RATIONALE: Automatic scoring of polysomnography records offers many advantages, but excessive editing time seriously limits its use. OBJECTIVES: To identify reasons for excessive editing time, and the clinical utility of such editing, and to develop an approach to optimize the editing process. METHODS: Forty-two polysomnograms scored manually were scored months later by an automatic system (Michele Sleep Scoring). Results were edited by the technologist who scored them initially. Editing actions and time were documented. An Editing Helper algorithm was developed on the basis of these results, and its effectiveness was tested in 60 new records. MEASUREMENTS AND MAIN RESULTS: Technologists performed 253 ± 110 actions, consuming 54.5 ± 26.3 minutes, per file. Of the edits, 33% were either subsequently reversed or not considered in the clinical summary. The electroencephalography pattern in 67% of epochs changed from awake to non-REM sleep, and vice versa, represented neither stable wakefulness nor sleep so that assigning a precise stage was arbitrary. Many opposing changes occurred. Ultimately the impact of editing on summary results was limited. In the second set, the Editing Helper algorithm reduced editing time from 59 ± 26 to 6 ± 7 minutes. Average (±SD) intraclass correlation coefficients for 15 reported variables were 0.77 ± 0.14 for manual versus unedited automatic, 0.89 ± 0.09 for manual versus fully edited automatic, and 0.87 ± 0.08 for manual versus automatic edited according to the Editing Helper's suggestions only, and there was no difference between the last two average intraclass correlation coefficients. CONCLUSIONS: Editing time does not reflect unreliable scoring. Comprehensive editing of a well-validated automatic scoring system is highly inefficient. Editing can be substantially optimized.
RATIONALE: Automatic scoring of polysomnography records offers many advantages, but excessive editing time seriously limits its use. OBJECTIVES: To identify reasons for excessive editing time, and the clinical utility of such editing, and to develop an approach to optimize the editing process. METHODS: Forty-two polysomnograms scored manually were scored months later by an automatic system (Michele Sleep Scoring). Results were edited by the technologist who scored them initially. Editing actions and time were documented. An Editing Helper algorithm was developed on the basis of these results, and its effectiveness was tested in 60 new records. MEASUREMENTS AND MAIN RESULTS: Technologists performed 253 ± 110 actions, consuming 54.5 ± 26.3 minutes, per file. Of the edits, 33% were either subsequently reversed or not considered in the clinical summary. The electroencephalography pattern in 67% of epochs changed from awake to non-REM sleep, and vice versa, represented neither stable wakefulness nor sleep so that assigning a precise stage was arbitrary. Many opposing changes occurred. Ultimately the impact of editing on summary results was limited. In the second set, the Editing Helper algorithm reduced editing time from 59 ± 26 to 6 ± 7 minutes. Average (±SD) intraclass correlation coefficients for 15 reported variables were 0.77 ± 0.14 for manual versus unedited automatic, 0.89 ± 0.09 for manual versus fully edited automatic, and 0.87 ± 0.08 for manual versus automatic edited according to the Editing Helper's suggestions only, and there was no difference between the last two average intraclass correlation coefficients. CONCLUSIONS: Editing time does not reflect unreliable scoring. Comprehensive editing of a well-validated automatic scoring system is highly inefficient. Editing can be substantially optimized.
Authors: Diego R Mazzotti; Diane C Lim; Kate Sutherland; Lia Bittencourt; Jesse W Mindel; Ulysses Magalang; Allan I Pack; Philip de Chazal; Thomas Penzel Journal: Physiol Meas Date: 2018-09-13 Impact factor: 2.833
Authors: Magdy Younes; Samuel T Kuna; Allan I Pack; James K Walsh; Clete A Kushida; Bethany Staley; Grace W Pien Journal: J Clin Sleep Med Date: 2018-02-15 Impact factor: 4.062
Authors: Anna Ricci; Fan He; Jidong Fang; Susan L Calhoun; Alexandros N Vgontzas; Duanping Liao; Magdy Younes; Edward O Bixler; Julio Fernandez-Mendoza Journal: Sleep Med Date: 2021-05-11 Impact factor: 4.842