PURPOSE: This study examined how well the Psychomotor Vigilance Task (PVT) performance was related to subjective measures of fatigue. In order to study subjects presenting with a wide range of fatigue symptoms, we studied healthy individuals as well as patients with varying severity of obstructive sleep apnea. We also examined if the PVT/fatigue relationship could be influenced by depressive symptoms. SUBJECTS AND METHODS: Forty-eight participants had their sleep monitored with polysomnography. Fatigue was assessed by Multidimensional Fatigue Symptom Inventory-short form (MFSI-sf). Depressed mood was assessed by the Center for Epidemiologic Studies-Depression (CES-D) Scale. After sleep monitoring and psychological assessments, the 10-minute PVT was administered. The main outcome variable was the PVT lapse count. Simple correlations and hierarchical linear regression were used to examine the association between age, body mass index (BMI), sleep variables, apnea hypopnea index (AHI), oxygen desaturation index (ODI), CES-D, fatigue, and PVT. RESULTS AND CONCLUSION: The PVT lapse count was significantly associated with MFSI-sf physical fatigue (r = 0.324, p = 0.025). In hierarchical regression (full model R2 = 0.256, p = 0.048), higher BMI (p = 0.038), and higher MFSI-sf physical fatigue (p= 0.040) were independent predictors of the PVT lapse count. Age, AHI, ODI, and CES-D were unrelated to the PVT lapse count. In conclusion, the findings suggest that even after controlling for age, BMI, depression, and apnea severity, physical fatigue is associated with the PVT lapse.
PURPOSE: This study examined how well the Psychomotor Vigilance Task (PVT) performance was related to subjective measures of fatigue. In order to study subjects presenting with a wide range of fatigue symptoms, we studied healthy individuals as well as patients with varying severity of obstructive sleep apnea. We also examined if the PVT/fatigue relationship could be influenced by depressive symptoms. SUBJECTS AND METHODS: Forty-eight participants had their sleep monitored with polysomnography. Fatigue was assessed by Multidimensional Fatigue Symptom Inventory-short form (MFSI-sf). Depressed mood was assessed by the Center for Epidemiologic Studies-Depression (CES-D) Scale. After sleep monitoring and psychological assessments, the 10-minute PVT was administered. The main outcome variable was the PVT lapse count. Simple correlations and hierarchical linear regression were used to examine the association between age, body mass index (BMI), sleep variables, apnea hypopnea index (AHI), oxygen desaturation index (ODI), CES-D, fatigue, and PVT. RESULTS AND CONCLUSION: The PVT lapse count was significantly associated with MFSI-sf physical fatigue (r = 0.324, p = 0.025). In hierarchical regression (full model R2 = 0.256, p = 0.048), higher BMI (p = 0.038), and higher MFSI-sf physical fatigue (p= 0.040) were independent predictors of the PVT lapse count. Age, AHI, ODI, and CES-D were unrelated to the PVT lapse count. In conclusion, the findings suggest that even after controlling for age, BMI, depression, and apnea severity, physical fatigue is associated with the PVT lapse.
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