RESUMEN

Percutaneous coronary intervention (PCI) has become a vital treatment approach for coronary artery disease, but the clinical data of PCI cannot be directly utilized due to its unstructured characteristics. The existing clinical named entity recognition (CNER) has been used to identify specific entities such as body parts, drugs, and diseases, but its specific potential in PCI clinical texts remains largely unexplored. How to effectively use CNER to deeply mine the information in the existing PCI clinical records is worth studying. In this paper, a total of 24 267 corpora are collected from the Cardiovascular Disease Treatment Center of the People's Hospital of Liaoning Province in China. We select three types of clinical record texts of fine-grained PCI surgical information, from which 5.8% of representative surgical records of PCI patients are selected as datasets for labeling. To fully utilize global information and multi-level semantic features, we design a novel character-level vector embedding method and further propose a new hybrid model based on it. Based on the classic Bidirectional Long Short-Term Memory Network (BiLSTM), the model further integrates Convolutional Neural Networks (CNNs) and Bidirectional Encoder Representations from Transformers (BERTs) for feature extraction and representation, and finally uses Conditional Random Field (CRF) for decoding and predicting label sequences. This hybrid model is referred to as BCC-BiLSTM in this paper. In order to verify the performance of the proposed hybrid model for extracting PCI surgical information, we simultaneously compare both representative traditional and intelligent methods. Under the same circumstances, compared with other intelligent methods, the BCC-BiLSTM proposed in this paper reduces the word vector dimension by 15%, and the F1 score reaches 86.2% in named entity recognition of PCI clinical texts, which is 26.4% higher than that of HMM. The improvement is 1.2% higher than BiLSTM + CRF and 0.7% higher than the most popular BERT + BiLSTM + CRF. Compared with the representative models, the hybrid model has better performance and can achieve optimal results faster in the model training process, so it has good clinical application prospects.

Asunto(s)

Redes Neurales de la Computación , Intervención Coronaria Percutánea , Humanos , Enfermedad de la Arteria Coronaria

RESUMEN

With the widespread adoption of electronic health records, the amount of stored medical data has been increasing. Clinical data, often in the form of semi-structured or unstructured electronic medical records (EMRs), contains rich patient information. However, due to the use of natural language by physicians when composing these records, the effectiveness of traditional methods such as dictionaries, rule matching, and machine learning in the extraction of information from these unstructured texts falls short of clinical standards. In this paper, a novel deep-learning-based natural language extraction method is proposed to overcome current shortcomings in data governance and Gensini score automatic calculation in coronary angiography. A pre-trained model called bidirectional encoder representation from transformers (BERT) with strong text feature representation capabilities is employed as the feature representation layer. It is combined with bidirectional long short-term memory (BiLSTM) and conditional random field (CRF) models to extract both global and local features from the text. The study included an evaluation of the model on a dataset from a hospital in China and it was compared with another model to validate its practical advantages. Hence, the BiLSTM-CRF model was employed to automatically extract relevant coronary angiogram information from EMR texts. The achieved F1 score was 91.19, which is approximately 0.87 higher than the BERT-BiLSTM-CRF model.

Asunto(s)

Aprendizaje Profundo , Humanos , Angiografía Coronaria , Procesamiento de Lenguaje Natural , Lenguaje , Aprendizaje Automático

RESUMEN

Machine learning provides increasingly reliable assistance for medical experts in diagnosing coronary heart disease. This study proposes a deep learning hybrid model based coronary heart disease (CAD) prediction method, which can significantly improve the prediction accuracy compared to traditional solutions. This research scheme is based on the data of 7291 patients and proposes a hybrid model, which uses two different deep neural network models and a recurrent neural network model as the main model for training. The prediction results based on the main model training use a k-nearest neighbor model for secondary training so as to improve the accuracy of coronary heart disease prediction. The comparison between the model prediction results and the clinical diagnostic results shows that the prediction model has a prediction accuracy rate of 82.8%, a prediction precision rate of 87.08%, a prediction recall rate of 88.57%, a prediction F1-score of 87.82%, and an area under the curve value of 0.8 in the test set. Compared to single model machine learning predictions, the hybrid model has a significantly improved accuracy and has effectively solved the problem of overfitting. A deep learning based CAD prediction hybrid model that combines multiple weak models into a strong model can fully explore the complex inter-relationships between various features under limited feature values and sample size, improve the evaluation indicators of the prediction model, and provide effective auxiliary support for CAD diagnosis.

Asunto(s)

Enfermedad Coronaria , Aprendizaje Profundo , Humanos , Enfermedad Coronaria/diagnóstico , Aprendizaje Automático , Redes Neurales de la Computación

RESUMEN

The data input process for most chest pain centers is not intelligent, requiring a lot of staff to manually input patient information. This leads to problems such as long processing times, high potential for errors, an inability to access patient data in a timely manner and an increasing workload. To address the challenge, an Internet of Things (IoT)-driven chest pain center is designed, which crosses the sensing layer, network layer and application layer. The system enables the construction of intelligent chest pain management through a pre-hospital app, Ultra-Wideband (UWB) positioning, and in-hospital treatment. The pre-hospital app is provided to emergency medical services (EMS) centers, which allows them to record patient information in advance and keep it synchronized with the hospital's database, reducing the time needed for treatment. UWB positioning obtains the patient's hospital information through the zero-dimensional base station and the corresponding calculation engine, and in-hospital treatment involves automatic acquisition of patient information through web and mobile applications. The system also introduces the Bidirectional Long Short-Term Memory (BiLSTM)-Conditional Random Field (CRF)-based algorithm to train electronic medical record information for chest pain patients, extracting the patient's chest pain clinical symptoms. The resulting data are saved in the chest pain patient database and uploaded to the national chest pain center. The system has been used in Liaoning Provincial People's Hospital, and its subsequent assistance to doctors and nurses in collaborative treatment, data feedback and analysis is of great significance.

Asunto(s)

Aprendizaje Profundo , Internet de las Cosas , Humanos , Clínicas de Dolor , Dolor en el Pecho/terapia , Internet

RESUMEN

Computed tomography angiography (CTA) has become the main imaging technique for cardiovascular diseases. Before performing the transcatheter aortic valve intervention operation, segmenting images of the aortic sinus and nearby cardiovascular tissue from enhanced images of the human heart is essential for auxiliary diagnosis and guiding doctors to make treatment plans. This paper proposes a nnU-Net (no-new-Net) framework based on deep learning (DL) methods to segment the aorta and the heart tissue near the aortic valve in cardiac CTA images, and verifies its accuracy and effectiveness. A total of 130 sets of cardiac CTA image data (88 training sets, 22 validation sets, and 20 test sets) of different subjects have been used for the study. The advantage of the nnU-Net model is that it can automatically perform preprocessing and data augmentation according to the input image data, can dynamically adjust the network structure and parameter configuration, and has a high model generalization ability. Experimental results show that the DL method based on nnU-Net can accurately and effectively complete the segmentation task of cardiac aorta and cardiac tissue near the root on the cardiac CTA dataset, and achieves an average Dice similarity coefficient of 0.9698 ± 0.0081. The actual inference segmentation effect basically meets the preoperative needs of the clinic. Using the DL method based on the nnU-Net model solves the problems of low accuracy in threshold segmentation, bad segmentation of organs with fuzzy edges, and poor adaptability to different patients' cardiac CTA images. nnU-Net will become an excellent DL technology in cardiac CTA image segmentation tasks.

Asunto(s)

Enfermedades Cardiovasculares , Aprendizaje Profundo , Humanos , Aorta/diagnóstico por imagen , Corazón , Tomografía Computarizada por Rayos X

RESUMEN

BACKGROUND: The coronary artery hemodynamics are impacted by both the macrocirculation and microcirculation. Whether microcirculation load impact the functional assessment of a coronary artery stenosis is unknown. The purpose of this study is to investigate the effect of porous media of the microcirculation on fractional flow reserve (FFR) in stenotic coronary artery model. METHODS: A three dimensional computational simulation of blood flow in coronary artery symmetric stenotic model was constructed. The computational fluid dynamics (CFD) model was developed with Fluent 16.0. Blood was modeled as a shear thinning, non-Newtonian fluid with the Carreau model. A seepage outlet boundary condition and transient inlet conditions were imposed on the model. Coronary physiologica diagnostic parameter such as pressure, velocity and fractional flow reserve (FFR) were investigated in the model and compared with the microcirculation load (ML) and constant pressure load (PL) condition. RESULTS: The present study showed the different hemodynamics in the ML and PL condition. The pre-stenotic pressure is almost the same in the two model. However the pressure in the post-stenotic artery domain is much lower in the PL model. The fluctuation range of the pressures is much higher in ML model than those in PL model. The velocity flow was more steady and lower in the ML model. For the PL model with 75% artery stenosis the FFR was 0.776, while for the ML model with the same stenosis, the FFR was 0.813. CONCLUSIONS: This study provides evidence that FFR increased in the presentation of ML condition. There is a strong hemodynamic effect of microcirculation on coronary artery stenosis.

Asunto(s)

Simulación por Computador , Estenosis Coronaria/fisiopatología , Vasos Coronarios/fisiopatología , Reserva del Flujo Fraccional Miocárdico , Hemodinámica , Microcirculación , Modelos Cardiovasculares , Humanos

RESUMEN

BACKGROUND: The purpose of this study was to develop a coronary artery disease (CAD) prediction model that optimally estimates the pre-test probability of CAD for patients suspected of CAD. METHODS AND RESULTS: This retrospective, multi-centre study included 7360 consecutive patients (4678 men, 57.87±11.42 years old; 2682 women, 61.60±9.58 years old) who underwent coronary angiography for evaluation of CAD. A prediction model was fitted for diagnosis of CAD with the help of eight significant risk factors including sex, age, smoking status, diabetes, hypertension, dyslipidaemia, serum creatinine and angina. All potential predictors were significantly associated with the presence of CAD. The prevalence of CAD was significantly higher in men than in women. The clinical model gives a relatively accurate prediction of CAD with an area under the curve (AUC) of 0.74 (95% CI, 0.88-0.96; P<0.001). Addition of angina to the prediction model improves the predictive precision of the model. The optimal cut-off for predicting CAD in this model was 0.79 with a sensitivity of 0.658 and a specificity of 0.709. CONCLUSION: A prediction model including age, sex, and cardiovascular risk factors allow for an accurate estimation of the pre-test probability of coronary artery disease in Chinese populations. This algorithm may be useful in making decisions relating to the diagnosis of CAD.

Asunto(s)

Algoritmos , Angiografía Coronaria/métodos , Enfermedad de la Arteria Coronaria/diagnóstico , Medición de Riesgo/métodos , Estudios de Casos y Controles , China/epidemiología , Enfermedad de la Arteria Coronaria/epidemiología , Vasos Coronarios , Femenino , Humanos , Incidencia , Masculino , Persona de Mediana Edad , Curva ROC , Estudios Retrospectivos , Índice de Severidad de la Enfermedad

RESUMEN

OBJECTIVE: To study the relationship of Nε-(carboxymethyl)-lysine level (CML) with microstructure changes of white matter (WM), and cognitive impairment in patients with type 2 diabetes mellitus (T2DM) and to discuss the potential mechanism underlying T2DM-associated cognitive impairment. METHODS: The study was performed in T2DM patients (n=22) with disease course ≥5 years and age ranging from 65 to 75 years old. A control group consisted of 25 sex- and age-matched healthy volunteers. Fractional anisotropy (FA) of several WM regions was analyzed by diffusion tensor imaging scan. Plasma CML levels were measured by enzyme-linked immunosorbent assay, and cognitive function was assessed by Mini-Mental State Examination and Montreal cognitive assessment (MoCA). RESULTS: The total Mini-Mental State Examination score in the patient group (25.72±3.13) was significantly lower than the control group (28.16±2.45) (p<0.05). In addition, the total MoCA score in the patient group (22.15±3.56) was significantly lower than the control group 25.63±4.12) (p<0.01). In the patient group, FA values were significantly decreased in the corpus callosum, cingulate fasciculus, inferior fronto-occipital fasciculus, parietal WM, hippocampus, and temporal lobes relative to corresponding regions of healthy controls (p<0.05). Plasma CML level was negatively correlated with average FA values in the global brain (r=-0.58, p<0.01) and MoCA scores (r=-0.47, p<0.05). CONCLUSIONS: In T2DM, WM microstructure changes occur in older patients, and elevations in CML may play a role in the development of cognitive impairment.

Asunto(s)

Trastornos del Conocimiento/etiología , Diabetes Mellitus Tipo 2/sangre , Diabetes Mellitus Tipo 2/complicaciones , Leucoencefalopatías/etiología , Lisina/análogos & derivados , Anciano , Anisotropía , Estudios de Casos y Controles , Trastornos del Conocimiento/diagnóstico por imagen , Diabetes Mellitus Tipo 2/diagnóstico por imagen , Imagen de Difusión por Resonancia Magnética , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador , Leucoencefalopatías/diagnóstico por imagen , Lisina/sangre , Masculino , Escala del Estado Mental , Pruebas Neuropsicológicas

RESUMEN

BACKGROUND: Impairment of coronary flow reserve (CFR) has been generally demonstrated in diabetic patients and animals with microvascular complications but without obvious obstructive coronary atherosclerosis. There have been few studies investigating CFR in cases of relatively well-controlled therapy. The purpose of this study is to evaluate the effect of treatment with a Sphingosine-1-phosphate (S1P) receptor potent agonist, FTY720, on early diabetic rats in terms of CFR. METHODS AND RESULTS: Male Sprague-Dawley (SD) rats were divided into 3 groups: (1) streptozotocin-uninjected rats (control rats); (2) streptozotocin-injected hyperglycemic rats (diabetic group); and (3) FTY720-fed and streptozotocin-injected hyperglycemic rats. FTY720 (1.25 mg/kg per day orally) was administrated for 9 weeks in SD rats (from 6 weeks old to 15 weeks old). CFR was evaluated by (13)NH3-positron emission tomography. No obvious pathological changes of macrovascular atherosclerosis were observed in each group. Diabetic rats had impaired CFR compared with the control group (1.39±0.26 vs. 1.94±0.24, P<0.05). Treatment with FTY720 for 9 weeks attenuated the heart histological changes and improved CFR in 32% of diabetic rats (1.84±0.36 vs. 1.39±0.26, P<0.05). CONCLUSIONS: In summary, long-term therapy with the Sphingosine-1-phosphate receptor agonist, FTY720, improved CFR by attenuating the heart histological changes, and it might have a beneficial effect on coronary microvascular function in diabetic rats.

Asunto(s)

Circulación Coronaria/efectos de los fármacos , Enfermedad Coronaria/tratamiento farmacológico , Diabetes Mellitus Experimental/fisiopatología , Angiopatías Diabéticas/tratamiento farmacológico , Glicoles de Propileno/uso terapéutico , Receptores de Lisoesfingolípidos/agonistas , Esfingosina/análogos & derivados , Amoníaco , Animales , Glucemia/análisis , Capilares/patología , Moléculas de Adhesión Celular/biosíntesis , Moléculas de Adhesión Celular/genética , Colágeno/biosíntesis , Colágeno/genética , Enfermedad Coronaria/diagnóstico por imagen , Enfermedad Coronaria/fisiopatología , Angiopatías Diabéticas/diagnóstico por imagen , Angiopatías Diabéticas/fisiopatología , Evaluación Preclínica de Medicamentos , Clorhidrato de Fingolimod , Regulación de la Expresión Génica/efectos de los fármacos , Interleucina-6/biosíntesis , Interleucina-6/genética , Lisofosfolípidos , Masculino , Microcirculación/efectos de los fármacos , Miocardio/química , Miocardio/patología , Radioisótopos de Nitrógeno , Tomografía de Emisión de Positrones/métodos , Glicoles de Propileno/farmacología , Ratas , Ratas Sprague-Dawley , Esfingosina/farmacología , Esfingosina/uso terapéutico , Factor de Crecimiento Transformador beta/biosíntesis , Factor de Crecimiento Transformador beta/genética

RESUMEN

BACKGROUND: Stem cells transplanted to the ischemic myocardium usually encounter massive cell death within a few days after transplantation, and hypoxic preconditioning (HPC) is currently used as a strategy to prepare stem cells for increased survival and engraftment in the heart. The purpose of this study is to determine whether Pim-1 kinase mediates any beneficial effects of HPC for human cardiac progenitor cells (CPCs). METHODS AND RESULTS: Human CPCs were isolated from an adult heart auricle and were purified by magnetic-activated cell sorting using c-kit magnetic beads; they were hypoxic preconditioned for 6h. Both Pim-1 and p-Akt were determined. CPCs were assigned to one of the following groups: (1) control (without HPC); (2) HPC; or (3) HPC+I (Pim-1 inhibitor). HPC can promote the survival of CPCs. HPC enhances the expression of Pim-1 kinase in a time-dependent manner, which causes a reduction of proapoptotic elements (cytochrome c and cleaved caspase-3) and the preservation/modulation of important components of the mitochondria (Bcl-2, Bcl-XL and p-Bad), and attenuates mitochondrial damages. All of these protective effects were blocked by a Pim-1 inhibitor. CONCLUSIONS: Pim-1 plays a pivotal role in the protective effect of HPC for CPCs, and the promotion of the expression of Pim-1 in CPCs can as serve part of molecular therapeutic interventional strategies in the treatment of cardiomyopathy damage by blunting CPC death.

Asunto(s)

Precondicionamiento Isquémico Miocárdico , Mitocondrias Cardíacas/metabolismo , Proteínas Musculares/metabolismo , Miocitos Cardíacos/metabolismo , Proteínas Proto-Oncogénicas c-pim-1/metabolismo , Células Madre/metabolismo , Adulto , Apoptosis/efectos de los fármacos , Cardiomiopatías/tratamiento farmacológico , Cardiomiopatías/metabolismo , Cardiomiopatías/patología , Supervivencia Celular/efectos de los fármacos , Femenino , Humanos , Masculino , Mitocondrias Cardíacas/patología , Proteínas Musculares/antagonistas & inhibidores , Miocitos Cardíacos/patología , Inhibidores de Proteínas Quinasas/farmacología , Proteínas Proto-Oncogénicas c-pim-1/antagonistas & inhibidores , Células Madre/patología

RESUMEN

Recent studies have found that cardiac stem cells (CSCs) are present in the adult heart. CSCs play an important role in maintaining the balance of the number of myocardial cells. The purpose of this study was to examine characteristics of human CSCs and their correlation with clinical characteristics of patients. We collected heart auricles of 105 patients (age range, 1-78 years; mean, 55.6 ± 17.0 years) undergoing cardiac surgery to obtain CSCs. We assayed the percentage of c-kit positive (c-kit(+)) CSCs with flow cytometry. Plasma N(ɛ)-(carboxymethyl)lysine (CML) concentrations were measured by enzyme-linked immunosorbent assay. The percentage of c-kit(+) CSCs was 4.96 ± 3.12% (0.98-17.17%), and this was significantly negatively correlated with age, the presence of diabetes mellitus (DM) and coronary heart disease (CHD) (r values were -0.797 [P < 0.01], -0.500 [P < 0.01] and -0.250 [P = 0.011], respectively). The percentage of c-kit(+) CSCs was significantly negatively correlated with CML concentrations (r = -0.859, P < 0.01). The percentage of c-kit(+) CSCs decreases with ageing and is further decreased in patients with DM and/or CHD. Furthermore, plasma CML concentrations may have potential as an indicator of the number of c-kit(+) CSCs.

Asunto(s)

Enfermedad de la Arteria Coronaria/patología , Diabetes Mellitus/patología , Miocardio/citología , Células Madre/fisiología , Adolescente , Adulto , Factores de Edad , Anciano , Células Cultivadas , Niño , Preescolar , Enfermedad de la Arteria Coronaria/cirugía , Complicaciones de la Diabetes/patología , Complicaciones de la Diabetes/cirugía , Citometría de Flujo , Humanos , Lactante , Lisina/análogos & derivados , Lisina/sangre , Persona de Mediana Edad , Miocitos Cardíacos/metabolismo , Proteínas Proto-Oncogénicas c-kit/metabolismo , Células Madre/patología , Adulto Joven

RESUMEN

Heart disease is one of the most important causes of death in developed countries. N(ε)-carboxymethyllysine (CML) is a major advanced glycation end product formed by combined reactions of non-enzymatic glycation and oxidation (glycoxidation), and it represents a general marker of oxidative stress. CML has been suggested to be involved in the pathogenesis of heart disease. Plasma CML is elevated in aging, atherosclerosis and/or diabetes. In this study, we measured cardiac CML levels to elucidate its role in the pathogenesis of heart disease. Cardiac tissues were collected from 105 patients (55.6 ± 17.0 years old: age range, 1-78 years) undergoing cardiac surgery. The diseases comprised coronary heart disease (CHD), CHD associated with diabetes mellitus (DM), valvular heart disease and congenital heart disease. The concentration of CML in cardiac tissues of each group was 4.31 ± 0.66, 5.29 ± 0.59, 2.74 ± 1.05 and 1.75 ± 1.16 µg/g, respectively. ELISA was used for measuring cardiac and plasma CML concentrations. Multiple linear regression analysis showed a significant positive correlation of CML concentrations with age (r = 0.803, p < 0.001), DM (r = 0.567, p < 0.001) and CHD (r = 0.523 p < 0.001). R(2) was 0.872 (p < 0.001); the three independent variables could explain 87.2% variation of CML concentrations. Cardiac CML concentrations exhibited a significant positive correlation with plasma CML (r = 0.983, p < 0.001). Our data indicate that cardiac CML concentrations increase with age, DM and/or CHD, and exhibit a positive correlation with plasma CML concentrations.

Asunto(s)

Envejecimiento/metabolismo , Enfermedad de la Arteria Coronaria/metabolismo , Diabetes Mellitus/metabolismo , Lisina/análogos & derivados , Miocardio/metabolismo , Adolescente , Adulto , Anciano , Envejecimiento/sangre , Niño , Preescolar , Enfermedad de la Arteria Coronaria/sangre , Diabetes Mellitus/sangre , Femenino , Glicosilación , Humanos , Lactante , Lisina/sangre , Lisina/metabolismo , Masculino , Persona de Mediana Edad , Miocardio/patología , Oxidación-Reducción , Fumar/efectos adversos , Adulto Joven

RESUMEN

BACKGROUND: N(ε)-carboxymethyl-lysine (CML) is a major advanced glycation end-product (AGEs) widely found in foods. The aim of our study was to evaluate how exogenous CML-peptide is dynamically absorbed from the gastrointestinal tract and eliminated by renal tubular secretion using microPET imaging. METHODS: The present study consisted of three investigations. In study I, we synthesized the imaging tracer (18)F-CML by reacting N-succinimidyl 4-(18)F-fluorobenzoate ((18)F-SFB) with CML. In study II, the biological activity of (18)F-CML was evaluated in RAW264.7 cells and HepG2 cells. In study III, the biodistribution and elimination of AGEs in ICR mice were studied in vivo following tail vein injection and intragastric administration of (18)F-CML. RESULT: The formation of (18)F-CML was confirmed by comparing its retention time with the corresponding reference compound (19)F-CML. The radiochemical purity (RCP) of (18)F-CML was >95%, and it showed a stable character in vitro and in vivo. Uptake of (18)F-CML by RAW264.7 cells and HepG2 cells could be inhibited by unmodified CML. (18)F-CML was quickly distributed via the blood, and it was rapidly excreted through the kidneys 20 min after tail vein injection. However, (18)F-CML was only slightly absorbed following intragastric administration. After administration of (18)F-CML via a stomach tube, the radioactivity was completely localized in the stomach for the first 15 min. At 150 min post intragastric administration, intense accumulation of radioactivity in the intestines was still observed. CONCLUSIONS: PET technology is a powerful tool for the in vivo analysis of the gastrointestinal absorption of orally administered drugs. (18)F-CML is hardly absorbed by the gastrointestinal tract. It is rapidly distributed and eliminated from blood following intravenous administration. Thus, it may not be harmful to healthy bodies. Our study showed the feasibility of noninvasively imaging (18)F-labeled AGEs and was the first to describe CML-peptide gastrointestinal absorption by means of PET.

Asunto(s)

Radioisótopos de Flúor , Lisina/análogos & derivados , Tomografía de Emisión de Positrones , Administración Intravenosa , Animales , Línea Celular , Radioisótopos de Flúor/química , Células Hep G2 , Humanos , Lisina/administración & dosificación , Lisina/química , Lisina/farmacocinética , Masculino , Ratones , Distribución Tisular