scholarly journals Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods

2021 ◽  
Author(s):  
Farshad Saberi-Movahed ◽  
Mahyar Mohammadifard ◽  
Adel Mehrpooya ◽  
Mohammad Rezaei-Ravari ◽  
Kamal Berahmand ◽  
...  
Keyword(s):  
Feature Selection ◽  
Poor Prognosis ◽  
Clinical Decision Making ◽  
Unmet Need ◽  
Clinical Decision ◽  
Clinical Indicators ◽  
Arterial Blood Gas ◽  
Clinical Biomarkers ◽  
Arterial Blood ◽  
Global Pandemic

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients' characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Ma- trix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O2 Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.

scholarly journals Can Alveolar-Arterial Difference and Lung Ultrasound Help the Clinical Decision Making in Patients with COVID-19?

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 761
Author(s):  
Gianmarco Secco ◽  
Francesco Salinaro ◽  
Carlo Bellazzi ◽  
Marco La Salvia ◽  
Marzia Delorenzo ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Lung Ultrasound ◽  
Signs And Symptoms ◽  
Clinical Decision ◽  
Arterial Oxygen ◽  
Arterial Blood Gas ◽  
Arterial Blood ◽  
Lung Dysfunction ◽  
Close Relationship

Background: COVID-19 is an emerging infectious disease, that is heavily challenging health systems worldwide. Admission Arterial Blood Gas (ABG) and Lung Ultrasound (LUS) can be of great help in clinical decision making, especially during the current pandemic and the consequent overcrowding of the Emergency Department (ED). The aim of the study was to demonstrate the capability of alveolar-to-arterial oxygen difference (AaDO2) in predicting the need for subsequent oxygen support and survival in patients with COVID-19 infection, especially in the presence of baseline normal PaO2/FiO2 ratio (P/F) values. Methods: A cohort of 223 swab-confirmed COVID-19 patients underwent clinical evaluation, blood tests, ABG and LUS in the ED. LUS score was derived from 12 ultrasound lung windows. AaDO2 was derived as AaDO2 = ((FiO2) (Atmospheric pressure − H2O pressure) − (PaCO2/R)) − PaO2. Endpoints were subsequent oxygen support need and survival. Results: A close relationship between AaDO2 and P/F and between AaDO2 and LUS score was observed (R2 = 0.88 and R2 = 0.67, respectively; p < 0.001 for both). In the subgroup of patients with P/F between 300 and 400, 94.7% (n = 107) had high AaDO2 values, and 51.4% (n = 55) received oxygen support, with 2 ICU admissions and 10 deaths. According to ROC analysis, AaDO2 > 39.4 had 83.6% sensitivity and 90.5% specificity (AUC 0.936; p < 0.001) in predicting subsequent oxygen support, whereas a LUS score > 6 showed 89.7% sensitivity and 75.0% specificity (AUC 0.896; p < 0.001). Kaplan–Meier curves showed different mortality in the AaDO2 subgroups (p = 0.0025). Conclusions: LUS and AaDO2 are easy and effective tools, which allow bedside risk stratification in patients with COVID-19, especially when P/F values, signs, and symptoms are not indicative of severe lung dysfunction.

Co-mutations of KRAS/BRAF and TP53 or the high tumor mutation burden to predict survival in patients with biliary tract carcinoma.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16650-e16650
Author(s):  
Lingling Guo ◽  
Xiaoxia Kou ◽  
Panpan Song ◽  
Xiaoyu Zhang ◽  
Hongjuan Zhang ◽  
...  
Keyword(s):  
Biliary Tract ◽  
Poor Prognosis ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Biliary Tract Carcinoma ◽  
Rank Test ◽  
Braf Mutations ◽  
Tumor Mutation Burden ◽  
Synonymous Mutations ◽  
Mutation Burden

e16650 Background: Biliary tract carcinoma (BTC), including cholangiocarcinoma and gallbladder carcinoma, is the second most common type of hepatobiliary cancer. Patients with BTC always show poor prognosis, here we revealed the molecular landscape of BTC in the Chinese population and evaluated the role of different mutations in informing prognosis. Methods: Formalin-Fixed Paraffin-Embedded (FFPE) or freshly-sampled tumor tissues from 59 BTC patients were conducted next-generation sequencing of 620 genes related to oncogenesis. Tumor mutation burden (TMB) value represents the number of non-synonymous mutations per mega base pairs in each sample. Kaplan-Meier survival curves were generated and compared using the log-rank test. Results: Altogether, 59 patients have mutations mainly in TP53, Ras/Raf, PI3K, CDK signaling pathways and SWI/SNF complex. The most frequently mutated gene was TP53(53%), followed by KRAS(23%), ARID1A(17%), ATM(12%), CDKN2A(10%), SMAD4(8%), BRCA2(8%), STK11(7%), BRAF(5%), IDH1(5%) and FGFR3 (3%). Noticeably, only one patient with FGFR2 fusion was detected. The Median TMB of these patients is 2.80 Muts/Mbp (0-36.52 Muts/Mbp). Existing data showed that KRAS/BRAF alterations were associated with a worse overall survival (OS) (median OS 166d vs. 294d, p= 0.063). Further analysis indicated that RAS/BRAF mutations were often co-current with TP53 alternations. And patients with coaltered RAS/BRAF and TP53 demonstrated the worst prognosis (media OS 123d vs. 294d, p= 0.087). In addition, a higher TMB ( > 2.80 Muts/Mb) was also associated with a worse survival (median OS 174d vs. 355d, p= 0.085). Conclusions: We identified KRAS/BRAF, or co-mutations with TP53 and high TMB could predict poor prognosis in BTC patients. These findings will be useful for clinical decision making in patients with refractory biliary tract cancer and for risk stratification of patients in future clinical studies.

scholarly journals The Monitoring Efficacy of Neurogenic Bowel Dysfunction Treatment on Response (MENTOR) in a Non-Hospital Setting

2021 ◽  
Vol 10 (2) ◽  
pp. 263
Author(s):  
Sofie Dagmar Studsgaard Slot ◽  
Simon Mark Dahl Baunwall ◽  
Anton Emmanuel ◽  
Peter Christensen ◽  
Klaus Krogh
Keyword(s):  
Clinical Decision Making ◽  
Unmet Need ◽  
Hospital Setting ◽  
Clinical Decision ◽  
Bowel Dysfunction ◽  
Social Activities ◽  
Ability To Work ◽  
Treatment Algorithms ◽  
Cord Injury ◽  
Neurogenic Bowel

Background: Most patients with a spinal cord injury (SCI) suffer from neurogenic bowel dysfunction (NBD). In spite of well-established treatment algorithms, NBD is often insufficiently managed. The Monitoring Efficacy of Neurogenic bowel dysfunction Treatment On Response (MENTOR) has been validated in a hospital setting as a tool to support clinical decision making in individual patients. The objective of the present study was to describe clinical decisions recommended by the MENTOR (either “monitor”, “discuss” or “act”) and the use of the tool to monitor NBD in a non-hospital setting. Methods: A questionnaire describing background data, the MENTOR, ability to work and participation in various social activities was sent by mail to all members of The Danish Paraplegic Association. Results: Among 1316 members, 716 (54%) responded, 429 men (61%) and 278 women (39%), aged 18 to 92 (median 61) years. Based on MENTOR, the recommended clinical decision is to monitor treatment of NBD in 281 (44%), discuss change in treatment in 175 (27%) and act/change treatment in 181 (28%). A recommendation to discuss or change treatment was associated with increasing age of the respondent (p = 0.016) and with impaired ability to work or participate in social activities (p < 0.0001). Conclusion: A surprisingly high proportion of persons with SCI have an unmet need for improved bowel care. The MENTOR holds promise as a tool for evaluation of treatment of NBD in a non-hospital setting.

scholarly journals The natural history of intracranial carotid artery atherosclerosis

2005 ◽  
Vol 18 (1) ◽  
pp. 1-3
Author(s):  
Ricardo J. Komotar ◽  
J Mocco ◽  
David A. Wilson ◽  
E. Sander Connolly ◽  
Sean D. Lavine ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Natural History ◽  
Medical Therapy ◽  
Poor Prognosis ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Intracranial Atherosclerosis ◽  
Carotid Artery Atherosclerosis ◽  
History Of ◽  
Maximal Medical Therapy

Intracranial atherosclerosis is the cause of a significant number of strokes. Despite maximal medical therapy, this disease continues to carry a poor prognosis. The authors reviewed studies in which the outcomes after conservative management in patients with intracranial carotid artery atherosclerosis were reported. Analysis of the literature demonstrates that maximal medical therapy frequently fails with this disease, leaving patients at high risk for cerebral infarction and death. A better understanding of the pathophysiological aspects and natural history of this condition may serve to guide clinical decision making and the choice of therapeutic options in this patient population.

scholarly journals Intelligent Approach for Analysis of Respiratory Signals and Oxygen Saturation in the Sleep Apnea/Hypopnea Syndrome

2014 ◽  
Vol 8 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Vicente Moret-Bonillo ◽  
Diego Alvarez-Estévez ◽  
Angel Fernández-Leal ◽  
Elena Hernández-Pereira
Keyword(s):  
Sleep Apnea ◽  
Oxygen Saturation ◽  
Clinical Decision Making ◽  
Temporal Correlation ◽  
Clinical Decision ◽  
Temporal Analysis ◽  
Arterial Blood ◽  
Intelligent Approach ◽  
Hypopnea Syndrome

This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints.

Use of Orange Data Mining Toolbox for Data Analysis in Clinical Decision Making

2018 ◽  
pp. 143-167
Author(s):  
Musa Peker ◽  
Osman Özkaraca ◽  
Ali Şaşar
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
Blood Sugar ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Diabetic Patients ◽  
Proposed Model ◽  
Treatment Of Diabetes

Diabetes is a life-long illness which occurs as a result of lack of insulin hormone or ineffectiveness of insulin hormone. Blood sugar, fructosamine, and hemoglobin A1c (HbA1c) values are widely used for diagnosis of this disease. Although the role of insulin in diagnosing diabetes is great, the HbA1c value is more accurate. This is because HbA1c value gives information about the past two or three months of blood sugar in the treatment of diabetes. This study aims to estimate the HbA1c value with high accuracy. Follow-up data of diabetic patients were used as data. The Orange data mining software is used because it is easy to use in the modeling phase and contains many methods. In this context, the chapter aims to develop an effective prediction model by using a large number of feature selection and classification methods. The results show that the proposed model successfully predicts the HbA1c parameter. In addition, determination of the parameters that are effective in the diagnosis of diabetes has been carried out with the feature selection methods.

Hereditary angioedema and shared decision making

2020 ◽  
Vol 41 (6) ◽  
pp. S55-S60 ◽  
Author(s):  
Russell A. Settipane ◽  
Don A. Bukstein ◽  
Marc A. Riedl
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Hereditary Angioedema ◽  
Clinical Decision Making ◽  
Unmet Need ◽  
Clinical Decision ◽  
Therapeutic Agents ◽  
Shared Decision ◽  
Widespread Implementation ◽  
High Degree

Clinical decision-making in hereditary angioedema (HAE) management involves a high degree of complexity given the number of therapeutic agents that are available and the risk for significant morbidity and potential mortality attributable to the disease. Given this complexity, there is an opportunity to develop shared decision-making (SDM) aids and/or tools that would facilitate the interactive participation of practitioners and patients in the SDM process. This article reviews the general constructs of SDM, the unmet need for SDM in HAE, and the steps necessary to create a SDM tool specific for HAE, and outlines the challenges that must be navigated to guide the establishment and widespread implementation of SDM in the management of HAE.

scholarly journals Current and New Biomarkers for Early Detection, Prognostic Stratification, and Management of Gallbladder Cancer Patients

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3670
Author(s):  
Patricia García ◽  
Angela Lamarca ◽  
Javier Díaz ◽  
Enrique Carrera ◽  
Juan Roa ◽  
...  
Keyword(s):  
Gallbladder Cancer ◽  
Clinical Decision Making ◽  
Unmet Need ◽  
Signs And Symptoms ◽  
Clinical Decision ◽  
Cytochrome P450 1A1 ◽  
Diagnosis And Prognosis ◽  
Molecular Events ◽  
Tumor Mutational Burden ◽  
New Biomarkers

Gallbladder cancer (GBC) is an aggressive disease that shows evident geographic variation and is characterized by a poor prognosis, mainly due to the late diagnosis and ineffective treatment. Genetic variants associated with GBC susceptibility, including polymorphisms within the toll-like receptors TLR2 and TLR4, the cytochrome P450 1A1 (CYP1A1), and the ATP-binding cassette (ABC) transporter ABCG8 genes, represent promising biomarkers for the stratification of patients at higher risk of GBC; thus, showing potential to prioritize cholecystectomy, particularly considering that early diagnosis is difficult due to the absence of specific signs and symptoms. Similarly, our better understanding of the gallbladder carcinogenic processes has led to identify several cellular and molecular events that may influence patient management, including HER2 aberrations, high tumor mutational burden, microsatellite instability, among others. Despite these reports on interesting and promising markers for risk assessment, diagnosis, and prognosis; there is an unmet need for reliable and validated biomarkers that can improve the management of GBC patients and support clinical decision-making. This review article examines the most potentially significant biomarkers of susceptibility, diagnosis, prognosis, and therapy selection for GBC patients, highlighting the need to find and validate existing and new molecular biomarkers to improve patient outcomes.

scholarly journals Prognostic Value of Long Noncoding RNAs in Patients with Gastrointestinal Cancer: A Systematic Review and Meta-Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Weibiao Kang ◽  
Qiang Zheng ◽  
Jun Lei ◽  
Changyu Chen ◽  
Changjun Yu
Keyword(s):  
Gastrointestinal Cancer ◽  
Poor Prognosis ◽  
Prognostic Value ◽  
Clinical Decision Making ◽  
Meta Analysis ◽  
Noncoding Rnas ◽  
Clinical Decision ◽  
Long Noncoding Rnas ◽  
Gastrointestinal Cancers ◽  
Lncrna Expression

Gastrointestinal cancers (GICs) are a huge threat to human health, which mainly include esophageal, gastric, and colorectal cancers. The purpose of this study was to clarify the prognostic value of long noncoding RNAs (lncRNAs) in GICs. A total of 111 articles were included, and 13103 patients (3123 with esophageal cancer, 4972 with gastric cancer, and 5008 with colorectal cancer) were enrolled in this study. The pooled hazard ratio (HR) values and corresponding 95% confidence interval (95% CI) of overall survival (OS) related to different lncRNA expressions in esophageal, gastric, colorectal, and gastrointestinal cancer patients were 1.92 (1.70–2.16), 1.96 (1.77–2.16), 2.10 (1.87–2.36), and 2.00 (1.87–2.13), respectively. We have identified 74 lncRNAs which were associated closely with poor prognosis of GIC patients, including 58 significantly upregulated lncRNA expression and 16 significantly downregulated lncRNA expression. In addition, 47 of the included studies revealed relative mechanisms and 12 of them investigated the correlation between lncRNAs and microRNAs. Taken together, this meta-analysis supports that specific lncRNAs are significantly related to the prognosis of GIC patients and may serve as novel markers for predicting the prognosis of GIC patients. Furthermore, lncRNAs may have a promising contribution to lncRNA-based targeted therapy and clinical decision-making in the future.

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