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.

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.

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.

Predictors of Surgical Outcomes of Uvulopalatopharyngoplasty for Obstructive Sleep Apnea Hypopnea Syndrome

2011 ◽  
Vol 145 (6) ◽  
pp. 1049-1054 ◽  
Author(s):  
Yuan Ping Xiong ◽  
Hong Liang Yi ◽  
Shan Kai Yin ◽  
Li Li Meng ◽  
Xu Lan Tang ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Lipid Metabolism ◽  
Sleep Apnea ◽  
Oxygen Saturation ◽  
Success Rate ◽  
Surgical Outcomes ◽  
Apnea Hypopnea Index ◽  
Glucose And Lipid Metabolism ◽  
Obstructive Sleep ◽  
Hypopnea Syndrome

Objectives. To investigate predictors of surgical outcomes of uvulopalatopharyngoplasty (UPPP) for obstructive sleep apnea hypopnea syndrome (OSAHS). Study Design. Case series with planned data collection. Setting. A university medical center. Subjects and Methods. Thirty-nine patients with OSAHS received Z-palatopharyngoplasty (ZPPP) or Han-uvulopalatopharyngoplasty (H-UPPP). All patients were evaluated within 3 months before surgery and at 6 to 12 months after surgery. Statistical analyses were conducted on preoperative parameters that could have affected surgical efficacy and outcome. Success was defined as an apnea–hypopnea index (AHI) fewer than 20 times per hour and a decrease of more than 50%. Results. The success rate was 56.4% (22/39 patients). There were statistically significant differences in AHI, lowest oxygen saturation (L-Sao2), time with oxygen saturation less than 90% (CT90), percentage of time with oxygen saturation less than 90% (CT90%), microarousal index (MI), apolipoprotein E (ApoE), high-density lipoprotein (HDL), fasting blood glucose (FBG), and Friedman OSA stage between the treatment success and failure groups. Higher success rate was predicted by lower severity, as indicated by lower AHI, CT90, CT90%, and MI; higher L-Sao2; and fewer glucose and lipid metabolism abnormalities, shown by lower ApoE and FBG and higher HDL. Conclusions. Disease severity, glucose and lipid metabolism, and Friedman OSA stage may be important predictors of surgical outcome of UPPP for OSAHS.

scholarly journals Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

2020 ◽  
Author(s):  
Jaewon Lee ◽  
Vincent Bernard ◽  
Alexander Semaan ◽  
Maria Monberg ◽  
Jonathan Huang ◽  
...  
Keyword(s):  
Single Cell ◽  
Clinical Decision Making ◽  
De Novo ◽  
Ex Vivo ◽  
Clinical Decision ◽  
Ductal Adenocarcinoma ◽  
Cancer Associated Fibroblast ◽  
Parental Tumor

Abstract Precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC) are imperative for improving disease outcomes. However, the long-term fidelity of recently deployed ex vivo preclinical platforms, such as patient-derived organoids (PDOs), remains unknown. Through single-cell RNA sequencing (scRNA-seq), we identify substantial transcriptomic evolution of PDOs propagated from the parental tumor, which may alter predicted drug sensitivity. In contrast, scRNA-seq is readily applicable to limited biopsies from human primary and metastatic PDAC and identifies most cancers as being an admixture of previously described epithelial transcriptomic subtypes. Integrative analyses of our data provide an in-depth characterization of the heterogeneity within the tumor microenvironment, including cancer-associated fibroblast (CAF) subclasses, and predict a multitude of ligand-receptor interactions, revealing potential targets for immunotherapy approaches. While PDOs continue to enable prospective therapeutic prediction, our analysis also demonstrates the complementarity of using orthogonal de novo biopsies from PDAC patients paired with scRNA-seq to inform clinical decision-making.

scholarly journals Circulating Tumor Cell Analysis: Technical and Statistical Considerations for Application to the Clinic

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Alison L. Allan ◽  
Michael Keeney
Keyword(s):  
Metastatic Disease ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Circulating Tumor Cell ◽  
Cell Analysis ◽  
Important Indicator ◽  
Robust Detection ◽  
Technological Advances ◽  
Clinical Detection

Solid cancers are a leading cause of death worldwide, primarily due to the failure of effective clinical detection and treatment of metastatic disease in distant sites. There is growing evidence that the presence of circulating tumor cells (CTCs) in the blood of cancer patients may be an important indicator of the potential for metastatic disease and poor prognosis. Technological advances have now facilitated the enumeration and characterization of CTCs using methods such as PCR, flow cytometry, image-based immunologic approaches, immunomagnetic techniques, and microchip technology. However, the rare nature of these cells requires that very sensitive and robust detection/enumeration methods be developed and validated in order to implement CTC analysis for widespread use in the clinic. This review will focus on the important technical and statistical considerations that must be taken into account when designing and implementing CTC assays, as well as the subsequent interpretation of these results for the purposes of clinical decision making.

Poincaré analysis of an overnight arterial oxygen saturation signal applied to the diagnosis of sleep apnea hypopnea syndrome

2009 ◽  
Vol 30 (4) ◽  
pp. 405-420 ◽  
Author(s):  
Daniel S Morillo ◽  
Juan L Rojas ◽  
Luis F Crespo ◽  
Antonio León ◽  
Nicole Gross
Keyword(s):  
Sleep Apnea ◽  
Oxygen Saturation ◽  
Arterial Oxygen Saturation ◽  
Arterial Oxygen ◽  
Hypopnea Syndrome

scholarly journals Correlation between oxidative stress and cognitive impairment in patients with obstructive sleep apnea hypopnea syndrome

2021 ◽  
pp. 93-93
Author(s):  
Pingdong Jia ◽  
Lewei Ma ◽  
Zhangxia Wang ◽  
Nannan Wang ◽  
Ruomin Liao
Keyword(s):  
Oxidative Stress ◽  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Cognitive Impairment ◽  
Sleep Apnea ◽  
Oxygen Saturation ◽  
Hypoxia Inducible Factor ◽  
Obstructive Sleep ◽  
Independent Risk Factors ◽  
Hypopnea Syndrome

Background/Aim. It is necessary to find eligible oxidative stress markers for predicting the severity of obstructive sleep apnea hypopnea syndrome (OSAHS), a sleep disorder-related respiratory disease. We aimed to explore the correlation between oxidative stress and cognitive impairment in OSAHS patients. Methods. A total of 220 eligible patients were divided into snoring, mild to moderate OSAHS and severe OSAHS groups according to polysomnography (PSG). Apnea-hypopnea index (AHI), oxygen desaturation index (ODI) and baseline data were monitored. Oxidative stress indices were measured by colorimetry in early morning. They were divided into normal cognitive and cognitive impairment groups based on Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Independent risk factors for cognitive impairment were analyzed by multivariate logistic regression. Correlation between oxidative stress and cognitive impairment was analyzed by Pearson?s method. Receiver operating characteristic (ROC) curves were plotted to analyze the efficiency of oxidative stress combined with detection for assessing the cognitive impairment in OSAHS patients. Results. Snoring, mild to moderate OSAHS and severe OSAHS groups had significantly different snoring loudness, BMI, AHI, ODI, MoCA and MMSE scores, and levels of malondialdehyde (MDA), glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD) (P<0.05). Cognitive impairment and normal cognitive groups had different BMI, GSH-Px, MDA and SOD levels, neuroglobin, hypoxia-inducible factor, AHI and lowest nocturnal oxygen saturation (P<0.05 or P<0.01). BMI, GSH-Px, MDA, SOD, neuroglobin, hypoxia-inducible factor, AHI and lowest nocturnal oxygen saturation were independent risk factors for cognitive impairment. The MoCA and MMSE scores of cognitive impairment had positive correlations with GSH-Px and SOD, but negative correlations with MDA (P<0.05). AUCs of GSH-Px, MDA, SOD and their combination for prediction were 0.670, 0.702, 0.705 and 0.836, respectively. Conclusion. Oxidative stress may be the biochemical basis of cognitive impairment in OSAHS patients.

scholarly journals Therapeutic Advances Propelled by Deciphering Tumor Biology and Immunology—Highlights of the 8th Heidelberg Myeloma Workshop

Cancers ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 4135
Author(s):  
Raphael Lutz ◽  
Mirco Friedrich ◽  
Marc Steffen Raab ◽  
Niels Weinhold ◽  
Hartmut Goldschmidt
Keyword(s):  
Patient Outcomes ◽  
Clinical Decision Making ◽  
Residual Disease ◽  
Tumor Biology ◽  
Clinical Decision ◽  
Opinion Leaders ◽  
Research Progress ◽  
Newly Diagnosed ◽  
Current Clinical Trial

The diagnostics and treatment of newly diagnosed and relapsed MM are continuously evolving. While advances in the field of (single cell) genetic analysis now allow for characterization of the disease at an unprecedented resolution, immunotherapeutic approaches and MRD testing are at the forefront of the current clinical trial landscape. Here, we discuss research progress aimed at gaining a better understanding of this heterogenous disease entity, presented at the 8th Heidelberg Myeloma Workshop. We address the questions of whether biology can guide treatment decisions in MM and how assessment for measurable residual disease can help physicians in clinical decision-making. Finally, we summarize current developments in immunotherapeutic approaches that promise improved patient outcomes for MM patients. Besides summarizing key developments in MM research, we highlight perspectives given by key opinion leaders in the field.

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