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A cardiac magnetic resonance test determined the mass to be more consistent with a thrombus than a myxoma through a stepwise approach using multiple pulse sequences.
We planned a stepwise approach using percutaneous transhepatic cholangiodrainage (PTCD) and portal vein embolization (PVE) for secure right hemihepatectomy and biliary-jejunum reconstruction and employed 99mTc-GSA SPECT/CT fusion imaging to estimate future remnant liver function.
Here, we report a case of severe bile duct injury treated with a stepwise approach using 99mTc-galactosyl human serum albumin (99mTc-GSA) single-photon emission computed tomography (SPECT /CT fusion imaging to accurately estimate liver function.
The best and most parsimonious model was chosen by means of a stepwise approach using Akaike's Information Criterion (AIC) as a measure of relative goodness of fit, where smaller values represent better fits, and variables remained in the final model if the associated P value was < 0.05.
The multivariate regression analyses adopted a stepwise approach using entrance/exit tolerance of 0.05/0.10.
In addition, a stepwise approach using DGT followed by WGC-PS as needed facilitated successful biliary cannulation and reduced the need for the needle-knife precut technique.
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Multivariate analysis used the proportional hazards model with a forward stepwise approach using a P-value for inclusion of 0.01.
Variables for multivariate analysis were selected by means of a forward stepwise approach, using a significance level of p < 0.10 for entering into or remaining in the model.
Multivariate analysis of survival data used the proportional hazards model with a forward stepwise approach using a P-value for inclusion of 0.01 because of the inclusion of so many variables.
Discussion: This stepwise approach using an in vitro device enabled us to demonstrate the determination of pharmacokinetic parameters of sotalol.
As with the identification of independent variables used in the S-TPI, a stepwise approach was used to delete from the model, in turn, the independent variable whose removal most improved the model to the point that removal of further variables no longer improve the model.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com