ObjectiveTo analyze the sensitivity of peak flow meter screening in different subgroups of chronic obstructive pulmonary disease (COPD). MethodsA total of 156 outpatients with COPD from Peking Union Medical Hospital from May 2013 to December 2014 were recruited in the study. Each patient's symptoms,history of exposure to risk factors,and the times of exacerbation in last year was recorded. All patients completed CAT,mMRC,the St George's Respiratory Questionnaire (SGRQ),6 minutes walking test,spirometry,and peak expiratory flow (PEF) by peak flow meter. ResultsUsing the cut-off of PEF%pred=80%,the PEF detected 120 COPD patients in 156 subjects. The predictive factors of abnormal PEF%pred in COPD was FEV1%pred and the total score of SGRQ (P<0.05). PEF screening could identify 76.9% of COPD patients,30.0%-60.0% of patients of less symptoms (mMRC<2 or CAT<10 or SGRQ<25),83.3%-90.9% of COPD patients with more symptoms (mMRC ≥ 2 or CAT ≥ 10 or SGRQ ≥ 25),27.7% of COPD patients with mild airflow limitation,68.5% of COPD patients with moderate airflow limitation,83.3% of COPD patients with moderate to very severe airflow limitation. When grouped by GOLD combined assessment method,PEF screening could identify 35.2% of patients of group A,75.0% of patients of group B,and 95.9% of patients of group C and D. The cut-off value of PEF% pred=80% showed low sensitivity to early stage of COPD,but when using the cut-off value of PEF% pred=95%,that sensitivity increased signifcantly. ConclusionsPeak flow meter may be used as a tool to screen COPD. It can identify part of COPD patients especially for those patients with more symptoms,requiring regular treatment,with deteriorated pulmonary function and high risk of exacerbation.
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.
Prostate cancer is a common disease in the USA and Europe, with a gradually increasing incidence in China, and presents a significant health burden for older men. The lack of modifiable risk factors has made early detection as a strategy to reduce mortality. Current methods of screening involve the measurement of serum prostate-specific antigen (PSA) and digital rectal examination followed by biopsy. With PSA screening evidence of level I absent, the evidence on the use of PSA as a screening test is still highly controversial. Furthermore, there is controversy over whether screen-detected lesions will become clinically significant. There are three major treatment options for localized disease: radical prostatectomy, radical radiotherapy and monitoring with treatment if required. There is no evidence of randomized controlled trial (RCT) to suggest a survival advantage of any of these treatments. Opinions about the related benefits and risks of screening vary widely. In the absence of RCT of benefit for screening, many now suggest “informed consensus” screening, which encourages a discussion between the patient and his physician with both sides informed of all of the issues.
Lung cancer is a malignant tumor with the highest incidence and mortality in China. Early diagnosis and early treatment is the key to improve the survival and prognosis of patients with lung cancer. In recent years, many studies have focused on biomarkers of lung cancer. Emerging biomarkers tests have shown some potential in lung cancer screening. Combining biomarkers, imaging omics and artificial intelligence to establish a comprehensive model for lung cancer screening and prediction may be the development direction for improving lung cancer screening in the future. This paper summarizes the application of biomarkers in lung cancer screening, introduces the emerging biomarkers and new technologies, and discusses the application prospects of biomarkers in lung cancer screening, in order to providea theoretical basis for improving screening, early diagnosis and early treatment of lung cancer.
Objective To evaluate the cost-effectiveness of three LTBI screening strategies: the tuberculin skin test (TST), the T-SPOT.TB and the combination of TST and T-SPOT (TST+T.SPOT), to provide economic evidence for T.SPOT application in China. Methods A decision analysis model evaluated three strategies among a cohort of 1000 tuberculosis (TB) close contacts, using incremental cost-effectiveness of prevention a active TB patient (1 year post contact). Meta analyses were conducted to calculate the key parameters of T.SPOT and TST. The official data or literature was searched and the unaccessible data was to specify other parameters, such as cost, LTBI prevalence, etc. The one-way sensitivity analysis was performed, varying key parameters over a wide range of reasonable values to evaluate the impact of data uncertainties and to determine the robustness of our overall conclusion. Results a) As for the total cost, the TST+T.SPOT strategy (?212 213.81 per 1 000 contacts) cost the least, while the single T.SPOT strategy cost the most; b) Subsequently, the TST+T.SPOT strategy required less contacts to be treated to prevent an active case of TB (8.31) than the single TST strategy (25.67); c) the TST+T.SPOT strategy shared the most cost-effectiveness (?3 063.50 per active TB case prevented) than the single TST or T.SPOT strategy; and d) The results of one-way sensitivity analyses showed that cost-effectiveness values were sensitive to changes in LTBI prevalence (gt;60%), Sen and Spn of TST test (gt;70%), with the single TST being superior to the single T.SPOT. Conclusion The Single T.SPOT strategy enjoys the most cases prevented from active TB, while the TST+S.SPOT strategy is the most cost-effective. The conclusion is sensitive to a few parameters, such as LTBI prevalence, but the TST+T.SPOT strategy is always the best.
ObjectivesTo evaluate the accuracy of liver cancer screening techniques to inform screening intervention and early diagnosis.MethodsWe searched PubMed, The Cochrane Library, EMbase, Web of Science, CNKI, WanFang Data, CBM, VIP databases to collect relevant diagnostic accuracy studies of screening technologies for liver cancer from January 1980 to December 2017. Two reviewers independently screened the literature, extracted the data and assessed the risk of bias of included studies. Then meta-analysis was performed by using Meta-Disc 1.4 software.ResultsA total of 54 publications with 47 728 individuals were included. In terms of pooled sensitivity from the meta-analysis, it was estimated as 0.71 (95%CI 0.70 to 0.72), 0.57 (95%CI 0.56 to 0.59) and 0.43 (95%CI 0.41 to 0.45); the pooled specificity was estimated as 0.92 (95%CI 0.92 to 0.93), 0.95 (95%CI 0.94 to 0.96) and 0.95 (95%CI 0.94 to 0.96); the pooled positive likelihood ratio was 5.65 (95%CI 4.37 to 7.30), 13.24(95%CI 4.25 to 41.22) and 11.39 (95%CI 4.01 to 32.35); the pooled negative likelihood ratio was 0.35 (95%CI 0.31 to 0.39), 0.38 (95%CI 0.29 to 0.52) and 0.49 (95%CI 0.39 to 0.62); the diagnosis odds ratio was 17.23 (95%CI 12.26 to 24.20), 33.79 (95%CI 12.65 to 90.24) and 24.41(95%CI 9.23 to 64.53) for AFP alone with cut-off of 20, 200 and 400 ng/mL, respectively. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnosis odds ratio were 0.65 (95%CI 0.62 to 0.69), 0.97 (95%CI 0.97 to 0.97), 16.48 (95%CI 9.55 to 28.42), 0.27 (95%CI 0.18 to 0.42) and 64.54 (95%CI 30.16 to 138.11) for ultrasound examination alone. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnosis odds ratio were 0.96 (95%CI 0.94 to 0.98), 0.96 (95%CI 0.96 to 0.96), 10.76 (95%CI 2.62 to 44.27), 0.07 (95%CI 0.02 to 0.22) and 160.59 (95%CI 31.61 to 816.03) for the combined strategy.ConclusionFor liver cancer screening technologies, the overall accuracy of serum AFP test alone is the optimum at cut-off of 20 ng/mL, and the sensitivity increased substantially when combined with ultrasound examination.
Diabetic retinopathy (DR) is the most common cause of preventable blindness in the working-age population. In addition to optimizing the hyperglycemia, hypertension, hyperlipidemia and other risk factors, regular fundus examination is essential for early diagnosis asymptomatic DR and timely treat the sight-threatening DR, so as to reduce blindness and severe visual impairment caused by DR. Clinical practice guidelines for the screening and management of DR have been implemented throughout the world, but there are reasonable differences between existing guidelines in the recommended timing of first retinal examination, screening intervals, methods for examination and criteria for referral to an ophthalmologist. It is of great clinical significance to have a detailed understanding of the current guidelines for DR screening and their clinical basis.
ObjectiveTo study the efficiency and difference of the artificial intelligence (AI) system based on fundus-reading in community and hospital scenarios in screening/diagnosing diabetic retinopathy (DR) among aged population, and further evaluate its application value. MethodsA combination of retrospective and prospective study. The clinical data of 1 608 elderly patients with diabetes were continuously treated in Henan Eye Hospital & Henan Eye Institute from July 2018 to March 2021, were collected. Among them, there were 659 males and 949 females; median age was 64 years old. From December 2018 to April 2019, 496 elderly diabetes patients were prospectively recruited in the community. Among them, there were 202 males and 294 female; median age was 62 years old. An ophthalmologist or a trained endocrinologist performed a non-mydriatic fundus color photographic examination in both eyes, and a 45° frontal radiograph was taken with the central fovea as the central posterior pole. The AI system was developed based on the deep learning YOLO source code, AI system based on the deep learning algorithm was applied in final diagnosis reporting by the "AI+manual-check" method. The diagnosis of DR were classified into 0-4 stage. The 2-4 stage patients were classified into referral DR group. ResultsA total of 1 989 cases (94.5%, 1 989/2 104) were read by AI, of which 437 (88.1%, 437/496) and 1 552 (96.5%, 1 552/1 608) from the community and hospital, respectively. The reading rate of AI films from community sources was lower than that from hospital sources, and the difference was statistically significant (χ2=51.612, P<0.001). The main reasons for poor image quality in the community were small pupil (47.1%, 24/51), cataract (19.6%, 10/51), and cataract combined with small pupil (21.6%, 11/51). The total negative rate of DR was 62.4% (1 241/1 989); among them, the community and hospital sources were 84.2% and 56.3%, respectively, and the AI diagnosis negative rate of community source was higher than that of hospital, and the difference was statistically significant (χ2=113.108, P<0.001). AI diagnosis required referral to DR 20.2% (401/1 989). Among them, community and hospital sources were 6.4% and 24.0%, respectively. The rate of referral for DR for AI diagnosis from community sources was lower than that of hospitals, and the difference was statistically significant (χ2=65.655, P<0.001). There was a statistically significant difference in the composition ratio of patients with different stages of DR diagnosed by AI from different sources (χ2=13.435, P=0.001). Among them, community-derived patients were mainly DR without referral (52.2%, 36/69); hospital-derived patients were mainly DR requiring referral (54.9%, 373/679), and the detection rate of treated DR was higher (14.3%). The first rank of the order of the fundus lesions number automatically identified by AI was drusen (68.4%) and intraretinal hemorrhage (48.5%) in the communities and hospitals respectively. Conclusions It is more suitable for early and negative DR screening for its high non-referral DR detection rate in the community. Whilst referral DR were mainly found in hospital scenario.
The incidence of obesity and type 2 diabetes mellitus (T2DM) in adolescents has been rapidly increasing over the past two decades due to dramatic changes in dietary structure and physical activity. The incidence of diabetic retinopathy (DR), a serious vision-threatening complication of diabetes, is also increasing yearly in the adolescent population with T2DM. Due to the insidious onset of retinal diseases in the early stages, regular screening is important for the timely diagnosis of DR. However, there are still problems such as low attention of the population and insufficient screening rate. In the future, we should strengthen the health education of the adolescent population and optimize the control of risk factors such as blood glucose and blood pressure. At the same time, appropriate screening strategies should be actively developed, and the use of telemedicine and emerging technologies should be promoted for early detection of treatable lesions to improve patient prognosis.
Objective To systematically review the current situation of health economics evaluation of gastric cancer screening. Methods The PubMed, EMbase, The Cochrane Library, Web of Science, CNKI, WanFang Data and VIP databases were electronically searched to collect the health economics evaluation studies on gastric cancer screening from January 1st, 1975 to September 30th, 2021. Two reviewers independently screened the literature, extracted data and assessed the risk of bias of the included studies. Then, qualitative analysis was performed. Results A total of 44 studies were included. Most of the targeted populations of the study were high-risk groups in areas with a high incidence of gastric cancer. Screening methods such as endoscopy and Helicobacter pylori infection detection were mainly evaluated in those studies. According to the results, about 47% of the studies evaluated a single screening method. A total of 35 studies showed that they established models, however, only a few calibrated the models. Conclusion Most studies of gastric cancer screening reviews neither calibrate the results nor consider the effect of smoking on the progression of gastric cancer. Those evaluated screening programs are limited.