Objective To evaluate the effectiveness of diabetic patient education on glycemic control for diabeties. Methods Fifty cases of type 2 diabetic patients with educational interventions from the Diabetic Educational Center of West China Hospital and 50 type 2 diabetic patients without educational intervention were selected randomly. All the patients completed the same questionnaire. The data were analyzed by SPSS 10.0. Results The age of patients in educational group was older and the duration of sickness was longer than those in the control group, but their blood glucoses were better controlled. Conclusions Diabetic patient education is important to improve their glycemic control and decrease the risks and deterioration of diabetic chronic complications.
Objective To explore the application of the GPT-4 large language model in simplifying lung cancer radiology reports to enhance patient comprehension and doctor–patient communication efficiency. Methods A total of 362 radiology reports of non-small cell lung cancer (NSCLC) patients were collected from two hospitals between September and December 2024. Interpretive radiology reports (IRRs) were generated using GPT-4. Original reports (ORRs) and IRRs were compared through radiologist consistency evaluation and volunteer-based assessments of reading time, comprehension scores, and simulated communication duration. Results The average word count of ORRs was (459.83±55.76) words, compared with (625.42±41.59) words for IRRs (P<0.001). No significant differences were observed in expert consistency scores between ORRs and IRRs across dimensions of image interpretation accuracy, report detail completeness, explanatory depth and insight, and clinical practicality. Compared with reading ORRs, volunteers (simulated patient) read IRRs with shorter time [(346.88±29.15) s versus (409.01 ±102.40) s], with higher comprehension scores [(7.83±1.04) points versus (5.53±0.94) points] and shorter doctor-patient communication times [(317.31±57.81) s versus (714.20±56.67) s]. All differences were statistically significant (all P<0.001). Conclusion GPT-4 generated IRRs significantly improve patient comprehension and shorten communication time while maintaining medical accuracy. These findings suggest a new approach to optimizing radiology report management and enhancing healthcare service quality.