Rheumatic heart disease: A review of the current status of global research activity

Dooley, Leanne M.; Ahmad, Tarek B.; Pandey, Manisha; Good, Michael F.; Kotiw, Michael

doi:10.1016/j.autrev.2020.102740

Cited by 38 publications

(31 citation statements)

References 239 publications

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“…However, more recently, other superficial streptococcal infections, such as impetigo and pyoderma, have been associated with RHD [71,72]. There is also emerging evidence potentially implicating group C and group G streptococcus in contributing to the pathogenesis of RHD [73][74][75][76][77].…”

Section: Advances In Understanding Rf/rhd Pathogenesismentioning

confidence: 99%

Recent Advances in the Rheumatic Fever and Rheumatic Heart Disease Continuum

Rwebembera

Nascimento

Minja³

et al. 2022

Pathogens

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Nearly a century after rheumatic fever (RF) and rheumatic heart disease (RHD) was eradicated from the developed world, the disease remains endemic in many low- and middle-income countries (LMICs), with grim health and socioeconomic impacts. The neglect of RHD which persisted for a semi-centennial was further driven by competing infectious diseases, particularly the human immunodeficiency virus (HIV) pandemic. However, over the last two-decades, slowly at first but with building momentum, there has been a resurgence of interest in RF/RHD. In this narrative review, we present the advances that have been made in the RF/RHD continuum over the past two decades since the re-awakening of interest, with a more concise focus on the last decade’s achievements. Such primary advances include understanding the genetic predisposition to RHD, group A Streptococcus (GAS) vaccine development, and improved diagnostic strategies for GAS pharyngitis. Echocardiographic screening for RHD has been a major advance which has unearthed the prevailing high burden of RHD and the recent demonstration of benefit of secondary antibiotic prophylaxis on halting progression of latent RHD is a major step forward. Multiple befitting advances in tertiary management of RHD have also been realized. Finally, we summarize the research gaps and provide illumination on profitable future directions towards global eradication of RHD.

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Section: Advances In Understanding Rf/rhd Pathogenesismentioning

confidence: 99%

Recent Advances in the Rheumatic Fever and Rheumatic Heart Disease Continuum

Rwebembera

Nascimento

Minja³

et al. 2022

Pathogens

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“…Recent studies have indicated that serum-related markers, such as IL-1β, IL-8, IL-6, CXCL-1, tumor necrosis factor α, antistreptolysin, antideoxyribose, and nuclease B concentrations have been widely used in prognostic evaluations of RHD. However, their prognostic values are limited, for they lack sensitivity or specificity ( 5 , 6 ). XGBoost is a machine learning technology with the noteworthy characteristics of assembling weak prediction models, and providing flexible and efficient missing data processing for establishing accurate prediction models ( 5 ).…”

Section: Introductionmentioning

confidence: 99%

“…However, their prognostic values are limited, for they lack sensitivity or specificity ( 5 , 6 ). XGBoost is a machine learning technology with the noteworthy characteristics of assembling weak prediction models, and providing flexible and efficient missing data processing for establishing accurate prediction models ( 5 ). A logistic regression model is usually developed by the variables of each patient that predict the outcomes of future patients.…”

Section: Introductionmentioning

confidence: 99%

Predicting ICU Mortality in Rheumatic Heart Disease: Comparison of XGBoost and Logistic Regression

Han

Zhang

et al. 2022

Front. Cardiovasc. Med.

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BackgroundRheumatic heart disease (RHD) accounts for a large proportion of Intensive Care Unit (ICU) deaths. Early prediction of RHD can help with timely and appropriate treatment to improve survival outcomes, and the XGBoost machine learning technology can be used to identify predictive factors; however, its use has been limited in the past. We compared the performance of logistic regression and XGBoost in predicting hospital mortality among patients with RHD from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database.MethodsThe patients with RHD in the MIMIC-IV database were divided into two groups retrospectively according to the availability of data and its clinical significance based on whether they survived or died. Backward stepwise regression was used to analyze the independent factors influencing patients with RHD, and to compare the differences between the two groups. The XGBoost algorithm and logistic regression were used to establish two prediction models, and the areas under the receiver operating characteristic curves (AUCs) and decision-curve analysis (DCA) were used to test and compare the models. Finally, DCA and the clinical impact curve (CIC) were used to validate the model.ResultsData on 1,634 patients with RHD were analyzed, comprising 207 who died during hospitalization and 1,427 survived. According to estimated results for the two models using AUCs [0.838 (95% confidence interval = 0.786–0.891) and 0.815 (95% confidence interval = 0.765–0.865)] and DCA, the logistic regression model performed better. DCA and CIC verified that the logistic regression model had convincing predictive value.ConclusionsWe used logistic regression analysis to establish a more meaningful prediction model for the final outcome of patients with RHD. This model might be clinically useful for patients with RHD and help clinicians to provide detailed treatments and precise management.

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“…Rheumatic heart disease (RHD) is a type of acute rheumatic fever (ARF), an autoimmune disorder triggered by group A β‐hemolytic streptococcus infection; recurrent ARF causes permanent valve disease. 1 , 2 Although the incidence of RHD is declining globally, it maintains a high incidence in low‐ and middle‐income countries such as in Africa. 3 At present, rheumatic valvular heart disease (RVHD) is a significant cause of the need for cardiac surgery in China, accounting for 40% of heart diseases.…”

Section: Introductionmentioning

confidence: 99%

“…Patients with mechanical valve replacement require life‐long anticoagulation therapy after surgery, all of which severely affect the quality of life. 1 At present, the essential examination method for RVHD is transthoracic echocardiography (TTE); however, the detection accuracy of TTE is affected by the operator, and the technique is prone to errors. The test indicators that assist in diagnosing RVHD include erythrocyte sedimentation rate, C‐reactive protein, mucin, and protein electrophoresis.…”

Section: Introductionmentioning

confidence: 99%

Hsa_circ_0000437 upregulates and promotes disease progression in rheumatic valvular heart disease

Zhu

Wang

et al. 2021

Clinical Laboratory Analysis

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Background: Currently, the diagnosis and outcome of rheumatic valvular heart disease (RVHD) are less than ideal, and there are no accurate biomarkers. Circular RNA (circRNA) might participate in the occurrence and development of RVHD. Materials and methods:We use circRNA microarray to filter out the target has_circ_0000437. qRT-PCR was used to measure the expression levels of hsa_ circ_0000437 in RVHD plasma samples. We assessed the diagnostic value of hsa_ circ_0000437 in RVHD. Cell function in vitro experiment was to explore the effect of has_circ_0000437 on RVHD.Results: Has_circ_0000437 is highly expressed in RVHD (p < 0.001). has_ circ_0000437 has the diagnostic value in RVHD. In RVHD, hsa_circ_0000437 can promote cell proliferation and migration but inhibits its apoptosis. This may be due to the combination of has_circ_0000437 and target miRNA in the cytoplasm that affects the progress of RVHD. Conclusions:Has_circ_0000437 can promote the process of RVHD and may be a potential for the diagnosis and treatment of RVHD.

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Rheumatic heart disease: A review of the current status of global research activity

Cited by 38 publications

References 239 publications

Recent Advances in the Rheumatic Fever and Rheumatic Heart Disease Continuum

Recent Advances in the Rheumatic Fever and Rheumatic Heart Disease Continuum

Predicting ICU Mortality in Rheumatic Heart Disease: Comparison of XGBoost and Logistic Regression

Hsa_circ_0000437 upregulates and promotes disease progression in rheumatic valvular heart disease

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