Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19.

BACKGROUND: During the fifth wave of the coronavirus disease 2019 (COVID-19) pandemic in Japan, which took place between June and September 2021, a significant number of COVID-19 cases with deterioration occurred in unvaccinated individuals < 65 years old. However, the risk factors for COVID-19 deterioration in this specific population have not yet been determined. This study developed a prediction method to identify COVID-19 patients < 65 years old who are at a high risk of deterioration. METHODS: This retrospective study analyzed data from 1,675 patients < 65 years old who were admitted to acute care institutions in Fukushima with mild-to-moderate-1 COVID-19 based on the Japanese disease severity criteria prior to the fifth wave. For validation, 324 similar patients were enrolled from 3 hospitals in Yamagata. Logistic regression analyses using cluster-robust variance estimation were used to determine predictors of disease deterioration, followed by creation of risk prediction scores. Disease deterioration was defined as the initiation of medication for COVID-19, oxygen inhalation, or mechanical ventilation starting one day or later after admission. RESULTS: The patients whose condition deteriorated (8.6%) tended to be older, male, have histories of smoking, and have high body temperatures, low oxygen saturation values, and comorbidities, such as diabetes/obesity and hypertension. Stepwise variable selection using logistic regression to predict COVID-19 deterioration retained comorbidities of diabetes/obesity (DO), age (A), body temperature (T), and oxygen saturation (S). Two predictive scores were created based on the optimism-corrected regression coefficients: the DOATS score, including all of the above risk factors, and the DOAT score, which was the DOATS score without oxygen saturation. In the original cohort, the areas under the receiver operating characteristic curve (AUROCs) of the DOATS and DOAT scores were 0.81 (95% confidence interval [CI] 0.77-0.85) and 0.80 (95% CI 0.76-0.84), respectively. In the validation cohort, the AUROCs for each score were both 0.76 (95% CI 0.69-0.83), and the calibration slopes were both 0.80. A decision curve analysis confirmed the clinical practicability of both scores in the validation cohort. CONCLUSIONS: We established two prediction scores that can quickly evaluate the risk of COVID-19 deterioration in mild/moderate patients < 65 years old.

A simple pre-disease state prediction method based on variations of gene vector features.

BACKGROUND: The progression of disease can be divided into three states: normal, pre-disease, and disease. Since a pre-disease state is the tipping point of disease deterioration, accurately predicting pre-disease state may help to prevent the progression of disease and develop feasible treatment in time. METHODS: In the perspective of gene regulatory network, the expression of a gene is regulated by its upstream genes, and then it also regulates that of its downstream genes. In this study, we define the expression value of these genes as a gene vector to depict its state in a specific sample. Then, we propose a novel pre-disease prediction method by such vector features. RESULTS: The results of an influenza virus infection dataset show that our method can successfully predict the pre-disease state. Furthermore, the pre-disease state related genes predicted by our methods are highly associated with each other and enriched in influenza virus infection related pathways. In addition, our method is more time efficient in calculation than previous works. The code of our method is accessed at https://github.com/ZhenshenBao/sPGVF.git.

A comparative analysis of the mastery of nursing knowledge for patients with deterioration between Chinese and Australian nursing students / 中华医学教育探索杂志

Objective To investigate the mastery of nursing knowledge for diabetic patients with disease deterioration between Chinese and Australian nursing students and possible influencing factors,and to provide a reference for improving nursing teaching method in China.Methods From May to June,2016,a self-designed online knowledge questionnaire was used to investigate the mastery of clinical emergency knowledge among the third-grade nursing students in Chongqing Medical University in China and Hinders University in South Australia.A total of 303 questionnaires were collected,among which 243 valid questionnaires (164 from Chinese students and 79 from Australian students) were included in statistical analysis,with an effective collection rate of 80.20％.SPSS 19.0 software was used for statistical analysis,and the paired t-test or the chi-square test was used for data comparison.Results Australian nursing students had a significantly higher score of clinical emergency knowledge than their Chinese counterparts (t=4.115,P=0.000).Compared with the low-score group (score ＜12),the high-score group (score ≥ 12) had a significantly higher proportion of students with a family/medical history of diabetes,clinical experience in diabetes care,or self-learning as the main method (P＜0.05).As for learning method,Australian nursing students tended to use online self-learning (60 students,75.95％) and do assignments (56 students,70.89％) and participate in class discussion (51 students,64.56％),while Chinese students tended to receive theoretical teaching (138 students,84.15％),consult clinical teachers (138 students,84.15％),and receive simulation/experimental teaching (123 students,75.00％).Conclusion Chinese nursing students have lower degrees of willingness for self-learning and mastery of knowledge for disease deterioration than Australian nursing students.Focus on specialized practice,development of online teaching,and cultivation of the awareness and ability for self-learning may help to improve the mastery of clinical emergency knowledge among nursing students.