Currently, the medical imaging methods based on artificial intelligence are developing rapidly, and the related literature reports are increasing year by year. However, there is no special reporting standard, and the reporting of the results is not standardized. In order to improve the report quality of this kind of research and help readers and evaluators evaluate the quality of this kind of research more scientifically, a checklist for artificial intelligence in medical imaging (CLAIM) was put forward abroad. This paper introduces the content of CLAIM and explains its items.
ObjectiveTo systematically review the accuracy of different stroke-associated pneumonia (SAP) assessment tools. MethodsThe PubMed, Cochrane Library, Embase, Web of Science, CNKI, VIP, WanFang Data, and CBM databases were electronically searched to collect studies related to the objectives from inception to January 2024. Two reviewers independently screened literature, extracted data and assessed the risk of bias of the included studies. A network meta-analysis was then performed by using Meta-disc 1.4 and Stata 17.0 software. ResultsA total of 20 studies were included, involving 6 SAP assessment tools. The results of network meta-analysis showed that the sensitivity of AIS-APS was higher than that of A2DS2, and the specificity of A2DS2 was higher than that of PANTHERIS, and the difference was statistically significant. The sensitivity SUCRA values from high to low were: AIS-APS (95.6%) > PANTHERIS (46.7%) > Kwon (44.1%) > A2DS2 (40.5%) > Chumbler (37.3%) > ISAN (35.8%). The specificity SUCRA values from high to low were: A2DS2 (84.0%) > Chumbler (66.0%) > ISAN (59.5%) > AIS-APS (41.4%) > Kwon (37.0%) > PANTHERIS (12.1%) ConclusionAmong the common stroke-associated pneumonia screening tools used to screen patients with ischemic stroke, AIS-APS has the highest sensitivity and A2DS2 has the highest specificity.
As precision medicine continues to gain momentum, the number of predictive model studies is increasing. However, the quality of the methodology and reporting varies greatly, which limits the promotion and application of these models in clinical practice. Systematic reviews of prediction models draw conclusions by summarizing and evaluating the performance of such models in different settings and populations, thus promoting their application in practice. Although the number of systematic reviews of predictive model studies has increased in recent years, the methods used are still not standardized and the quality varies greatly. In this paper, we combine the latest advances in methodologies both domestically and abroad, and summarize the production methods and processes of a systematic review of prediction models. The aim of this study is to provide references for domestic scholars to produce systematic reviews of prediction models.
The use of clinical predictive modeling to guide clinical decision-making and thus provide accurate diagnosis and treatment services for patients has become a clinical consensus and trend. However, the models available for clinical use are more limited due to unstandardised research methods and poor quality of evidence. This paper introduces the development process of clinical prediction models from six aspects, data collection, model development, performance evaluation, model validation, model presentation and model updating, as well as the clinical prediction model research report statement and risk of bias assessment tools in order to provide methodological references for domestic researchers.
Acute pharyngitis belongs to the category of “acute throat impediment” in traditional Chinese medicine (TCM), which has a high incidence and is easy to recur. In clinical practice of TCM, Chinese patent medicines with the effects of clearing heat and detoxifying, reducing swelling and relieving pain are widely used in the treatment of acute pharyngitis. These medicines have the advantages of definite efficacy, low side effects, and low risk of developing drug resistance. However, at present, there are no standardized clinical diagnostic and therapeutic evaluation norms for acute pharyngitis in TCM, which has hindered the application of TCM in the prevention and treatment of acute pharyngitis and the development of new TCM preparations. Therefore, the China Association of Chinese Medicine initiated this expert consensus, which was led the formulation by Xiyuan Hospital, China Academy of Chinese Medical Sciences. This expert consensus integrates the current best evidence and extensive clinical expert experience from the front line, covering seven aspects: applicable scope, diagnosis in both Chinese and Western medicine, syndrome classification and evaluation scales, basis for efficacy evaluation, and time for efficacy evaluation. It has formed 8 types of TCM syndromes for acute pharyngitis, as well as the diagnostic criteria, syndrome classification and evaluation scales, evaluation basis for efficacy, and scoring standards for syndromes and diseases. This expert consensus can be used to standardize the diagnosis of the TCM syndromes of acute pharyngitis, as well as the core indicators and evaluation methods for syndrome and disease efficacy, with the aim of providing references for clinical practice and scientific research on acute pharyngitis.