in Norway.

METHODS

Patient characteristics and outcomes of treatment were prospectively registered. We retrospectively reviewed the medical records for information on limitations in treatment.

RESULTS

In total, 1287 patients were admitted to the ICU. The ICU mortality was 208 (16%), and the hospital mortality was 341 (26%). In total, 301 patients (23%) had treatment withheld or withdrawn. Medical and unscheduled surgical patients with limitations in treatment had higher Simplified Acute Physiology Score II (P < 0.001) and were older (P < 0.001) than those without limitations in treatment. The most common main reason for withdrawing treatment was poor prognosis. According to the medical records, the patient was involved in the decision-making regarding withdrawal of treatment in only 2% of the cases, and the patient's relatives were involved in the decision-making in 77% of the cases. In 12% of the cases, type of treatment withdrawn was not documented.

CONCLUSION

Withholding or withdrawing treatment in the ICU was common. Medical and unscheduled surgical patients with limitations in treatment were older and more severely ill than patients without limitations. There is a potential for better documentation of the processes regarding withholding or withdrawing life-sustaining intensive care treatment.

The relationship between the timing of a palliative care consult and utilization outcomes for ventilator-assisted intensive care unit patients

OBJECTIVE

Given the great number of chronic care patients facing the end of life and the challenges of critical care delivery, there has been emerging evidence supporting the benefit of palliative care in the intensive care unit (ICU). We studied the relationship between the timing of a palliative care consult (PCC) and two utilization outcomes - length of stay (LOS) and pharmacy costs - in ventilator-assisted ICU patients.

METHOD

A retrospective chart review was conducted (N = 90). Summed pharmacy costs were compared using a paired t test before and after PCC. Spearman correlations were performed between days to PCC and ICU LOS, ventilator days, and days to death following ventilator discontinuation.

RESULTS

Number of days from admission to PCC was correlated with total days on ventilator (ρ = 0.685, p < 0.0001) and total ICU LOS (ρ = 0.654, p < 0.0001). Number of days to PCC was correlated with pre-PCC total medication costs (ρ = 0.539, p < 0.0001). Median medication costs were significantly reduced after the PCC (p < 0.0001), from $230.96 to 30.62. Median medication costs decreased for all categories except for analgesics, antiemetics, and opioids. The number of patients receiving opioid infusion increased (37 vs. 90%) after PCC (p < 0.0001).

SIGNIFICANCE OF RESULTS

Earlier timing for PCC in the ICU is associated with a lower LOS through quicker mechanical ventilation (MV) withdrawal, presenting a unique opportunity to both decrease costs and improve patient care.

Nighttime intensivist staffing and the timing of death among ICU decedents: a retrospective cohort study

Introduction

Intensive care units (ICUs) are increasingly adopting 24-hour intensivist physician staffing. Although nighttime intensivist staffing does not consistently reduce mortality, it may affect other outcomes such as the quality of end-of-life care.

Methods

We conducted a retrospective cohort study of ICU decedents using the 2009–2010 Acute Physiology and Chronic Health Evaluation clinical information system linked to a survey of ICU staffing practices. We restricted the analysis to ICUs with high-intensity daytime staffing, in which the addition of nighttime staffing does not influence mortality. We used multivariable regression to assess the relationship between nighttime intensivist staffing and two separate outcomes potentially related to the quality of end-of-life care: time from ICU admission to death and death at night.

Results

Of 30,456 patients admitted to 27 high-intensity daytime staffed ICUs, 3,553 died in the hospital within 30 days. After adjustment for potential confounders, admission to an ICU with nighttime intensivist staffing was associated with a shorter duration between ICU admission and death (adjusted difference: –2.5 days, 95% CI -3.5 to -1.5, p-value < 0.001) and a decreased odds of nighttime death (adjusted odds ratio: 0.75, 95% CI 0.60 to 0.94, p-value 0.011) compared to admission to an ICU without nighttime intensivist staffing.

Conclusions

Among ICU decedents, nighttime intensivist staffing is associated with reduced time between ICU admission and death and reduced odds of nighttime death.

Factors associated with palliative withdrawal of mechanical ventilation and time to death after withdrawal

BACKGROUND

In imminently dying patients, mechanical ventilation withdrawal is often a comfort measure and avoids prolonging the dying process.

OBJECTIVE

The aim of the study was to identify factors associated with palliative withdrawal of mechanical ventilation and time to death after extubation.

METHODS

Logistic regression models were used to identify factors associated with palliative withdrawal of mechanical ventilation. Cox proportional hazards models were used to determine factors associated with time to death after extubation. We retrospectively evaluated 322 patients who died on mechanical ventilation or after palliative ventilator withdrawal at a single tertiary care center.

RESULTS

Of the 322 ventilated deaths, 159 patients had palliative withdrawal of mechanical ventilation and 163 patients died on the ventilator. Clinical service was associated with palliative withdrawal of mechanical ventilation: Patients withdrawn from the ventilator were less likely to be on the surgery service and more likely to be on the neurology/neurosurgical service. The median time to death was 0.9 hours (range 0-165 hours). Fraction of inspired oxygen (FIO2) greater than 70% (hazard ratio [HR] 1.92, 95% confidence interval [CI ]1.24-2.99) and a requirement for vasopressors (HR 2.06, 95% CI 1.38-3.09) were associated with shorter time to death. Being on the neurology/neurosurgical service at the time of ventilator withdrawal was associated with a longer time to death (HR 0.60, 95% CI 0.39-0.92).

CONCLUSIONS

Palliative withdrawal of mechanical ventilation was performed in only half of dying mechanically ventilated patients. Because clinical service rather than physiologic parameters are associated with withdrawal, targeted interventions may improve withdrawal decisions. Considering FIO2 and vasopressor requirements may facilitate counseling families about anticipated time to death.

Prediction of potential for organ donation after cardiac death in patients in neurocritical state: a prospective observational study

BACKGROUND

Successful donation of organs after cardiac death (DCD) requires identification of patients who will die within 60 min of withdrawal of life-sustaining treatment (WLST). We aimed to validate a straightforward model to predict the likelihood of death within 60 min of WLST in patients with irreversible brain injury.

METHODS

In this multicentre, observational study, we prospectively enrolled consecutive comatose patients with irreversible brain injury undergoing WLST at six medical centres in the USA and the Netherlands. We assessed four clinical characteristics (corneal reflex, cough reflex, best motor response, and oxygenation index) as predictor variables, which were selected on the basis of previous findings. We excluded patients who had brain death or were not intubated. The primary endpoint was death within 60 min of WLST. We used univariate and multivariable logistic regression analyses to assess associations with predictor variables. Points attributed to each variable were summed to create a predictive score for cardiac death in patients in neurocritical state (the DCD-N score). We assessed performance of the score using area under the curve analysis.

FINDINGS

We included 178 patients, 82 (46%) of whom died within 60 min of WLST. Absent corneal reflexes (odds ratio [OR] 2·67, 95% CI 1·19-6·01; p=0·0173; 1 point), absent cough reflex (4·16, 1·79-9·70; p=0·0009; 2 points), extensor or absent motor responses (2·99, 1·22-7·34; p=0·0168; 1 point), and an oxygenation index score of more than 3·0 (2·31, 1·10-4·88; p=0·0276; 1 point) were predictive of death within 60 min of WLST. 59 of 82 patients who died within 60 min of WLST had DCD-N scores of 3 or more (72% sensitivity), and 75 of 96 of those who did not die within this interval had scores of 0-2 (78% specificity); taking into account the prevalence of death within 60 min in this population, a score of 3 or more was translated into a 74% chance of death within 60 min (positive predictive value) and a score of 0-2 translated into a 77% chance of survival beyond 60 min (negative predictive value).

INTERPRETATION

The DCD-N score can be used to predict potential candidates for DCD in patients with non-survivable brain injury. However, this score needs to be tested specifically in a cohort of potential donors participating in DCD protocols.

FUNDING

None.

Providing a "good death" for oncology patients during the final hours of life in the intensive care unit

Cancer is a leading cause of death in the United States. Aggressiveness of cancer care continues to rise in parallel with scientific discoveries in the treatment of a variety of malignancies. As a result, patients with cancer often require care in intensive care units (ICUs). Although growth in hospice and palliative care programs has occurred nationwide, access to these programs varies by geographic region and hospital type. Thus, critical care nurses may be caring for patients with cancer during the final hours of life in the ICU without the support of palliative care experts. This article provides an overview of the meaning of the final hours of life for cancer patients and uses principles of a "good death" and the tenets of hospice care to organize recommendations for critical care nurses for providing high quality end-of-life care to patients with cancer in the ICU.