scholarly journals Discrepant Hemophilia A: An Underdiagnosed Disease Entity

2020 ◽  
Vol 154 (1) ◽  
pp. 78-87
Author(s):  
Ahmad Al-Huniti ◽  
Anjali Sharathkumar ◽  
Michelle Krantz ◽  
Karla Watkinson ◽  
Sharathkumar Bhagavathi
Keyword(s):  
Literature Review ◽  
Clinical Management ◽  
Hemophilia A ◽  
Gene Mutations ◽  
Retrospective Chart Review ◽  
Current Understanding ◽  
Pooled Prevalence ◽  
Diagnosis And Classification ◽  
High Index Of Suspicion

Abstract Objectives The term discrepant hemophilia A (DHA) denotes the discrepancy between factor VIII activity (FVIII:C) measured by different assay methodologies in patients with nonsevere hemophilia A (HA). The objective was to review the characteristics and the current understanding of mechanisms contributing to assay discrepancy in DHA. Methods Characteristics of the DHA patients treated were examined by retrospective chart review. In addition, a literature review was performed to determine the current understanding of DHA. Results Three cases of DHA were diagnosed based on bleeding phenotype: 2 cases represented missed diagnoses of HA, and 1 represented misclassification of hemophilia severity. The revised diagnosis and classification of hemophilia directly affected clinical management. Review of the literature identified 18 articles with an estimated pooled prevalence of 36% (95% CI, 23%-56%; I2 = 85%; P < .01) among nonsevere HA. Furthermore, literature indicated that DHA is a feature of how different FVIII gene mutations affect FVIII:C activity within different assay methodologies. Conclusions Our experience and literature review suggested that DHA is not only a laboratory phenomenon—it can affect clinical management in a subset of patients. A high index of suspicion for DHA is necessary while evaluating bleeding patients and/or classifying nonsevere HA.

scholarly journals Pediatric CNS-isolated hemophagocytic lymphohistiocytosis

2019 ◽  
Vol 6 (3) ◽  
pp. e560 ◽  
Author(s):  
Leslie A. Benson ◽  
Hojun Li ◽  
Lauren A. Henderson ◽  
Isaac H. Solomon ◽  
Ariane Soldatos ◽  
...  
Keyword(s):  
Hemophagocytic Lymphohistiocytosis ◽  
Chart Review ◽  
Gene Mutations ◽  
Retrospective Chart Review ◽  
Germline Mutations ◽  
Accurate Diagnosis ◽  
Hematopoietic Stem ◽  
Familial Hemophagocytic Lymphohistiocytosis ◽  
Disease Remission

ObjectiveTo highlight a novel, treatable syndrome, we report 4 patients with CNS-isolated inflammation associated with familial hemophagocytic lymphohistiocytosis (FHL) gene mutations (CNS-FHL).MethodsRetrospective chart review.ResultsPatients with CNS-FHL are characterized by chronic inflammation restricted to the CNS that is not attributable to any previously described neuroinflammatory etiology and have germline mutations in known FHL-associated genes with no signs of systemic inflammation. Hematopoietic stem cell transplantation (HCT) can be well tolerated and effective in achieving or maintaining disease remission in patients with CNS-FHL.ConclusionsEarly and accurate diagnosis followed by treatment with HCT can reduce morbidity and mortality in CNS-FHL, a novel, treatable syndrome.Classification of evidenceThis study provides Class IV evidence that HCT is well tolerated and effective in treating CNS-FHL.

scholarly journals A comparative study of different classification algorithms on RNA-Seq cancer data

2020 ◽  
pp. 24-35
Author(s):  
Nihat Yilmaz Simsek ◽  
Bulent Haznedar ◽  
Cihan Kuzudisli
Keyword(s):  
Clear Cell ◽  
Cell Cancer ◽  
Gene Mutations ◽  
Rna Seq ◽  
Accuracy Rate ◽  
Cancer Data ◽  
Diagnosis And Classification ◽  
Cancer Types ◽  
Artificial Neural Network Ann

Gene mutations are the most important reason of cancer diseases, and there are different kind of causing genes across these diseases. RNA-Seq technology enables us to allow for gathering information about many genes simultaneously; hence, RNA-Seq data can be used for cancer diagnosis and classification. In this study, RNA-Seq dataset for renal cell cancer is analysed using three different developed classification methods: random forest (RF), artificial neural network (ANN) and deep learning (DL). The genes in our dataset are related to the following cancer types: kidney renal papillary cell, kidney renal clear cell and kidney chromophore carcinomas. It suggests that the DL method gives the highest accuracy rate compared to RF and ANN for 95.15%, 91.83% and 89.22%, respectively. We believe that the results acquired in this study will make a contribution to the classification of cancer types and support doctors in their processes of decision making.   Keywords: Classification, gene-expression, RNA-Seq, DL.

Breast Cancer Detection and Classification using Traditional Computer Vision Techniques: A Comprehensive Review

2020 ◽  
Vol 16 ◽  
Author(s):  
Saliha Zahoor ◽  
Ikram Ullah Lali ◽  
Muhammad Attique Khan ◽  
Kashif Javed ◽  
Waqar Mehmood
Keyword(s):  
Breast Cancer ◽  
Computer Aided Diagnosis ◽  
Diagnose Breast Cancer ◽  
Initial Stage ◽  
Computer Aided ◽  
Diagnosis And Classification ◽  
And Performance ◽  
Tools And Techniques ◽  
Aided Diagnosis

: Breast Cancer is a common dangerous disease for women. In the world, many women died due to Breast cancer. However, in the initial stage, the diagnosis of breast cancer can save women's life. To diagnose cancer in the breast tissues there are several techniques and methods. The image processing, machine learning and deep learning methods and techniques are presented in this paper to diagnose the breast cancer. This work will be helpful to adopt better choices and reliable methods to diagnose breast cancer in an initial stage to survive the women's life. To detect the breast masses, microcalcifications, malignant cells the different techniques are used in the Computer-Aided Diagnosis (CAD) systems phases like preprocessing, segmentation, feature extraction, and classification. We have been reported a detailed analysis of different techniques or methods with their usage and performance measurement. From the reported results, it is concluded that for the survival of women’s life it is essential to improve the methods or techniques to diagnose breast cancer at an initial stage by improving the results of the Computer-Aided Diagnosis systems. Furthermore, segmentation and classification phases are challenging for researchers for the diagnosis of breast cancer accurately. Therefore, more advanced tools and techniques are still essential for the accurate diagnosis and classification of breast cancer.

Depression

2017 ◽  
Author(s):  
Philip Cowen
Keyword(s):  
International Classification Of Diseases ◽  
Behavioural Therapy ◽  
Historical Background ◽  
Cognitive Behavioural ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Diagnosis And Classification ◽  
Modern Experience ◽  
Symptoms And Signs

This chapter discusses the symptomatology, diagnosis, and classification of depression. It begins with a brief historical background on depression, tracing its origins to the classical term ‘melancholia’ that describes symptoms and signs now associated with modern concepts of the condition. It then considers the phenomenology of the modern experience of depression, its diagnosis in the operational scheme of ICD-10 (International Classification of Diseases, tenth edition), and current classificatory schemes. It looks at the symptoms needed to meet the criteria for ‘depressive episode’ in ICD-10, as well as clinical features of depression with ‘melancholic’ features or ‘somatic depression’ in ICD-10. It also presents an outline of the clinical assessment of an episode of depression before concluding with an overview of issues that need to be taken into account when addressing approaches to treatment, including cognitive behavioural therapy and the administration of antidepressants.

Diagnoses, Dimensions, and DSM-5

2010 ◽  
pp. 254-279
Author(s):  
Thomas A. Widiger ◽  
Maryanne Edmundson
Keyword(s):  
Substance Use ◽  
Mental Disorders ◽  
Paradigm Shift ◽  
Empirical Support ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Dimensional Classification ◽  
Diagnosis And Classification

The Diagnostic and Statistical Manual of Mental Disorders, Third Edition (DSM-III) is often said to have provided a significant paradigm shift in how psychopathology is diagnosed. The authors of DSM-5 have the empirical support and the opportunity to lead the field of psychiatry to a comparably bold new future in diagnosis and classification. The purpose of this chapter is to address the validity of the categorical and dimensional models for the classification and diagnosis of psychopathology. Considered in particular will be research concerning substance use disorders, mood disorders, and personality disorders. Limitations and concerns with respect to a dimensional classification of psychopathology are also considered. The chapter concludes with a recommendation for a conversion to a more quantitative, dimensional classification of psychopathology.

scholarly journals Genetic and epigenetic mechanisms in the development of congenital heart diseases

2021 ◽  
Vol 4 (2) ◽  
pp. e000196
Author(s):  
Yue Wu ◽  
Xiaosi Jin ◽  
Yuhao Zhang ◽  
Jing Zheng ◽  
Rulai Yang
Keyword(s):  
Congenital Heart ◽  
Heart Diseases ◽  
Gene Mutations ◽  
Morbidity And Mortality ◽  
Molecular Medicine ◽  
Epigenetic Mechanisms ◽  
Epigenetic Factors ◽  
Near Future

Congenital heart disease (CHD) is the most common of congenital cardiovascular malformations associated with birth defects, and it results in significant morbidity and mortality worldwide. The classification of CHD is still elusive owing to the complex pathogenesis of CHD. Advances in molecular medicine have revealed the genetic basis of some heart anomalies. Genes associated with CHD might be modulated by various epigenetic factors. Thus, the genetic and epigenetic factors are gradually accepted as important triggers in the pathogenesis of CHD. However, few literatures have comprehensively elaborated the genetic and epigenetic mechanisms of CHD. This review focuses on the etiology of CHD from genetics and epigenetics to discuss the role of these factors in the development of CHD. The interactions between genetic and epigenetic in the pathogenesis of CHD are also elaborated. Chromosome abnormalities and gene mutations in genetics, and DNA methylations, histone modifications and on-coding RNAs in epigenetics are summarized in detail. We hope the summative knowledge of these etiologies may be useful for improved diagnosis and further elucidation of CHD so that morbidity and mortality of children with CHD can be reduced in the near future.

scholarly journals Retinoblastoma genetics screening and clinical management

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Himika Gupta ◽  
Sivasankar Malaichamy ◽  
Ashwin Mallipatna ◽  
Sakthivel Murugan ◽  
Nallathambi Jeyabalan ◽  
...  
Keyword(s):  
Clinical Management ◽  
Detection Rate ◽  
Mutation Detection ◽  
Gene Mutations ◽  
Disease Recurrence ◽  
Germline Mutations ◽  
Global Studies ◽  
Mutation Detection Rate ◽  
Gene Deletions

Abstract Background India accounts for 20% of the global retinoblastoma (RB) burden. However, the existing data on RB1 gene germline mutations and its influence on clinical decisions is minimally explored. Methods Fifty children with RB underwent complete clinical examination and appropriate multidisciplinary management. Screening of germline RB1 gene mutations was performed through next-generation sequencing and Multiplex Ligation-dependent Probe Amplification (MLPA) analysis. The mutation and non-mutation groups were compared for clinical parameters especially severity, progression and recurrence. Results Twenty-nine patients had bilateral RB (BLRB) and 21 had unilateral RB (ULRB). The genetic analysis revealed 20 RB1 variations in 29 probands, inclusive of 3 novel mutations, known 16 mutations and heterozygous whole gene deletions. The mutation detection rate (MDR) was 86.2% in BLRB and 19% in ULRB. Associations of disease recurrence (p = 0.021), progression (p = 0.000) and higher percentage of optic nerve invasion, subretinal seeds and high-risk pathological factors were observed in the mutation group. Clinical management was influenced by the presence of germline mutations, particularly while deciding on enucleation, frequency of periodic follow up and radiotherapy. Conclusions We identified novel RB1 mutations, and our mutation detection rate was on par with the previous global studies. In our study, genetic results influenced clinical management and we suggest that it should be an essential and integral component of RB-care in India and elsewhere.

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