STUDY OBJECTIVES: Manual scoring of polysomnograms (PSG) is labor intensive and has considerable variance between scorers. Automation of scoring could reduce cost and improve reproducibility. The purpose of this study was to compare a new automated scoring system (YST-Limited, Winnipeg, Canada) with computer-assisted manual scoring. DESIGN: Technical assessment. SETTING: Five academic medical centers. PARTICIPANTS: N/A. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Seventy PSG files were selected at University of Pennsylvania (Penn) and distributed to five US academic sleep centers. Two blinded technologists from each center scored each file. Automatic scoring was performed at Penn by a YST Limited technician using a laptop containing the software. Variables examined were sleep stages, arousals, and apnea-hypopnea index (AHI) using three methods of identifying hypopneas. Automatic scores were not edited and were compared to the average scores of the 10 technologists. Intraclass correlation coefficient (ICC) was obtained for the 70 pairs and compared to across-sites ICCs for manually scored results. ICCs for automatic versus manual scoring were > 0.8 for total sleep time, stage N2, and nonrapid eye movement arousals and > 0.9 for AHI scored by primary and secondary American Academy of Sleep Medicine criteria. ICCs for other variables were not as high but were comparable to the across-site ICCs for manually scored results. CONCLUSION: The automatic system yielded results that were similar to those obtained by experienced technologists. Very good ICCs were obtained for many primary PSG outcome measures. This automated scoring software, particularly if supplemented with manual editing, may increase laboratory efficiency and standardize PSG scoring results within and across sleep centers.
STUDY OBJECTIVES: Manual scoring of polysomnograms (PSG) is labor intensive and has considerable variance between scorers. Automation of scoring could reduce cost and improve reproducibility. The purpose of this study was to compare a new automated scoring system (YST-Limited, Winnipeg, Canada) with computer-assisted manual scoring. DESIGN: Technical assessment. SETTING: Five academic medical centers. PARTICIPANTS: N/A. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Seventy PSG files were selected at University of Pennsylvania (Penn) and distributed to five US academic sleep centers. Two blinded technologists from each center scored each file. Automatic scoring was performed at Penn by a YST Limited technician using a laptop containing the software. Variables examined were sleep stages, arousals, and apnea-hypopnea index (AHI) using three methods of identifying hypopneas. Automatic scores were not edited and were compared to the average scores of the 10 technologists. Intraclass correlation coefficient (ICC) was obtained for the 70 pairs and compared to across-sites ICCs for manually scored results. ICCs for automatic versus manual scoring were > 0.8 for total sleep time, stage N2, and nonrapid eye movement arousals and > 0.9 for AHI scored by primary and secondary American Academy of Sleep Medicine criteria. ICCs for other variables were not as high but were comparable to the across-site ICCs for manually scored results. CONCLUSION: The automatic system yielded results that were similar to those obtained by experienced technologists. Very good ICCs were obtained for many primary PSG outcome measures. This automated scoring software, particularly if supplemented with manual editing, may increase laboratory efficiency and standardize PSG scoring results within and across sleep centers.
Authors: T Hori; Y Sugita; E Koga; S Shirakawa; K Inoue; S Uchida; H Kuwahara; M Kousaka; T Kobayashi; Y Tsuji; M Terashima; K Fukuda; N Fukuda Journal: Psychiatry Clin Neurosci Date: 2001-06 Impact factor: 5.188
Authors: Stephen D Pittman; Mary M MacDonald; Robert B Fogel; Atul Malhotra; Koby Todros; Baruch Levy; Amir B Geva; David P White Journal: Sleep Date: 2004-11-01 Impact factor: 5.849
Authors: Peter Anderer; Arnaud Moreau; Michael Woertz; Marco Ross; Georg Gruber; Silvia Parapatics; Erna Loretz; Esther Heller; Andrea Schmidt; Marion Boeck; Doris Moser; Gerhard Kloesch; Bernd Saletu; Gerda M Saletu-Zyhlarz; Heidi Danker-Hopfe; Josef Zeitlhofer; Georg Dorffner Journal: Neuropsychobiology Date: 2010-09-09 Impact factor: 2.328
Authors: Vladimir Svetnik; Junshui Ma; Keith A Soper; Scott Doran; John J Renger; Steve Deacon; Ken S Koblan Journal: Sleep Date: 2007-11 Impact factor: 5.849
Authors: Einas M Yousef; Daniela Furrer; David L Laperriere; Muhammad R Tahir; Sylvie Mader; Caroline Diorio; Louis A Gaboury Journal: Mod Pathol Date: 2017-01-13 Impact factor: 7.842
Authors: Lien Desteghe; Jeroen M L Hendriks; R Doug McEvoy; Ching Li Chai-Coetzer; Paul Dendale; Prashanthan Sanders; Hein Heidbuchel; Dominik Linz Journal: Clin Res Cardiol Date: 2018-04-12 Impact factor: 5.460
Authors: Xiaoling Gao; Ali Azarbarzin; Brendan T Keenan; Michele Ostrowski; Frances M Pack; Bethany Staley; Greg Maislin; Allan I Pack; Magdy Younes; Samuel T Kuna Journal: Sleep Date: 2017-06-01 Impact factor: 5.849
Authors: Dae Y Kang; Pamela N DeYoung; Atul Malhotra; Robert L Owens; Todd P Coleman Journal: IEEE Trans Biomed Eng Date: 2017-05-08 Impact factor: 4.538
Authors: Cathy A Goldstein; Richard B Berry; David T Kent; David A Kristo; Azizi A Seixas; Susan Redline; M Brandon Westover Journal: J Clin Sleep Med Date: 2020-04-15 Impact factor: 4.062