Sleep Disorders and Sleep Deprivation: An Unmet Public

Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem
http://www.nap.edu/catalog/11617.html
224 SLEEP DISORDERS AND SLEEP DEPRIVATION
using a careful history; lung function tests are used to gauge disease severity
and treatment responses and sometimes to help differentiate asthma from
other respiratory conditions. The issues that plague equipment development
and laboratory access in the sleep laboratory have not impeded the
development of lung function laboratories. Rather, the development and
accreditation of lung function laboratories and lung function equipment
(including portable spirometers) are based on collecting reproducible data
that meet physiological criteria for accuracy, independent of the role of
such equipment as tools evaluated on their ability to independently classify
disease status. It is recognized that the latter requires consideration of multiple
factors, including symptoms, level of impairment, response to allergic
and irritant triggers, and often empiric responses to therapeutic trials.
Other challenges relate to designing studies that specifically address
a number of distinct potential applications of portable sleep monitoring.
These include screening—which is often population-based, and
intended to detect cases independent of symptoms; clinical case definition—
identification of cases among patients referred because of health concerns;
disease management in which sleep monitoring provides quantitative data
on progression or regression of disease severity; and epidemiological studies—in
which sleep monitoring is used to provide a quantitative assessment
of a physiological exposure or outcome. It is important that any given
evaluation study of new technologies be designed to address a specific question
or related series of questions.
Scoring and Processing of Sleep Studies
Current scoring approaches use a system of epoch by epoch scoring (30
seconds per epoch) developed over 40 years ago when polysomnography used
only paper-based systems based on analog data. This approach is recognized
to be both labor-intensive and time-consuming. Further, reliance on human
scorers using visual pattern recognition requires intensive and ongoing training
to achieve high reliability (Whitney et al., 1998), which may be lower
than that potentially attained by automated methods (which also have their
limitations). Visual scoring also may not maximally utilize the spectral components
of the electrophysiological data, which may provide useful information
on sleep architecture. Furthermore, there is a shortage of trained sleep
technicians. Currently there are only 2,198 certified technicians to monitor
and score sleep tests, far below the need (Association of Polysomnographic
Technologists, 1999). Recognizing these issues, the AASM convened a task
force in 2004 to reassess current scoring approaches, critically evaluate both
sensors and scoring algorithms, and update scoring approaches as appropriate
to include digital analysis of electrophysiological data. This report, scheduled
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