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BACKGROUND: A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, describe, and appraise AI-Ms of CVD prediction in the general and special populations and develop a new independent validation score (IVS) for AI-Ms replicability evaluation. METHODS: PubMed, Web of Science, Embase, and IEEE library were searched up to July 2021. Data extraction and analysis were performed for the populations, distribution, predictors, algorithms, etc. The risk of bias was evaluated with the prediction risk of bias assessment tool (PROBAST). Subsequently, we designed IVS for model replicability evaluation with five steps in five items, including transparency of algorithms, performance of models, feasibility of reproduction, risk of reproduction, and clinical implication, respectively. The review is registered in PROSPERO (No. CRD42021271789). RESULTS: In 20,887 screened references, 79 articles (82.5% in 2017-2021) were included, which contained 114 datasets (67 in Europe and North America, but 0 in Africa). We identified 486 AI-Ms, of which the majority were in development (n = 380), but none of them had undergone independent external validation. A total of 66 idiographic algorithms were found; however, 36.4% were used only once and only 39.4% over three times. A large number of different predictors (range 5-52,000, median 21) and large-span sample size (range 80-3,660,000, median 4466) were observed. All models were at high risk of bias according to PROBAST, primarily due to the incorrect use of statistical methods. IVS analysis confirmed only 10 models as "recommended"; however, 281 and 187 were "not recommended" and "warning," respectively. CONCLUSION: AI has led the digital revolution in the field of CVD prediction, but is still in the early stage of development as the defects of research design, report, and evaluation systems. The IVS we developed may contribute to independent external validation and the development of this field.
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Inteligencia Artificial , Enfermedades Cardiovasculares , Humanos , Enfermedades Cardiovasculares/diagnóstico , Medición de Riesgo/métodos , Tamizaje Masivo/métodos , Reproducibilidad de los ResultadosRESUMEN
In recent years, there has been explosive development in artificial intelligence (AI), which has been widely applied in the health care field. As a typical AI technology, machine learning models have emerged with great potential in predicting cardiovascular diseases by leveraging large amounts of medical data for training and optimization, which are expected to play a crucial role in reducing the incidence and mortality rates of cardiovascular diseases. Although the field has become a research hot spot, there are still many pitfalls that researchers need to pay close attention to. These pitfalls may affect the predictive performance, credibility, reliability, and reproducibility of the studied models, ultimately reducing the value of the research and affecting the prospects for clinical application. Therefore, identifying and avoiding these pitfalls is a crucial task before implementing the research. However, there is currently a lack of a comprehensive summary on this topic. This viewpoint aims to analyze the existing problems in terms of data quality, data set characteristics, model design, and statistical methods, as well as clinical implications, and provide possible solutions to these problems, such as gathering objective data, improving training, repeating measurements, increasing sample size, preventing overfitting using statistical methods, using specific AI algorithms to address targeted issues, standardizing outcomes and evaluation criteria, and enhancing fairness and replicability, with the goal of offering reference and assistance to researchers, algorithm developers, policy makers, and clinical practitioners.
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Enfermedades Cardiovasculares , Aprendizaje Automático , Humanos , Reproducibilidad de los Resultados , AlgoritmosRESUMEN
The present study developed an ultra-fast liquid chromatography coupled with triple quadrupole-linear ion trap composite mass spectrometry(UHPLC-QTRAP-MS) to simultaneously determine the content of potential active components in Scutellariae Barbatae Herba and also to provide a reference approach for screening out the differential quality control components among different batches of Scutellariae Barbatae Herba. Chromatographic separations were conducted on a Thermo Acclaim~(TM) RSLC 120 C_(18) column(3.0 mm×100 mm, 2.2 µm) in a gradient program. The mobile phase consisted of 0.1% aqueous formic acid and acetonitrile, and the column temperature was maintained at 40 â. The flow rate was 0.4 mL·min~(-1) and the injection volume was 2 µL. The targeted compounds were monitored in the multiple reaction monitoring(MRM) mode. The acquired data were processed by hierarchical cluster analysis(HCA) and partial least square discriminant analysis(PLS-DA). Sixteen compounds all showed good linear relationship within the corresponding linear ranges and the R~2 values were all higher than 0.993 2. The RSDs of precision, repeatability, and stability were less than or equal to 3.7%. Mean recovery rates were in the range of 95.67% and 104.8% with RSDs≤3.2%. According to HCA and PLS-DA, all samples were clustered into four categories. Scutellarin, acteoside, scutellarein, and scutebarbatine X(VIP>1) were considered as differential chemical markers in the four categories. In conclusion, the developed method can be used for the simulta-neous determination of the multiple components and quality control of Scutellariae Barbatae Herba.
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Scutellaria , Espectrometría de Masas en Tándem , Quimiometría , Cromatografía Líquida de Alta Presión/métodos , Cromatografía Liquida , Espectrometría de Masas en Tándem/métodosRESUMEN
BACKGROUND: Coronavirus disease 2019 (COVID-19) is a new respiratory and systemic disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The purpose of the present study was to investigate the association between cytokine profiles and lung injury in COVID-19 pneumonia. METHODS: This retrospective study was conducted in COVID-19 patients. Demographic characteristics, symptoms, signs, underlying diseases, and laboratory data were collected. The patients were divided into COVID-19 with pneumonia and without pneumonia. CT severity score and PaO2/FiO2 ratio were used to assess lung injury. RESULTS: 106 patients with 12 COVID-19 without pneumonia and 94 COVID-19 with pneumonia were included. Compared with COVID-19 without pneumonia, COVID-19 with pneumonia had significantly higher serum interleukin (IL)-2R, IL-6, and tumor necrosis factor (TNF)-α. Correlation analysis showed that CT severity score and PaO2/FiO2 were significantly correlated with age, presence of any coexisting disorder, lymphocyte count, procalcitonin, IL-2R, and IL-6. In multivariate analysis, log IL6 was the only independent explanatory variables for CT severity score (ß = 0.397, p < 0.001) and PaO2/FiO2 (ß = - 0.434, p = 0.003). CONCLUSIONS: Elevation of circulating cytokines was significantly associated with presence of pneumonia in COVID-19 and the severity of lung injury in COVID-19 pneumonia. Circulating IL-6 independently predicted the severity of lung injury in COVID-19 pneumonia.
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Betacoronavirus , Infecciones por Coronavirus/complicaciones , Citocinas/sangre , Lesión Pulmonar/etiología , Neumonía Viral/complicaciones , Adulto , Biomarcadores/sangre , COVID-19 , Infecciones por Coronavirus/sangre , Infecciones por Coronavirus/epidemiología , Femenino , Humanos , Lesión Pulmonar/sangre , Lesión Pulmonar/diagnóstico , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/sangre , Neumonía Viral/diagnóstico , Neumonía Viral/epidemiología , Estudios Retrospectivos , SARS-CoV-2 , Tomografía Computarizada por Rayos XRESUMEN
INTRODUCTION: Colorectal cancer (CRC) is a clinically heterogeneous disease, which necessitates a variety of treatments and leads to different outcomes. Only some CRC patients will benefit from neoadjuvant chemotherapy (NACT). OBJECTIVES: An accurate prediction of response to NACT in CRC patients would greatly facilitate optimal personalized management, which could improve their long-term survival and clinical outcomes. METHODS: In this study, plasma metabolite profiling was performed to identify potential biomarker candidates that can predict response to NACT for CRC. Metabolic profiles of plasma from non-response (n = 30) and response (n = 27) patients to NACT were studied using UHPLC-quadruple time-of-flight)/mass spectrometry analyses and statistical analysis methods. RESULTS: The concentrations of nine metabolites were significantly different when comparing response to NACT. The area under the receiver operating characteristic curve value of the potential biomarkers was up to 0.83 discriminating the non-response and response group to NACT, superior to the clinical parameters (carcinoembryonic antigen and carbohydrate antigen 199). CONCLUSION: These results show promise for larger studies that could result in more personalized treatment protocols for CRC patients.
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Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Neoplasias Colorrectales/tratamiento farmacológico , Neoplasias Colorrectales/metabolismo , Metabolómica , Biomarcadores de Tumor/sangre , Cromatografía Líquida de Alta Presión , Neoplasias Colorrectales/sangre , Femenino , Humanos , Masculino , Espectrometría de Masas , Persona de Mediana Edad , Terapia NeoadyuvanteRESUMEN
OBJECTIVE: Powerful adjuvant strategies are required to improve the survival of patients with completely resected stage ΙΙΙA non-small cell lung cancer (NSCLC). We aimed to compare the efficacy of traditional Chinese medicine (TCM) treatment versus observation after adjuvant chemotherapy in these patients. METHODS: Eligible patients were randomized 1:1 to receive either oral decoctions based on Qi-Yin syndrome differentiation (TCM group) or observation (observation group). The intervention lasted for 12 months. The primary endpoint was 1-year disease-free survival (DFS). Secondary endpoints were DFS, quality of life, regulatory T cells (Tregs), and cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) on the surface of Tregs in peripheral blood. We used EORTC QLQ-LC43 to evaluate quality of life. RESULTS: Between Apr 29, 2019, and Nov 11, 2021, 75 patients were randomly assigned to oral decoctions based on Qi-Yin syndrome differentiation (n = 38) or observation (n = 37). The full analysis set included 35 patients in the TCM group and 35 in the observation group. After a median follow-up of 24.2 months, oral decoctions based on Qi-Yin syndrome differentiation improved DFS compared with observation (HR 0.378, 95% CI: 0.157-0.912; P = .03). One-year DFS was 82.1% in the TCM group and 61.9% in the observation group (P = .06). Three months after randomization, scores of total health, role function, emotional function, and social function in the TCM group were higher than those in the observation group (P < .01 for all), scores of fatigue, pain, insomnia, appetite loss, constipation, cough, and chest pain were lower than those in the observation group (P < .05 for all); there was no significant difference in the proportion of Tregs between the TCM group and the observation group (P = .58); the proportion of CTLA-4+Tregs in the TCM group was lower than that in the observation group (P = .046). There were no adverse events that occurred in both groups. CONCLUSIONS: Oral decoctions based on Qi-Yin syndrome differentiation after adjuvant chemotherapy prolonged DFS, reduced the risk of disease recurrence and metastasis, improved quality of life, and down-regulated the proportion of CTLA-4+Tregs in completely resected stage ΙΙΙA NSCLC patients. TRIAL REGISTRATION: Chinese Clinical Trial Register, No. ChiCTR1800019396. Date of registration: 9 November 2018.
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Carcinoma de Pulmón de Células no Pequeñas , Medicamentos Herbarios Chinos , Neoplasias Pulmonares , Medicina Tradicional China , Calidad de Vida , Humanos , Masculino , Femenino , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Carcinoma de Pulmón de Células no Pequeñas/patología , Persona de Mediana Edad , Neoplasias Pulmonares/tratamiento farmacológico , Neoplasias Pulmonares/cirugía , Medicamentos Herbarios Chinos/farmacología , Medicamentos Herbarios Chinos/uso terapéutico , Quimioterapia Adyuvante/métodos , Medicina Tradicional China/métodos , Anciano , Qi , Estadificación de Neoplasias , Supervivencia sin EnfermedadRESUMEN
Quinoa saponins have outstanding activity, and there are an increasing number of extraction methods, but there are few research programs on green preparation technology. The extraction conditions of quinoa saponins with deep eutectic solvents (DESs) were optimized by single-factor experiments combined with response surface methodology. The antioxidant capacity of saponins extracted by DESs and traditional methods was evaluated by the DPPH clearance rate, iron ion chelation rate and potassium ferricyanide reducing power. The results show that the optimal DES is choline chloride: 1,2-propylene glycol (1 : 1), and its water content is 40%. The optimal extraction conditions were as follows: the solid-to-solvent ratio was 0.05 g mL-1, the extraction time was 89 min, and the extraction temperature was 75 °C. Under these conditions, the extraction of quinoa saponins by DES was more effective than the traditional extraction methods. The saponins extracted by DES and traditional methods were analyzed by UPLC-MS, and five main saponins were identified. Quantitative analysis by HPLC-UV showed that Q1 (m/z = 971) and Q2 (m/z = 809) had higher contents of saponins. In vitro antioxidant experiments showed that all DES saponin extracts showed good antioxidant capacity. This study provides new insight into the development and utilization of quinoa saponins.
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BACKGROUND: This study aimed to explore the significance of neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH), D-dimer, and CT score in evaluating the severity and prognosis of coronavirus disease 2019 (COVID-19). METHODS: Patients with laboratory-confirmed COVID-19 were retrospectively enrolled. The baseline data, laboratory findings, chest computed tomography (CT) results evaluated by CT score on admission, and clinical outcomes were collected and compared. Logistic regression was used to assess the independent relationship between the baseline level of the four indicators (NLR, LDH, D-dimer, and CT score) and the severity of COVID-19. RESULTS: Among the 432 patients, 125 (28.94%) and 307 (71.06%) were placed in the severe and non-severe groups, respectively. As per the multivariate logistic regression, high levels of NLR and LDH were independent predictors of severe COVID-19 (OR=2.163; 95% CI=1.162-4.026; p=0.015 for NLR>3.82; OR=2.298; 95% CI=1.327-3.979; p=0.003 for LDH>246 U/L). Combined NLR>3.82 and LDH>246 U/L increased the sensitivity of diagnosis in patients with severe disease (NLR>3.82 [50.40%] vs. combined diagnosis [72.80%]; p=0.0007; LDH>246 [59.2%] vs. combined diagnosis [72.80%]; p<0.0001). CONCLUSIONS: High levels of serum NLR and LDH have potential value in the early identification of patients with severe COVID-19. Moreover, the combination of LDH and NLR can improve the sensitivity of diagnosis.
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COVID-19/sangre , COVID-19/diagnóstico por imagen , Productos de Degradación de Fibrina-Fibrinógeno/metabolismo , L-Lactato Deshidrogenasa/sangre , Linfocitos/patología , Neutrófilos/patología , Tomografía Computarizada por Rayos X , Femenino , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Análisis Multivariante , Pronóstico , Curva ROCRESUMEN
PURPOSE: Since the outbreak in late December 2019 in Wuhan, China, coronavirus disease-2019 (COVID-19) has become a global pandemic. We analyzed and compared the clinical, laboratory, and radiological characteristics between survivors and non-survivors and identify risk factors for mortality. METHODS: Clinical and laboratory variables, radiological features, treatment approach, and complications were retrospectively collected in two centers of Hubei province, China. Cox regression analysis was conducted to identify the risk factors for mortality. RESULTS: A total of 432 patients were enrolled, and the median patient age was 54 years. The overall mortality rate was 5.09% (22/432). As compared with the survivor group (n = 410), those in the non-survivor group (n = 22) were older, and they had a higher frequency of comorbidities and were more prone to suffer from dyspnea. Several abnormal laboratory variables indicated that acute cardiac injury, hepatic damage, and acute renal insufficiency were detected in the non-survivor group. Non-surviving patients also had a high computed tomography (CT) score and higher rate of consolidation. The most common complication causing death was acute respiratory distress syndrome (ARDS) (18/22, 81.8%). Multivariate Cox regression analysis revealed that hemoglobin (Hb) <90 g/L (hazard ratio, 10.776; 95% confidence interval, 3.075-37.766; p<0.0001), creatine kinase (CK-MB) >8 U/L (9.155; 2.424-34.584; p = 0.001), lactate dehydrogenase (LDH) >245 U/L (5.963; 2.029-17.529; p = 0.001), procalcitonin (PCT) >0.5 ng/ml (7.080; 1.671-29.992; p = 0.008), and CT score >10 (39.503; 12.430-125.539; p<0.0001) were independent risk factors for the mortality of COVID-19. CONCLUSIONS: Low Hb, high LDH, PCT, and CT score on admission were the predictors for mortality and could assist clinicians in early identification of poor prognosis among COVID-19 patients.
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COVID-19/epidemiología , Adulto , Anciano , Causas de Muerte , China/epidemiología , Comorbilidad , Brotes de Enfermedades , Femenino , Hospitalización , Humanos , Masculino , Persona de Mediana Edad , Pandemias , Pronóstico , Estudios Retrospectivos , Factores de Riesgo , SARS-CoV-2/aislamiento & purificaciónRESUMEN
Major histocompatibility complex (MHC) II deficiency is a rare primary immunodeficiency disorder that is characterized by the deficiency of MHC class II molecules. The disease is caused by transcription factor mutations including class II transactivator (CIITA), regulatory factor X-5 (RFX5), RFX-associated protein (RFXAP), and RFXAP-containing ankyrin repeat (RFXANK), respectively. Mutations in the RFXANK gene account for >70% of all known patients worldwide. Herein, we reported a 10-month-old boy with MHC II deficiency caused by a novel mutation in the RFXANK gene (c.337 + 1G>C). The boy was admitted to the hospital due to pneumonia and diarrhea at 4 months of age. Genetic analysis revealed a novel homozygous mutation in the RFXANK gene, which derived from the c.337 + 1G>C heterozygous mutations in the RFXANK gene of his parents. The boy died 3 months after diagnosis. More than 200 cases have been reported, and a review of the literature revealed different mutation rates of 4 transcription factors in different countries or regions. This is the first case report of MHC II deficiency from East Asia. We also describe all gene mutations that cause MHC II deficiency and the epidemiology of MHC II deficiency with gene mutations in this paper.
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BACKGROUND: Despite its rarity, studies have shown the incidence of gastric neuroendocrine tumors (G-NETs) is increasing. This study investigated the risk factors affecting the survival of G-NETs patients and their prognosis over time. METHOD: A retrospective analysis of 506 G-NETs patients who underwent surgery for nonmetastatic disease from the Surveillance, Epidemiology and End Result database from 1988 to 2011 was conducted. Multivariate Cox regression analyses identified the prognostic factors affecting overall survival (OS) and disease-specific survival (DSS). Three-year conditional survival (COS3 and CDS3) estimates at "x" year after treatment were calculated as follows: COS3 = OS(x + 3)/OS(x) and CDS3 = DSS(x + 3)/DSS(x). RESULTS: The 1-, 3-, and 5-year OS rates of all patients after surgery were 90.2%, 77.3%, and 68.8%, respectively. The 1-, 3-, and 5-year DSS rates after surgery were 93.9%, 84.5%, and 80.9%, respectively. In the multivariate analysis, age, tumor grade, and T stage were independent prognostic factors of OS and DSS (all P < 0.05). With 1-, 3-, and 5-year survivorship, the COS3 improved by +5.2 (82.2%), +7.2 (84.4%), and +8.5 (85.5%), respectively, and the CDS3 improved by +4.4 (89.4%), +9.1 (94.1%), and +12.5 (97.5%), respectively. Notably, the CDS3 improved dramatically among patients with advanced stage disease (eg, N0 stage: 93.0%-98.9%, Δ5.9% vs N1 stage: 52.0%-95.7%, Δ43.7%). CONCLUSION: For G-NETs patients, age, tumor grade, T stage, and N stage were the clinicopathological factors significantly associated with prognosis. There were excellent outcomes for most G-NETs patients, with a CDS3 of greater than 90% across all independent prognostic factors after 5 years of survival.