Algorithm-aided diagnosis of chronic pulmonary aspergillosis in low- and middle-income countries by use of a lateral flow device

Kwizera, Richard; Katende, Andrew; Teu, Anneth; Apolot, Denise; Worodria, William; Kirenga, Bruce; Bongomin, Felix

doi:10.1007/s10096-019-03782-x

Cited by 25 publications

(20 citation statements)

References 15 publications

(19 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a single study among Nigerians, 13 of the 17 patients with CPA were being treated for "smear-negative PTB" [15]. In addition, the lack of awareness and low index of suspicion for CPA among clinicians, as well as the non-availability of essential diagnostics for CPA, are associated with misdiagnosis of CPA [24]. Other differential diagnoses such as chronic cavitary pulmonary histoplasmosis [25], coccidioidomycosis, paracoccidioidomycosis in endemic areas, non-tuberculous mycobacterial (NTM) infection, and other cavitary lung diseases should be considered and evaluated if indicated.…”

Section: Why Is Cpa Misdiagnosed As Ptb?mentioning

confidence: 99%

“…Therefore, Aspergillus serology is the cornerstone for CPA diagnosis. Introduction of a cheap and rapid point-of-care Aspergillus IgG/IgM lateral flow assay with a sensitivity and specificity of 91.6% (86%-95.4%) and 98.0% (94.2%-99.6%), respectively, has made the diagnosis of CPA possible even in resource-constrained settings [24,27]. PTB can usually be excluded through routine sputum microscopy or culture or by use of the rapid molecular assay (GeneXpert) [30,31].…”

Section: How Is Cpa Differentiated From Ptb and Ptbld?mentioning

confidence: 99%

See 1 more Smart Citation

Post-tuberculosis chronic pulmonary aspergillosis: An emerging public health concern

Bongomin

2020

PLoS Pathog

Self Cite

View full text Add to dashboard Cite

How common is CPA after treated PTB? CPA is a progressive respiratory syndrome that largely occur in immunocompetent or subtly immunocompromised individuals with underlying structural lung diseases, most commonly treated TB [11]. Residual cavities remain in between 20% to 40% of lungs of patients following treatment for PTB [12,13]. Cavitation and ectatic lesions in PTBLD allows saprophytic colonisation and growth of Aspergillus species following inhalation of infectious spores from the environment. This leads to expansion of the existing or creation of new cavities with associated parenchymal and pleural damage [11]. A complex mixture of Aspergillus hyphae, tissue debris, inflammatory cells, and mucin known as a fungal ball (aspergilloma) may form in these cavities [11]. The significance of treated PTB in the pathogenesis of CPA was established by a large cohort study across over 50 clinics in Great Britain in the mid-to late 1960s [14]. In this landmark study, 544 patients who had a persistent cavity of at least 2.5 cm in diameter and negative M. tuberculosis bacilli in their sputum for at least a year were studied. About 25% of the patients had positive Aspergillus precipitins (i.e., precipitating immunoglobulin M [IgM] and immunoglobulin G

show abstract

Section: Why Is Cpa Misdiagnosed As Ptb?mentioning

confidence: 99%

Section: How Is Cpa Differentiated From Ptb and Ptbld?mentioning

confidence: 99%

Post-tuberculosis chronic pulmonary aspergillosis: An emerging public health concern

Bongomin

2020

PLoS Pathog

Self Cite

View full text Add to dashboard Cite

show abstract

“…Although the model has been successfully implemented, the fine tuning of the CNN parameters has not been performed which can further enhance the overall classification accuracy of the model. To categorize the COVID-infected images, a novel approach based on multi-objective differential evolution (MODE) and CNN has been devised by Singh et al [ 17 ]. For the classification of the COVID-19-infected cases, a multi-objective fitness function is used.…”

Section: Introductionmentioning

confidence: 99%

An Automated Lightweight Deep Neural Network for Diagnosis of COVID-19 from Chest X-ray Images

Nayak

Sinha

et al. 2021

Arab J Sci Eng

View full text Add to dashboard Cite

Coronavirus (COVID-19) is an epidemic that is rapidly spreading and causing a severe healthcare crisis resulting in more than 40 million confirmed cases across the globe. There are many intensive studies on AI-based technique, which is time consuming and troublesome by considering heavyweight models in terms of more training parameters and memory cost, which leads to higher time complexity. To improve diagnosis, this paper is aimed to design and establish a unique lightweight deep learning-based approach to perform multi-class classification (normal, COVID-19, and pneumonia) and binary class classification (normal and COVID-19) on X-ray radiographs of chest. This proposed CNN scheme includes the combination of three CBR blocks (convolutional batch normalization ReLu) with learnable parameters and one global average pooling (GP) layer and fully connected layer. The overall accuracy of the proposed model achieved 98.33% and finally compared with the pre-trained transfer learning model (DenseNet-121, ResNet-101, VGG-19, and XceptionNet) and recent state-of-the-art model. For validation of the proposed model, several parameters are considered such as learning rate, batch size, number of epochs, and different optimizers. Apart from this, several other performance measures like tenfold cross-validation, confusion matrix, evaluation metrics, sarea under the receiver operating characteristics, kappa score and Mathew’s correlation, and Grad-CAM heat map have been used to assess the efficacy of the proposed model. The outcome of this proposed model is more robust, and it may be useful for radiologists for faster diagnostics of COVID-19.

show abstract

“…It is of great concern that resistant strains against currently available anti-influenza drugs are frequently identified in human or avian influenza virus [ 99 ]. Driven by structural and functional characterization of influenza HA, the development of potent HA inhibitors has raised hopes for new antiviral therapies.…”

Section: Discussionmentioning

confidence: 99%

Small Molecule Inhibitors of Influenza Virus Entry

et al. 2021

View full text Add to dashboard Cite

Hemagglutinin (HA) plays a critical role during influenza virus receptor binding and subsequent membrane fusion process, thus HA has become a promising drug target. For the past several decades, we and other researchers have discovered a series of HA inhibitors mainly targeting its fusion machinery. In this review, we summarize the advances in HA-targeted development of small molecule inhibitors. Moreover, we discuss the structural basis and mode of action of these inhibitors, and speculate upon future directions toward more potent inhibitors of membrane fusion and potential anti-influenza drugs.

show abstract

Algorithm-aided diagnosis of chronic pulmonary aspergillosis in low- and middle-income countries by use of a lateral flow device

Cited by 25 publications

References 15 publications

Post-tuberculosis chronic pulmonary aspergillosis: An emerging public health concern

Post-tuberculosis chronic pulmonary aspergillosis: An emerging public health concern

An Automated Lightweight Deep Neural Network for Diagnosis of COVID-19 from Chest X-ray Images

Small Molecule Inhibitors of Influenza Virus Entry

Contact Info

Product

Resources

About