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Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis

OBJECTIVES: To elucidate the dynamics of analgesic consumption regarding intravenous patient controlled analgesia (IVPCA) during postoperative period is rather complex partly due to between-patient variation and partly due to within-patient variation. A statistical method was proposed to classify se...

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Autores principales: Lin, Shih-Pin, Chang, Kuang-Yi, Tsou, Mei-Yung, Chen, Tony Hsiu-Hsi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4894765/
https://www.ncbi.nlm.nih.gov/pubmed/26710218
http://dx.doi.org/10.1097/AJP.0000000000000312
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author Lin, Shih-Pin
Chang, Kuang-Yi
Tsou, Mei-Yung
Chen, Tony Hsiu-Hsi
author_facet Lin, Shih-Pin
Chang, Kuang-Yi
Tsou, Mei-Yung
Chen, Tony Hsiu-Hsi
author_sort Lin, Shih-Pin
collection PubMed
description OBJECTIVES: To elucidate the dynamics of analgesic consumption regarding intravenous patient controlled analgesia (IVPCA) during postoperative period is rather complex partly due to between-patient variation and partly due to within-patient variation. A statistical method was proposed to classify serial analgesic consumption into different classifications that were further taken as the multiple outcomes on which to explore the associated predictors. METHODS: We retrospectively included 3284 patients administrated by IVPCA for 3 days after surgery. A repeated measurement design corresponding to serial analgesic consumption variables defined as six-hour total analgesic consumptions was adopted. After determining the numbers of clusters, serial analgesic consumptions were classified into several homogeneous subgroups. Factors associated with new classifications were identified and quantified with a multinominal logistic regression model. RESULTS: Three distinct analgesic classifications were aggregated, including “high”, ”middle” and “low” level of analgesic consumption of IVPCA. The mean analgesic consumptions on 12 successive analgesic consumptions at 6-hour interval of each classification consistently revealed a decreasing trend. As the trends were almost parallel with time, this suggests the time-invariant proportionality of analgesic consumption between the levels of analgesic consumption of IVPCA. Patient’s characteristics, like age, gender, weight, height, and cancer status, were significant factors associated with analgesic classifications. Surgical sites had great impacts on analgesic classifications. DISCUSSION: The serial analgesic consumptions were simplified into 3 analgesic consumptions classifications. The identified predictors are useful to recognize patient’s analgesic classifications before using IVPCA. This study explored a new approach to analysing dynamic changes of postoperative analgesic consumptions.
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spelling pubmed-48947652016-06-21 Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis Lin, Shih-Pin Chang, Kuang-Yi Tsou, Mei-Yung Chen, Tony Hsiu-Hsi Clin J Pain Original Articles OBJECTIVES: To elucidate the dynamics of analgesic consumption regarding intravenous patient controlled analgesia (IVPCA) during postoperative period is rather complex partly due to between-patient variation and partly due to within-patient variation. A statistical method was proposed to classify serial analgesic consumption into different classifications that were further taken as the multiple outcomes on which to explore the associated predictors. METHODS: We retrospectively included 3284 patients administrated by IVPCA for 3 days after surgery. A repeated measurement design corresponding to serial analgesic consumption variables defined as six-hour total analgesic consumptions was adopted. After determining the numbers of clusters, serial analgesic consumptions were classified into several homogeneous subgroups. Factors associated with new classifications were identified and quantified with a multinominal logistic regression model. RESULTS: Three distinct analgesic classifications were aggregated, including “high”, ”middle” and “low” level of analgesic consumption of IVPCA. The mean analgesic consumptions on 12 successive analgesic consumptions at 6-hour interval of each classification consistently revealed a decreasing trend. As the trends were almost parallel with time, this suggests the time-invariant proportionality of analgesic consumption between the levels of analgesic consumption of IVPCA. Patient’s characteristics, like age, gender, weight, height, and cancer status, were significant factors associated with analgesic classifications. Surgical sites had great impacts on analgesic classifications. DISCUSSION: The serial analgesic consumptions were simplified into 3 analgesic consumptions classifications. The identified predictors are useful to recognize patient’s analgesic classifications before using IVPCA. This study explored a new approach to analysing dynamic changes of postoperative analgesic consumptions. Lippincott Williams & Wilkins 2016-06 2016-05-16 /pmc/articles/PMC4894765/ /pubmed/26710218 http://dx.doi.org/10.1097/AJP.0000000000000312 Text en Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially.
spellingShingle Original Articles
Lin, Shih-Pin
Chang, Kuang-Yi
Tsou, Mei-Yung
Chen, Tony Hsiu-Hsi
Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis
title Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis
title_full Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis
title_fullStr Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis
title_full_unstemmed Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis
title_short Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis
title_sort serial analgesic consumptions and predictors of intravenous patient-controlled analgesia with cluster analysis
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4894765/
https://www.ncbi.nlm.nih.gov/pubmed/26710218
http://dx.doi.org/10.1097/AJP.0000000000000312
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