br Epidemiology of IFL A study using

Epidemiology of IFL
A study using a representative population sample based on a census of Sao Paolo, Brazil evaluated the distribution of IFL in asymptomatic versus symptomatic subjects [34]. The goal was to define how much IFL exists in the general population and to determine a threshold beyond which IFL is considered pathologic.
The study took advantage of an existing epidemiologic cohort of 1,101 individuals who had undergone PSG to identify normal asymptomatic subjects. Subjects with moderate-to-severe OSA were excluded from the analysis, as IFL is unnecessary to support the diagnosis in these cases and tends to be absent in cases where monensin predominates. The scoring of IFL was performed manually by visual inspection. Periods of IFL were defined as at least four consecutive breaths showing inspiratory flattening of the airflow curve that did not meet criteria for hypopnea. Three scorers evaluated 20 studies and the inter-scorer agreement rate for percent rate of IFL was 0.950 (p<0.001). The normal group (n=163) was defined by the following criteria: (1) no known diagnosis of a sleep disorder or sleep complaints, (2) no OSA according to International Classification of Sleep Disorders (ICSD-2) criteria, and (3) no significant primary lung disease.
IFL-related EEG changes during sleep
In prior studies, it has been demonstrated that UARS patients have an important disruption of sleep EEG with a continuous increase in fast range EEG frequencies, and that the sleep EEG is as disturbed with continuous IFL as it is with repetitive hypopneas [35,36]. Black et al. showed that patients with SDB, predominantly IFL, did not re-open their airway only with presence of an alpha EEG burst; but often upper airway re-opening occurred in association with a burst of delta [37]. An alpha rhythm often followed the delta burst, but was commonly very short and did not respond to the definition of the EEG arousals from the AASM.
A large amount of work has been performed indicating that disturbance of sleep based on the sleep-EEG analysis did not respond to the definition of the EEG arousal [38]. Definitions of disturbance of sleep EEG based on specific patterns seen during non-rapid eye movement (NREM) sleep were tested and published under the label of “cyclic alternating pattern” or CAP. The CAP is a periodic EEG activity of NREM sleep characterized by sequences of transient electro-cortical events that are distinct from background EEG activity and recur at up to 1-min intervals as seen in Fig. 6[39]. CAP activity may signify sleep stage instability, sleep disturbance, or both.
A prospective, single-blinded study compared the CAP rate of subjects with UARS and controls [40]. Results of CAP analysis demonstrated a significant reduction in NREM sleep, an elevated CAP rate, and an increase in EEG arousals based on CAP rate analysis. There was a significant positive correlation between CAP rate and Epworth sleepiness scale (ESS) score.
Another study sought to define the relationship between chronic fatigue, unrefreshing sleep, and abnormal SWS involving symptomatic and asymptomatic (control) subjects by evaluating breathing using nasal cannula and Pes [36]. After performing conventional PSG scoring, Fast Fourier Transformation (FFT) was applied for investigation of the sleep EEG frequency bands. Symptomatic subjects presented an abnormal amount of IFL detected by nasal cannula monitoring and abnormal Pes recording providing evidence of increased inspiratory efforts. There was nocturnal sleep disturbances with reduction of SWS and sleep efficiency, increase in CAP rate, and FFT analysis showed an abnormal increase of the delta-1 (0.5–2Hz) band with decrease in all other EEG bands compared to controls.
Guilleminault et al. also conducted a study involving OSA split into a hypopnea and apnea-hypopnea subgroup, UARS patients and an asymptomatic normal breathing control group matched for age and body-mass-index. The study compared the nocturnal sleep EEG after treatment using FFT to dissociate the different EEG band activity using a 4min over-lapping time-window [40]. All SDB groups had a significantly different sleep EEG than controls, but the UARS patients were also significantly different than both OSA patients groups: There was a significant increase in both delta and alpha bandwidth powers in UARS compared to OSA, and a much higher alpha power with less delta power than controls. The conclusion of the authors was that the UARS patient demonstrated less sleep disturbance when considering the bands other than alpha, but had a much more “alert type” of EEG during the total sleep time with much higher alpha relative power leading to a maintenance of air exchange at the cost of continuous near-awakening.