scholarly journals A Study on the Psychological Status of the Caregivers to Patients Out of ICU after Craniocerebral Tumor Surgery and Their Factors

2021 ◽  
Vol 12 (01) ◽  
pp. 1-11
Author(s):  
Ying Li ◽  
Daili Zou ◽  
Yu Yang ◽  
Yunjia Li ◽  
Qinqin Zhao ◽  
...  
Keyword(s):  
Psychological Status ◽  
Tumor Surgery

Glomus Tumor Surgery: The Approach, Results, and Problems

1982 ◽  
Vol 15 (4) ◽  
pp. 897-916 ◽  
Author(s):  
C.Gary Jackson ◽  
Michael E. Glasscock ◽  
Alan J. Nissen ◽  
Mitchell K. Schwäher
Keyword(s):  
Glomus Tumor ◽  
Tumor Surgery

Endoscopic Pituitary Tumor Surgery: The Learning Curve

2014 ◽  
Vol 75 (S 01) ◽  
Author(s):  
Amjad Anaizi ◽  
Christopher Taylor ◽  
Jennifer Kosty ◽  
Lee Zimmer ◽  
Philip Theodosopoulos
Keyword(s):  
Learning Curve ◽  
Pituitary Tumor ◽  
Tumor Surgery

3D Printed Models for Surgical Planning and Reconstructive Implant Design in Sphenoorbital Tumor Surgery

2016 ◽  
Vol 77 (S 02) ◽  
Author(s):  
Hassan Othman ◽  
Sam Evans ◽  
Daniel Morris ◽  
Saty Bhatia ◽  
Caroline Hayhurst
Keyword(s):  
Surgical Planning ◽  
Implant Design ◽  
Tumor Surgery ◽  
3D Printed

A Strategy for Analysing Multiple Risk Factors with Application to Cervical Pain Syndrome

1989 ◽  
Vol 28 (01) ◽  
pp. 14-19 ◽  
Author(s):  
J. F. Dartigues ◽  
Ph. Peytour ◽  
E. Puymirat ◽  
P. Henry ◽  
M. Gagnon ◽  
...  
Keyword(s):  
Risk Factors ◽  
Low Power ◽  
Head Trauma ◽  
Pain Syndrome ◽  
Psychological Status ◽  
Confounding Factors ◽  
Cervical Pain ◽  
Extreme Form ◽  
Explanatory Variables ◽  
Multiple Risk Factors

Abstract:When studying the possible effects of several factors in a given disease, two major problems arise: (1) confounding, and (2) multiplicity of tests. Frequently, in order to cope with the problem of confounding factors, models with multiple explanatory variables are used. However, the correlation structure of the variables may be such that the corresponding tests have low power: in its extreme form this situation is coined by the term “multicollinearity”. As the problem of multiplicity is still relevant in these models, the interpretation of results is, in most cases, very hazardous. We propose a strategy - based on a tree structure of the variables - which provides a guide to the interpretation and controls the risk of erroneously rejecting null hypotheses. The strategy was applied to a study of cervical pain syndrome involving 990 subjects and 17 variables. Age, sex, head trauma, posture at work and psychological status were all found to be important risk factors.

Smoking and Perioperative Adverse Events in Cranial Tumor Surgery

2018 ◽  
Author(s):  
M.C. Neidert ◽  
L. Padevit ◽  
O. Bozinov ◽  
L. Regli ◽  
J. Sarnthein
Keyword(s):  
Adverse Events ◽  
Tumor Surgery

Machine Learning Algorithm to Predict Early Complications after Brain Tumor Surgery

2018 ◽  
Author(s):  
C.H.B. van Niftrik ◽  
F. van der Wouden ◽  
V. Staartjes ◽  
J. Fierstra ◽  
M. Stienen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Tumor Surgery ◽  
Early Complications ◽  
Brain Tumor Surgery

Integration of an Enhanced Recovery after Anesthesia Program for Patients Undergoing Skull Base Tumor Surgery

2020 ◽  
Author(s):  
Stephanie Flukes ◽  
Ilya Laufer ◽  
Martin Hanson ◽  
Jennifer Cracchiolo ◽  
Eliza Geer ◽  
...  
Keyword(s):  
Skull Base ◽  
Enhanced Recovery ◽  
Skull Base Tumor ◽  
Tumor Surgery
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