1.Design and application of auxiliary recovering device after retinal detachment operation
Lilan LI ; Lianhong NI ; Xiaoxin WU
Chinese Medical Equipment Journal 2017;38(5):45-47
Objective To develop an auxiliary recovering device for prone position nursing after the retina vitrectomy in order to improve comfort and treatment compliance.Methods The device was made of stainless steel,and consisted of a base,pulleys,supporting rods and a placing case.Totally 40 patients receiving retinal detachment operation were divided into an experimental group and a control group.The patients in the experimental group applied the auxiliary device and the ones in the control group underwent conventional nursing,and then a 2-week observation was executed on the prone time,overall satisfaction and adverse response after the operation.Results The device behaved well in prone time,patient comfort and satisfaction,and the experimental group gained advantages over the control group in prone time,relieving muscle pains,arthralgia,poor breath,anxiety and insomnia.Chi-square test proved the experimental group had the patient satisfaction significantly enhanced when compared with the control group (P<0.05).Conclusion The device can be used for auxiliary nursing after retinal detachment operation with simple structure,easy operation and high comfort,and thus is worthy promoting practically.
2.Nomogram including serum ferritin to predict the occurrence of diabetic retinopathy
Xiaoyu WU ; Dandan XIE ; Jiana CHEN ; Lianhong NI ; Weina LI
International Eye Science 2024;24(5):671-676
AIM:To establish a nomogram model to predict the effect of serum ferritin on diabetic retinopathy and evaluate the model.METHODS:A total of 21 variables, including ferritin, were screened by univariate and multivariate regression analysis to determine the risk factors of diabetic retinopathy. A nomogram prediction model was established for evaluation and calibration.RESULTS:Ferritin, duration of diabetes, hemoglobin, urine microalbumin, regularity of medication and body mass index were included in the nomogram model. The consistency index of the prediction model with serum ferritin was 0.813(95%CI: 0.748-0.879). The calibration curves of internal and external verification showed good performance, and the probability of the threshold suggested by the decision curve was in the range 10% to 90%. The model had a high net profit value.CONCLUSIONS:Serum ferritin is an important risk factor for diabetic retinopathy. A new nomogram model, which includes body mass index, duration of diabetes, ferritin, hemoglobin, urine microalbumin and regularity of medication, has a high predictive accuracy and could provide early prediction for clinicians.