Research Article
A Preoperative Risk Prediction Model for Complications After Radical Resection of Esophageal Cancer
Issue:
Volume 7, Issue 1, March 2026
Pages:
1-11
Received:
6 March 2026
Accepted:
18 March 2026
Published:
28 March 2026
Abstract: Objective: To analyze preoperative risk factors for complications following radical esophageal cancer surgery, and to establish a preoperative risk prediction model for postoperative complications, thereby providing a reference for medical staff to formulate and implement reasonable intervention measures for patients. Methods: Clinical data from 485 patients who underwent surgery for esophageal cancer were retrospectively collected and randomly divided into a training set (340 cases) and a validation set (145 cases) at a ratio of 7: 3. Independent predictors were identified by univariate logistic regression, LASSO regression, and multivariate logistic regression analysis, and a nomogram model was constructed. The model's discriminative ability, calibration, and clinical utility were evaluated using ROC curves, calibration curves, DCA curves, and CIC curves. Results: The incidence of postoperative complications in this study was 36.9%. The proportions of various complication types were: pleural effusion 49.2%, aspiration pneumonia 7.3%, pulmonary infection 40.2%, pneumothorax 16.8%, atelectasis 2.8%, and respiratory failure 2.8%. Five predictors—age, BMI, underlying lung disease, NRS 2002 score, and tumor location—were included in the final model. The AUCs of the training set and validation set were 0.777 (95% CI: 0.725–0.829) and 0.702 (95% CI: 0.609–0.790), respectively, indicating good calibration and clinical practicability. Conclusion: The preoperative risk prediction model established in this study demonstrates good discrimination, calibration, and clinical effectiveness.
Abstract: Objective: To analyze preoperative risk factors for complications following radical esophageal cancer surgery, and to establish a preoperative risk prediction model for postoperative complications, thereby providing a reference for medical staff to formulate and implement reasonable intervention measures for patients. Methods: Clinical data from 48...
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Research Article
Effectiveness of Kahoot Game-based Learning and Satisfaction of Newly Graduated Nurses: A Pilot Randomized Controlled Trial
Issue:
Volume 7, Issue 1, March 2026
Pages:
12-21
Received:
3 March 2026
Accepted:
1 April 2026
Published:
16 April 2026
DOI:
10.11648/j.ajnhs.20260701.12
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Abstract: Purpose: Teachers often face the challenges in maintaining the student attention in class. This study aimed to evaluate the effectiveness of the Kahoot! game-based learning (KGBL) platform in enhancing attention span, theoretical knowledge acquisition, and satisfaction among newly graduated nurses in a hospital setting. Methods: This study employed a randomized controlled trial design. Newly graduated nurses from a tertiary hospital in China were recruited in September 2023. Participants were randomly assigned to either the experimental group (n=44) or the control group (n=43). The experimental group underwent a 5-day training program incorporating pre-class quizzes via the KGBL platform, while the control group received traditional classroom-based training without the gamified component. The training content followed the 2016 “Newly Employed Nurse Training Outline,” covering essential theoretical knowledge and practical guidelines. The concentration indicator was used to assess the nurses classroom attention; the acquisition of theoretical knowledge was measured using a closed-book exam. A 9-item questionnaire was used to survey the intervention group's satisfaction and attitude toward KGBL Results: The results showed that the KGBL group's concentration scores (eye contact, body language, classroom behaviour, and total score) were significantly higher than those of the control group at 5, 15, and 25 minutes (P < 0.001). At 35 minutes, the KGBLgroup continued to show significantly higher scores in eye contact, body language, and overall attention was a statistically significant difference (P < 0.001). Test of theoretical knowledge: the KGBL group had an average score of 91.1±4.1, while the control group had an average score of 77.3±5.5 was a statistically significant difference (P<0.001). The majority of nurses reported KGBL reinforced the content learning in class and they enjoyed the learning process (95.3%). Almost all participants (95.3%) expressed a desire that the KGBL could be integrated into their future learning or education. Conclusions: This pilot study demonstrated the feasibility of KGBL in the nursing training program in hospital situations and suggested its potential effectiveness in enhancing attention, test scores, and satisfaction. Despite limitations such as the short study duration and lack of long-term follow-up, these preliminary findings suggest that gamified learning tools like KGBL could play a valuable role in enhancing nurse training. Further research is needed to explore the long-term impact of KGBL on learning outcomes and its broader applicability in nursing education.
Abstract: Purpose: Teachers often face the challenges in maintaining the student attention in class. This study aimed to evaluate the effectiveness of the Kahoot! game-based learning (KGBL) platform in enhancing attention span, theoretical knowledge acquisition, and satisfaction among newly graduated nurses in a hospital setting. Methods: This study employed...
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,
Hongjuan Wu*
