Objective:To investigate the feasibility of flight fatigue being detected via photoplethysmography (PPG) and regional cerebral oxygen saturation (rScO 2) in order to address the challenges posed by flight fatigue during prolonged or multiple consecutive flights. Methods:A total of 16 healthy male volunteers were enrolled. A wireless cerebral oximetry monitor headband was employed to collect PPG and rScO 2 data from the forehead while a multi-lead physiological data acquisition system was used concurrently to record three-lead electrocardiograms (ECGs). After 18 h of sleep deprivation, each volunteer performed a flight-simulating task, which was divided into 4 stages: the baseline period (T1), relaxation period (T2), early fatigue period (T3) and severe fatigue period (T4). Five-minute data was collected from each stage for analysis using AcqKnowledge 6.0. Heart rate (HR) and 3 HR variability (HRV) metrics, namely standard deviation of NN intervals (SDNN), root mean square of successive differences (RMSSD), and low frequency to high frequency power ratio (LF/HF), were computed independently from both ECG and PPG traces. The mean rScO 2 value for each stage was used to represent the cerebral oxygen saturation during that stage. The intra-class correlation coefficient (ICC) was employed to assess the consistency of the measurements, and the differences in HR and HRV indicators of the volunteers in the 4 stages of the experiment were analyzed. Results:The HR measured by ECG and PPG was highly consistent across the 4 stages among the 14 volunteers ( ICC=0.951, 0.963, 0.962, 0.963, P=0.013, 0.011, 0.021, 0.015), so were SDNN, RMSSD and LF/HF values ( ICC=0.935-0.983, all P<0.05). HR values calculated with either method showed significant differences across the 4 stages in the 14 volunteers ( F=21.63, 20.52, P=0.007, 0.008). HR gradually declined from T1 to T4, and was significantly lower at T4 than at T1 ( P=0.011, 0.009). There were significant differences in SDNN ( F=22.31, 24.26, P=0.006, 0.003), RMSSD ( F=22.30, 22.26, P=0.006, 0.006), and LF/HF ( F=20.37, 25.13, P=0.009, 0.002) across the 4 stages among the 14 volunteers. SDNN and RMSSD kept increasing as fatigue was intensified, while LF/HF decreased correspondingly. Statistically significant differences were found in SDNN, RMSSD and LF/HF values between T4 and T1 (all P<0.01). rScO 2 measured during the flight-simulating trial also differed significantly across the 4 stages ( F=21.39, P=0.007). rScO? at both T3 and T4 was significantly lower than at T1 ( P=0.009, 0.007). Conclusions:PPG can replace ECG for monitoring HR and HRV indicators under flight fatigue. Furthermore, the combination of PPG with rScO 2 monitoring allows for earlier detection of flight fatigue. This study is expected to offer a user-friendly and non-invasive approach to management of pilot fatigue.

Objective:To investigate the feasibility of flight fatigue being detected via photoplethysmography (PPG) and regional cerebral oxygen saturation (rScO 2) in order to address the challenges posed by flight fatigue during prolonged or multiple consecutive flights. Methods:A total of 16 healthy male volunteers were enrolled. A wireless cerebral oximetry monitor headband was employed to collect PPG and rScO 2 data from the forehead while a multi-lead physiological data acquisition system was used concurrently to record three-lead electrocardiograms (ECGs). After 18 h of sleep deprivation, each volunteer performed a flight-simulating task, which was divided into 4 stages: the baseline period (T1), relaxation period (T2), early fatigue period (T3) and severe fatigue period (T4). Five-minute data was collected from each stage for analysis using AcqKnowledge 6.0. Heart rate (HR) and 3 HR variability (HRV) metrics, namely standard deviation of NN intervals (SDNN), root mean square of successive differences (RMSSD), and low frequency to high frequency power ratio (LF/HF), were computed independently from both ECG and PPG traces. The mean rScO 2 value for each stage was used to represent the cerebral oxygen saturation during that stage. The intra-class correlation coefficient (ICC) was employed to assess the consistency of the measurements, and the differences in HR and HRV indicators of the volunteers in the 4 stages of the experiment were analyzed. Results:The HR measured by ECG and PPG was highly consistent across the 4 stages among the 14 volunteers ( ICC=0.951, 0.963, 0.962, 0.963, P=0.013, 0.011, 0.021, 0.015), so were SDNN, RMSSD and LF/HF values ( ICC=0.935-0.983, all P<0.05). HR values calculated with either method showed significant differences across the 4 stages in the 14 volunteers ( F=21.63, 20.52, P=0.007, 0.008). HR gradually declined from T1 to T4, and was significantly lower at T4 than at T1 ( P=0.011, 0.009). There were significant differences in SDNN ( F=22.31, 24.26, P=0.006, 0.003), RMSSD ( F=22.30, 22.26, P=0.006, 0.006), and LF/HF ( F=20.37, 25.13, P=0.009, 0.002) across the 4 stages among the 14 volunteers. SDNN and RMSSD kept increasing as fatigue was intensified, while LF/HF decreased correspondingly. Statistically significant differences were found in SDNN, RMSSD and LF/HF values between T4 and T1 (all P<0.01). rScO 2 measured during the flight-simulating trial also differed significantly across the 4 stages ( F=21.39, P=0.007). rScO? at both T3 and T4 was significantly lower than at T1 ( P=0.009, 0.007). Conclusions:PPG can replace ECG for monitoring HR and HRV indicators under flight fatigue. Furthermore, the combination of PPG with rScO 2 monitoring allows for earlier detection of flight fatigue. This study is expected to offer a user-friendly and non-invasive approach to management of pilot fatigue.

Objective: To investigate the clinical effect and safety of long-acting pegylated interferon-α-2b (Peg-IFN-α-2b) (Y shape, 40 kD) injection (180 μg/week) in the treatment of HBeAg-positive chronic hepatitis B (CHB) patients, with standard-dose Peg-IFN-α-2a as positive control. Methods: This study was a multicenter, randomized, open-label, and positive-controlled phase III clinical trial. Eligible HBeAg-positive CHB patients were screened out and randomized to Peg-IFN-α-2b (Y shape, 40 kD) trial group and Peg-IFN-α-2a control group at a ratio of 2:1. The course of treatment was 48 weeks and the patients were followed up for 24 weeks after drug withdrawal. Plasma samples were collected at screening, baseline, and 12, 24, 36, 48, 60, and 72 weeks for centralized detection. COBAS® Ampliprep/COBAS® TaqMan® HBV Test was used to measure HBV DNA level by quantitative real-time PCR. Electrochemiluminescence immunoassay with Elecsys kit was used to measure HBV markers (HBsAg, anti-HBs, HBeAg, anti-HBe). Adverse events were recorded in detail. The primary outcome measure was HBeAg seroconversion rate after the 24-week follow-up, and non-inferiority was also tested. The difference in HBeAg seroconversion rate after treatment between the trial group and the control group and two-sided confidence interval (CI) were calculated, and non-inferiority was demonstrated if the lower limit of 95% CI was > -10%. The t-test, chi-square test, or rank sum test was used according to the types and features of data. Results: A total of 855 HBeAg-positive CHB patients were enrolled and 820 of them received treatment (538 in the trial group and 282 in the control group). The data of the full analysis set showed that HBeAg seroconversion rate at week 72 was 27.32% in the trial group and 22.70% in the control group with a rate difference of 4.63% (95% CI -1.54% to 10.80%, P = 0.1493). The data of the per-protocol set showed that HBeAg seroconversion rate at week 72 was 30.75% in the trial group and 27.14% in the control group with a rate difference of 3.61% (95% CI -3.87% to 11.09%, P = 0.3436). 95% CI met the non-inferiority criteria, and the trial group was non-inferior to the control group. The two groups had similar incidence rates of adverse events, serious adverse events, and common adverse events. Conclusion In Peg-IFN-α regimen for HBeAg-positive CHB patients, the new drug Peg-IFN-α-2b (Y shape, 40 kD) has comparable effect and safety to the control drug Peg-IFN-α-2a.