The "4+4" Medical Doctor (MD) Pilot Program at PUMC: Implementation, Performance, and Prospects.

Peking Union Medical College (PUMC) launched the "4+4" Medical Doctor (MD) pilot program in 2018, admitting students with non-medical backgrounds from top universities, aligning with national medical talent training policies to foster diverse and eager learners in medicine. On the occasion of the graduation of the first class of the "4+4" MD pilot class at PUMC in 2023, we reviewed the teaching reform in the pilot program and carried out a systematic survey and interviews with students, faculties, and management staff of the pilot class. This article reports on the measures taken by the pilot class at PUMC in enrollment and curriculum setting, and demonstrates the achievements of the pilot class in terms of student academic background structure, knowledge acquisition and skill learning, scientific research ability, and course evaluation. The results indicated that the pilot class had met the national demand for the "Medicine + X" talent training model. More specifically, with a diverse academic backgrounds, the pilot class graduates had academic levels comparable to the eight-year medical education graduates, and their scientific research abilities were satisfactory. The pilot program at PUMC will optimize the curriculum setting, strengthen the construction of faculty, learning resources, and teaching facilities, and reform the academic evaluation methods, thus deepening the reform of medical education and improving the "4+4" MD program as a novel medical education model.

Cerebral infarction in centrum semiovale presenting with hemichorea: a case report and literature review.

Hemichorea caused by cerebral infarction in the centrum semiovale is a rare condition that can often be misdiagnosed. In this case report, we present a rare case of a 66-year-old man who experienced involuntary movement in his left limbs due to acute cerebral infarction in the centrum semiovale. The patient did not have any obvious inducements for the hemichorea. In this case, the treatment approach followed the guidelines for treating acute cerebral infarction, combined with the use of dopamine receptor blockers. The involuntary movements gradually improved and completely remitted after 5 days of treatment, with no relapse within the following 6 months. To summarize, this case report highlights the rare occurrence of hemichorea caused by cerebral infarction in the centrum semiovale. Prompt recognition and appropriate treatment are essential to prevent misdiagnosis and ensure optimal management of the condition.

Establishment of a model for predicting the outcome of induced labor in full-term pregnancy based on machine learning algorithm.

To evaluate and establish a prediction model of the outcome of induced labor based on machine learning algorithm. This was a cross-sectional design. The subjects were divided into primipara and multipara, and the risk factors for the outcomes of induced labor were assessed by multifactor logistic regression analysis. The outcome model of labor induced with oxytocin (OT) was constructed based on the four machine learning algorithms, including AdaBoost, logistic regression, naive Bayes classifier, and support vector machine. Factors, such as accuracy, recall, precision, F1 value, and receiver operating characteristic curve, were used to evaluate the prediction performance of the model, and the clinical application of the model was verified. A total of 907 participants were included in this study. Logistic regression algorithm obtained better results in both primipara and multipara groups compared to the other three models. The accuracy of the model for the prediction of "successful induction of labor" was 94.24% and 96.55%, and that of "failed induction of labor" was 65.00% and 66.67% in the primipara and the multipara groups, respectively. This study established a prediction model of OT-induced labor based on the Logistic regression algorithm, with rapid response, high accuracy, and strong extrapolation, which was critical for obstetric clinical nursing.

Vaccination status, acceptance, and knowledge toward a COVID-19 vaccine among healthcare workers: a cross-sectional survey in China.

Healthcare workers (HCWs) are considered both a high-risk population regarding infections and effective vaccine recommenders whose willingness to be vaccinated is the key to herd immunity. However, the vaccination status, acceptance, and knowledge of the 2019 coronavirus disease (COVID-19) vaccine among HCWs remain unknown. Therefore, we conducted an online survey regarding the above among HCWs in China after the vaccine was made available. Questionnaires returned by 1,779 HCWs were analyzed. Among these participants, 34.9% were vaccinated, 93.9% expressed their willingness to receive the COVID-19 vaccine, and vaccine knowledge level was high (89.2%). A bivariate analysis found that participants with a college degree, low level of knowledge, non-exposure to COVID-19 status, and those who are females or nurses have a lower vaccination rate, while participants who are married, with a monthly income of more than 5,000 yuan, and low knowledge levels are less willing to be vaccinated. A multivariate analysis found that participants with a high (OR = 7.042, 95% CI = 4.0918-12.120) or medium (OR = 3.709, 95% CI = 2.072-6.640) knowledge level about COVID-19 vaccines were more willing to be vaccinated. Participants were less likely to accept a COVID-19 vaccine if they were married (OR = 0.503, 95% CI = 0.310-0.815). In summary, Chinese HCWs have a strong willingness to be vaccinated and a high level of knowledge. Measures, such as targeted education for HCWs with low willingness and low level of knowledge, open vaccine review procedures, increased government trust, reduced vaccine costs, and provide vaccination guarantee policies, may improve the vaccination coverage of the at-risk group.