scholarly journals New real-time bowel sound analysis may predict disease severity in septic patients

Critical Care ◽  
2015 ◽  
Vol 19 (Suppl 1) ◽  
pp. P2
Author(s):  
J Goto ◽  
K Matsuda ◽  
N Harii ◽  
T Moriguchi ◽  
M Yanagisawa ◽  
...  
JGH Open ◽  
2021 ◽  
Author(s):  
Tsutomu Namikawa ◽  
Sachi Yamaguchi ◽  
Kazune Fujisawa ◽  
Maho Ogawa ◽  
Jun Iwabu ◽  
...  

2014 ◽  
Vol 18 (1) ◽  
pp. 86-91 ◽  
Author(s):  
Junko Goto ◽  
Kenichi Matsuda ◽  
Norikazu Harii ◽  
Takeshi Moriguchi ◽  
Masahiko Yanagisawa ◽  
...  

2019 ◽  
Vol 12 ◽  
pp. 240-253 ◽  
Author(s):  
Gary Allwood ◽  
Xuhao Du ◽  
K. Mary Webberley ◽  
Adam Osseiran ◽  
Barry James Marshall

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1091
Author(s):  
Ali A. Rabaan ◽  
Raghavendra Tirupathi ◽  
Anupam A Sule ◽  
Jehad Aldali ◽  
Abbas Al Mutair ◽  
...  

Real-time RT-PCR is considered the gold standard confirmatory test for coronavirus disease 2019 (COVID-19). However, many scientists disagree, and it is essential to understand that several factors and variables can cause a false-negative test. In this context, cycle threshold (Ct) values are being utilized to diagnose or predict SARS-CoV-2 infection. This practice has a significant clinical utility as Ct values can be correlated with the viral load. In addition, Ct values have a strong correlation with multiple haematological and biochemical markers. However, it is essential to consider that Ct values might be affected by pre-analytic, analytic, and post-analytical variables such as collection technique, specimen type, sampling time, viral kinetics, transport and storage conditions, nucleic acid extraction, viral RNA load, primer designing, real-time PCR efficiency, and Ct value determination method. Therefore, understanding the interpretation of Ct values and other influential factors could play a crucial role in interpreting viral load and disease severity. In several clinical studies consisting of small or large sample sizes, several discrepancies exist regarding a significant positive correlation between the Ct value and disease severity in COVID-19. In this context, a revised review of the literature has been conducted to fill the knowledge gaps regarding the correlations between Ct values and severity/fatality rates of patients with COVID-19. Various databases such as PubMed, Science Direct, Medline, Scopus, and Google Scholar were searched up to April 2021 by using keywords including “RT-PCR or viral load”, “SARS-CoV-2 and RT-PCR”, “Ct value and viral load”, “Ct value or COVID-19”. Research articles were extracted and selected independently by the authors and included in the present review based on their relevance to the study. The current narrative review explores the correlation of Ct values with mortality, disease progression, severity, and infectivity. We also discuss the factors that can affect these values, such as collection technique, type of swab, sampling method, etc.


2018 ◽  
Vol 39 (7) ◽  
pp. 1267-1272 ◽  
Author(s):  
A.F. Bezuidenhout ◽  
D. Khatami ◽  
C.B. Heilman ◽  
E.M. Kasper ◽  
S. Patz ◽  
...  

2017 ◽  
Vol 19 (01) ◽  
pp. 145-151 ◽  
Author(s):  
Um e Ammara ◽  
Abdullah Mohammed Al-Sadi ◽  
Adel Al-Shihi ◽  
Imran Amin

2021 ◽  
pp. 096228022110619
Author(s):  
Yuanke Qu ◽  
Chun Yin Lee ◽  
KF Lam

Infectious diseases, such as the ongoing COVID-19 pandemic, pose a significant threat to public health globally. Fatality rate serves as a key indicator for the effectiveness of potential treatments or interventions. With limited time and understanding of novel emerging epidemics, comparisons of the fatality rates in real-time among different groups, say, divided by treatment, age, or area, have an important role to play in informing public health strategies. We propose a statistical test for the null hypothesis of equal real-time fatality rates across multiple groups during an ongoing epidemic. An elegant property of the proposed test statistic is that it converges to a Brownian motion under the null hypothesis, which allows one to develop a sequential testing approach for rejecting the null hypothesis at the earliest possible time when statistical evidence accumulates. This property is particularly important as scientists and clinicians are competing with time to identify possible treatments or effective interventions to combat the emerging epidemic. The method is widely applicable as it only requires the cumulative number of confirmed cases, deaths, and recoveries. A large-scale simulation study shows that the finite-sample performance of the proposed test is highly satisfactory. The proposed test is applied to compare the difference in disease severity among Wuhan, Hubei province (exclude Wuhan) and mainland China (exclude Hubei) from February to March 2020. The result suggests that the disease severity is potentially associated with the health care resource availability during the early phase of the COVID-19 pandemic in mainland China.


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