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Machine learning radiomics of magnetic resonance imaging predicts recurrence-free survival after surgery and correlation of LncRNAs in patients with breast cancer: a multicenter cohort study. Breast cancer research : BCR BACKGROUND:Several studies have indicated that magnetic resonance imaging radiomics can predict survival in patients with breast cancer, but the potential biological underpinning remains indistinct. Herein, we aim to develop an interpretable deep-learning-based network for classifying recurrence risk and revealing the potential biological mechanisms. METHODS:In this multicenter study, 1113 nonmetastatic invasive breast cancer patients were included, and were divided into the training cohort (n = 698), the validation cohort (n = 171), and the testing cohort (n = 244). The Radiomic DeepSurv Net (RDeepNet) model was constructed using the Cox proportional hazards deep neural network DeepSurv for predicting individual recurrence risk. RNA-sequencing was performed to explore the association between radiomics and tumor microenvironment. Correlation and variance analyses were conducted to examine changes of radiomics among patients with different therapeutic responses and after neoadjuvant chemotherapy. The association and quantitative relation of radiomics and epigenetic molecular characteristics were further analyzed to reveal the mechanisms of radiomics. RESULTS:The RDeepNet model showed a significant association with recurrence-free survival (RFS) (HR 0.03, 95% CI 0.02-0.06, P < 0.001) and achieved AUCs of 0.98, 0.94, and 0.92 for 1-, 2-, and 3-year RFS, respectively. In the validation and testing cohorts, the RDeepNet model could also clarify patients into high- and low-risk groups, and demonstrated AUCs of 0.91 and 0.94 for 3-year RFS, respectively. Radiomic features displayed differential expression between the two risk groups. Furthermore, the generalizability of RDeepNet model was confirmed across different molecular subtypes and patient populations with different therapy regimens (All P < 0.001). The study also identified variations in radiomic features among patients with diverse therapeutic responses and after neoadjuvant chemotherapy. Importantly, a significant correlation between radiomics and long non-coding RNAs (lncRNAs) was discovered. A key lncRNA was found to be noninvasively quantified by a deep learning-based radiomics prediction model with AUCs of 0.79 in the training cohort and 0.77 in the testing cohort. CONCLUSIONS:This study demonstrates that machine learning radiomics of MRI can effectively predict RFS after surgery in patients with breast cancer, and highlights the feasibility of non-invasive quantification of lncRNAs using radiomics, which indicates the potential of radiomics in guiding treatment decisions. 10.1186/s13058-023-01688-3
Disruption of Circadian Rhythms by Shift Work Exacerbates Reperfusion Injury in Myocardial Infarction. Journal of the American College of Cardiology BACKGROUND:Shift work is associated with increased risk of acute myocardial infarction (AMI) and worsened prognosis. However, the mechanisms linking shift work and worsened prognosis in AMI remain unclear. OBJECTIVES:This study sought to investigate the impact of shift work on reperfusion injury, a major determinant of clinical outcomes in AMI. METHODS:Study patient data were obtained from the database of the EARLY-MYO-CMR (Early Assessment of Myocardial Tissue Characteristics by CMR in STEMI) registry, which was a prospective, multicenter registry of patients with ST-segment elevation myocardial infarction (STEMI) undergoing cardiac magnetic resonance (CMR) imaging after reperfusion therapy. The primary endpoint was CMR-defined post-reperfusion infarct size. A secondary clinical endpoint was the composite of major adverse cardiac events (MACE) during follow-up. Potential mechanisms were explored with the use of preclinical animal AMI models. RESULTS:Of 706 patients enrolled in the EARLY-MYO-CMR registry, 412 patients with STEMI were ultimately included. Shift work was associated with increased CMR-defined infarct size (β = 5.94%; 95% CI: 2.94-8.94; P < 0.0001). During a median follow-up of 5.0 years, shift work was associated with increased risks of MACE (adjusted HR: 1.92; 95% CI: 1.12-3.29; P = 0.017). Consistent with clinical findings, shift work simulation in mice and sheep significantly augmented reperfusion injury in AMI. Mechanism studies identified a novel nuclear receptor subfamily 1 group D member 1/cardiotrophin-like cytokine factor 1 axis in the heart that played a crucial role in mediating the detrimental effects of shift work on myocardial injury. CONCLUSIONS:The current study provided novel findings that shift work increases myocardial infarction reperfusion injury. It identified a novel nuclear receptor subfamily 1 group D member 1/cardiotrophin-like cytokine factor 1 axis in the heart that might play a crucial role in mediating this process. (Early Assessment of Myocardial Tissue Characteristics by CMR in STEMI [EARLY-MYO-CMR] registry; NCT03768453). 10.1016/j.jacc.2022.03.370
The effectiveness and safety of Chinese Patent Medicines based on syndrome differentiation in patients following percutaneous coronary intervention due to acute coronary syndrome (CPM trial): A nationwide Cohort Study. Phytomedicine : international journal of phytotherapy and phytopharmacology BACKGROUND:The incidence of cardiovascular events remains not unusual in patients following percutaneous coronary intervention (PCI) due to acute coronary syndrome (ACS). Chinese patent medicine (CPM) therapy based on syndrome differentiation in addition to conventional medicine (CM) had been expected to further reduce the risk of cardiovascular events. PURPOSE:To assess the effectiveness and safety of CPM based on syndrome differentiation in patients following PCI due to ACS. STUDY DESIGN:Nationwide prospective cohort study. METHODS:CPM study was conducted in 40 centers in mainland China. Patients following PCI due to ACS entered to syndrome differentiation-based CPM (SDCPM) or CM group according to whether they received CPM or not. The CPM comprised Guanxin Danshen dripping pills, Qishen Yiqi dripping pills, or Danlou tablets, and was used correspondingly with the syndrome differentiation of traditional Chinese medicine. The follow-up time was 36 months. The primary endpoint was composed of cardiac death, non-fatal myocardial infarction and urgent revascularization. The secondary endpoint included rehospitalization due to ACS, heart failure, stroke, other thrombotic events. Seattle Angina Questionnaire (SAQ) was used to evaluate quality of life. RESULTS:Between February 2012 and December 2018, ascertainment of the primary endpoint was completed in 2,724 patients of follow-up. 1,380 patients were in SDCPM group. At a median follow-up of 541 (interquartile range 513 - 564) days, the primary endpoint occurred in 126 (8.61%) patients in SDCPM group and 167 (11.62%) patients in CM group (adjusted hazard ratio [HR] = 0.70; [95% confidence interval [CI] 0.55 - 0.89]; p = 0.003). The secondary endpoint occurred in 144 (9.84%) patients in SDCPM group and 197 (13.71%) patients in CM group (adjusted HR = 0.66; [95% CI 0.53 - 0.82]; p < 0.001). The SAQ score in SDCPM group was higher than CM group (366.78 ± 70.19 vs 356.43 ± 73.80, p < 0.001). There were no significant differences of adverse events between two groups. CONCLUSION:In patients following PCI due to ACS, SDCPM in addition to CM treatment reduced the primary and secondary endpoints, as well as improved the quality of life without adverse events. 10.1016/j.phymed.2022.154554
Prevalence, risk factors, and management of dementia and mild cognitive impairment in adults aged 60 years or older in China: a cross-sectional study. Jia Longfei,Du Yifeng,Chu Lan,Zhang Zhanjun,Li Fangyu,Lyu Diyang,Li Yan,Li Yan,Zhu Min,Jiao Haishan,Song Yang,Shi Yuqing,Zhang Heng,Gong Min,Wei Cuibai,Tang Yi,Fang Boyan,Guo Dongmei,Wang Fen,Zhou Aihong,Chu Changbiao,Zuo Xiumei,Yu Yueyi,Yuan Quan,Wang Wei,Li Fang,Shi Shengliang,Yang Heyun,Zhou Chunkui,Liao Zhengluan,Lv Yan,Li Yang,Kan Minchen,Zhao Huiying,Wang Shan,Yang Shanshan,Li Hao,Liu Zhongling,Wang Qi,Qin Wei,Jia Jianping, The Lancet. Public health BACKGROUND:China has a large population of older people, but has not yet undertaken a comprehensive study on the prevalence, risk factors, and management of both dementia and mild cognitive impairment (MCI). METHODS:For this national cross-sectional study, 46 011 adults aged 60 years or older were recruited between March 10, 2015, and Dec 26, 2018, using a multistage, stratified, cluster-sampling method, which considered geographical region, degree of urbanisation, economic development status, and sex and age distribution. 96 sites were randomly selected in 12 provinces and municipalities representative of all socioeconomic and geographical regions in China. Participants were interviewed to obtain data on sociodemographic characteristics, lifestyle, medical history, current medications, and family history, and then completed a neuropsychological testing battery administered by a psychological evaluator. The prevalence of dementia (Alzheimer's disease, vascular dementia, and other dementias) and MCI were calculated and the risk factors for different groups were examined using multivariable-adjusted analyses. FINDINGS:Overall age-adjusted and sex-adjusted prevalence was estimated to be 6·0% (95% CI 5·8-6·3) for dementia, 3·9% (3·8-4·1) for Alzheimer's disease, 1·6% (1·5-1·7) for vascular dementia, and 0·5% (0·5-0·6) for other dementias. We estimated that 15·07 million (95% CI 14·53-15·62) people aged 60 years or older in China have dementia: 9·83 million (9·39-10·29) with Alzheimer's disease, 3·92 million (3·64-4·22) with vascular dementia, and 1·32 million (1·16-1·50) with other dementias. Overall MCI prevalence was estimated to be 15·5% (15·2-15·9), representing 38·77 million (37·95-39·62) people in China. Dementia and MCI shared similar risk factors including old age (dementia: odds ratios ranging from 2·69 [95% CI 2·43-2·98] to 6·60 [5·24-8·32]; MCI: from 1·89 [1·77-2·00] to 4·70 [3·77-5·87]); female sex (dementia: 1·43 [1·31-1·56]; MCI: 1·51 [1·43-1·59]); parental history of dementia (dementia: 7·20 [5·68-9·12]; MCI: 1·91 [1·48-2·46]); rural residence (dementia: 1·16 [1·06-1·27]; MCI: 1·45 [1·38-1·54]); fewer years of education (dementia: from 1·17 [1·06-1·29] to 1·55 [1·38-1·73]; MCI: from 1·48 [1·39-1·58] to 3·48 [3·25-3·73]); being widowed, divorced, or living alone (dementia: from 2·59 [2·30-2·90] to 2·66 [2·29-3·10]; MCI: from 1·58 [1·44-1·73] to 1·74 [1·56-1·95]); smoking (dementia: 1·85 [1·67-2·04]; MCI: 1·27 [1·19-1·36]), hypertension (dementia: 1·86 [1·70-2·03]; MCI: 1·62 [1·54-1·71] for MCI), hyperlipidaemia (dementia: 1·87 [1·71-2·05]; MCI: 1·29 [1·21-1·37]), diabetes (dementia: 2·14 [1·96-2·34]; MCI: 1·44 [1·35-1·53]), heart disease (dementia: 1·98 [1·73-2·26]; MCI: 1·17 [1·06-1·30]), and cerebrovascular disease (dementia: 5·44 [4·95-5·97]; MCI: 1·49 [1·36-1·62]). Nine of these risk factors are modifiable. INTERPRETATION:Dementia and MCI are highly prevalent in China and share similar risk factors. A prevention strategy should be developed to target the identified risk factors in the MCI population to thwart or slow down disease progression. It is also crucial to optimise the management of dementia and MCI as an important part of China's public health system. FUNDING:Key Project of the National Natural Science Foundation of China, National Key Scientific Instrument and Equipment Development Project, Mission Program of Beijing Municipal Administration of Hospitals, Beijing Scholars Program, Beijing Brain Initiative from Beijing Municipal Science & Technology Commission, Project for Outstanding Doctor with Combined Ability of Western and Chinese Medicine, and Beijing Municipal Commission of Health and Family Planning. 10.1016/S2468-2667(20)30185-7
Electrocardiogram machine learning for detection of cardiovascular disease in African Americans: the Jackson Heart Study. European heart journal. Digital health AIMS:Almost half of African American (AA) men and women have cardiovascular disease (CVD). Detection of prevalent CVD in community settings would facilitate secondary prevention of CVD. We sought to develop a tool for automated CVD detection. METHODS AND RESULTS:Participants from the Jackson Heart Study (JHS) with analysable electrocardiograms (ECGs) (=3679; age, 6212 years; 36% men) were included. Vectorcardiographic (VCG) metrics QRS, T, and spatial ventricular gradient vectors magnitude and direction, and traditional ECG metrics were measured on 12-lead ECG. Random forests, convolutional neural network (CNN), lasso, adaptive lasso, plugin lasso, elastic net, ridge, and logistic regression models were developed in 80% and validated in 20% samples. We compared models with demographic, clinical, and VCG input (43 predictors) and those after the addition of ECG metrics (695 predictors). Prevalent CVD was diagnosed in 411 out of 3679 participants (11.2%). Machine learning models detected CVD with the area under the receiver operator curve (ROC AUC) 0.690.74. There was no difference in CVD detection accuracy between models with VCG and VCG + ECG input. Models with VCG input were better calibrated than models with ECG input. Plugin-based lasso model consisting of only two predictors (age and peak QRS-T angle) detected CVD with AUC 0.687 [95% confidence interval (CI) 0.6250.749], which was similar (=0.394) to the CNN (0.660; 95% CI 0.5970.722) and better (<0.0001) than random forests (0.512; 95% CI 0.4930.530). CONCLUSIONS:Simple model (age and QRS-T angle) can be used for prevalent CVD detection in limited-resources community settings, which opens an avenue for secondary prevention of CVD in underserved communities. 10.1093/ehjdh/ztab003
LASSO-Based Machine Learning Algorithm for Prediction of Lymph Node Metastasis in T1 Colorectal Cancer. Kang Jeonghyun,Choi Yoon Jung,Kim Im-Kyung,Lee Hye Sun,Kim Hogeun,Baik Seung Hyuk,Kim Nam Kyu,Lee Kang Young Cancer research and treatment PURPOSE:The role of tumor-infiltrating lymphocytes (TILs) in predicting lymph node metastasis (LNM) in patients with T1 colorectal cancer (CRC) remains unclear. Furthermore, clinical utility of a machine learning-based approach has not been widely studied. MATERIALS AND METHODS:Immunohistochemistry for TILs against CD3, CD8, and forkhead box P3 in both center and invasive margin of the tumor were performed using surgically resected T1 CRC slides. Three hundred and sixteen patients were enrolled and categorized into training (n=221) and validation (n=95) sets via random sampling. Using clinicopathologic variables including TILs, the least absolute shrinkage and selection operator (LASSO) regression model was applied for variable selection and predictive signature building in the training set. The predictive accuracy of our model and the Japanese criteria were compared using area under the receiver operating characteristic (AUROC), net reclassification improvement (NRI)/integrated discrimination improvement (IDI), and decision curve analysis (DCA) in the validation set. RESULTS:LNM was detected in 29 (13.1%) and 12 (12.6%) patients in training and validation sets, respectively. Nine variables were selected and used to generate the LASSO model. Its performance was similar in training and validation sets (AUROC, 0.795 vs. 0.765; p=0.747). In the validation set, the LASSO model showed better outcomes in predicting LNM than Japanese criteria, as measured by AUROC (0.765 vs. 0.518, p=0.003) and NRI (0.447, p=0.039)/IDI (0.121, p=0.034). DCA showed positive net benefits in using our model. CONCLUSION:Our LASSO model incorporating histopathologic parameters and TILs showed superior performance compared to conventional Japanese criteria in predicting LNM in patients with T1 CRC. 10.4143/crt.2020.974
Prospective cohort studies of association between family history of liver cancer and risk of liver cancer. Yang Yang,Wu Qi-Jun,Xie Li,Chow Wong-Ho,Rothman Nat,Li Hong-Lan,Gao Yu-Tang,Zheng Wei,Shu Xiao-Ou,Xiang Yong-Bing International journal of cancer Uncertainty remains on the relationship between a family history of liver cancer and liver cancer risk in prospective cohort studies in a general population. Thus, we examined this association in 133,014 participants in the Shanghai Women's and Men's Health Studies. Family history of liver cancer was categorized through dichotomous and proportional score approaches. Hazard ratios (HRs) and 95% confidence intervals (CIs) were derived using the Cox proportional hazards models with adjustment for potential confounders. A meta-analysis of observational studies through December 2013 on liver cancer risk in relation to family history of liver cancer was also performed. Study-specific risk estimates were combined using fixed or random effects models depending on whether significant heterogeneity was detected. For the Shanghai Women's and Men's Health Studies, 299 liver cancer cases were identified during follow-up through 2010. Family history of liver cancer was associated with liver cancer risk using both binary indicator (HR = 2.60, 95% CI: 1.77-3.80) and proportional score (high-risk vs. minimal-risk category: HR = 3.03, 95% CI: 1.73-5.31), with increasing HRs for increasing score categories. The meta-analysis also showed an increased risk for those with a family history of liver cancer (relative risk = 2.55, 95% CI: 2.05-3.16). Family history of liver cancer was related to increased risk of liver cancer in Chinese population. This risk is particularly high for those with an affected mother. The "dose-response" of risk with an increasing family history score of liver cancer might further facilitate future cancer prevention programs on identifying individuals with the highest potential liver cancer risk. 10.1002/ijc.28792
Liver cancer prediction in a viral hepatitis cohort: A deep learning approach. Phan Dinh-Van,Chan Chien-Lung,Li Ai-Hsien Adams,Chien Ting-Ying,Nguyen Van-Chuc International journal of cancer Viral hepatitis is the primary cause of liver diseases, among which liver cancer is the leading cause of death from cancer. However, this cancer is often diagnosed in the later stages, which makes treatment difficult or even impossible. This study applied deep learning (DL) models for the early prediction of liver cancer in a hepatitis cohort. In this study, we surveyed 1 million random samples from the National Health Insurance Research Database (NHIRD) to analyze viral hepatitis patients from 2002 to 2010. Then, we used DL models to predict liver cancer cases based on the history of diseases of the hepatitis cohort. Our results revealed the annual prevalence of hepatitis in Taiwan increased from 2002 to 2010, with an average annual percentage change (AAPC) of 5.8% (95% CI: 4.2-7.4). However, young people (aged 16-30 years) exhibited a decreasing trend, with an AAPC of -5.6 (95% CI: -8.1 to -2.9). The results of applying DL models showed that the convolution neural network (CNN) model yielded the best performance in terms of predicting liver cancer cases, with an accuracy of 0.980 (AUC: 0.886). In conclusion, this study showed an increasing trend in the annual prevalence of hepatitis, but a decreasing trend in young people from 2002 to 2010 in Taiwan. The CNN model may be applied to predict liver cancer in a hepatitis cohort with high accuracy. 10.1002/ijc.33245
Risk-Based Selection of Individuals for Oral Cancer Screening. Journal of clinical oncology : official journal of the American Society of Clinical Oncology PURPOSE:We evaluated proof of principle for resource-efficient, risk-based screening through reanalysis of the Kerala Oral Cancer Screening Trial. METHODS:The cluster-randomized trial included three triennial rounds of visual inspection (seven clusters, n = 96,516) versus standard of care (six clusters, n = 95,354) and up to 9 years of follow-up. We developed a Cox regression-based risk prediction model for oral cancer incidence. Using this risk prediction model to adjust for the oral cancer risk imbalance between arms, through intention-to-treat (ITT) analyses that accounted for cluster randomization, we calculated the relative (hazard ratios [HRs]) and absolute (rate differences [RDs]) screening efficacy on oral cancer mortality and compared screening efficiency across risk thresholds. RESULTS:Oral cancer mortality was reduced by 27% in the screening versus control arms (HR = 0.73; 95% CI, 0.54 to 0.98), including a 29% reduction in ever-tobacco and/or ever-alcohol users (HR = 0.71; 95% CI, 0.51 to 0.99). This relative efficacy was similar across oral cancer risk quartiles ( interaction = .59); consequently, the absolute efficacy increased with increasing model-predicted risk-overall trial: RD in the lowest risk quartile (Q1) = 0.5/100,000 versus 13.4/100,000 in the highest quartile (Q4), trend = .059 and ever-tobacco and/or ever-alcohol users: Q1 RD = 1.0/100,000 versus Q4 = 22.5/100,000; trend = .026. In a population akin to the Kerala trial, screening of 100% of individuals would provide 27.1% oral cancer mortality reduction at number needed to screen (NNS) = 2,043. Restriction of screening to ever-tobacco and/or ever-alcohol users with no additional risk stratification would substantially enhance efficiency (43.4% screened for 23.3% oral cancer mortality reduction at NNS = 1,029), whereas risk prediction model-based screening of 50% of ever-tobacco and/or ever-alcohol users at highest risk would further enhance efficiency with little loss in program sensitivity (21.7% screened for 19.7% oral cancer mortality reduction at NNS = 610). CONCLUSION:In the Kerala trial, the efficacy of oral cancer screening was greatest in individuals at highest oral cancer risk. These results provide proof of principle that risk-based oral cancer screening could substantially enhance the efficiency of screening programs. 10.1200/JCO.20.02855
Bone mineral density, nutrient intake, and physical activity among young women from Uganda. Archives of osteoporosis Few studies have characterized bone mineral density (BMD) among health young African women. In our study of 496 Ugandan women age ≤25 years, we found that women had healthy BMD that were lower on average than the standard reference ranges. Reference ranges available for BMD measurements need greater precision. PURPOSE:Data describing bone mineral density (BMD), nutrient intake, and body composition among healthy, young women in sub-Saharan Africa are limited. Using baseline data from a cohort of young, healthy Ugandan women, we summarize bone health and associated risk factors for reduced bone mass. METHODS:Using baseline data from Ugandan women ages 16-25 years who enrolled in an ongoing cohort study of bone health with concurrent use of injectable contraception and oral HIV pre-exposure prophylaxis, we describe the distribution of BMD, nutrient intake, physical activity, and body composition. The association of low BMD (1 or more standard deviations below the age, sex, and race-matched reference range from the USA) and calcium intake, vitamin D intake, physical activity, and body composition was estimated using multivariable logistic regression. RESULTS:In 496 healthy, Ugandan women with median age of 20 years (interquartile range [IQR] 19-21) and median fat:lean mass ratio of 0.55 (IQR 0.46-0.64), median lumbar spine and total hip BMD was 0.9g/cm (IQR 0.9-1.0) each. For lumbar spine, Z-score distributions were lower overall than the reference population and 9.3% and 36.3% of women had Z-score >2 and >1 standard deviations below the reference range, respectively. For total hip, Z-scores were similar to the reference population and 1.0% and 12.3% of women had Z-score >2 and >1 standard deviations below the reference range, respectively. In the week prior to enrollment, 41.1% of women consumed >7 servings of calcium, 56.5% had >7 servings of vitamin D, and 98.6% reported ≥2.5 h of physical activity. Having greater body fat was associated with greater frequency of low lumbar spine BMD (p<0.01 for fat:lean mass ratio, total body fat percentage, waist circumference, and BMI). CONCLUSION:Young Ugandan women exhibited healthy levels of BMD that were lower than the reference range population. 10.1007/s11657-022-01155-0
Machine learning-based prediction of critical illness in children visiting the emergency department. Hwang Soyun,Lee Bongjin PloS one OBJECTIVES:Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have attempted to augment this process with machine learning models, showing advantages in predicting critical conditions and hospitalization outcomes. The aim of this study was to utilize nationwide registry data to develop a machine learning-based classification model to predict the clinical course of pediatric ED visits. METHODS:This cross-sectional observational study used data from the National Emergency Department Information System on emergency visits of children under 15 years of age from January 1, 2016, to December 31, 2017. The primary and secondary outcomes were to identify critically ill children and predict hospitalization from triage data, respectively. We developed and tested a random forest model with the under sampled dataset and validated the model using the entire dataset. We compared the model's performance with that of the conventional triage system. RESULTS:A total of 2,621,710 children were eligible for the analysis and included 12,951 (0.5%) critical outcomes and 303,808 (11.6%) hospitalizations. After validation, the area under the receiver operating characteristic curve was 0.991 (95% confidence interval [CI] 0.991-0.992) for critical outcomes and 0.943 (95% CI 0.943-0.944) for hospitalization, which were higher than those of the conventional triage system. CONCLUSIONS:The machine learning-based model using structured triage data from a nationwide database can effectively predict critical illness and hospitalizations among children visiting the ED. 10.1371/journal.pone.0264184
Association between hyperglycaemia and adverse perinatal outcomes in south Asian and white British women: analysis of data from the Born in Bradford cohort. Farrar Diane,Fairley Lesley,Santorelli Gillian,Tuffnell Derek,Sheldon Trevor A,Wright John,van Overveld Lydia,Lawlor Debbie A The lancet. Diabetes & endocrinology BACKGROUND:Diagnosis of gestational diabetes predicts risk of infants who are large for gestational age (LGA) and with high adiposity, which in turn aims to predict a future risk of obesity in the offspring. South Asian women have higher risk of gestational diabetes, lower risk of LGA, and on average give birth to infants with greater adiposity than do white European women. Whether the same diagnostic criteria for gestational diabetes should apply to both groups of women is unclear. We aimed to assess the association between maternal glucose and adverse perinatal outcomes to ascertain whether thresholds used to diagnose gestational diabetes should differ between south Asian and white British women. We also aimed to assess whether ethnic origin affected prevalence of gestational diabetes irrespective of criteria used. METHODS:We used data (including results of a 26-28 week gestation oral glucose tolerance test) of women from the Born in Bradford study, a prospective study that recruited women attending the antenatal clinic at the Bradford Royal Infirmary, UK, between 2007 and 2011 and who intended to give birth to their infant in that hospital. We studied the association between fasting and 2 h post-load glucose and three primary outcomes (LGA [defined as birthweight >90th percentile for gestational age], high infant adiposity [sum of skinfolds >90th percentile for gestational age], and caesarean section). We calculated adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) for a 1 SD increase in fasting and post-load glucose. We established fasting and post-load glucose thresholds that equated to an OR of 1·75 for LGA and high infant adiposity in each group of women to identify ethnic-specific criteria for diagnosis of gestational diabetes. FINDINGS:Of 13,773 pregnancies, 3420 were excluded from analyses. Of 10,353 eligible pregnancies, 4088 women were white British, 5408 were south Asian, and 857 were of other ethnic origin. The adjusted ORs of LGA per 1 SD fasting glucose were 1·22 (95% CI 1·08-1·38) in white British women and 1·43 (1·23-1·67) in south Asian women (pinteraction with ethnicity = 0·39). Results for high infant adiposity were 1·35 (1·23-1·49) and 1·35 (1·18-1·54; pinteraction with ethnicity=0·98), and for caesarean section they were 1·06 (0·97-1·16) and 1·11 (1·02-1·20; pinteraction with ethnicity=0·47). Associations between post-load glucose and the three primary outcomes were weaker than for fasting glucose. A fasting glucose concentration of 5·4 mmol/L or a 2 h post-load level of 7·5 mmol/L identified white British women with 75% or higher relative risk of LGA or high infant adiposity; in south Asian women, the cutoffs were 5·2 mmol/L or 7·2 mml/L; in the whole cohort, the cutoffs were 5·3 mmol/L or 7·5 mml/L. The prevalence of gestational diabetes in our cohort ranged from 1·2% to 8·7% in white British women and 4% to 24% in south Asian women using six different criteria. Compared with the application of our whole-cohort criteria, use of our ethnic-specific criteria increased the prevalence of gestational diabetes in south Asian women from 17·4% (95% CI 16·4-18·4) to 24·2% (23·1-25·3). INTERPRETATION:Our data support the use of lower fasting and post-load glucose thresholds to diagnose gestational diabetes in south Asian than white British women. They also suggest that diagnostic criteria for gestational diabetes recommended by UK NICE might underestimate the prevalence of gestational diabetes compared with our criteria or those recommended by the International Association of Diabetes and Pregnancy Study Groups and WHO, especially in south Asian women. FUNDING:The National Institute for Health Research. 10.1016/S2213-8587(15)00255-7
Adjuvant Chemotherapy vs Postoperative Observation Following Preoperative Chemoradiotherapy and Resection in Gastroesophageal Cancer: A Propensity Score-Matched Analysis. JAMA oncology IMPORTANCE:Distant recurrence following preoperative chemoradiotherapy and resection in patients with gastroesophageal adenocarcinoma is common. Adjuvant chemotherapy may improve survival. OBJECTIVE:To compare adjuvant chemotherapy with postoperative observation following preoperative chemoradiotherapy and resection in patients with gastroesophageal adenocarcinoma. DESIGN, SETTING, AND PARTICIPANTS:Propensity score-matched analysis using the National Cancer Database. We included adult patients who received a diagnosis between 2006 and 2013 of clinical stage T1N1-3M0 or T2-4N0-3M0 adenocarcinoma of the distal esophagus or gastric cardia who were treated with preoperative chemoradiotherapy and curative-intent resection. Patients receiving adjuvant chemotherapy were matched by propensity score to patients undergoing postoperative observation. EXPOSURES:Adjuvant chemotherapy and postoperative observation. MAIN OUTCOMES AND MEASURES:Overall survival. RESULTS:We identified 10 086 patients (8840 [88%] male; mean [SD] age, 61 [9.5] years), 9272 in the postoperative observation group and 814 in the adjuvant chemotherapy group. Patients receiving adjuvant chemotherapy were younger (18-54 years: 252 [31%] vs 1989 [21%]; P < .001) and were more likely to have advanced disease (ypT3/4: 458 [62%] vs 3531 [46%]; P < .001; ypN+: 572 [72%] vs 3428 [39%]; P < .001), as well as shorter postoperative inpatient stays (>2 weeks: 94 [13%] vs 1589 [20%]; P < .001). A total of 732 patients in the adjuvant chemotherapy group were matched by propensity score to 3660 patients in the postoperative observation group. Adjuvant chemotherapy was associated with improved overall survival compared with postoperative observation (median survival: 40 months; 95% CI, 36-46 months vs 34 months; 95% CI, 32-35 months; stratified log-rank P < .001; hazard ratio, 0.79; 95% CI, 0.72-0.88). Overall survival at 1, 3, and 5 years was 88%, 47%, and 34% in the observation group, and 94%, 54%, and 38% in the adjuvant chemotherapy group, respectively. Adjuvant chemotherapy was associated with a survival benefit compared with postoperative observation in most patient subgroups. CONCLUSIONS AND RELEVANCE:For patients with locally advanced gastroesophageal adenocarcinoma treated with preoperative chemoradiotherapy and resection, adjuvant chemotherapy was associated with improved overall survival. Our findings have important implications for the postoperative treatment of this patient group for which few data are available. 10.1001/jamaoncol.2017.2805
Long-term night shift work is associated with the risk of atrial fibrillation and coronary heart disease. European heart journal AIMS:The aim of this study was to test whether current and past night shift work was associated with incident atrial fibrillation (AF) and whether this association was modified by genetic vulnerability. Its associations with coronary heart disease (CHD), stroke, and heart failure (HF) were measured as a secondary aim. METHODS AND RESULTS:This cohort study included 283 657 participants in paid employment or self-employed without AF and 276 009 participants free of CHD, stroke, and HF at baseline in the UK Biobank. Current and lifetime night shift work information was obtained. Cox proportional hazard models were used. Weighted genetic risk score for AF was calculated. During a median follow-up of 10.4 years, 5777 incident AF cases were documented. From 'day workers', 'shift but never/rarely night shifts', and 'some night shifts' to 'usual/permanent night shifts', there was a significant increasing trend in the risk of incident AF (P for trend 0.013). Usual or permanent night shifts were associated with the highest risk [hazard ratio (HR) 1.16, 95% confidence interval (CI) 1.02-1.32]. Considering a person's lifetime work schedule and compared with shift workers never working nights, participants with a duration over 10 years and an average 3-8 nights/month frequency of night shift work exposure possessed higher AF risk (HR 1.18, 95% CI 0.99-1.40 and HR 1.22, 95% CI 1.02-1.45, respectively). These associations between current and lifetime night shifts and AF were not modified by genetic predisposition to AF. Usual/permanent current night shifts, ≥10 years and 3-8 nights/month of lifetime night shifts were significantly associated with a higher risk of incident CHD (HR 1.22, 95% CI 1.11-1.35, HR 1.37, 95% CI 1.20-1.58 and HR 1.35, 95% CI 1.18-1.55, respectively). These associations in stroke and HF were not significant. CONCLUSION:Both current and lifetime night shift exposures were associated with increased AF risk, regardless of genetic AF risk. Night shift exposure also increased the risk of CHD but not stroke or HF. Whether decreasing night shift work frequency and duration might represent another avenue to improve heart health during working life and beyond warrants further study. 10.1093/eurheartj/ehab505
Acupuncture for Chronic Severe Functional Constipation: A Randomized Trial. Liu Zhishun,Yan Shiyan,Wu Jiani,He Liyun,Li Ning,Dong Guirong,Fang Jianqiao,Fu Wenbin,Fu Lixin,Sun Jianhua,Wang Linpeng,Wang Shun,Yang Jun,Zhang Hongxing,Zhang Jianbin,Zhao Jiping,Zhou Wei,Zhou Zhongyu,Ai Yanke,Zhou Kehua,Liu Jia,Xu Huanfang,Cai Yuying,Liu Baoyan Annals of internal medicine BACKGROUND:Acupuncture has been used for chronic constipation, but evidence for its effectiveness remains scarce. OBJECTIVE:To determine the efficacy of electroacupuncture (EA) for chronic severe functional constipation (CSFC). DESIGN:Randomized, parallel, sham-controlled trial. (ClinicalTrials.gov: NCT01726504). SETTING:15 hospitals in China. PARTICIPANTS:Patients with CSFC and no serious underlying pathologic cause for constipation. INTERVENTION:28 sessions of EA at traditional acupoints or sham EA (SA) at nonacupoints over 8 weeks. MEASUREMENTS:The primary outcome was the change from baseline in mean weekly complete spontaneous bowel movements (CSBMs) during weeks 1 to 8. Participants were followed until week 20. RESULTS:1075 patients (536 and 539 in the EA and SA groups, respectively) were enrolled. The increase from baseline in mean weekly CSBMs during weeks 1 to 8 was 1.76 (95% CI, 1.61 to 1.89) in the EA group and 0.87 (CI, 0.73 to 0.97) in the SA group (between-group difference, 0.90 [CI, 0.74 to 1.10]; P < 0.001). The change from baseline in mean weekly CSBMs during weeks 9 to 20 was 1.96 (CI, 1.78 to 2.11) in the EA group and 0.89 (CI, 0.69 to 0.95) in the SA group (between-group difference, 1.09 [CI, 0.94 to 1.31]; P < 0.001). The proportion of patients having 3 or more mean weekly CSBMs in the EA group was 31.3% and 37.7% over the treatment and follow-up periods, respectively, compared with 12.1% and 14.1% in the SA group (P < 0.001). Acupuncture-related adverse events during treatment were infrequent in both groups, and all were mild or transient. LIMITATIONS:Longer-term follow-up was not assessed. Acupuncturists could not be blinded. CONCLUSION:Eight weeks of EA increases CSBMs and is safe for the treatment of CSFC. Additional study is warranted to evaluate a longer-term treatment and follow-up. PRIMARY FUNDING SOURCE:Ministry of Science and Technology of the People's Republic of China through the Twelfth Five-Year National Science and Technology Pillar Program. 10.7326/M15-3118
The combined use of salivary biomarkers and clinical parameters to predict the outcome of scaling and root planing: A cohort study. Liu Yiying,Duan Dingyu,Ma Rui,Ding Yi,Xu Yi,Zhou Xuedong,Zhao Lei,Xu Xin Journal of clinical periodontology AIM:To explore the application of the combined use of baseline salivary biomarkers and clinical parameters in predicting the outcome of scaling and root planing (SRP). MATERIALS AND METHODS:Forty patients with advanced periodontitis were included. Baseline saliva samples were analysed for interleukin-1β (IL-1β), matrix metalloproteinase-8 and the loads of Porphyromonas gingivalis, Prevotella intermedia, Aggregatibacter actinomycetemcomitans and Tannerella forsythia. After SRP, pocket closure and further attachment loss at 6 months post-treatment were chosen as outcome variables. Models to predict the outcomes were established by generalized estimating equations. RESULTS:The combined use of baseline clinical attachment level (CAL), site location and IL-1β (area under the curve [AUC] = 0.764) better predicted pocket closure than probing depth (AUC = 0.672), CAL (AUC = 0.679), site location (AUC = 0.654) or IL-1β (AUC = 0.579) alone. The combination of site location, tooth loss, percentage of deep pockets, detection of A. actinomycetemcomitans and T. forsythia load (AUC = 0.842) better predicted further clinical attachment loss than site location (AUC = 0.715), tooth loss (AUC = 0.530), percentage of deep pockets (AUC = 0.659) or T. forsythia load (AUC = 0.647) alone. CONCLUSION:The combination of baseline salivary biomarkers and clinical parameters better predicted SRP outcomes than each alone. The current study indicates the possible usefulness of salivary biomarkers in addition to tooth-related parameters in predicting SRP outcomes. 10.1111/jcpe.13367
Machine learning methods are comparable to logistic regression techniques in predicting severe walking limitation following total knee arthroplasty. Pua Yong-Hao,Kang Hakmook,Thumboo Julian,Clark Ross Allan,Chew Eleanor Shu-Xian,Poon Cheryl Lian-Li,Chong Hwei-Chi,Yeo Seng-Jin Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA PURPOSE:Machine-learning methods are flexible prediction algorithms with potential advantages over conventional regression. This study aimed to use machine learning methods to predict post-total knee arthroplasty (TKA) walking limitation, and to compare their performance with that of logistic regression. METHODS:From the department's clinical registry, a cohort of 4026 patients who underwent elective, primary TKA between July 2013 and July 2017 was identified. Candidate predictors included demographics and preoperative clinical, psychosocial, and outcome measures. The primary outcome was severe walking limitation at 6 months post-TKA, defined as a maximum walk time ≤ 15 min. Eight common regression (logistic, penalized logistic, and ordinal logistic with natural splines) and ensemble machine learning (random forest, extreme gradient boosting, and SuperLearner) methods were implemented to predict the probability of severe walking limitation. Models were compared on discrimination and calibration metrics. RESULTS:At 6 months post-TKA, 13% of patients had severe walking limitation. Machine learning and logistic regression models performed moderately [mean area under the ROC curves (AUC) 0.73-0.75]. Overall, the ordinal logistic regression model performed best while the SuperLearner performed best among machine learning methods, with negligible differences between them (Brier score difference, < 0.001; 95% CI [- 0.0025, 0.002]). CONCLUSIONS:When predicting post-TKA physical function, several machine learning methods did not outperform logistic regression-in particular, ordinal logistic regression that does not assume linearity in its predictors. LEVEL OF EVIDENCE:Prognostic level II. 10.1007/s00167-019-05822-7
Comparison of different devices to measure the intraocular pressure in thyroid-associated orbitopathy. Kuebler Aylin Garip,Wiecha Caroline,Reznicek Lukas,Klingenstein Annemarie,Halfter Kathrin,Priglinger Siegfried,Hintschich Christoph Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie PURPOSE:To evaluate the correlation of the intraocular pressure measurements (IOP) with non-contact tonometer Corvis Scheimpflug technology (Corvis ST), Goldmann applanation tonometry (GAT), ocular response analyzer (ORA), and iCARE rebound tonometer in patients with thyroid-associated orbitopathy (TAO) and eye-healthy subjects (control group). METHODS:Twenty-nine consecutive patients with TAO (79% female) and 30 eye-healthy subjects (60% female) were included in this prospective, age- and sex-matched study. The IOP measurement with Corvis, ORA, GAT, iCARE, and central corneal thickness (CCT) with Corvis was obtained from all study participants. RESULTS:The mean age of the patients was 51 ± 10 years in patients with TAO and 56 ± 13 years in the control group. The mean IOP measurements with GAT, Corvis, ORA, and iCARE were 15.93 ± 4.42 mmHg, 18.10 ± 7.54 mmHg, 18.40 ± 7.93 mmHg, and 16.61 ± 7.96 mmHg in patients with TAO and 14.52 ± 3.02 mmHg, 14.48 ± 3.38 mmHg, 15.29 ± 4.64 mmHg, and 14.13 ± 3.85 mmHg in the control group (P = 0.157, P = 0.004, P = 0.017, and P = 0.176 respectively). The mean CCT was 547.5 ± 39.2 μm in patients with TAO and 560.8 ± 49.8 μm in the control group ( P= 0.261). CONCLUSIONS:The data collected shows an agreement between the iCARE and GAT IOP measurements in TAO patients and in eye-healthy patients. However, the mean value of IOP measurements with Corvis and ORA was significantly higher in patients with TAO in comparison with the control group (P = 0.044 and P = 0.029 respectively). 10.1007/s00417-019-04367-2
High-Resolution Magnetic Resonance Imaging Can Reliably Detect Orbital Tumor Recurrence after Enucleation in Children with Retinoblastoma. Sirin Selma,de Jong Marcus C,de Graaf Pim,Brisse Hervé J,Galluzzi Paolo,Maeder Philippe,Bornfeld Norbert,Biewald Eva,Metz Klaus A,Temming Petra,Castelijns Jonas A,Goericke Sophia L, Ophthalmology PURPOSE:Orbital tumor recurrence is a rare but serious complication in children with retinoblastoma, leading to a high risk of metastasis and death. Therefore, we assume that these recurrences have to be detected and treated as early as possible. Preliminary studies used magnetic resonance imaging (MRI) to evaluate postsurgical findings in the orbit. In this study, we assessed the diagnostic accuracy of high-resolution MRI to detect orbital tumor recurrence in children with retinoblastoma in a large study cohort. DESIGN:Consecutive retrospective study (2007-2013) assessing MRI findings after enucleation. PARTICIPANTS:A total of 103 MRI examinations of 55 orbits (50 children, 27 male/23 female, mean age 16.3±12.4 months) with a median time of 8 months (range, 0-93) after enucleation for retinoblastoma. METHODS:High-resolution MRI using orbital surface coils was performed on 1.5 Tesla MRI systems to assess abnormal orbital findings. MAIN OUTCOME MEASURES:Five European experts in retinoblastoma imaging evaluated the MRI examinations regarding the presence of abnormal orbital gadolinium enhancement and judged them as "definitive tumor," "suspicious of tumor," "postsurgical condition/scar formation," or "without pathologic findings." The findings were correlated to histopathology (if available), MRI, and clinical follow-up. RESULTS:Abnormal orbital enhancement was a common finding after enucleation (100% in the first 3 months after enucleation, 64.3% >3 years after enucleation). All histopathologically confirmed tumor recurrences (3 of 55 orbits, 5.5%) were correctly judged as "definitive tumor" in MRI. Two orbits from 2 children rated as "suspicious of tumor" received intravenous chemotherapy without histopathologic confirmation; further follow-up (67 and 47 months) revealed no sign of tumor recurrence. In 90.2%, no tumor was suspected on MRI, which was clinically confirmed during follow-up (median follow-up after enucleation, 45 months; range, 8-126). CONCLUSIONS:High-resolution MRI with orbital surface coils may reliably distinguish between common postsurgical contrast enhancement and orbital tumor recurrence, and therefore may be a useful tool to evaluate orbital tumor recurrence after enucleation in children with retinoblastoma. We recommend high-resolution MRI as a potential screening tool for the orbit in children with retinoblastoma to exclude tumor recurrence, especially in high-risk patients within the critical first 2 years after enucleation. 10.1016/j.ophtha.2015.10.054
Circulating microRNA miR-323-3p as a biomarker of ectopic pregnancy. Zhao Zhen,Zhao Qiuhong,Warrick Joshua,Lockwood Christina M,Woodworth Alison,Moley Kelle H,Gronowski Ann M Clinical chemistry BACKGROUND:The use of serum human chorionic gonadotropin (hCG) and progesterone to identify patients with ectopic pregnancy (EP) has been shown to have poor clinical utility. Pregnancy-associated circulating microRNAs (miRNAs) have been proposed as potential biomarkers for the diagnosis of pregnancy-associated complications. This proof-of-concept study examined the diagnostic accuracy of various miRNAs to detect EP in an emergency department (ED) setting. METHODS:This study was a retrospective case-control analysis of 89 women who presented to the ED with vaginal bleeding and/or abdominal pain/cramping and received a diagnosis of viable intrauterine pregnancy (VIP), spontaneous abortion (SA), or EP. Serum hCG and progesterone concentrations were measured by immunoassays. The serum concentrations of miRNAs miR-323-3p, miR-517a, miR-519d, and miR-525-3p were measured with TaqMan real-time PCR. Statistical analysis was performed to determine the clinical utility of these biomarkers, both as single markers and as multimarker panels for EP. RESULTS:Concentrations of serum hCG, progesterone, miR-517a, miR-519d, and miR-525-3p were significantly lower in EP and SA cases than in VIP cases (P < 0.01). In contrast, the concentration of miR-323-3p was significantly increased in EP cases, compared with SA and VIP cases (P < 0.01). As a single marker, miR-323-3p had the highest sensitivity of 37.0% (at a fixed specificity of 90%). In comparison, the combined panel of hCG, progesterone, and miR-323-3p yielded the highest sensitivity (77.8%, at a fixed specificity of 90%). A stepwise analysis that used hCG first, added progesterone, and then added miR-323-3p yielded a 96.3% sensitivity and a 72.6% specificity. CONCLUSIONS:Pregnancy-associated miRNAs, especially miR-323-3p, added substantial diagnostic accuracy to a panel including hCG and progesterone for the diagnosis of EP. 10.1373/clinchem.2011.179283
Pregnancy-associated microRNAs in plasma as potential molecular markers of ectopic pregnancy. Miura Kiyonori,Higashijima Ai,Mishima Hiroyuki,Miura Shoko,Kitajima Michio,Kaneuchi Masanori,Yoshiura Koh-Ichiro,Masuzaki Hideaki Fertility and sterility OBJECTIVE:To investigate cell-free pregnancy-associated microRNAs as molecular markers for the diagnosis of ectopic pregnancy. DESIGN:Laboratory study using human plasma samples. SETTING:Research unit in a university hospital. PATIENT(S):Plasma samples from 18 women with ectopic pregnancies (EP group), 12 women with spontaneous abortion (SA group), and 26 normal women with singleton pregnancies (NP group). INTERVENTION(S):Total RNAs containing small RNA molecules extracted from 1.2 mL of plasma. MAIN OUTCOME MEASURE(S):Plasma concentrations of cell-free microRNAs measured by quantitative real-time reverse-transcriptase polymerase chain reaction. RESULT(S):Plasma concentrations of cell-free pregnancy-associated microRNAs (miR-323-3p, miR-515-3p, miR-517a, miR-517c, and miR-518b) and serum concentration of human chorionic gonadotropin (hCG) were confirmed to have statistically significantly different plasma or serum concentrations in women with EP, SA, or NP. There was no statistically significant difference in the plasma concentrations of cell-free miR-21 between the three groups. By correlation coefficient analysis, no relationship was detected between serum hCG levels and plasma cell-free miR-517c, miR-515-3p, miR-517a, miR-518b, miR-323-3p, or miR-21 levels. Plasma concentrations of cell-free miR-517a could distinguish EP/SA from NP, yielding an area under the curve of 0.9654 (95% confidence interval, 0.9172-1.0). Plasma concentrations of cell-free miR-323-3p could distinguish EP from SA, yielding an area under the curve of 0.7454 (95% confidence interval, 0.5558-0.9349). CONCLUSION(S):Cell-free pregnancy-associated microRNAs have potential as molecular markers of ectopic pregnancy. 10.1016/j.fertnstert.2015.01.041
MicroRNA-873 is a Potential Serum Biomarker for the Detection of Ectopic Pregnancy. Lu Qi,Yan Qi,Xu Fengying,Li Yuhong,Zhao Wenxia,Wu Chunzhu,Wang Yudong,Lang Xiao Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology BACKGROUND:Ectopic pregnancy (EP) refers to the implantation of the zygote outside the uterine cavity. In clinical practice, the diagnosis of EP relies on a combination of ultrasound findings and serum human chorionic gonadotrophin (hCG) measurements. However, the need for serial hCG measurements increases the risk of tubal rupture and death, underscoring the need to identify biomarkers for the early detection of EP. METHODS:The serum concentrations of 21 microRNAs (miRNAs) associated with pregnancy or with known placental expression, as well as serum hCG and progesterone levels were analyzed 36 patients with viable intrauterine pregnancy (VIP), 30 patients with spontaneous abortion (SA), and 34 patients with EP using specific assay kits and reverse transcription PCR. The diagnostic performance of the different serum markers for detecting EP was analyzed by ROC curve analysis. RESULTS:Five miRNAs were differentially expressed between the three groups, of which miR-873 and miR-223 were significantly lower in EP than in VIP and SA patients and did not change significantly according to gestational age, and miR-323 was significantly higher in EP than in VIP and SA. As a single marker, miR-873 had the highest sensitivity for detecting EP at 61.76% (at a fixed specificity of 90%). In comparison, the combination of hCG, progesterone and miR-873 had the highest sensitivity for detecting EP at 79.41% (at a fixed specificity of 90%). CONCLUSION:Although further validation in large-scale prospective studies is necessary, our results suggest that miR-873 could be a valuable noninvasive and stable biomarker for the early detection of EP. 10.1159/000475946
Early triage of critically ill COVID-19 patients using deep learning. Nature communications The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern. It is imperative to identify these patients early. We show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness based on clinical characteristics at admission. We develop this model using a cohort of 1590 patients from 575 medical centers, with internal validation performance of concordance index 0.894 We further validate the model on three separate cohorts from Wuhan, Hubei and Guangdong provinces consisting of 1393 patients with concordance indexes of 0.890, 0.852 and 0.967 respectively. This model is used to create an online calculation tool designed for patient triage at admission to identify patients at risk of severe illness, ensuring that patients at greatest risk of severe illness receive appropriate care as early as possible and allow for effective allocation of health resources. 10.1038/s41467-020-17280-8
Association of Skipping Breakfast With Cardiovascular and All-Cause Mortality. Rong Shuang,Snetselaar Linda G,Xu Guifeng,Sun Yangbo,Liu Buyun,Wallace Robert B,Bao Wei Journal of the American College of Cardiology BACKGROUND:Skipping breakfast is common among U.S. adults. Limited evidence suggests that skipping breakfast is associated with atherosclerosis and cardiovascular disease. OBJECTIVES:The authors sought to examine the association of skipping breakfast with cardiovascular and all-cause mortality. METHODS:This is a prospective cohort study of a nationally representative sample of 6,550 adults 40 to 75 years of age who participated in the National Health and Nutrition Examination Survey III 1988 to 1994. Frequency of breakfast eating was reported during an in-house interview. Death and underlying causes of death were ascertained by linkage to death records through December 31, 2011. The associations between breakfast consumption frequency and cardiovascular and all-cause mortality were investigated by using weighted Cox proportional hazards regression models. RESULTS:Among the 6,550 participants (mean age 53.2 years; 48.0% male) in this study, 5.1% never consumed breakfast, 10.9% rarely consumed breakfast, 25.0% consumed breakfast some days, and 59.0% consumed breakfast every day. During 112,148 person-years of follow-up, 2,318 deaths occurred including 619 deaths from cardiovascular disease. After adjustment for age, sex, race/ethnicity, socioeconomic status, dietary and lifestyle factors, body mass index, and cardiovascular risk factors, participants who never consumed breakfast compared with those consuming breakfast everyday had hazard ratios of 1.87 (95% confidence interval: 1.14 to 3.04) for cardiovascular mortality and 1.19 (95% confidence interval: 0.99 to 1.42) for all-cause mortality. CONCLUSIONS:In a nationally representative cohort with 17 to 23 years of follow-up, skipping breakfast was associated with a significantly increased risk of mortality from cardiovascular disease. Our study supports the benefits of eating breakfast in promoting cardiovascular health. 10.1016/j.jacc.2019.01.065
Speckle tracking quantification of lung sliding for the diagnosis of pneumothorax: a multicentric observational study. Duclos Gary,Bobbia Xavier,Markarian Thibaut,Muller Laurent,Cheyssac Camille,Castillon Sarah,Resseguier Noémie,Boussuges Alain,Volpicelli Giovanni,Leone Marc,Zieleskiewicz Laurent Intensive care medicine PURPOSE:Lung ultrasound is used for the diagnosis of pneumothorax, based on lung sliding abolition which is a qualitative and operator-dependent assessment. Speckle tracking allows the quantification of structure deformation over time by analysing acoustic markers. We aimed to test the ability of speckle tracking technology to quantify lung sliding in a selected cohort of patients and to observe how the technology may help the process of pneumothorax diagnosis. METHODS:We performed retrospectively a pleural speckle tracking analysis on ultrasound loops from patients with pneumothorax. We compared the values measured by two observers from pneumothorax side with contralateral normal lung side. The receiver operating characteristic (ROC) curve was constructed to evaluate the performance of maximal pleural strain to detect the lung sliding abolition. Diagnosis performance and time to diagnosis between B-Mode and speckle tracking technology were compared from a third blinded observer. RESULTS:We analysed 104 ultrasound loops from 52 patients. The area under the ROC curve of the maximal pleural strain value to identify lung sliding abolition was 1.00 [95%CI 1.00; 1.00]. Specificity was 100% [95%CI 93%; 100%] and sensitivity was 100% [95%CI 93%; 100%] with the best cut-off of 4%. Over 104 ultrasound loops, the blinded observer made two errors with B-Mode and none with speckle tracking. The median diagnosis time was 3 [2-5] seconds for B-Mode versus 2 [1-2] seconds for speckle tracking (p = 0.001). CONCLUSION:Speckle tracking technology allows lung sliding quantification and detection of lung sliding abolition in case of pneumothorax on selected ultrasound loops. 10.1007/s00134-019-05710-1
Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19. Liang Wenhua,Liang Hengrui,Ou Limin,Chen Binfeng,Chen Ailan,Li Caichen,Li Yimin,Guan Weijie,Sang Ling,Lu Jiatao,Xu Yuanda,Chen Guoqiang,Guo Haiyan,Guo Jun,Chen Zisheng,Zhao Yi,Li Shiyue,Zhang Nuofu,Zhong Nanshan,He Jianxing, JAMA internal medicine Importance:Early identification of patients with novel coronavirus disease 2019 (COVID-19) who may develop critical illness is of great importance and may aid in delivering proper treatment and optimizing use of resources. Objective:To develop and validate a clinical score at hospital admission for predicting which patients with COVID-19 will develop critical illness based on a nationwide cohort in China. Design, Setting, and Participants:Collaborating with the National Health Commission of China, we established a retrospective cohort of patients with COVID-19 from 575 hospitals in 31 provincial administrative regions as of January 31, 2020. Epidemiological, clinical, laboratory, and imaging variables ascertained at hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive risk score (COVID-GRAM). The score provides an estimate of the risk that a hospitalized patient with COVID-19 will develop critical illness. Accuracy of the score was measured by the area under the receiver operating characteristic curve (AUC). Data from 4 additional cohorts in China hospitalized with COVID-19 were used to validate the score. Data were analyzed between February 20, 2020 and March 17, 2020. Main Outcomes and Measures:Among patients with COVID-19 admitted to the hospital, critical illness was defined as the composite measure of admission to the intensive care unit, invasive ventilation, or death. Results:The development cohort included 1590 patients. the mean (SD) age of patients in the cohort was 48.9 (15.7) years; 904 (57.3%) were men. The validation cohort included 710 patients with a mean (SD) age of 48.2 (15.2) years, and 382 (53.8%) were men and 172 (24.2%). From 72 potential predictors, 10 variables were independent predictive factors and were included in the risk score: chest radiographic abnormality (OR, 3.39; 95% CI, 2.14-5.38), age (OR, 1.03; 95% CI, 1.01-1.05), hemoptysis (OR, 4.53; 95% CI, 1.36-15.15), dyspnea (OR, 1.88; 95% CI, 1.18-3.01), unconsciousness (OR, 4.71; 95% CI, 1.39-15.98), number of comorbidities (OR, 1.60; 95% CI, 1.27-2.00), cancer history (OR, 4.07; 95% CI, 1.23-13.43), neutrophil-to-lymphocyte ratio (OR, 1.06; 95% CI, 1.02-1.10), lactate dehydrogenase (OR, 1.002; 95% CI, 1.001-1.004) and direct bilirubin (OR, 1.15; 95% CI, 1.06-1.24). The mean AUC in the development cohort was 0.88 (95% CI, 0.85-0.91) and the AUC in the validation cohort was 0.88 (95% CI, 0.84-0.93). The score has been translated into an online risk calculator that is freely available to the public ( Conclusions and Relevance:In this study, a risk score based on characteristics of COVID-19 patients at the time of admission to the hospital was developed that may help predict a patient's risk of developing critical illness. 10.1001/jamainternmed.2020.2033
Comparison of Abbreviated Breast MRI vs Digital Breast Tomosynthesis for Breast Cancer Detection Among Women With Dense Breasts Undergoing Screening. Comstock Christopher E,Gatsonis Constantine,Newstead Gillian M,Snyder Bradley S,Gareen Ilana F,Bergin Jennifer T,Rahbar Habib,Sung Janice S,Jacobs Christina,Harvey Jennifer A,Nicholson Mary H,Ward Robert C,Holt Jacqueline,Prather Andrew,Miller Kathy D,Schnall Mitchell D,Kuhl Christiane K JAMA Importance:Improved screening methods for women with dense breasts are needed because of their increased risk of breast cancer and of failed early diagnosis by screening mammography. Objective:To compare the screening performance of abbreviated breast magnetic resonance imaging (MRI) and digital breast tomosynthesis (DBT) in women with dense breasts. Design, Setting, and Participants:Cross-sectional study with longitudinal follow-up at 48 academic, community hospital, and private practice sites in the United States and Germany, conducted between December 2016 and November 2017 among average-risk women aged 40 to 75 years with heterogeneously dense or extremely dense breasts undergoing routine screening. Follow-up ascertainment of cancer diagnoses was complete through September 12, 2019. Exposures:All women underwent screening by both DBT and abbreviated breast MRI, performed in randomized order and read independently to avoid interpretation bias. Main Outcomes and Measures:The primary end point was the invasive cancer detection rate. Secondary outcomes included sensitivity, specificity, additional imaging recommendation rate, and positive predictive value (PPV) of biopsy, using invasive cancer and ductal carcinoma in situ (DCIS) to define a positive reference standard. All outcomes are reported at the participant level. Pathology of core or surgical biopsy was the reference standard for cancer detection rate and PPV; interval cancers reported until the next annual screen were included in the reference standard for sensitivity and specificity. Results:Among 1516 enrolled women, 1444 (median age, 54 [range, 40-75] years) completed both examinations and were included in the analysis. The reference standard was positive for invasive cancer with or without DCIS in 17 women and for DCIS alone in another 6. No interval cancers were observed during follow-up. Abbreviated breast MRI detected all 17 women with invasive cancer and 5 of 6 women with DCIS. Digital breast tomosynthesis detected 7 of 17 women with invasive cancer and 2 of 6 women with DCIS. The invasive cancer detection rate was 11.8 (95% CI, 7.4-18.8) per 1000 women for abbreviated breast MRI vs 4.8 (95% CI, 2.4-10.0) per 1000 women for DBT, a difference of 7 (95% CI, 2.2-11.6) per 1000 women (exact McNemar P = .002). For detection of invasive cancer and DCIS, sensitivity was 95.7% (95% CI, 79.0%-99.2%) with abbreviated breast MRI vs 39.1% (95% CI, 22.2%-59.2%) with DBT (P = .001) and specificity was 86.7% (95% CI, 84.8%-88.4%) vs 97.4% (95% CI, 96.5%-98.1%), respectively (P < .001). The additional imaging recommendation rate was 7.5% (95% CI, 6.2%-9.0%) with abbreviated breast MRI vs 10.1% (95% CI, 8.7%-11.8%) with DBT (P = .02) and the PPV was 19.6% (95% CI, 13.2%-28.2%) vs 31.0% (95% CI, 17.0%-49.7%), respectively (P = .15). Conclusions and Relevance:Among women with dense breasts undergoing screening, abbreviated breast MRI, compared with DBT, was associated with a significantly higher rate of invasive breast cancer detection. Further research is needed to better understand the relationship between screening methods and clinical outcome. Trial Registration:ClinicalTrials.gov Identifier: NCT02933489. 10.1001/jama.2020.0572