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BackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has become a global pandemic acute infectious disease, especially with the features of possible asymptomatic carriers and high contagiousness. It causes acute respiratory distress syndrome and results in a high mortality rate if pneumonia is involved. Currently, it is difficult to quickly identify asymptomatic cases or COVID-19 patients with pneumonia due to limited access to reverse transcription-polymerase chain reaction (RT-PCR) nucleic acid tests and CT scans, which facilitates the spread of the disease at the community level, and contributes to the overwhelming of medical resources in intensive care units. GoalThis study aimed to develop a scientific and rigorous clinical diagnostic tool for the rapid prediction of COVID-19 cases based on a COVID-19 clinical case database in China, and to assist global frontline doctors to efficiently and precisely diagnose asymptomatic COVID-19 patients and cases who had a false-negative RT-PCR test result. MethodsWith online consent, and the approval of the ethics committee of Zhongshan Hospital Fudan Unversity (approval number B2020-032R) to ensure that patient privacy is protected, clinical information has been uploaded in real-time through the New Coronavirus Intelligent Auto-diagnostic Assistant Application of cloud plus terminal (nCapp) by doctors from different cities (Wuhan, Shanghai, Harbin, Dalian, Wuxi, Qingdao, Rizhao, and Bengbu) during the COVID-19 outbreak in China. By quality control and data anonymization on the platform, a total of 3,249 cases from COVID-19 high-risk groups were collected. These patients had SARS-CoV-2 RT-PCR test results and chest CT scans, both of which were used as the gold standard for the diagnosis of COVID-19 and COVID-19 pneumonia. In particular, the dataset included 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, and 122 asymptomatic cases who had positive RT-PCR test results, amongst whom 31 cases were diagnosed. We also integrated the function of a survey in nCapp to collect user feedback from frontline doctors. FindingsWe applied the statistical method of a multi-factor regression model to the training dataset (1,624 cases) and developed a prediction model for COVID-19 with 9 clinical indicators that are fast and accessible: Residing or visiting history in epidemic regions, Exposure history to COVID-19 patient, Dry cough, Fatigue, Breathlessness, No body temperature decrease after antibiotic treatment, Fingertip blood oxygen saturation [≤]93%, Lymphopenia, and C-reactive protein (CRP) increased. The area under the receiver operating characteristic (ROC) curve (AUC) for the model was 0.88 (95% CI: 0.86, 0.89) in the training dataset and 0.84 (95% CI: 0.82, 0.86) in the validation dataset (1,625 cases). To ensure the sensitivity of the model, we used a cutoff value of 0.09. The sensitivity and specificity of the model were 98.0% (95% CI: 96.9%, 99.1%) and 17.3% (95% CI: 15.0%, 19.6%), respectively, in the training dataset, and 96.5% (95% CI: 95.1%, 98.0%) and 18.8% (95% CI: 16.4%, 21.2%), respectively, in the validation dataset. In the subset of the 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, the model predicted 132 cases, accounting for 96.4% (95% CI: 91.7%, 98.8%) of the cases. In the subset of the 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, the model predicted 59 cases, accounting for 95.2% (95% CI: 86.5%, 99.0%) of the cases. Considering the specificity of the model, we used a cutoff value of 0.32. The sensitivity and specificity of the model were 83.5% (95% CI: 80.5%, 86.4%) and 83.2% (95% CI: 80.9%, 85.5%), respectively, in the training dataset, and 79.6% (95% CI: 76.4%, 82.8%) and 81.3% (95% CI: 78.9%, 83.7%), respectively, in the validation dataset, which is very close to the published AI model. The results of the online survey Questionnaire Star showed that 90.9% of nCapp users in WeChat mini programs were satisfied or very satisfied with the tool. The WeChat mini program received a significantly higher satisfaction rate than other platforms, especially for availability and sharing convenience of the App and fast speed of log-in and data entry. DiscussionWith the assistance of nCapp, a mobile-based diagnostic tool developed from a large database that we collected from COVID-19 high-risk groups in China, frontline doctors can rapidly identify asymptomatic patients and avoid misdiagnoses of cases with false-negative RT-PCR results. These patients require timely isolation or close medical supervision. By applying the model, medical resources can be allocated more reasonably, and missed diagnoses can be reduced. In addition, further education and interaction among medical professionals can improve the diagnostic efficiency for COVID-19, thus avoiding the transmission of the disease from asymptomatic patients at the community level.
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Objective To explorer the effect of midnight-noon ebb-flow of five elements of music therapy on anxiety and depression in type 2 diabetic patients.Methods A total of 60 type 2 diabetic patients with anxiety and depression in our hospital were divided into the experiment group and the control group according to the order of admission,with 30 patients in each group.The control group received routine nursing care and general music therapy.The experiment group received routine nursing care and midnight-noon ebb-flow of five elements of music therapy.After four weeks,the results of the two groups were compared using HAMD and HAMA scales.Result Four weeks after intervention,there was improvements in the two groups ((P＜0.01) and the anxiety and depression levels in the experiment group were significantly improved than those in the control group (P＜0.01).Conclusion The midnight-noon ebb-flow of five elements of music therapy can alleviate the levels of anxiety and depression in patients with type 2 diabetes.
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To analyze and research the transformation of teaching thoughts,adjustment of professional teachers,renewal of teaching contents and so on,and establish the foundation for the revolution of professional English teaching in medical university under the new situation.
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Objective To study the clinical effect of acupuncture therapy combining with biofeedback therapy on senile chronic insomnia patients. Methods 150 cases of senile chronic insomnia were divided into 3groups randomly: group A received acupuncture therapy only, group B received biofeedback therapy only, and group C received both therapies. The scores of Pittsburgh Sleep Quality Index (PSQI) ,sleep efficacy,sleep latency, total sleep time and the scores of Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD-17) were assessed before the treatment and at the end of the 4th and 8th week during the treatment.Results After 8 weeks treatment, the scores of PSQI, sleep efficacy, sleep latency, total sleep time and the scores of HAMA and HAMD-17 of group C((7.92 ±2.59)score,(82.52 ±8.93)% ,(24.06 ±8.23)minutes,(413.75± 42.41) minutes, (9.63 ± 3.75) score, (10.10 ± 3.27) score) were better than that of group A (( 9.51 ± 2.92)score, (79.06 ± 10.70) %, (33.16 ± 11.31) minutes, (373.47 ± 40.65) minutes, (15.08 ± 4.20) score, (14.33±± 3.56) score) and group B (( 11.46 ± 3.75) score, (68.85 ± 12.34) %, (33.65 ± 11. 38) minutes, (281.88 ±38.02) minutes, (11.63 ± 4.15) score, (12.08 ± 4.08) score) significantly (P ＜ 0.01). Conclusion The therapy of acupuncture combining with biofeedback is benefit to improve the sleep quality of senile chronic insomnia patients,meanwhile the anxiety and depression associated with insomnia can be improved.
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Objective To investigate the effect of aquaporin 5(AQP5)gene to the differentiation and development of bone marrow-deriued dendritic cells(BMDC).Methotis The DCs obtained from the bone marrow of the AQP5-/- and the wild type(WT)mice were cultured and induced to maturation by LPS.The phenotype of the two types DCs were assayed by FACS,and the phagocytosis ability Was assayed by co-incubating with FITC-conjucted ovalbumin.Results Contrast to the DCs from the WT mice,the DCs from the A9P5-/-mice showed reducing positive rate of expression of the co-stimulating molecular such as CD40,CD80.CD86.And the phagoeytosis ability of DCs from the AOP5-/-mice was lower than that of the WT mice.The relationship of the phagncytosis rate to the time from the AOP5-/- mice was different from that of the WT mice.The stimulating ability of the AOP5-/-DCs was lower than that of the WT mice.Conclusion Water transmembrane moving mediated by AQP5 iS very important to the normal function of DCs.The certain mechanism of the signal moleeular is to be determined. Aquaporin 5;Dendritic cell;Gene knockout;Co-stimulating molecular
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Objective:To investigate the blood lipid status and its variation regularity of a population of teaching staff in order to provide evidence for preventing hyperlipidemia.Method:Lipid indexes such as TC,Triglyceride(TG),LDL-C and HDL-C are inspected of a group of teaching staff over 40 years old in some certain university,and data statistics and analysis are conducted.Conclusion:Main behaviors of male and female teaching staff's hyperlipidemia are high TG and high LDL-C.Special focus should be put on blood lipid's variation level of middle aged males around 40 years old,periodical clinical monitoring should be done for female teaching staff over 50 years old.Medical information instruction on the prevention and control of high blood lipid should be strengthened in order to realize the unity of self control and social control.
