scholarly journals Preliminary study regarding the predicted body weight-based dexamethasone therapy in patients with COVID-19 pneumonia

2021 ◽  
pp. 102108
Author(s):  
Yuri Isaka ◽  
Yasutaka Hirasawa ◽  
Jiro Terada ◽  
Yu Shionoya ◽  
Yuichiro Takeshita ◽  
...  
Keyword(s):  
Body Weight ◽  
Predicted Body Weight ◽  
Dexamethasone Therapy ◽  
Preliminary Study

scholarly journals Assessment of Fluid Responsiveness After Tidal Volume Challenge During Pressure-Controlled Ventilation Volume Guaranteed: An observational study

2020 ◽  
Author(s):  
Yu Jiang ◽  
Lingling Jiang ◽  
Jun Hu ◽  
Ye Zhang
Keyword(s):  
Body Weight ◽  
Tidal Volume ◽  
Fluid Responsiveness ◽  
Transient Increase ◽  
Anesthesia Induction ◽  
Predicted Body Weight ◽  
Controlled Ventilation ◽  
Pressure Controlled Ventilation ◽  
Pressure Controlled ◽  
Volume Challenge

Abstract Background: The reliability of pulse pressure variation (PPV) and stroke volume variation (SVV) to predict fluid responsiveness have not previously been established when using pressure-controlled ventilation-volume guaranteed (PCV-VG) mode. We hypothesized that with a transient increase in tidal volume from 6 to 8 mL/kg of predicted body weight (PBW), which we reference as the “tidal volume challenge (TVC)”, the changes to PPV and SVV will be an indicator of fluid responsiveness.Methods: The patients were first ventilated with a tidal volume of (Vt) 6 mL/kg of predicted body weight (PBW) using PCV-VG. Following intravenous anesthesia induction, PPV6 and SVV6 were recorded, then the TVC was performed, which increased Vt from 6 mL/kg to 8 mL/kg PBW for 1 minute and PPV8 and SVV8 were recorded again. The changes in value of PPV and SVV (ΔPPV6-8 and ΔSVV6-8) were calculated after TVC. Following the minute of TVC, the tidal volume was returned to 6 ml/kg PBW for the fluid challenge (FC), a colloid infusion of 6ml/kg PBW for 20 minutes. Patients were classified as responders if there was an increase in cardiac index (CI) of more than 15% after FC, otherwise the patients were identified as non-responders. Eligible patients were divided into groups of responders or non-responders.Results: 37 patients were classified as responders and 44 were non-responders. PPV6 and SVV6 could not predict the fluid responsiveness, while PPV8 and SVV8 could predict the fluid responsiveness when using PCV-VG mode. The changes in value of PPV and SVV after TVC (ΔPPV6-8 and ΔSVV6-8) identified true fluid responders with the highest sensitivity and specificity in the above variables, which predicted fluid responsiveness with the area under the receiver operating characteristic curves (AUCs) (95% CIs) being 0.96 (0.93-1.00) and 0.98 (0.96-1.00), respectively. No significant difference was found when comparing the AUCs of ΔPPV6-8 and ΔSVV6-8 (P > 0.05). Linear correlation was represented between the change value of CI after FC and the change value of SVV or PPV after TVC (r = 0.68; P < 0.0001 and r = 0.77; P < 0.0001, respectively).Conclusions: A transient increase in tidal volume, which we reference as the “tidal volume challenge (TVC)” could enhance the predictive value of PPV and SVV for the evaluation of fluid responsiveness in patients under ventilation with PCV-VG.Trial registration: Chinese Clinical Trial Registry (ChiCTR2000028995). Prospectively registered on 11 January 2020. http://www.medresman.org.

A preliminary study of insulin participation in the growth regulation of coho salmon (Oncorhynchus kisutch)

1977 ◽  
Vol 55 (10) ◽  
pp. 1756-1758 ◽  
Author(s):  
Bryan Ludwig ◽  
David A. Higgs ◽  
Ulf H. M. Fagerlund ◽  
Jack R. McBride
Keyword(s):  
Body Weight ◽  
Growth Regulation ◽  
Specific Growth ◽  
Coho Salmon ◽  
Pacific Salmon ◽  
Oncorhynchus Kisutch ◽  
Growth Promoter ◽  
Pancreatic B Cells ◽  
Preliminary Study ◽  
Specific Growth Rates

As part of an ongoing survey to identify hormones capable of stimulating growth in Pacific salmon, groups of underyearling coho salmon were injected with bovine (Ultralente) insulin (0.32, 1.0, 3.2, or 10 IU/kg body weight) into the peritoneal cavity either once or twice weekly for 70 days.All doses of insulin, when injected twice weekly, increased the values for specific growth rates and decreased those for food–gain ratios relative to solvent-injected controls, but the differences were not statistically significant. All doses of insulin caused a marked increase in the granulation of the pancreatic B cells. Plasma glucose concentrations in starved coho injected with 10 IU insulin/kg body weight were significantly lower than in solvent-injected controls 4 h after injection.It is concluded that proper evaluation of the effectiveness of insulin as a growth promoter for salmon requires further studies preferably using insulin preparations specific to teleosts.

Predicted Body Weight (PBW)

2012 ◽  
pp. 1803-1803
Author(s):  
Cedric W. Lefebvre ◽  
Jay P. Babich ◽  
James H. Grendell ◽  
James H. Grendell ◽  
John E. Heffner ◽  
...  
Keyword(s):  
Body Weight ◽  
Predicted Body Weight

Effects of Feedback and Education on Nurses’ Clinical Competence in Mechanical Ventilation and Accurate Tidal Volume Setting

2021 ◽  
Author(s):  
Samira Norouzrajabi ◽  
Shahrzad Ghiyasvandian ◽  
Alireza Jeddian ◽  
Ali Karimi Rozveh ◽  
Leila Sayadi
Keyword(s):  
Mechanical Ventilation ◽  
Body Weight ◽  
Tidal Volume ◽  
Clinical Competence ◽  
High Tidal Volume ◽  
Education Intervention ◽  
Predicted Body Weight ◽  
Post Test ◽  
The Mean ◽  
Effects Of Feedback

Background: Patients under mechanical ventilation are at risk of ventilator-associated complications. One of these complications is lung injury due to high tidal volume. Nurses’ competence in mechanical ventilation is critical for preventing ventilator-associated complications. This study assessed the effects of feedback and education on nurses’ clinical competence in mechanical ventilation and accurate tidal volume setting. Methods: This single arm pretest-post-test interventional study was conducted in 2019 at Shariati hospital affiliated to Tehran University of Medical Sciences. Participants were 75 conveniently selected nurses. Initially, nurses’ clinical competence in mechanical ventilation and ventilator parameters of 250 patients were assessed. A mechanical ventilation -based feedback and education intervention was implemented for nurses. Finally, mechanical ventilation clinical competence of nurses and ventilator parameters of 250 new patients were assessed. Moreover, patients’ height was estimated based on their ulna length and then, their predicted body weight was calculated using their estimated height. Accurate tidal volume was determined per predicted body weight.  Results: The mean score of nurses’ clinical competence increased from 8.27±3.09 at pretest to 10.07±3.34 at post-test (p<0.001). The mean values of both total tidal volume and tidal volume per kilogram of predicted body weight were significantly reduced respectively from 529.84±69.11 and 9.11±1.73 (ml) at pretest to 476.30±31.01 and 7.79±1.14 (ml) at post-test (p<0.001). Conclusion: The feedback and education intervention is effective in promoting nurses’ clinical competence in mechanical ventilation and reducing tidal volume. Thereby, it can reduce lung injuries associated with high tidal volume and ensure patient safety.

scholarly journals Using phenotypic distribution models to predict livestock performance

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
M. Lozano-Jaramillo ◽  
S. W. Alemu ◽  
T. Dessie ◽  
H. Komen ◽  
J. W. M. Bastiaansen
Keyword(s):  
Body Weight ◽  
Production Systems ◽  
Machine Learning Algorithms ◽  
Sub Saharan Africa ◽  
Environment Interaction ◽  
Production Environment ◽  
Distribution Models ◽  
Predicted Body Weight ◽  
Lower Productivity ◽  
Phenotype Distribution

Abstract Livestock production systems of the developing world use indigenous breeds that locally adapted to specific agro-ecologies. Introducing commercial breeds usually results in lower productivity than expected, as a result of unfavourable genotype by environment interaction. It is difficult to predict of how these commercial breeds will perform in different conditions encountered in e.g. sub-Saharan Africa. Here, we present a novel methodology to model performance, by using growth data from different chicken breeds that were tested in Ethiopia. The suitability of these commercial breeds was tested by predicting the response of body weight as a function of the environment across Ethiopia. Phenotype distribution models were built using machine learning algorithms to make predictions of weight in the local environmental conditions based on the productivity for the breed. Based on the predicted body weight, breeds were assigned as being most suitable in a given agro-ecology or region. We identified the most important environmental variables that explained the variation in body weight across agro-ecologies for each of the breeds. Our results highlight the importance of acknowledging the role of environment in predicting productivity in scavenging chicken production systems. The use of phenotype distribution models in livestock breeding is recommended to develop breeds that will better fit in their intended production environment.

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