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Carotid atherosclerosis (CAS) is closely associated with the decline of cognitive function in the elderly, which can lead to persistent or progressive cognitive function and neurological dysfunction. Vascular cognitive impairment (VCI) is considered to be an intervenable disease. Studies have shown that CAS is one of the main causes of VCI. Further study on the relationship between CAS and VCI will help to better prevention and treatment of VCI.
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COVID-19 is a disease with vast impact, yet much remains unclear about patient outcomes. Most approaches to risk prediction of COVID-19 focus on binary or tertiary severity outcomes, despite the heterogeneity of the disease. In this work, we identify heterogeneous subtypes of COVID-19 outcomes by considering axes of prognosis. We propose two innovative clustering approaches - Layered Axes and Prognosis Space - to apply on patients outcome data. We then show how these clusters can help predict a patients deterioration pathway on their hospital admission, using random forest classification. We illustrate this methodology on a cohort from Wuhan in early 2020. We discover interesting subgroups of poor prognosis, particularly within respiratory patients, and predict respiratory subgroup membership with high accuracy. This work could assist clinicians in identifying appropriate treatments at patients hospital admission. Moreover, our method could be used to explore subtypes of long COVID and other diseases with heterogeneous outcomes.
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BackgroundAccurate risk prediction of clinical outcome would usefully inform clinical decisions and intervention targeting in COVID-19. The aim of this study was to derive and validate risk prediction models for poor outcome and death in adult inpatients with COVID-19. MethodsModel derivation using data from Wuhan, China used logistic regression with death and poor outcome (death or severe disease) as outcomes. Predictors were demographic, comorbidity, symptom and laboratory test variables. The best performing models were externally validated in data from London, UK. Findings4.3% of the derivation cohort (n=775) died and 9.7% had a poor outcome, compared to 34.1% and 42.9% of the validation cohort (n=226). In derivation, prediction models based on age, sex, neutrophil count, lymphocyte count, platelet count, C-reactive protein and creatinine had excellent discrimination (death c-index=0.91, poor outcome c-index=0.88), with good-to-excellent calibration. Using two cut-offs to define low, high and very-high risk groups, derivation patients were stratified in groups with observed death rates of 0.34%, 15.0% and 28.3% and poor outcome rates 0.63%, 8.9% and 58.5%. External validation discrimination was good (c-index death=0.74, poor outcome=0.72) as was calibration. However, observed rates of death were 16.5%, 42.9% and 58.4% and poor outcome 26.3%, 28.4% and 64.8% in predicted low, high and very-high risk groups. InterpretationOur prediction model using demography and routinely-available laboratory tests performed very well in internal validation in the lower-risk derivation population, but less well in the much higher-risk external validation population. Further external validation is needed. Collaboration to create larger derivation datasets, and to rapidly externally validate all proposed prediction models in a range of populations is needed, before routine implementation of any risk prediction tool in clinical care. FundingMRC, Wellcome Trust, HDR-UK, LifeArc, participating hospitals, NNSFC, National Key R&D Program, Pudong Health and Family Planning Commission Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSeveral prognostic models for predicting mortality risk, progression to severe disease, or length of hospital stay in COVID-19 have been published.1 Commonly reported predictors of severe prognosis in patients with COVID-19 include age, sex, computed tomography scan features, C-reactive protein (CRP), lactic dehydrogenase, and lymphocyte count. Symptoms (notably dyspnoea) and comorbidities (e.g. chronic lung disease, cardiovascular disease and hypertension) are also reported to have associations with poor prognosis.2 However, most studies have not described the study population or intended use of prediction models, and external validation is rare and to date done using datasets originating from different Wuhan hospitals.3 Given different patterns of testing and organisation of healthcare pathways, external validation in datasets from other countries is required. Added value of this studyThis study used data from Wuhan, China to derive and internally validate multivariable models to predict poor outcome and death in COVID-19 patients after hospital admission, with external validation using data from Kings College Hospital, London, UK. Mortality and poor outcome occurred in 4.3% and 9.7% of patients in Wuhan, compared to 34.1% and 42.9% of patients in London. Models based on age, sex and simple routinely available laboratory tests (lymphocyte count, neutrophil count, platelet count, CRP and creatinine) had good discrimination and calibration in internal validation, but performed only moderately well in external validation. Models based on age, sex, symptoms and comorbidity were adequate in internal validation for poor outcome (ICU admission or death) but had poor performance for death alone. Implications of all the available evidenceThis study and others find that relatively simple risk prediction models using demographic, clinical and laboratory data perform well in internal validation but at best moderately in external validation, either because derivation and external validation populations are small (Xie et al3) and/or because they vary greatly in casemix and severity (our study). There are three decision points where risk prediction may be most useful: (1) deciding who to test; (2) deciding which patients in the community are at high-risk of poor outcomes; and (3) identifying patients at high-risk at the point of hospital admission. Larger studies focusing on particular decision points, with rapid external validation in multiple datasets are needed. A key gap is risk prediction tools for use in community triage (decisions to admit, or to keep at home with varying intensities of follow-up including telemonitoring) or in low income settings where laboratory tests may not be routinely available at the point of decision-making. This requires systematic data collection in community and low-income settings to derive and evaluate appropriate models.
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BackgroundThe National Early Warning Score (NEWS2) is currently recommended in the United Kingdom for risk stratification of COVID outcomes, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for severe COVID outcome and identify and validate a set of routinely-collected blood and physiological parameters taken at hospital admission to improve the score. MethodsTraining cohorts comprised 1276 patients admitted to Kings College Hospital NHS Foundation Trust with COVID-19 disease from 1st March to 30th April 2020. External validation cohorts included 5037 patients from four UK NHS Trusts (Guys and St Thomas Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID disease (transfer to intensive care unit or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. ResultsA baseline model of NEWS2 + age had poor-to-moderate discrimination for severe COVID infection at 14 days (AUC in training sample = 0.700; 95% CI: 0.680, 0.722; Brier score = 0.192; 95% CI: 0.186, 0.197). A supplemented model adding eight routinely-collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI: 0.715, 0.757) and these improvements were replicated across five UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. ConclusionsNEWS2 score had poor-to-moderate discrimination for medium-term COVID outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID. KO_SCPLOWEYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWMESSAGESC_SCPLOWO_LIThe National Early Warning Score (NEWS2), currently recommended for stratification of severe COVID-19 disease in the UK, showed poor-to-moderate discrimination for medium-term outcomes (14-day transfer to ICU or death) among COVID-19 patients. C_LIO_LIRisk stratification was improved by the addition of routinely-measured blood and physiological parameters routinely at hospital admission (supplemental oxygen, urea, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) which provided moderate improvements in a risk stratification model for 14-day ICU/death. C_LIO_LIThis improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites. C_LIO_LIWe benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches. C_LI
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A novel coronavirus pneumonia (NCP) epidemic has occurred in Wuhan, Hubei Province since December 2019, caused by a novel coronavirus (2019-nCoV) never been seen previously in human. China has imposed the strictest quarantine and closed management measures in history to control the spreading of the disease. However, severe trauma can still occur in the NCP patients. In order to standardize the emergency treatment and the infection prevention and control of severe trauma patients with hidden infection, suspected or confirmed infection of 2019-nCoV, Trauma Surgery Branch of Chinese Medical Doctors' Association organized this expert consensus. The consensus illustrated the classification of the NCP patients, severe trauma patients in need of emergency surgery, emergency surgery type, hierarchical protection for medical personnel and treatment places. Meanwhile, the consensus standardized the screening, injury severity evaluation, emergency surgical treatment strategy and postoperative management strategy of severe trauma patients during the epidemic period of NCP, providing a basis for the clinical treatment of such kind of patients.
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Epidemic of corona virus disease 2019 (COVID-19) has occurred in Wuhan, Hubei Province since December 2019, caused by a novel coronavirus (2019-nCoV) never been seen previously in human. China has imposed the strictest quarantine and closed management measures in history to control the spreading of the disease. However, severe trauma can still occur in the COVID-19 patients. In order to standardize the emergency treatment and the infection prevention and control of severe trauma patients with hidden infection, suspected or confirmed infection of 2019-nCoV, Trauma Surgery Branch of Chinese Medical Doctors' Association organized this expert consensus. The consensus illustrated the classification of the COVID-19 patients, severe trauma patients in need of emergency surgery, emergency surgery type, hierarchical protection for medical personnel and treatment places. Meanwhile, the consensus standardized the screening, injury severity evaluation, emergency surgical treatment strategy and postoperative management strategy of severe trauma patients during the epidemic period of COVID-19, providing a basis for the clinical treatment of such kind of patients.
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Objective@#To construct and identify a mouse model with conditional knockout (cKO) of p75 neurotrophin receptor (p75NTR-cKO) gene in epidermis cells by Cre-loxP system.@*Methods@#Five p75NTRflox/flox transgenic C57BL/6J mice (aged 6-8 weeks, male and female unlimited, the age and sex of mice used for reproduction were the same below) and five keratin 14 promotor-driven (KRT14-) Cre+ /- transgenic C57BL/6J mice were bred and hybridized via Cre-loxP system. Five p75NTRflox/+ ·KRT14-Cre+ /- mice selected from the first generation of mice were mated with five p75NTRflox/flox mice to obtain the second generation hybrids. After the second generation mice were born 20-25 days, the parts of the mice tail were cut off to identify the genotype by polymerase chain reaction method. Four p75NTR gene complete cKO mice (6 weeks old) and 4 wild-type mice (6 weeks old) were selected and sacrificed respectively. The abdominal skin tissue and brain tissue were excised to observe the expression of p75NTR in the two tissue of two types of mice by immunohistochemical staining. The abdominal skin tissue of two types of mice was obtained to observe the histomorphological changes by hematoxylin and eosin staining.@*Results@#(1) Twenty second generation mice were bred. The genotype of 4 mice was p75NTRflox/flox·KRT14-Cre+ /-(p75NTR-/-), i. e. p75NTR gene complete cKO mice; the genotype of 5 mice was p75NTRflox/+ ·KRT14-Cre+ /-, i. e. p75NTR gene partial cKO mice; the genotype of 5 mice was p75NTRflox/flox·KRT14-Cre-/-, and that of 6 mice was p75NTRflox/+ ·KRT14-Cre-/-, all of which were wild-type mice. (2) The expression of p75NTR was negative in skin epidermis tissue of p75NTR gene complete cKO mice, while numerous p75NTR positive expression was observed in skin epidermis tissue of wild-type mice. Abundant p75NTR positive expression was observed in brain tissue of both wild-type mice and p75NTR gene complete cKO mice. (3) There was no abnormal growth of skin epidermis tissue in both wild-type mice and p75NTR gene complete cKO mice, with intact hair follicle structure.@*Conclusions@#Applying Cre-loxP system can successfully construct a p75NTR-cKO mice model in epidermis cells without obvious changes in skin histomorphology.
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BACKGROUND: This meta-analysis was conducted to investigate the diagnostic performance of P16INK4a gene promoter methylation as a biomarker of non-small cell lung cancer (NSCLC). METHODS: Two reviewers independently searched the Web of Science, PubMed, Cochrane, Embase, China National Knowledge Infrastructure, and Chinese Biomedical Literature databases. Publications relevant to P16INK4a gene promoter methylation in serum or bronchoalveolar fluid/sputum were screened and included in this meta-analysis. Pooled diagnostic sensitivity, specificity, and symmetric receiver operating characteristic curve were calculated. RESULTS: Twenty-six publications with 1768 lung cancer cases and 1323 controls were included. The pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were 0.46 (95% confidence interval [CI] 0.43-0.48), 0.90 (95% CI 0.88-0.91), 6.33 (95% CI 3.89-10.30), 0.57 (95% CI 0.50-0.65) and 10.72 (95% CI 6.94-16.56), respectively, for P16INK4a gene promoter methylation as a biomarker for the diagnosis of NSCLC. The area under the symmetric receiver operating characteristic curve was 0.75 with a standard error of 0.004. No publication bias was detected via line regression test (t = 0.95; P = 0.35) and Begg's funnel plot. CONCLUSION: P16INK4a gene promoter methylation detection in serum or bronchoalveolar fluid/sputum may be a potential biomarker for NSCLC diagnosis; however, the sensitivity was relatively low, which is not suitable for NSCLC screening.
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Carcinoma de Pulmón de Células no Pequeñas/diagnóstico , Inhibidor p16 de la Quinasa Dependiente de Ciclina/genética , Metilación de ADN , Neoplasias Pulmonares/diagnóstico , Biomarcadores de Tumor/sangre , Biomarcadores de Tumor/genética , Líquido del Lavado Bronquioalveolar/química , Carcinoma de Pulmón de Células no Pequeñas/genética , Inhibidor p16 de la Quinasa Dependiente de Ciclina/sangre , Detección Precoz del Cáncer , Humanos , Neoplasias Pulmonares/genética , Regiones Promotoras Genéticas , Curva ROC , Sensibilidad y Especificidad , Esputo/químicaRESUMEN
Objective To evaluate the application value of absorbable hemostat textile as submucosal injection of endoscopic submucosal dissection(ESD). Methods Twelve New Zealand rabbits were injected with absorbable hemostat textile solution,glycerol fructose and normal saline. The uplift effect was measured after injection. Simulated ESD was performed in the rabbit stomach and bleeding amount was measured. The injection site was pathologically examined at 30 minutes after the soluble hemostat textile and normal saline were injected. Fifteen pigs were injected with absorbable hemostat textile at two locations of 20-30 cm from the anus,and injected normal saline at another two locations of 20-30 cm from the anus.One site was performed simulated ESD and the other was not. Fifteen simulated ESD were performed in the soluble hemostatic group and the normal saline group, respectively. Operation time was recorded and difference in wound healing was compared between the two groups. Results In the uplift experiment, the absorbable hemostat textile group had higher uplift height(4.3±1.4 mm,4.1±1.9 mm,3.8±0.7 mm, 3.3±0.9 mm, respectively)at 0 min,10 min,20 min,30 min than that of the glycerol fructose group(4.3±2.2 mm,4.1± 2.0 mm,3.6±1.4 mm, 3.2±0.8 mm, respectively, P<0.05), and the glycerol fructose group was higher than that of the normal saline group(3.8±1.6 mm,2.6±1.4 mm,1.9±1.9 mm,1.1±0.7 mm, P<0.05). There was no significant difference in uplift height between the absorbable hemostat textile group and the glycerol fructose group(P>0.05). In the bleeding experiment, the bleeding amount of absorbable hemostat textile group was significantly less than that of the glycerol fructose group(0.36±0.07 mL VS 0.42±0.06 mL, P<0.05);the bleeding amount of glycerol fructose group was significantly lower than that of the normal saline group(0.42±0.06 mL VS 0.55±0.07 mL,P<0.05). There was no obvious tissue necrosis and other adverse complications in the absorbable hemostat textile group and the normal saline group. In simulated ESD experiment,complete resection rate of the absorbable hemostat textile group was higher than that of the normal saline group[86.7%(13/15)VS 46.7%(7/15), P<0.05], and mean operation time of the absorbable hemostat textile group was less than that of the normal saline group(3.2± 0.3 min VS 3.8± 0.5 min, P<0.05). No hemorrhage, perforations or other related adverse events occurred in non-ESD lesions. Conclusion Absorbable hemostat textile is safe and effective as submucosal injection of ESD.
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Objective To investigate the clinical value of hemostatic silk in prevention of wound bleeding and wound healing after endoscopic submucosal dissection (ESD). Methods Experiment group: animal model was made by rabbit underwent ESD simulation in its' stomach and laying hemostatic silk on its' wound;control group: animal model was made by pig underwent ESD simulation in its' colon without any healing management. All the ulcers sites were endoscopically and pathologically examined to evaluate the hemorrhage and healing of the wound on 3 days, 1 week, 2 weeks and 4 weeks after the procedure. Results The blood loss in experiment group was significantly lower than that in control group. The wounds of all the experimental pigs underwent colon ESD successfully covered with hemostatic silk postoperatively. Endoscopic pathological examination shown better healing procedure in experiment group. No procedure-related adverse event occurred in both groups. Conclusions Hemostatic silk has potential application value in healing the wound after ESD demonstrated by animal experiment.