ObjectiveTo systematically review the efficacy and safety of Molnupiravir in the treatment of COVID-19. MethodsThe CNKI, VIP, WanFang Data, PubMed, Web of Science, Cochrane Library, and Epistemonikos COVID-19 L·OVE databases were electronically searched to collect randomized controlled trials (RCTs) related to Molnupiravir therapy for COVID-19 from inception to July, 2023. Two reviewers independently screened literature, extracted data and assessed the risk of bias of the included studies. Meta-analysis was then performed by using RevMan 5.4 software. ResultsA total of 9 RCTs involving 32 086 patients were included. The meta-analysis results revealed that no significant differences were observed in the 28-29 day hospitalization rate, the 28-29 day mortality rate, 14-15 day PCR test conversion rate, or adverse event incidence between the two groups. However, there was a significant increase in adverse events related to four types of systemic organ diseases in the Monolaurin group. Conclusion Current evidence shows that the safety profile of Monolaurin and its potential benefits for COVID-19 patients with a high risk of progressing to severe illness is unclear. Due to the limited quality and quantity of the included studies, more high quality studies are needed to verify the above conclusion.
ObjectivesTo analyze the trend of incidence and mortality of bladder cancer from 1990 to 2017 and the effects of age, time period and birth cohort on bladder cancer incidence and mortality.MethodsData on age-standardized incidence rate (ASIR) and age-standardized death rate (ASDR) of bladder cancer from 1990 to 2017 were extracted from the Global Burden of Disease 2017 (GBD 2017) database. Joinpoint regression model was used to analyze the average annual percentage change of ASIR and ASDR of bladder cancer. The age-period-cohort model was established to analyze the age, period and birth cohort effects on ASIR and ASDR of bladder cancer.ResultsFrom 1990 to 2017, both ASIR and ASDR of bladder cancer decreased slightly. ASIR decreased from 6.42 per 100 000 in 1990 to 6.04 per 100 000 in 2017, with an average annual percentage change of −0.9% (−1.0% to −0.8%), and ASDR decreased from 3.15 per 100 000 in 1990 to 2017 2.57/100 000, with an average annual percentage change of −0.4% (−0.4% to −0.3%). The age-period-cohort model results showed that as age increased, the risk of bladder cancer incidence and mortality increased; as the birth cohort progressed, the risk of bladder cancer morbidity and mortality decreased. The time period had little effect on the incidence and mortality of bladder cancer.ConclusionsThe incidence and mortality of bladder cancer are declining globally. On the other hand, the increase of the aging global population could reverse the incidence and mortality trend, active measures should be taken to address the adverse effects of aging.
ObjectiveTo investigate the clinical value of artificial intelligence (AI)-assisted chest computed tomography (CT) in the diagnosis of peripheral lung shadow. MethodsThe CT image data of 810 patients with peripheral pulmonary shadow treated by thoracic surgery in Tianjin Chest Hospital Affiliated to Tianjin University from January 2018 to July 2019 were retrospectively analyzed using AI-assisted chest CT imaging diagnosis system. There were 339 males and 471 females with a median age of 63 years. The malignant probability of preoperative AI-assisted diagnosis of peripheral pulmonary shadow was compared with the results of postoperative pathology. ResultsThe pathological diagnosis of 810 patients with peripheral pulmonary shadow was lung cancer in 627 (77.4%) patients, precancerous lesion in 30 (3.7%) patients and benign lesion in 153 (18.9%) patients. The median probability of malignant AI diagnosis before operation was 86.0% (lung cancer), 90.0% (precancerous lesion) and 37.0% (benign lesion), respectively. According to the analysis of receiver operating characteristic (ROC) curve of AI malignant probability distribution in this group of patients, the area under the ROC curve was 0.882. The critical value of malignant probability for diagnosis of lung cancer was 75.0% with a sensitivity of 0.856 and specificity of 0.814. A total of 571 patients were diagnosed with AI malignancy probability≥75.0%, among whom 537 patients were pathologically diagnosed as lung cancer with a positive predictive value of 94.0% (537/571). ConclusionThe AI-assisted chest CT diagnosis system has a high accuracy in the diagnosis of peripheral lung cancer with malignant probability≥75.0% as the diagnostic threshold.
ObjectiveTo study the effect of quality control circle activities on reducing the risk of observed patients. MethodBy carrying out the quality control circle, it was done that confirming the subject, grasping the risk of observed patients, setting a goal, analyzing the risk factors of existing problems, finding out the real reasons, drawing up and actualizing the countermeasures. ResultsAfter carrying out the quality control circle, the main risk factor, emergency rescue, of observed patients was ameliorated significantly (P < 0.05). The risk was declined from 0.41% to 0.14% (P < 0.05). The self-evaluation of circle members was improved (P < 0.001). ConclusionBy the quality control circle, it is actualized effectively that reducing the risk of observed patients and improving the overall qualities of nurses. This thing is helpful to improve the quality of nursing.
Trial sequential analysis (TSA) can identify inclusive results of apparently conclusive of meta-analyses by providing require information size and monitoring boundary. Certain methods of calculating information size are existed. Our objective was to give a brief introduction of four methods to help readers to better perform TSA in making meta-analyses.
Objective To develop an evaluation tool for the screening of high risk population for oral complications in critically ill patients, which can be performed accurately and scientifically. Methods Basing on the related foreign oral assessment scale, combined with the method of brainstorming, expert consultation, method of clinical status and so on, the item pool of the assessment scale was determined. Five nursing experts and two oral experts assessed the content validity and 50 ICU nurses were tested. Then, the screening accuracy of the assessment scale was proved by application in 100 critically ill patients selected randomly. Results The Cronbach’s a coefficient of final version of the High Risk Assessment Scale for Oral Complications in Critically Ill Patients (including seven parts contents of oral health assessment and oral pH value test) was 0.815, the content validity index (Sr-CVI/Ave) was 0.932. The results of 50 nurses to the 91.2% assessment items of the assessment scale were very important and important. For screening related indicators of oral complications in high-risk patients, the sensitivity of the assessment scale was 97.53%, the specificity was 94.11%, the positive predictive value was 98.75%, the negative predictive value was 88.89%, and the crude agreement was 95%. Conclusion There are good reliability, validity and a high accuracy of screening test in the High Risk Assessment Scale for Oral Complications in Critically Ill Patients. It can be used for screening patients at high risk for oral complications in critically ill patients, and help clinical nurses to complete the oral health status of the critically ill patients quickly.
Objectives To analyze the risk factors of secondary infections in breast cancer or lung cancer patients with chemotherapy-induced degree Ⅳ neutropenia, so as to provide reference for clinical treatment. Methods The case-control study design was used. Thirty-seven in-patients of breast cancer or lung cancer with secondary infections and 87 in-patients without secondary infection in the First Affiliated Hospital of Xi’an Jiaotong University from January to December 2014 were enrolled as study population. We collected the retrospective information and analyzed the risk factors of secondary infection with chemotherapy-induced degree Ⅳ neutropenia using factors under univariate analysis and logistic regression analysis. Results Single factor analysis showed that the patients whose MASCC<21 the had higher infection risks (P<0.05). For breast cancer patients with degree Ⅳ neutropenia, secondary infection risk of first two chemotherapy cycles was 2.87 times of subsequent cycles of chemotherapy. For lung cancer patients with degree Ⅳ neutropenia, invasive procedures and preventive use of antibiotics increased risk of infection (P<0.05). Logistic regression analysis showed MASCC score and chemotherapy cycles were significantly associated with secondary infection in breast cancer degree Ⅳ neutropenia patients (P<0.05). Invasive procedures were significantly correlated to secondary infection of patients with lung cancer degree Ⅳ neutropenia (P<0.05). Conclusions MASCC score and chemotherapy cycles are the risk factors of infection in breast cancer patients with degree Ⅳ neutropenia, and invasive procedures are the independent risk factors of infection in lung cancer patients with degree Ⅳ neutropenia.
Most statistical data in observational studies is expressed as the effect value and its 95% confidence interval (95% CI), which do not correspond to the data format used for traditional meta-analyses, so special data conversion is to be needed when Review Manager software is applied to do a meta-analysis for this type of data, which will make the operation complicated and cumbersome. In addition, Stata software is such a powerful statistical software that can be used directly to conduct a meta-analysis with the effect value and its 95% CI. Therefore, it is an indispensable statistical tool for meta-analysis in observational studies. And this study will give a brief introduction how to use Stata software to conduct a meta-analysis with effect value and its 95% CI based on the published meta-analysis data.
With the increasing popularity of smart phones, the electronic test of clinical trials has become a common means of investigation research. The APP of REDCap system can quickly construct a multi-center questionnaire system and obtain a large quantity of reliable and complete questionnaire data, shortening the cost and cycle of research. This paper primarily introduces how to conduct research on electronic questionnaire based on mobile APPs of REDCap system.