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Association of Functional Status and Symptom Severity Among Patients Who Received Palliative Care Consultations.

Moritz BlumLi ZengEmily ChaiLaura P Gelfman
Published in: Journal of palliative medicine (2024)
Background: The relationship between functional status and the severity of different symptoms in patients with serious illnesses has not been explored in detail. Methods: We retrospectively evaluated registry data of hospitalized patients who received inpatient palliative care consults at the Mount Sinai Health System between January 01, 2020, and December 31, 2022. The registry was approved by the local institutional review board. During the initial consult, palliative care clinicians administered the Australia-modified Karnofsky Performance Status (KPS) and the Edmonton Symptom Assessment System (ESAS). We extracted these measures and other variables of interest from electronic health records and billing data, and assessed the association of functional status and symptom severity for different symptoms using ordinal logistic regression models. Results: The study included 9800 patients who received a palliative care consult. When modeling the association of functional status and the severity of different symptoms, two distinct groups of symptoms emerged: Nausea, physical discomfort, anxiety, depression, and constipation were more prevalent and severe among patients with higher functional status. Conversely, drowsiness, inactivity, dyspnea, anorexia, and agitation were more prevalent and severe among patients with lower functional status. These findings remained statistically significant after adjusting for possible confounders. Conclusion: Among patients who received inpatient palliative care consults, lower functional status was associated with a higher symptom burden. Furthermore, symptom profiles differed between patients with reduced functional status and those with preserved functional status.
Keyphrases
  • palliative care
  • advanced cancer
  • electronic health record
  • sleep quality
  • mental health
  • primary care
  • depressive symptoms
  • early onset
  • acute care
  • data analysis
  • artificial intelligence