Incidence, predictors and prognostic implications of dyspnea at admission among acute coronary syndrome patients without heart failure

Unsupervised machine learning identifies symptoms of indigestion as a predictor of acute decompensation and adverse cardiac events in patients with heart failure presenting to the emergency department

BACKGROUND

Patients with known heart failure (HF) present to emergency departments (ED) with a plethora of symptoms. Although symptom clusters have been suggested as prognostic features, accurately triaging HF patients is a longstanding challenge.

OBJECTIVES

We sought to use machine learning to identify subtle phenotypes of patient symptoms and evaluate their diagnostic and prognostic value among HF patients seeking emergency care.

METHODS

This was a secondary analysis of a prospective cohort study of consecutive patients seen in the ED for chest pain or equivalent symptoms. Independent reviewers extracted clinical data from charts, including nine categories of subjective symptoms reported during initial evaluation. The diagnostic outcome was acute HF exacerbation and prognostic outcome was 30-day major adverse cardiac events (MACE). Outcomes were adjudicated by two independent reviewers. K-means clustering was used to derive latent patient symptom clusters, and their associations with outcomes were assessed using multivariate logistic regression.

RESULTS

Sample included 438 patients (age 65±14 years; 45% female, 49% Black, 18% HF exacerbation, 32% MACE). K-means clustering identified three presentation phenotypes: patients with dyspnea only (Cluster A, 40%); patients with indigestion, with or without dyspnea (Cluster B, 23%); patients with neither dyspnea nor indigestion (Cluster C, 37%). Compared to Cluster C, indigestion was a significant predictor of acute HF exacerbation (OR=1.8, 95%CI=1.0-3.4) and 30-day MACE (OR=1.8, 95%CI=1.0-3.1), independent of age, sex, race, and other comorbidities.

CONCLUSION

Indigestion symptoms in patients with known HF signify excess risk of adverse events, suggesting that these patients should be triaged as high-risk during initial ED evaluation.

Patterns and predictors of dyspnoea following left ventricular assist device implantation

AIMS

Dyspnoea is a common symptom of heart failure (HF) that often prompts patients to seek treatment. Implantation of a left ventricular assist device (LVAD) has been associated with reduced dyspnoea but it is unclear if all patients experience similar improvements in dyspnoea over time following LVAD implantation. Our aim was to identify distinct trajectories of dyspnoea symptoms over time following LVAD implantation and predictors of dyspnoea trajectory. We hypothesized that at least two, distinct trajectories of dyspnoea would be observed following LVAD implantation.

METHODS AND RESULTS

This was a secondary analysis of data from the Profiling Biobehavioral Responses to Mechanical Support in Advanced Heart Failure study. In the parent study, sociodemographic and clinical data were collected prior to LVAD implantation and at 1, 3, and 6 months following LVAD implantation from a sample (n = 101) of patients with advanced HF. Latent growth mixture modelling was performed to identify distinct trajectories of dyspnoea symptoms. Backwards stepwise logistic regression was used to identify predictors of dyspnoea trajectory. Two, distinct trajectories of dyspnoea symptoms were identified: sustained improvement and unsustained improvement. Participants who experienced sustained improvement (86.7% of sample) demonstrated large, significant improvement in dyspnoea from pre-implantation to 3 months post-implant followed by smaller, non-significant improvement from 3 to 6 months. Participants who experienced unsustained improvement (13.3% of sample) demonstrated initial improvement from pre-implantation to 3 months post-implantation followed by worsening of dyspnoea from 3 to 6 months. Greater depressive symptoms at baseline and living alone were significant predictors of unsustained improvement.

CONCLUSION

Patients experience different patterns of dyspnoea over time following LVAD implantation. Clinicians should inquire about living arrangements and depressive symptoms at each visit to determine risk of unsustained improvement in dyspnoea.