Cargando…
Using Computed Tomography Scans and Patient Demographic Data to Estimate Thoracic Epidural Space Depth
Background and Objectives. Previous studies have used varying methods to estimate the depth of the epidural space prior to placement of an epidural catheter. We aim to use computed tomography scans, patient demographics, and vertebral level to estimate the depth of the loss of resistance for placeme...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415614/ https://www.ncbi.nlm.nih.gov/pubmed/25960890 http://dx.doi.org/10.1155/2015/470240 |
_version_ | 1782369099018403840 |
---|---|
author | Kosturakis, Alyssa Soliz, Jose Su, Jackson Cata, Juan P. Feng, Lei Harun, Nusrat Amsbaugh, Ashley Gebhardt, Rodolfo |
author_facet | Kosturakis, Alyssa Soliz, Jose Su, Jackson Cata, Juan P. Feng, Lei Harun, Nusrat Amsbaugh, Ashley Gebhardt, Rodolfo |
author_sort | Kosturakis, Alyssa |
collection | PubMed |
description | Background and Objectives. Previous studies have used varying methods to estimate the depth of the epidural space prior to placement of an epidural catheter. We aim to use computed tomography scans, patient demographics, and vertebral level to estimate the depth of the loss of resistance for placement of thoracic epidural catheters. Methods. The records of consecutive patients who received a thoracic epidural catheter were reviewed. Patient demographics, epidural placement site, and technique were collected. Preoperative computed tomography scans were reviewed to measure the skin to epidural space distance. Linear regression was used for a multivariate analysis. Results. The records of 218 patients were reviewed. The mean loss of resistance measurement was significantly larger than the mean computed tomography epidural space depth measurement by 0.79 cm (p < 0.001). Our final multivariate model, adjusted for demographic and epidural technique, showed a positive correlation between the loss of resistance and the computed tomography epidural space depth measurement (R (2) = 0.5692, p < 0.0001). Conclusions. The measured loss of resistance is positively correlated with the computed tomography epidural space depth measurement and patient demographics. For patients undergoing thoracic or abdominal surgery, estimating the loss of resistance can be a valuable tool. |
format | Online Article Text |
id | pubmed-4415614 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-44156142015-05-10 Using Computed Tomography Scans and Patient Demographic Data to Estimate Thoracic Epidural Space Depth Kosturakis, Alyssa Soliz, Jose Su, Jackson Cata, Juan P. Feng, Lei Harun, Nusrat Amsbaugh, Ashley Gebhardt, Rodolfo Pain Res Treat Research Article Background and Objectives. Previous studies have used varying methods to estimate the depth of the epidural space prior to placement of an epidural catheter. We aim to use computed tomography scans, patient demographics, and vertebral level to estimate the depth of the loss of resistance for placement of thoracic epidural catheters. Methods. The records of consecutive patients who received a thoracic epidural catheter were reviewed. Patient demographics, epidural placement site, and technique were collected. Preoperative computed tomography scans were reviewed to measure the skin to epidural space distance. Linear regression was used for a multivariate analysis. Results. The records of 218 patients were reviewed. The mean loss of resistance measurement was significantly larger than the mean computed tomography epidural space depth measurement by 0.79 cm (p < 0.001). Our final multivariate model, adjusted for demographic and epidural technique, showed a positive correlation between the loss of resistance and the computed tomography epidural space depth measurement (R (2) = 0.5692, p < 0.0001). Conclusions. The measured loss of resistance is positively correlated with the computed tomography epidural space depth measurement and patient demographics. For patients undergoing thoracic or abdominal surgery, estimating the loss of resistance can be a valuable tool. Hindawi Publishing Corporation 2015 2015-04-16 /pmc/articles/PMC4415614/ /pubmed/25960890 http://dx.doi.org/10.1155/2015/470240 Text en Copyright © 2015 Alyssa Kosturakis et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Kosturakis, Alyssa Soliz, Jose Su, Jackson Cata, Juan P. Feng, Lei Harun, Nusrat Amsbaugh, Ashley Gebhardt, Rodolfo Using Computed Tomography Scans and Patient Demographic Data to Estimate Thoracic Epidural Space Depth |
title | Using Computed Tomography Scans and Patient Demographic Data to Estimate Thoracic Epidural Space Depth |
title_full | Using Computed Tomography Scans and Patient Demographic Data to Estimate Thoracic Epidural Space Depth |
title_fullStr | Using Computed Tomography Scans and Patient Demographic Data to Estimate Thoracic Epidural Space Depth |
title_full_unstemmed | Using Computed Tomography Scans and Patient Demographic Data to Estimate Thoracic Epidural Space Depth |
title_short | Using Computed Tomography Scans and Patient Demographic Data to Estimate Thoracic Epidural Space Depth |
title_sort | using computed tomography scans and patient demographic data to estimate thoracic epidural space depth |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415614/ https://www.ncbi.nlm.nih.gov/pubmed/25960890 http://dx.doi.org/10.1155/2015/470240 |
work_keys_str_mv | AT kosturakisalyssa usingcomputedtomographyscansandpatientdemographicdatatoestimatethoracicepiduralspacedepth AT solizjose usingcomputedtomographyscansandpatientdemographicdatatoestimatethoracicepiduralspacedepth AT sujackson usingcomputedtomographyscansandpatientdemographicdatatoestimatethoracicepiduralspacedepth AT catajuanp usingcomputedtomographyscansandpatientdemographicdatatoestimatethoracicepiduralspacedepth AT fenglei usingcomputedtomographyscansandpatientdemographicdatatoestimatethoracicepiduralspacedepth AT harunnusrat usingcomputedtomographyscansandpatientdemographicdatatoestimatethoracicepiduralspacedepth AT amsbaughashley usingcomputedtomographyscansandpatientdemographicdatatoestimatethoracicepiduralspacedepth AT gebhardtrodolfo usingcomputedtomographyscansandpatientdemographicdatatoestimatethoracicepiduralspacedepth |