Cargando…

Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study

BACKGROUND: Despite the limitations in the use of cycle threshold (CT) values for individual patient care, population distributions of CT values may be useful indicators of local outbreaks. OBJECTIVE: We aimed to conduct an exploratory analysis of potential correlations between the population distri...

Descripción completa

Detalles Bibliográficos
Autores principales:	Tso, Chak Foon, Garikipati, Anurag, Green-Saxena, Abigail, Mao, Qingqing, Das, Ritankar
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2021
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8176948/ https://www.ncbi.nlm.nih.gov/pubmed/33999831 http://dx.doi.org/10.2196/28265

Ejemplares similares

Semisupervised Deep Learning Techniques for Predicting Acute Respiratory Distress Syndrome From Time-Series Clinical Data: Model Development and Validation Study
por: Lam, Carson, et al.
Publicado: (2021)

Machine learning to predict progression of non‐alcoholic fatty liver to non‐alcoholic steatohepatitis or fibrosis
por: Ghandian, Sina, et al.
Publicado: (2022)

Clinical Outcomes of a Hybrid Model Approach to Applied Behavioral Analysis Treatment
por: Garikipati, Anurag, et al.
Publicado: (2023)

Machine learning early prediction of respiratory syncytial virus in pediatric hospitalized patients
por: Tso, Chak Foon, et al.
Publicado: (2022)

Prediction of short-term mortality in acute heart failure patients using minimal electronic health record data
por: Radhachandran, Ashwath, et al.
Publicado: (2021)

Prediction of diabetic kidney disease with machine learning algorithms, upon the initial diagnosis of type 2 diabetes mellitus
por: Allen, Angier, et al.
Publicado: (2022)

Retrospective validation of a machine learning clinical decision support tool for myocardial infarction risk stratification
por: Panchavati, Saarang, et al.
Publicado: (2021)

Predicting Falls in Long-term Care Facilities: Machine Learning Study
por: Thapa, Rahul, et al.
Publicado: (2022)

Machine learning determination of applied behavioral analysis treatment plan type
por: Maharjan, Jenish, et al.
Publicado: (2023)

Application of deep learning to identify COVID-19 infection in posteroanterior chest X-rays
por: Maharjan, Jenish, et al.
Publicado: (2021)

Predicting ventilator-associated pneumonia with machine learning
por: Giang, Christine, et al.
Publicado: (2021)

Personalized stratification of hospitalization risk amidst COVID-19: A machine learning approach
por: Lam, Carson, et al.
Publicado: (2021)

Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm
por: Maharjan, Jenish, et al.
Publicado: (2022)

Multitask Learning With Recurrent Neural Networks for Acute Respiratory Distress Syndrome Prediction Using Only Electronic Health Record Data: Model Development and Validation Study
por: Lam, Carson, et al.
Publicado: (2022)

Evaluation of cycle threshold values at deisolation
por: Mowrer, Clayton T., et al.
Publicado: (2021)

Early prediction of prostate cancer risk in younger men using polygenic risk scores and electronic health records
por: Varma, Amita, et al.
Publicado: (2022)

Prognostic Value of “Cycle Threshold” in Confirmed COVID-19 Patients
por: Rajyalakshmi, B, et al.
Publicado: (2021)

The many clinical advantages of reporting the cycle threshold (Ct) value
por: Lippi, Giuseppe, et al.
Publicado: (2022)

Laboratory Considerations for Reporting Cycle Threshold Value in COVID-19
por: Punchoo, Rivak, et al.
Publicado: (2022)

A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients
por: Ryan, Logan, et al.
Publicado: (2021)

Assessing the effects of data drift on the performance of machine learning models used in clinical sepsis prediction
por: Rahmani, Keyvan, et al.
Publicado: (2022)

Sociodemographic Factors, Cycle Threshold Values, and Clinical Outcomes of COVID-19
por: Rivera, Frida, et al.
Publicado: (2021)

An exploratory study to estimate cost-effectiveness threshold value for life saving treatments in western Iran
por: Moradi, Najmeh, et al.
Publicado: (2020)

Time Length of Negativization and Cycle Threshold Values in 182 Healthcare Workers with Covid-19 in Milan, Italy: An Observational Cohort Study
por: Cariani, Lisa, et al.
Publicado: (2020)

Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: A retrospective study
por: Ryan, Logan, et al.
Publicado: (2020)

Convolutional Neural Network Model for Intensive Care Unit Acute Kidney Injury Prediction
por: Le, Sidney, et al.
Publicado: (2021)

360. Evaluation of Cycle Threshold Values in Patients with Symptomatic COVID-19 Infection
por: Dixon, Danielle, et al.
Publicado: (2021)

Age and clinical signs as predictors of COVID-19 symptoms and cycle threshold value
por: Dergaa, Ismail, et al.
Publicado: (2021)

Initial viral cycle threshold values in patients with COVID-19 and their clinical significance
por: AlBahrani, Salma, et al.
Publicado: (2022)

Systematic Review on the Correlation of Quantitative PCR Cycle Threshold Values of Gastrointestinal Pathogens With Patient Clinical Presentation and Outcomes
por: Bonacorsi, Stéphane, et al.
Publicado: (2021)

Could threshold cycle value correctly reflect the severity of novel coronavirus disease 2019 (COVID-19)?()
por: Asai, Nobuhiro, et al.
Publicado: (2021)

The importance of cycle threshold values in interpreting molecular tests for SARS-CoV-2
por: Drew, Richard J., et al.
Publicado: (2020)

A Systematic Review of the Clinical Utility of Cycle Threshold Values in the Context of COVID-19
por: Rao, Sonia N., et al.
Publicado: (2020)

Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar
por: Andriamandimby, Soa Fy, et al.
Publicado: (2022)

Natural history and cycle threshold values analysis of COVID-19 in Xiamen City, China
por: Deng, Bin, et al.
Publicado: (2022)

Epidemiology of COVID-19 and the Utility of Cycle Threshold (Ct) Values in Predicting the Severity of Disease
por: George, Anuja, et al.
Publicado: (2023)

Factors associated with cycle threshold values (Ct-values) of SARS-CoV2-rRT-PCR
por: Shoaib, Naila, et al.
Publicado: (2022)

Predicting pulmonary embolism among hospitalized patients with machine learning algorithms
por: Ryan, Logan, et al.
Publicado: (2022)

A longitudinal study on the interchangeable use of whole-body and local exercise thresholds in cycling
por: Caen, Kevin, et al.
Publicado: (2022)

Duration of infectiousness and correlation with RT-PCR cycle threshold values in cases of COVID-19, England, January to May 2020
por: Singanayagam, Anika, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_t7hh231lsvhm2ihj73latq2v2e