Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Humans ; Parkinson Disease/diagnosis* ; Machine Learning

BACKGROUND:Magnesium can be degraded voluntarily in vivo, so a second surgery is avoided. However, its aloys have not been widely used in the clinical orthopedics because there is a lack of accurate and reliable methods to assess its degradationin vivo.
OBJECTIVE:To explore the degradation of micro-arc-oxidized AZ31 magnesium aloy in the femoral condyle of rabbits based on micro-CT images and relative data.
METHODS:Forty micro-arc-oxidized AZ31 magnesium aloys were implanted into the right femoral condyle of 40 New Zealand rabbits. Then 10 right femoral condyles were removed at 5, 10, 15 and 20 weeks after surgery, respectively, to quantitatively analyze and evaluate the degradation of AZ31 magnesium aloys by micro-CT images and relative data.
RESULTS AND CONCLUSION:The surface of AZ31 aloys was corroded progressively with dark color and distorted appearance at 5-20 weeks post implantation. Micro-CT images showed that in the first 5 weeks, the degradation was inactive, and at the 10th week, it turned active; at the 15th week, the corrosion pits were obviously increased in number, and the corrosion area and corrosion speed were enlarged and fastened, respectively. Up to the 20th week, the aloy surfaces were ful of corrosion pits besides roughness and discontinuity. Relevant data analysis showed that the volume fraction of magnesium aloy was 98.6%, 97.1% and 86.4% at the 5th, 10th and 20th weeks after implantation, respectively, and it had a significant decrease from the 10th to 15th week and from the 15th to 20th week (P < 0.05). Within 15-20 weeks, the volume fraction of magnesium aloy was decreased by 6.5% that was the maximum volume reduction per unit cycle. With the progress of corrosion, the surface continuously became rough and vague, and its surface area was enlarged; the ratio of surface area to volume continuously increased, and there was a significant difference at 15 and 20 weeks (P < 0.05). Because of the increasing number of corrosion pits, the cross-sectional radius decreased, which was reflected by the trabecular thickness decreasing from 1.00 to 0.87 mm. From the view of the slope of curve, the trabecular thickness decreased most rapidly at 10-15 weeks. The mineral density of magnesium aloy continuously decreased from 649.302 to 356.445 mg/cm3 during the whole experiment period (P< 0.05). In addition, the micro-CT image density decreased from 679.710 to 644.947 mg/cm3, but there was no significant difference. To conclude, the degradation speed is peaked at 10-20 weeks after implantation, and the content of magnesium aloys decrease with degradation, but the magnesium density has no significant change.