Patients with ILD receive poorer access to specialist EOL care services and experience more breathlessness than patients with lung cancer. This study highlights the need of better EOL care in oxygen-dependent ILD.

We report a case of Cryptococcus neoformans pneumonia in a patient taking ruxolitinib, a janus kinase 1,2 inhibitor approved for the treatment of myelofibrosis. We hypothesize that ruxolitinib contributed to this infection through its effects on cell-mediated immunity. Clinicians should be aware of the potential for intracellular or opportunistic infections associated with this novel drug class.

Patients with chronic lung disease have symptom burdens similar to those of patients with lung cancer at the time of first palliative care encounter. Given the population burden of chronic lung disease and limitations in the palliative care workforce, attention should be focused on ensuring that pulmonologists are prepared to assess and manage the common palliative care needs of patients with chronic lung disease.

Objective-Addressing the quality gap in intensive care unit (ICU)-based palliative care is limited by uncertainty about acceptable models of collaborative specialist and generalist care. Therefore, we characterized the attitudes of physicians and nurses about palliative care delivery in an ICU environment. Design-Mixed-methods study.Setting-Medical and surgical ICUs at three large academic hospitals.Participants-303 nurses, intensivists, and advanced practice providers. Author Manuscript Author ManuscriptAuthor Manuscript Author ManuscriptMeasurements and main results-Clinicians completed written surveys that assessed attitudes about specialist palliative care presence and integration into the ICU setting, as well as acceptability of 23 published palliative care prompts ('triggers') for specialist consultation. Most (n=225, 75%) reported that palliative care consultation was underutilized. Prompting consideration of eligibility for specialist consultation by electronic health record searches for triggers was most preferred (n=123, 41%); only 17 (6%) felt current processes were adequate. The most acceptable specialist triggers were metastatic malignancy, unrealistic goals of care, end of life decision making, and persistent organ failure. Advanced age, length of stay, and duration of life support were the least acceptable. Screening led by either specialists or ICU teams was equally preferred. Central themes derived from qualitative analysis of 65 written responses to open-ended items included concerns about the roles of physicians and nurses, implementation, and impact on ICU team-family relationships.Conclusions-Integration of palliative care specialists in the ICU is broadly acceptable and desired. However, the most commonly used current triggers for prompting specialist consultation were among the least well accepted, while more favorable triggers are difficult to abstract from electronic health record systems. There is also disagreement about the role of ICU nurses in palliative care delivery. These findings provide important guidance to the development of collaborative care models for the ICU setting.

COPD patients are burdened with a daily risk of acute exacerbation and loss of control, which could be mitigated by effective, on-demand decision support tools. In this study, we present a machine learning-based strategy for early detection of exacerbations and subsequent triage. Our application uses physician opinion in a statistically and clinically comprehensive set of patient cases to train a supervised prediction algorithm. The accuracy of the model is assessed against a panel of physicians each triaging identical cases in a representative patient validation set. Our results show that algorithm accuracy and safety indicators surpass all individual pulmonologists in both identifying exacerbations and predicting the consensus triage in a 101 case validation set. The algorithm is also the top performer in sensitivity, specificity, and ppv when predicting a patient’s need for emergency care.

BackgroundWeb-based decision aids are increasingly important in medical research and clinical care. However, few have been studied in an intensive care unit setting. The objectives of this study were to develop a Web-based decision aid for family members of patients receiving prolonged mechanical ventilation and to evaluate its usability and acceptability.MethodsUsing an iterative process involving 48 critical illness survivors, family surrogate decision makers, and intensivists, we developed a Web-based decision aid addressing goals of care preferences for surrogate decision makers of patients with prolonged mechanical ventilation that could be either administered by study staff or completed independently by family members (Development Phase). After piloting the decision aid among 13 surrogate decision makers and seven intensivists, we assessed the decision aid’s usability in the Evaluation Phase among a cohort of 30 surrogate decision makers using the Systems Usability Scale (SUS). Acceptability was assessed using measures of satisfaction and preference for electronic Collaborative Decision Support (eCODES) versus the original printed decision aid.ResultsThe final decision aid, termed ‘electronic Collaborative Decision Support’, provides a framework for shared decision making, elicits relevant values and preferences, incorporates clinical data to personalize prognostic estimates generated from the ProVent prediction model, generates a printable document summarizing the user’s interaction with the decision aid, and can digitally archive each user session. Usability was excellent (mean SUS, 80 ± 10) overall, but lower among those 56 years and older (73 ± 7) versus those who were younger (84 ± 9); p = 0.03. A total of 93% of users reported a preference for electronic versus printed versions.ConclusionsThe Web-based decision aid for ICU surrogate decision makers can facilitate highly individualized information sharing with excellent usability and acceptability. Decision aids that employ an electronic format such as eCODES represent a strategy that could enhance patient-clinician collaboration and decision making quality in intensive care.Electronic supplementary materialThe online version of this article (doi:10.1186/s13613-015-0045-0) contains supplementary material, which is available to authorized users.

Context Measurement of dyspnea is important for clinical care and research. Objectives To characterize the relationship between the 0–10 Numerical Rating Scale (NRS) and four-level categorical Verbal Descriptor Scale (VDS) for dyspnea assessment. Methods This was a substudy of a double-blind randomized controlled trial comparing palliative oxygen to room air for relief of refractory breathlessness in patients with life-limiting illness. Dyspnea was assessed with both a 0–10 NRS and a four-level categorical VDS over the one-week trial. NRS and VDS responses were analyzed in cross section and longitudinally. Relationships between NRS and VDS responses were portrayed using descriptive statistics and visual representations. Results Two hundred twenty-six participants contributed responses. At baseline, mild and moderate levels of breathlessness were reported by 41.9% and 44.6% of participants, respectively. NRS scores demonstrated increasing mean and median levels for increasing VDS intensity, from a mean (SD) of 0.6 (±1.04) for VDS none category to 8.2 (1.4) for VDS severe category. The Spearman correlation coefficient was strong at 0.78 (P < 0.0001). Based on the distribution of NRS scores within VDS categories, we calculated test characteristics of two different cutpoint models. Both models yielded 75% correct translations from NRS to VDS; however, Model A was more sensitive for moderate or greater dyspnea, with fewer misses downcoded. Conclusion There is strong correlation between VDS and NRS measures for dyspnea. Proposed practical cutpoints for the relationship between the dyspnea VDS and NRS are 0 for none, 1–4 for mild, 5–8 for moderate, and 9–10 for severe.

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