Predictors of short- and long-term mortality in critically ill, older adults admitted to the emergency department: an observational study

Link to article at PubMed

BMC Emerg Med. 2022 Jan 27;22(1):15. doi: 10.1186/s12873-022-00571-2.

ABSTRACT

BACKGROUND: In the future, we can expect an increase in older patients in emergency departments (ED) and acute wards. The main purpose of this study was to identify predictors of short- and long-term mortality in the ED and at hospital discharge.

METHODS: This is a retrospective, observational, single-center, cohort study, involving critically ill older adults, recruited consecutively in an ED. The primary outcome was mortality. All patients were followed for 6.5-7.5 years. The Cox proportional hazards model was used.

RESULTS: Regarding all critically ill patients aged ≥ 70 years and identified in the ED (n = 402), there was a significant association between mortality at 30 days after ED admission and unconsciousness on admission (HR 3.14, 95% CI 2.09-4.74), hypoxia on admission (HR 2.51, 95% CI 1.69-3.74) and age (HR 1.06 per year, 95% CI 1.03-1.09), (all p < 0.001). Of 402 critically ill patients aged ≥ 70 years and identified in the ED, 303 were discharged alive from hospital. There was a significant association between long-term mortality and the Charlson Comorbidity Index (CCI) > 2 (HR 1.90, 95% CI 1.46-2.48), length of stay (LOS) > 7 days (HR 1.72, 95% CI 1.32-2.23), discharge diagnosis of pneumonia (HR 1.65, 95% CI 1.24-2.21) and age (HR 1.08 per year, 95% CI 1.05-1.10), (all p < 0.001). The only symptom or vital sign associated with long-term mortality was hypoxia on admission (HR 1.70, 05% CI 1.30-2.22).

CONCLUSIONS: Among critically ill older adults admitted to an ED and discharged alive the following factors were predictive of long-term mortality: CCI > 2, LOS > 7 days, hypoxia on admission, discharge diagnosis of pneumonia and age. The following factors were predictive of mortality at 30 days after ED admission: unconsciousness on admission, hypoxia and age. These data might be clinically relevant when it comes to individualized care planning, which should take account of risk prediction and estimated prognosis.

PMID:35086496 | DOI:10.1186/s12873-022-00571-2

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