Sleep-disordered breathing (SDB) is prevalent but underdiagnosed in chronic heart
failure (CHF). The aim of this thesis was to investigate the utility of simple portable
monitoring and clinical features to identify CHF patients with SDB. In addition, the
influence of scoring criteria on diagnosis and classification of SDB in CHF was
investigated.
In the first study, clinical characteristics in CHF patients with SDB were compared to
those without SDB. No specific symptom, anthropometric characteristic or measure of
heart failure severity was reliably able to identify CHF patients with SDB.
In the second study, the accuracy of heart rate variability (HRV) analysis and overnight
pulse oximetry for diagnosis of SDB in CHF were investigated. The percent very low
frequency increment (%VLFI) of HRV had low accuracy for diagnosis of SDB. In
contrast, the >3% oxygen desaturation index measured by pulse oximetry had a high
diagnostic accuracy, with sensitivity 0.97 and negative likelihood ratio 0.08 at a prespecified
cutoff of >7.5 desaturations per hour.
In the third study, the impact of hypopnoea scoring criteria on SDB diagnosis in CHF
was evaluated. The prevalence of SDB changed significantly from 29% when
hypopnoeas were scored with a corroborative ≥4% oxygen desaturation, to 46% when
hypopnoeas were scored with a corroborative ≥3% oxygen desaturation or arousal
from sleep (p<0.001). Respiratory event scoring criteria did not influence the
classification of SDB as obstructive or central sleep apnoea.
In summary, this thesis has shown that clinical features and HRV analysis can not be
used to identify CHF patients with SDB. Overnight pulse oximetry has a high diagnostic
accuracy and would be of greatest clinical use to rule out SDB in patients with CHF.
The criteria used to score respiratory events during sleep studies can have a significant
impact on the diagnosis and prevalence of SDB in CHF.