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Objective:This paper examines the access control mechanisms of a big data platform and explores its integration with the ChatGPT artificial intelligence platform for nursing management. The aim was to pilot a self-monitoring and follow-up big data platform for valve disease patients in the Northeastern region of China and assess its effectiveness, providing healthcare professionals with a more practical follow-up tool.Methods:Convenience sampling was used to select 32 patients who underwent mechanical valve replacement surgery or postoperative follow-up at the affiliated hospital of North Sichuan Medical College between January and October 2022 by a retrospective study, were taking oral warfarin anticoagulant therapy, and were willing to use the platform. Based on their platform usage data from November to December 2022, the 32 patients were divided into two groups according to their INR compliance rates: a high compliance group (16 patients) and a low compliance group (16 patients). Evaluate the operational effectiveness of the platform and its impact on patient anticoagulation efficacy based on its usage frequency and INR value compliance rate.Results:The number of login times and INR values written by patients in the high-standard-rate group were (11.31 ± 3.38) and (7.00 ± 1.63) times respectively, which were higher than those in the low-standard-rate group (9.44 ± 3.39) and (6.06 ± 1.88) times, the difference were not statistically significant (all P>0.05). The number of INR values written within the normal range and the number of occurrences of warning values by patients in the high-standard-rate group were (6.38 ± 1.50) and 1.00(0, 2.00) times, which were different than that in the low-standard-rate group (4.05 ± 1.57) and 2.00(2.00, 3.50) times, the differences were statistically significant ( t = 4.26, Z = - 2.22, P<0.05). Conclusions:The self-monitoring and follow-up big data platform for patients after artificial mechanical valve replacement equipped with ChatGPT can optimize and standardize the nursing follow-up workflow, improve nursing work efficiency, reduce the workload of medical staff. At the same time, it provides a better self-management platform for patients after artificial mechanical valve replacement. Assist patients in monitoring INR values and predicting possible changes in their condition, providing corresponding warnings and recommendations helps patients better participate in self-anticoagulation management, and improves the quality of life of patients.
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Objective:To compare the safety and effectiveness of disposable and reusable flexible electronic ureteroscopes in the treatment of upper urinary tract stones in elderly patients.Methods:A retrospective analysis was made on clinical data of elderly patients with unilateral upper urinary tract calculi receiving flexible ureteroscopic lithotripsy at Beijing Hospital between March 2020 and November 2022.According to the type of the flexible ureteroscope used, patients who met the requirements for inclusion were divided into a single-use flexible ureteroscope group and a reusable flexible ureteroscope group.The stone-free rate, the operative time, the length of postoperative hospitalization and the incidence of postoperative systemic inflammatory response syndrome(SIRS)were compared between the two groups.Results:A total of 225 eligible participants were enrolled from Beijing Hospital, of whom 107 in the single-use flexible ureteroscope group and 118 in the reusable flexible ureteroscope group underwent evaluation.The operative time[60(40, 97)min vs.75(60, 110)min, Z=-2.947, P=0.003]and the length of postoperative hospitalization[1(1, 2)days vs.1(1, 2)days, Z=-2.554, P=0.011]of the single-use flexible ureteroscope group were shorter than those of the reusable flexible ureteroscope group.There were no statistically significant differences in the lithotripsy success rate[89/107(83.2%) vs.92/118(78.0%), χ2=0.969, P=0.325]and the incidence of postoperative SIRS[8/107(7.5%) vs.14/118(11.9%), χ2=1.225, P=0.268]. Conclusions:There is no significant difference in the lithotripsy success rate and postoperative SIRS rate between single-use digital flexible ureteroscopes and reusable flexible digital ureteroscopes for lithotripsy of upper ureteral stones in elderly patients, while the operative time and the length of postoperative hospitalization of using single-use flexible ureteroscopes are shorter than those of using reusable flexible ureteroscopes.Single-use digital flexible ureteroscopes have satisfactory safety and effectiveness for the treatment of upper urinary tract calculi in elderly patients.
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Objective:To explore the efficacy and safety of neoadjuvant chemoimmunotherapy combined with surgery for stage ⅢA NSCLC patients.Methods:Six patients with NSCLC who were diagnosed as ⅢA and received two cycles of neoadjuvant chemoimmunotherapy and surgery between September 2019 and January 2020 were described in this study.Results:Five of them experienced AEs during neoadjuvant therapy. All of them received surgery and achieved an MPR of 50%. No viable tumor cells were found in the tissues of one patient. One patient with a small bronchopleural fistula after lobectomy.Conclusion:Neoadjuvant chemoimmunotherapy combined with surgery for stage ⅢA NSCLC patients is safe and efficient. Long-term outcomes of neoadjuvant chemoimmunotherapy combined with surgery should be further validated.
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PurposeThe pandemic of Covid-19 has caused tremendous losses to lives and economy in the entire world. The machine learning models have been applied to the radiological images of the Covid-19 positive patients for disease prediction and severity assessment. However, a segmentation model for detecting the opacity regions like haziness, ground-glass opacity and lung consolidation from the Covid-19 positive chest X-rays is still lacking. MethodsThe recently published collection of the radiological images for a rural population in United States had made the development of such a model a possibility, for the high quality images and consistent clinical measurements. We manually annotated 221 chest X-ray images with the lung fields and the opacity regions and trained a segmentation model for the opacity region using the Unet framework and the Resnet18 backbone. In addition, we applied the percentage of the opacity region over the area of the total lung fields for predicting the severity of patients. ResultsThe model has a good performance regarding the overlap between the predicted and the manually labelled opacity regions. The performance is comparable for both the testing data set and the validation data set which comes from very diverse sources. However, careful manual examinations by experienced radiologists show mistakes in the predictions, which could be caused by the anatomical complexities. Nevertheless, the percentage of the opacity region can predict the severity of the patients well in regards to the ICU admissions and mortality. ConclusionIn view of the above, our model is a successful first try in the development of a segmentation model for the opacity regions for the Covid-19 positive chest X-rays. However, additional work is needed before a robust model can be developed for the ultimate goal of the implementations in the clinical setting. Model and supporting materials can be found in https://github.com/haimingt/opacity_segmentation_covid_chest_X_ray.