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1.
J Nucl Cardiol ; 2022 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-35274211

RESUMO

BACKGROUND: Advanced cardiac imaging with positron emission tomography (PET) is a powerful tool for the evaluation of known or suspected cardiovascular disease. Deep learning (DL) offers the possibility to abstract highly complex patterns to optimize classification and prediction tasks. METHODS AND RESULTS: We utilized DL models with a multi-task learning approach to identify an impaired myocardial flow reserve (MFR <2.0 ml/g/min) as well as to classify cardiovascular risk traits (factors), namely sex, diabetes, arterial hypertension, dyslipidemia and smoking at the individual-patient level from PET myocardial perfusion polar maps using transfer learning. Performance was assessed on a hold-out test set through the area under receiver operating curve (AUC). DL achieved the highest AUC of 0.94 [0.87-0.98] in classifying an impaired MFR in reserve perfusion polar maps. Fine-tuned DL for the classification of cardiovascular risk factors yielded the highest performance in the identification of sex from stress polar maps (AUC = 0.81 [0.73, 0.88]). Identification of smoking achieved an AUC = 0.71 [0.58, 0.85] from the analysis of rest polar maps. The identification of dyslipidemia and arterial hypertension showed poor performance and was not statistically significant. CONCLUSION: Multi-task DL for the evaluation of quantitative PET myocardial perfusion polar maps is able to identify an impaired MFR as well as cardiovascular risk traits such as sex, smoking and possibly diabetes at the individual-patient level.

3.
Ann Nucl Med ; 36(6): 507-514, 2022 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-35192160

RESUMO

PURPOSE: To estimate the interobserver agreement of the Carimas software package (SP) on global, regional, and segmental levels for the most widely used myocardial perfusion PET tracer-Rb-82. MATERIALS AND METHODS: Rest and stress Rb-82 PET scans of 48 patients with suspected or known coronary artery disease (CAD) were analyzed in four centers using the Carimas SP. We considered values to agree if they simultaneously had an intraclass correlation coefficient (ICC) > 0.75 and a difference < 20% of the median across all observers. RESULTS: The median values on the segmental level were 1.08 mL/min/g for rest myocardial blood flow (MBF), 2.24 mL/min/g for stress MBF, and 2.17 for myocardial flow reserve (MFR). For the rest MBF and MFR, all the values at all the levels fulfilled were in excellent agreement. For stress MBF, at the global and regional levels, all the 24 comparisons showed excellent agreement. Only 1 out of 102 segmental comparisons (seg. 14) was over the adequate agreement limit-23.5% of the median value (ICC = 0.95). CONCLUSION: Interobserver agreement for Rb-82 PET myocardial perfusion quantification analyzed with Carimas is good at any LV segmentation level-global, regional, and segmental. It is good for all the estimates-rest MBF, stress MBF, and MFR.


Assuntos
Doença da Artéria Coronariana , Imagem de Perfusão do Miocárdio , Doença da Artéria Coronariana/diagnóstico por imagem , Circulação Coronária/fisiologia , Humanos , Variações Dependentes do Observador , Perfusão , Tomografia por Emissão de Pósitrons , Reprodutibilidade dos Testes , Radioisótopos de Rubídio , Software
4.
Curr Cardiol Rep ; 24(4): 307-316, 2022 04.
Artigo em Inglês | MEDLINE | ID: mdl-35171443

RESUMO

PURPOSE OF REVIEW: As machine learning-based artificial intelligence (AI) continues to revolutionize the way in which we analyze data, the field of nuclear cardiology provides fertile ground for the implementation of these complex analytics. This review summarizes and discusses the principles regarding nuclear cardiology techniques and AI, and the current evidence regarding its performance and contribution to the improvement of risk prediction in cardiovascular disease. There is a growing body of evidence on the experimentation with and implementation of machine learning-based AI on nuclear cardiology studies both concerning SPECT and PET technology for the improvement of risk-of-disease (classification of disease) and risk-of-events (prediction of adverse events) estimations. These publications still report objective divergence in methods either utilizing statistical machine learning approaches or deep learning with varying architectures, dataset sizes, and performance. Recent efforts have been placed into bringing standardization and quality to the experimentation and application of machine learning-based AI in cardiovascular imaging to generate standards in data harmonization and analysis through AI. Machine learning-based AI offers the possibility to improve risk evaluation in cardiovascular disease through its implementation on cardiac nuclear studies. AI in improving risk evaluation in nuclear cardiology. * Based on the 2019 ESC guidelines.


Assuntos
Cardiologia , Doenças Cardiovasculares , Inteligência Artificial , Cardiologia/métodos , Doenças Cardiovasculares/diagnóstico por imagem , Humanos , Aprendizado de Máquina
5.
Health Policy Plan ; 37(3): 359-368, 2022 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-34875689

RESUMO

Like most of the world, low- and middle-income countries have faced a growing demand for new health technologies and higher budget constraints. It is necessary to have technical instruments to make decisions based on real-world evidence that allows maximization of the population's health with a limited budget. We estimated the supply-based cost-effectiveness elasticity, which was then used to determine the cost-effectiveness threshold for the healthcare system of Colombia, a middle-income country where multiple insurers, paid under capitation rules, manage the compulsory contributions of the citizens and government subsidies. Using administrative data, we explored the variation of health expenditures and outcomes at the insurer, geographical region, diagnosis group and year levels. To deal with endogeneity in a two-way fixed-effects model, we instrumented health expenditures using characteristics of the health system such as drug-price regulation. We estimated the threshold to be US$4487.5 per years of life lost avoided [14.7 million Colombian pesos (COP) at 2019 prices] and US$5180.8 per quality-adjusted life-years gained (17 million COP at 2019 prices), around one times the gross domestic product GDP per capita. To the best of our knowledge, this is the first estimation of the cost-effectiveness threshold elasticity supply-based in a middle-income country with a managed healthcare system.


Assuntos
Atenção à Saúde , Gastos em Saúde , Colômbia , Análise Custo-Benefício , Humanos , Anos de Vida Ajustados por Qualidade de Vida
6.
EBioMedicine ; 75: 103783, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34968759

RESUMO

BACKGROUND: Alterations in the anatomic and biomechanical properties of the ascending aorta (AAo) can give rise to various vascular pathologies. The aim of the current study is to gain additional insights in the biology of the AAo size and function. METHODS: We developed an AI based analysis pipeline for the segmentation of the AAo, and the extraction of AAO parameters. We then performed genome-wide association studies of AAo maximum area, AAo minimum area and AAo distensibility in up to 37,910 individuals from the UK Biobank. Variants that were significantly associated with AAo phenotypes were used as instrumental variables in Mendelian randomization analyses to investigate potential causal relationships with coronary artery disease, myocardial infarction, stroke and aneurysms. FINDINGS: Genome-wide association studies revealed a total of 107 SNPs in 78 loci. We annotated 101 candidate genes involved in various biological processes, including connective tissue development (THSD4 and COL6A3). Mendelian randomization analyses showed a causal association with aneurysm development, but not with other vascular diseases. INTERPRETATION: We identified 78 loci that provide insights into mechanisms underlying AAo size and function in the general population and provide genetic evidence for their role in aortic aneurysm development.


Assuntos
Aneurisma Aórtico , Estudo de Associação Genômica Ampla , Aorta , Genômica , Humanos , Análise da Randomização Mendeliana
9.
Toxins (Basel) ; 13(9)2021 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-34564632

RESUMO

The bean (Phaseolus vulgaris) pathogen Pseudomonas syringae pv. phaseolicola NPS3121 synthesizes phaseolotoxin in a thermoregulated way, with optimum production at 18 °C. Gene PSPPH_4550 was previously shown to be thermoregulated and required for phaseolotoxin biosynthesis. Here, we established that PSPPH_4550 is part of a cluster of 16 genes, the Pbo cluster, included in a genomic island with a limited distribution in P. syringae and unrelated to the possession of the phaseolotoxin biosynthesis cluster. We identified typical non-ribosomal peptide synthetase, and polyketide synthetase domains in several of the pbo deduced products. RT-PCR and the analysis of polar mutants showed that the Pbo cluster is organized in four transcriptional units, including one monocistronic and three polycistronic. Operons pboA and pboO are both essential for phaseolotoxin biosynthesis, while pboK and pboJ only influence the amount of toxin produced. The three polycistronic units were transcribed at high levels at 18 °C but not at 28 °C, whereas gene pboJ was constitutively expressed. Together, our data suggest that the Pbo cluster synthesizes secondary metabolite(s), which could participate in the regulation of phaseolotoxin biosynthesis.


Assuntos
Família Multigênica/genética , Ornitina/análogos & derivados , Pseudomonas syringae/genética , Regulação da Temperatura Corporal , Ornitina/biossíntese , Pseudomonas syringae/metabolismo
10.
J Nucl Cardiol ; 2021 Aug 18.
Artigo em Inglês | MEDLINE | ID: mdl-34409572

RESUMO

PURPOSE: To cross-compare three software packages (SPs)-Carimas, FlowQuant, and PMOD-to quantify myocardial perfusion at global, regional, and segmental levels. MATERIALS AND METHODS: Stress N-13 ammonia PET scans of 48 patients with HCM were analyzed in three centers using Carimas, FlowQuant, and PMOD. Values agreed if they had an ICC > 0.75 and a difference < 20% of the median across all observers. RESULTS: When using 1TCM on the global level, the agreement was good, and the maximum difference between 1TCM MBF values was 17.2% (ICC = 0.83). On the regional level, the agreement was acceptable except in the LCx region (25.5% difference, ICC = 0.74) between FlowQuant and PMOD. Carimas-1TCM agreed well with PMOD-1TCM and FlowQuant-1TCM. Values obtained with FlowQuant-1TCM had a somewhat lesser agreement with PMOD-1TCM, especially at the segmental level. CONCLUSIONS: The global and regional MBF values (with one exception) agree well between the different software packages. There is significant variability in segmental values, mainly located in the LCx region and segments. Out of the studied tools, Carimas can be used interchangeably with both PMOD and FlowQuant for 1TCM implementation on all levels-global, regional, and segmental.

11.
Foods ; 10(8)2021 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-34441525

RESUMO

Bioactive compounds (BC) present in muicle leaves were extracted using the best extraction conditions obtained with a Box-Behnken experimental design, extracting 95% of BC. Microencapsulation of muicle BC was carried out by spray drying using DE10 maltodextrin (MD) and soy protein isolate (SPI) as encapsulating agents. The best conditions for the ethanolic extraction of BC from muicle were 30 °C, 40% aqueous ethanol, and one extraction for 1 h. The best spray drying encapsulating conditions for BC and antioxidant capacity (AC) using MD as an encapsulating agent were: 160-80 °C and 10% MD in the feeding solution, and for SPI: 180-70 °C and 5% SPI in the feeding solution. Microcapsules were added to yogurt and a sensory evaluation and retention of BC during 15-day storage at 4 °C was performed. Sensory evaluation showed that yogurt with added MD microcapsules had better acceptance than that with SPI microcapsules. Based on this, a jelly with added muicle MD microcapsules was also prepared which obtained better acceptance by the judges. At the end of the storage period, yogurt with SPI microcapsules showed better retention of BC and AC than yogurts with MD microcapsules; however, products with MD microcapsules had better acceptance.

12.
Med Sci Monit ; 27: e934134, 2021 Aug 30.
Artigo em Inglês | MEDLINE | ID: mdl-34456329

RESUMO

Non-alcoholic fatty liver disease (NAFLD) affects almost a quarter of the world's population and is the most common cause of chronic liver disease in children and adolescents. The recent proposal to replace the terminology of NAFLD with metabolic-associated fatty liver disease (MAFLD) aims to reflect the pathophysiology and risk factors for this disease. Importantly, the risk factors for MAFLD may be prenatal, such as genetic factors, or postnatal, such as obesity and insulin resistance. MAFLD is increasingly recognized in children and adolescents. Early diagnosis and identification of high-risk individuals with type 2 diabetes mellitus and metabolic syndrome is important. The diagnosis and management of MAFLD in children and adolescents should follow international clinical guidelines, such as those from the American Diabetes Association (ADA) and the International Society for Pediatric and Adolescent Diabetes (ISPAD). Current guidelines recommend lifestyle and dietary modifications, exercise, screening, individualized patient assessment, and multidisciplinary patient management. This review assesses the revised terminology and discusses the epidemiology, risk factors, pathophysiology, diagnosis, and prevention of MAFLD in children and adolescents worldwide and in Mexico, and also considers the implications for public health.


Assuntos
Diabetes Mellitus Tipo 2/epidemiologia , Síndrome Metabólica/fisiopatologia , Hepatopatia Gordurosa não Alcoólica/epidemiologia , Obesidade/fisiopatologia , Adolescente , Criança , Diabetes Mellitus Tipo 2/patologia , Saúde Global , Humanos , México/epidemiologia , Hepatopatia Gordurosa não Alcoólica/patologia , Prevalência , Prognóstico , Saúde Pública
13.
Emerg Med J ; 38(11): 814-819, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-34373266

RESUMO

OBJECTIVES: The History, ECG, Age, Risk Factors and Troponin (HEART) Score is a decision support tool applied by physicians in the emergency department developed to risk stratify low-risk patients presenting with chest pain. We assessed the potential value of this tool in prehospital setting, when applied by emergency medical services (EMS), and derived and validated a tool adapted to the prehospital setting in order to determine if it could assist with decisions regarding conveyance to a hospital. METHODS: In 2017, EMS personnel prospectively determined the HEART Score, including point-of-care (POC) troponin measurements, in patients presenting with chest pain, in the north of the Netherlands. The primary endpoint was a major adverse cardiac event (MACE), consisting of acute myocardial infarction or death, within 3 days. The components of the HEART Score were evaluated for their discriminatory value, cut-offs were calibrated for the prehospital setting and sex was substituted for cardiac risk factors to develop a prehospital HEART (preHEART) Score. This score was validated in an independent prospective cohort of 435 patients in 2018. RESULTS: Among 1208 patients prospectively recruited in the first cohort, 123 patients (10.2%) developed a MACE. The HEART Score had a negative predictive value (NPV) of 98.4% (96.4-99.3), a positive predictive value (PPV) of 35.5% (31.8-39.3) and an area under the receiver operating characteristic curve (AUC) of 0.81 (0.78-0.85). The preHEART Score had an NPV of 99.3% (98.1-99.8), a PPV of 49.4% (42.0-56.9) and an AUC of 0.85 (0.82-0.88), outperforming the HEART Score or POC troponin measurements on their own. Similar results were found in a validation cohort. CONCLUSIONS: The HEART Score can be used in the prehospital setting to assist with conveyance decisions and choice of hospitals; however, the preHEART Score outperforms both the HEART Score and single POC troponin measurements when applied by EMS personnel in the prehospital setting.


Assuntos
Dor no Peito/terapia , Gestão de Riscos/métodos , Idoso , Área Sob a Curva , Dor no Peito/complicações , Dor no Peito/epidemiologia , Serviços Médicos de Emergência , Serviço Hospitalar de Emergência/organização & administração , Serviço Hospitalar de Emergência/estatística & dados numéricos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Países Baixos/epidemiologia , Estudos Prospectivos , Curva ROC , Medição de Risco/métodos , Fatores de Risco , Gestão de Riscos/estatística & dados numéricos
14.
Med Sci Monit ; 27: e933860, 2021 Jul 12.
Artigo em Inglês | MEDLINE | ID: mdl-34248137

RESUMO

In 2020, international consensus guidelines recommended the renaming of non-alcoholic fatty liver disease (NAFLD) to metabolic-associated fatty liver disease (MAFLD), supported by diagnostic criteria. MAFLD affects up to 25% of the global population. However, the rates of MAFLD are likely to be underestimated due to the increasing prevalence of type 2 diabetes mellitus (T2DM) and obesity. Within the next decade, MAFLD has been projected to become a major cause of cirrhosis and hepatocellular carcinoma (HCC) worldwide, as well as the most common indication for liver transplantation in the US. This transition in terminology and clinical criteria may increase momentum and clinical evidence at multiple levels, including patient diagnosis, management, and care, and provide the basis for new research areas and clinical development for therapeutics. The diagnostic criteria for MAFLD are practical, simple, and superior to the existing NAFLD criteria for identifying patients at increased risk of developing progressive liver disease. This Editorial aims to present the historical evolution of the terminology for fatty liver disease and the advantages of diagnosis, patient management, and future research on MAFLD.


Assuntos
Fígado Gorduroso , Terminologia como Assunto , Carcinoma Hepatocelular , Diabetes Mellitus Tipo 2 , Fibrose , Humanos , Cirrose Hepática , Neoplasias Hepáticas , Hepatopatia Gordurosa não Alcoólica , Prevalência
15.
Rev. peru. ginecol. obstet. (En línea) ; 67(3): 00003, jul.-sep 2021. tab
Artigo em Espanhol | LILACS-Express | LILACS | ID: biblio-1361087

RESUMO

RESUMEN Objetivo . Precisar el concepto de salud sexual y reproductiva, situarla dentro de los Derechos Humanos y, como consecuencia, dentro de los Derechos Sexuales y Reproductivos; discutir algunas cuestiones de género; examinar la situación de los derechos sexuales y reproductivos en nuestro país y lo que esperamos para los años venideros. Metodología . Revisión de la literatura médica nacional en relación a los derechos sexuales y reproductivos y sistematizar la información. Resultados . En los diversos componentes de la salud sexual y reproductiva se encuentran deficiencias importantes que es necesario superar para alcanzar el bienestar que señalan los Objetivos de Desarrollo Sostenible. Conclusión . Hay todavía mucho que desarrollar en el reconocimiento de los derechos sexuales y reproductivos, apelando al mejor desempeño y compromiso de los profesionales de la salud.


ABSTRACT Objective : To clarify the concept of sexual and reproductive health, to situate it within Human Rights and, as a consequence, within Sexual and Reproductive Rights; to discuss some gender issues; to examine the situation of sexual and reproductive rights in our country and what we expect for the years to come. Methodology : Review of the national medical literature in relation to sexual and reproductive rights and systematize the information. Results : In the various components of sexual and reproductive health there are important deficiencies that need to be overcome in order to achieve the well-being indicated by the Sustainable Development Goals. Conclusion : There is still much to be developed in the recognition of sexual and reproductive rights, appealing to the best performance and commitment of health professionals.

17.
Minerva Gastroenterol (Torino) ; 67(4): 326-338, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33978392

RESUMO

Nutraceuticals are defined as products isolated or purified from foods that are generally sold in medicinal or dosage forms not usually associated with food which is demonstrated to have a physiological benefit or provide protection against chronic disease. In this context, the products offered should be rigorously evaluated by international regulatory agencies. More recently, nutraceuticals have been proposed as a potential preventive and therapeutic option in the assessment of chronic diseases, mainly by altering the microbiome composition. However, the current lack of conclusive evidence supporting the "healthy" or "normal" microbiome, along with the dysbiosis concept paradigm, could be both contributing to the lack of homogeneous results. These issues may be solved in the next years with the use of emergent technologies in the individual's microbiome assessment and its fluctuations in time or related to many factors, such as nutraceuticals. Additionally, future research assessing the independent association between the dysbiosis modification and any "potential" nutraceutical product (including bioactive ingredient or chemical compound in food) is going to enlarge the currently reduced "established nutraceuticals" group. In this work we have assessed the nutraceutical's potential role as a microbiome-targeted manipulation therapy, and the gut-liver axis involved in the digestive diseases' pathogenesis and progression, including the chronic liver diseases. Moreover, microbiome targeted nutraceuticals that show consistent results might be further included in clinical research and trials in the therapeutic assessment of chronic diseases. Finally, the indication of these quality microbiome-targeted nutraceuticals will undoubtedly carry health benefits for individuals.


Assuntos
Microbioma Gastrointestinal , Microbiota , Suplementos Nutricionais , Disbiose , Humanos , Fígado
18.
Eur J Nucl Med Mol Imaging ; 48(5): 1399-1413, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33864509

RESUMO

In daily clinical practice, clinicians integrate available data to ascertain the diagnostic and prognostic probability of a disease or clinical outcome for their patients. For patients with suspected or known cardiovascular disease, several anatomical and functional imaging techniques are commonly performed to aid this endeavor, including coronary computed tomography angiography (CCTA) and nuclear cardiology imaging. Continuous improvement in positron emission tomography (PET), single-photon emission computed tomography (SPECT), and CT hardware and software has resulted in improved diagnostic performance and wide implementation of these imaging techniques in daily clinical practice. However, the human ability to interpret, quantify, and integrate these data sets is limited. The identification of novel markers and application of machine learning (ML) algorithms, including deep learning (DL) to cardiovascular imaging techniques will further improve diagnosis and prognostication for patients with cardiovascular diseases. The goal of this position paper of the European Association of Nuclear Medicine (EANM) and the European Association of Cardiovascular Imaging (EACVI) is to provide an overview of the general concepts behind modern machine learning-based artificial intelligence, highlights currently prefered methods, practices, and computational models, and proposes new strategies to support the clinical application of ML in the field of cardiovascular imaging using nuclear cardiology (hybrid) and CT techniques.


Assuntos
Medicina Nuclear , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Inteligência Artificial , Humanos , Tomografia por Emissão de Pósitrons , Tomografia Computadorizada de Emissão de Fóton Único , Tomografia Computadorizada por Raios X
20.
Int J Cardiol ; 335: 130-136, 2021 07 15.
Artigo em Inglês | MEDLINE | ID: mdl-33831505

RESUMO

BACKGROUND: Standard computed tomography angiography (CTA) outputs a myriad of interrelated variables in the evaluation of suspected coronary artery disease (CAD). But an important proportion of obstructive lesions does not cause significant myocardial ischemia. Nowadays, machine learning (ML) allows integration of numerous variables through complex interdependencies that optimize classification and prediction at the individual level. We evaluated ML performance in integrating CTA and clinical variables to identify patients that demonstrate myocardial ischemia through PET and those who ultimately underwent early revascularization. METHODS AND RESULTS: 830 patients with CTA and selective PET were analyzed. Nine clinical and 58 CTA variables were integrated through ensemble-boosting ML to identify patients with ischemia and those who underwent early revascularization. ML performance was compared against expert CTA interpretation, calcium score and clinical variables. While ML using all CTA variables achieved an AUC = 0.85, it was outperformed by expert CTA interpretation (AUC = 0.87, p < 0.01 for comparison), comparable to ML integration of CTA variables with clinical variables. However, the best performance was achieved by ML integration of expert CTA interpretation and clinical variables for both dependent variables (AUCs = 0.91 and 0.90, p < 0.001). CONCLUSIONS: Machine learning integration of diagnostic CTA and clinical data may improve identification of patients with myocardial ischemia and those requiring early revascularization at the individual level. This could potentially aid in sparing the need for subsequent advanced imaging and better identifying patients in ultimate need for revascularization. While ML integrating all CTA variables did not outperform expert CTA interpretation, ML data integration from different sources consistently improves diagnostic performance.


Assuntos
Doença da Artéria Coronariana , Estenose Coronária , Imagem de Perfusão do Miocárdio , Angiografia por Tomografia Computadorizada , Angiografia Coronária , Doença da Artéria Coronariana/diagnóstico por imagem , Humanos , Aprendizado de Máquina , Valor Preditivo dos Testes
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