Timing is everything: Early do-not-resuscitate orders in the intensive care unit and patient outcomes

Ouyang, Jie; Lief, Lindsay; Russell, David; Xu, Jiehui; Berlin, David; Gentzler, Eliza; Su, Amanda; Cooper, Zara; Senglaub, Steven S.; Maciejewski, Paul K.; Prigerson, Holly G.

doi:10.1371/journal.pone.0227971

Cited by 27 publications

(27 citation statements)

References 45 publications

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“…In contrast to a study in which nurses were more comfortable giving opioids for pain management at the EOL [6], our study found that EDNR is associated with decreased narcotic use. We hypothesize that the shorter duration from DNR placement to death and shorter hospital LOS associated with EDNR allowed less time for physicians to address the family members on patients' comfort during the care.…”

Section: Hospital Carecontrasting

confidence: 99%

“…In theory, the DNR order itself should not directly impact care until the moment of cardiac arrest. However, one study found that EDNR directly influenced both resuscitative and ancillary care, with fewer invasive interventions being performed in the last week of life, including dialysis, mechanical ventilation, feeding tubes, and CPR, compared to those with LDNR and no DNR [6]. Another study on out-of-hospital cardiac arrest (OHCA) patients found that EDNR is associated with a significant decrease in potentially critical therapeutic options, including cardiac catheterization, bypass surgery, and blood transfusion after resuscitation, and is associated with less aggressive hospital care, fewer potentially beneficial procedures, and worse survival [3].…”

Section: Hospital Carementioning

confidence: 99%

“…In theory, the DNR order itself should not directly impact care until the moment of cardiac arrest. However, early DNR (EDNR: order placement within 24 h of ED presentation) was found to directly influence both resuscitative and ancillary care [6] and resulted in a decrease in potentially critical hospital interventions, with wide variability in practice patterns between hospitals [3]. EDNR often is a proxy of patient's underlying disease, prehospital frailty, and burden of comorbidities [4], an independent predictor of 28-day mortality [7]; and a strong predictor of short-term mortality risk [8].…”

Section: Introductionmentioning

confidence: 99%

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Differences in Characteristics, Hospital Care and Outcomes between Acute Critically Ill Emergency Department Patients with Early and Late Do-Not-Resuscitate Orders

Chang

Yang

Lai

et al. 2021

IJERPH

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Background: A do-not-resuscitate (DNR) order is associated with an increased risk of death among emergency department (ED) patients. Little is known about patient characteristics, hospital care, and outcomes associated with the timing of the DNR order. Aim: Determine patient characteristics, hospital care, survival, and resource utilization between patients with early DNR (EDNR: signed within 24 h of ED presentation) and late DNR orders. Design: Retrospective observational study. Setting/Participants: We enrolled consecutive, acute, critically ill patients admitted to the emergency intensive care unit (EICU) at Taipei Veterans General Hospital from 1 February 2018, to 31 January 2020. Results: Of the 1064 patients admitted to the EICU, 619 (58.2%) had EDNR and 445 (41.8%) LDNR. EDNR predictors were age >85 years (adjusted odd ratios (AOR) 1.700, 1.027–2.814), living in long-term care facilities (AOR 1.880, 1.066–3.319), having advanced cardiovascular diseases (AOR 2.128, 1.039–4.358), “medical staff would not be surprised if the patient died within 12 months” (AOR 1.725, 1.193–2.496), and patients’ family requesting palliative care (AOR 2.420, 1.187–4.935). EDNR patients underwent lesser endotracheal tube (ET) intubation (15.6% vs. 39.9%, p < 0.001) and had reduced epinephrine injection (19.9% vs. 30.3%, p = 0.009), ventilator support (16.7% vs. 37.9%, p < 0.001), and narcotic use (51.1% vs. 62.6%, p = 0.012). EDNR patients had significantly lower 7-day (p < 0.001), 30-day (p < 0.001), and 90-day (p = 0.023) survival. Conclusions: EDNR patients underwent decreased ET intubation and had reduced epinephrine injection, ventilator support, and narcotic use during EOL as well as decreased length of hospital stay, hospital expenditure, and survival compared to LDNR patients.

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Section: Hospital Carecontrasting

confidence: 99%

Section: Hospital Carementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Differences in Characteristics, Hospital Care and Outcomes between Acute Critically Ill Emergency Department Patients with Early and Late Do-Not-Resuscitate Orders

Chang

Yang

Lai

et al. 2021

IJERPH

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“…Nava et al, investigating 6,008 patients in European respiratory intermediate care units and high-dependency units, found that merely 21% of patients received end-of-life decision, including withholding of treatment, DNR/do-not-intubate orders, and non-invasive MV (37). Furthermore, studies have shown that timely communication with families and the interprofessional collaboration for individualized balance between aggressiveness and responsiveness of care, which was recently reported by Rak et al through conducting a large and delicate ethnographic study in eight long-term acute care hospitals, are crucial in the end-oflife care among patients requiring PMV (39,40). Therefore, we think that the mortality prediction model and the illustration of main features attributed to high mortality in patients with PMV might indicate the need for timely communication regarding end-of-life issues.…”

Section: Discussionmentioning

confidence: 90%

Explainable Machine Learning to Predict Successful Weaning Among Patients Requiring Prolonged Mechanical Ventilation: A Retrospective Cohort Study in Central Taiwan

Lin

et al. 2021

Front. Med.

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Objective: The number of patients requiring prolonged mechanical ventilation (PMV) is increasing worldwide, but the weaning outcome prediction model in these patients is still lacking. We hence aimed to develop an explainable machine learning (ML) model to predict successful weaning in patients requiring PMV using a real-world dataset.Methods: This retrospective study used the electronic medical records of patients admitted to a 12-bed respiratory care center in central Taiwan between 2013 and 2018. We used three ML models, namely, extreme gradient boosting (XGBoost), random forest (RF), and logistic regression (LR), to establish the prediction model. We further illustrated the feature importance categorized by clinical domains and provided visualized interpretation by using SHapley Additive exPlanations (SHAP) as well as local interpretable model-agnostic explanations (LIME).Results: The dataset contained data of 963 patients requiring PMV, and 56.0% (539/963) of them were successfully weaned from mechanical ventilation. The XGBoost model (area under the curve [AUC]: 0.908; 95% confidence interval [CI] 0.864–0.943) and RF model (AUC: 0.888; 95% CI 0.844–0.934) outperformed the LR model (AUC: 0.762; 95% CI 0.687–0.830) in predicting successful weaning in patients requiring PMV. To give the physician an intuitive understanding of the model, we stratified the feature importance by clinical domains. The cumulative feature importance in the ventilation domain, fluid domain, physiology domain, and laboratory data domain was 0.310, 0.201, 0.265, and 0.182, respectively. We further used the SHAP plot and partial dependence plot to illustrate associations between features and the weaning outcome at the feature level. Moreover, we used LIME plots to illustrate the prediction model at the individual level. Additionally, we addressed the weekly performance of the three ML models and found that the accuracy of XGBoost/RF was ~0.7 between weeks 4 and week 7 and slightly declined to 0.6 on weeks 8 and 9.Conclusion: We used an ML approach, mainly XGBoost, SHAP plot, and LIME plot to establish an explainable weaning prediction ML model in patients requiring PMV. We believe these approaches should largely mitigate the concern of the black-box issue of artificial intelligence, and future studies are warranted for the landing of the proposed model.

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“…In other hospitalized patient populations earlier goals of care conversations and DNR placement were linked to less intensive end-of-life care and better quality of life. 35,36 However, the effect of having a DNR and DNR placement timing on the relationship between dementia and end-of-life care intensity is unknown.…”

Section: Introductionmentioning

confidence: 99%

Dementia and Early Do-Not-Resuscitate Orders Associated With Less Intensive of End-of-Life Care: A Retrospective Cohort Study

Luth

Pan

Viola

et al. 2021

Am J Hosp Palliat Care

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Background: Dementia is a leading cause of death among US older adults. Little is known about end-of-life care intensity and do-not-resuscitate orders (DNRs) among patients with dementia who die in hospital. Aim: Examine the relationship between dementia, DNR timing, and end-of-life care intensity. Design: Observational cohort study. Setting/Participants: Inpatient electronic health record extraction for 2,566 persons age 65 and older who died in 2 New York City hospitals in the United States from 2015 to 2017. Results: Multivariable logistic regression analyses modeled associations between dementia diagnosis, DNR timing, and 6 end-of-life care outcomes. 31% of subjects had a dementia diagnosis; 23% had a DNR on day of hospital admission. Patients with dementia were 18%-40% less likely to have received 4 of 6 types of intensive care (mechanical ventilation AOR: 0.82, 95%CI: 0.67 -1.00; intensive care unit admission AOR: 0.60, 95%CI: 0.49-0.83). Having a DNR on file was inversely associated with staying in the intensive care unit (AOR: 0.57, 95%CI: 0.47-0.70) and avoiding other intensive care measures. DNR placement later during the hospitalization and not having a DNR were associated with more intensive care compared to having a DNR upon admission. Conclusions: Having dementia and a do-not resuscitate order upon hospital admission are associated with less intensive end-of-life care. Additional research is needed to understand why persons with dementia receive less intensive care. In clinical practice, encouraging advance care planning prior to and at hospital admission may be particularly important for patients wishing to avoid intensive end-of-life care, including patients with dementia.

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Timing is everything: Early do-not-resuscitate orders in the intensive care unit and patient outcomes

Cited by 27 publications

References 45 publications

Differences in Characteristics, Hospital Care and Outcomes between Acute Critically Ill Emergency Department Patients with Early and Late Do-Not-Resuscitate Orders

Differences in Characteristics, Hospital Care and Outcomes between Acute Critically Ill Emergency Department Patients with Early and Late Do-Not-Resuscitate Orders

Explainable Machine Learning to Predict Successful Weaning Among Patients Requiring Prolonged Mechanical Ventilation: A Retrospective Cohort Study in Central Taiwan

Dementia and Early Do-Not-Resuscitate Orders Associated With Less Intensive of End-of-Life Care: A Retrospective Cohort Study

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