Treatment of Dyspnea in Do-not-intubate Patients

Summary

Participation Requirements

Description

Background: Respiratory symptoms, dyspnea and acute respiratory failure are often reported in patients admitted to the Hospital with a do-not-intubate (DNI) order. These patients are routinely treated with medical therapy, sometimes to reverse the underlying process, but also often to achieve pallia...

Background: Respiratory symptoms, dyspnea and acute respiratory failure are often reported in patients admitted to the Hospital with a do-not-intubate (DNI) order. These patients are routinely treated with medical therapy, sometimes to reverse the underlying process, but also often to achieve palliation. The therapies include opioids or anxiolytics, oxygen, CPAP and non-invasive ventilation (NIV) depending on the underlying disease. Rationale: Considering that most of the available data on the palliative use of NIV are limited to short-term prognosis and are collected selecting DNI patients among those subjects already receiving NIV treatment. A prospective observational study focusing on therapies offered to patients entering the hospital with or switching to a DNI status during the hospitalization would be helpful to fill in the blanks regarding the current palliative treatment of dyspnea in critically ill DNI patients. The assessment of patients' symptoms and comfort and family members' perspective would be important to further understand how the discussion with healthcare proxies and families should be addressed in relation to end-of life-decisions. In addition, the collection of health care providers' impressions on the use of different treatments to alleviate dyspnea and respiratory distress in this situation could help to better understand how to implement palliative treatment of respiratory symptoms in DNI patients. Our aim is to monitor and establish the prevalence of use of NIV among DNI patients and to assess patients, family members' and caregivers' perspectives on the patient's and their own experience of NIV relative to other approaches to palliating symptoms. Study design: A prospective, observational study enrolling all consecutive patients with dyspnea and/or acute respiratory failure with DNI orders admitted to the study site. Study procedures: Subjects participating in the study will be treated as per hospital procedure and according to the attending physician orders, to maintain oxygen saturation at the targeted level and to optimize patient comfort using anxiolytics and narcotics as indicated. No changes in the standard of care will be performed based on participation in the study. Some data (demographics, medications, vitals, arterial blood gas, history of present illnes and past medical history, treatment plan) will be extracted from medical records. A daily assessment of dyspnea score (Numeric rating scale, (NRS)), comfort (NRS) and pain (NRS) will be performed. Patients and family members will be asked to fill in a questionnaire at day 3. Heal care providers (attending physician, nurse and RT) will be asked to fill in a questionnaire at discharge. Family members and/or patients will be contacted by phone 30 days after discharge to get additional information about patient's outcome. Research plan: Demographics and baseline characteristics of patients will be summarized for each group overall and by cohorts (DNI on NIV, DNI on CPAP, DNI with no ventilator support). Continuous variables will be reported as mean ± standard deviation. Categorical variables will be reported as n and %. For the primary outcome, a one-way ANOVA will be used to compare the difference in means between the groups. If the data are not normally distributed, the Krusman-Wallis test will be performed. Regression analysis will also be conducted to evaluate the consistency of treatment effects across the cohorts, controlling for potential confounding factors at baseline. A Chi-square test (or Fisher's exact test if the counts are below 5) will be used to compare the distribution of categorical outcomes between the groups. Where appropriate, generalized linear models will be fitted with categorical and count data to evaluate the consistency of treatment effects across the cohorts, controlling for potential confounding factors at baseline.

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