A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain. / Juul, Rasmus V; Knøsgaard, Katrine R; Olesen, Anne E; Pedersen, Katja Venborg; Kreilgaard, Mads; Christrup, Lona L; Osther, Palle J; Drewes, Asbjørn M; Lund, Trine M.

In: A A P S Journal, Vol. 18, No. 4, 07.2016, p. 1013-1022.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Juul, RV, Knøsgaard, KR, Olesen, AE, Pedersen, KV, Kreilgaard, M, Christrup, LL, Osther, PJ, Drewes, AM & Lund, TM 2016, 'A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain', A A P S Journal, vol. 18, no. 4, pp. 1013-1022. https://doi.org/10.1208/s12248-016-9921-2

APA

Juul, R. V., Knøsgaard, K. R., Olesen, A. E., Pedersen, K. V., Kreilgaard, M., Christrup, L. L., Osther, P. J., Drewes, A. M., & Lund, T. M. (2016). A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain. A A P S Journal, 18(4), 1013-1022. https://doi.org/10.1208/s12248-016-9921-2

Vancouver

Juul RV, Knøsgaard KR, Olesen AE, Pedersen KV, Kreilgaard M, Christrup LL et al. A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain. A A P S Journal. 2016 Jul;18(4):1013-1022. https://doi.org/10.1208/s12248-016-9921-2

Author

Juul, Rasmus V ; Knøsgaard, Katrine R ; Olesen, Anne E ; Pedersen, Katja Venborg ; Kreilgaard, Mads ; Christrup, Lona L ; Osther, Palle J ; Drewes, Asbjørn M ; Lund, Trine M. / A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain. In: A A P S Journal. 2016 ; Vol. 18, No. 4. pp. 1013-1022.

Bibtex

@article{b260fb0d450a4f2495f6385ac6a19f58,
title = "A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain",
abstract = "Joint analysis of pain intensity and opioid consumption is encouraged in trials of postoperative pain. However, previous approaches have not appropriately addressed the complexity of their interrelation in time. In this study, we applied a non-linear mixed effects model to simultaneously study pain intensity and opioid consumption in a 4-h postoperative period for 44 patients undergoing percutaneous kidney stone surgery. Analysis was based on 748 Numerical Rating Scale (NRS) scores of pain intensity and 51 observed morphine and oxycodone dosing events. A joint model was developed to describe the recurrent pattern of four key phases determining the development of pain intensity and opioid consumption in time; (A) Distribution of pain intensity scores which followed a truncated Poisson distribution with time-dependent mean score ranging from 0.93 to 2.45; (B) Probability of transition to threshold pain levels (NRS ≥ 3) which was strongly dependent on previous pain levels ranging from 2.8-15.2% after NRS of 0-2; (C) Probability of requesting opioid when allowed (NRS ≥ 3) which was strongly correlated with the number of previous doses, ranging from 89.8% for requesting the first dose to 26.1% after three previous doses; (D) Reduction in pain scores after opioid dosing which was significantly related to the pain intensity at time of opioid request (P < 0.001). This study highlights the importance of analyzing pain intensity and opioid consumption in an integrated manner. Non-linear mixed effects modeling proved a valuable tool for analysis of interventions that affect pain intensity, probability of rescue dosing or the effect of opioids in the postoperative pain period.",
author = "Juul, {Rasmus V} and Kn{\o}sgaard, {Katrine R} and Olesen, {Anne E} and Pedersen, {Katja Venborg} and Mads Kreilgaard and Christrup, {Lona L} and Osther, {Palle J} and Drewes, {Asbj{\o}rn M} and Lund, {Trine M}",
year = "2016",
month = jul,
doi = "10.1208/s12248-016-9921-2",
language = "English",
volume = "18",
pages = "1013--1022",
journal = "A A P S Journal",
issn = "1550-7416",
publisher = "Springer",
number = "4",

}

RIS

TY - JOUR

T1 - A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain

AU - Juul, Rasmus V

AU - Knøsgaard, Katrine R

AU - Olesen, Anne E

AU - Pedersen, Katja Venborg

AU - Kreilgaard, Mads

AU - Christrup, Lona L

AU - Osther, Palle J

AU - Drewes, Asbjørn M

AU - Lund, Trine M

PY - 2016/7

Y1 - 2016/7

N2 - Joint analysis of pain intensity and opioid consumption is encouraged in trials of postoperative pain. However, previous approaches have not appropriately addressed the complexity of their interrelation in time. In this study, we applied a non-linear mixed effects model to simultaneously study pain intensity and opioid consumption in a 4-h postoperative period for 44 patients undergoing percutaneous kidney stone surgery. Analysis was based on 748 Numerical Rating Scale (NRS) scores of pain intensity and 51 observed morphine and oxycodone dosing events. A joint model was developed to describe the recurrent pattern of four key phases determining the development of pain intensity and opioid consumption in time; (A) Distribution of pain intensity scores which followed a truncated Poisson distribution with time-dependent mean score ranging from 0.93 to 2.45; (B) Probability of transition to threshold pain levels (NRS ≥ 3) which was strongly dependent on previous pain levels ranging from 2.8-15.2% after NRS of 0-2; (C) Probability of requesting opioid when allowed (NRS ≥ 3) which was strongly correlated with the number of previous doses, ranging from 89.8% for requesting the first dose to 26.1% after three previous doses; (D) Reduction in pain scores after opioid dosing which was significantly related to the pain intensity at time of opioid request (P < 0.001). This study highlights the importance of analyzing pain intensity and opioid consumption in an integrated manner. Non-linear mixed effects modeling proved a valuable tool for analysis of interventions that affect pain intensity, probability of rescue dosing or the effect of opioids in the postoperative pain period.

AB - Joint analysis of pain intensity and opioid consumption is encouraged in trials of postoperative pain. However, previous approaches have not appropriately addressed the complexity of their interrelation in time. In this study, we applied a non-linear mixed effects model to simultaneously study pain intensity and opioid consumption in a 4-h postoperative period for 44 patients undergoing percutaneous kidney stone surgery. Analysis was based on 748 Numerical Rating Scale (NRS) scores of pain intensity and 51 observed morphine and oxycodone dosing events. A joint model was developed to describe the recurrent pattern of four key phases determining the development of pain intensity and opioid consumption in time; (A) Distribution of pain intensity scores which followed a truncated Poisson distribution with time-dependent mean score ranging from 0.93 to 2.45; (B) Probability of transition to threshold pain levels (NRS ≥ 3) which was strongly dependent on previous pain levels ranging from 2.8-15.2% after NRS of 0-2; (C) Probability of requesting opioid when allowed (NRS ≥ 3) which was strongly correlated with the number of previous doses, ranging from 89.8% for requesting the first dose to 26.1% after three previous doses; (D) Reduction in pain scores after opioid dosing which was significantly related to the pain intensity at time of opioid request (P < 0.001). This study highlights the importance of analyzing pain intensity and opioid consumption in an integrated manner. Non-linear mixed effects modeling proved a valuable tool for analysis of interventions that affect pain intensity, probability of rescue dosing or the effect of opioids in the postoperative pain period.

U2 - 10.1208/s12248-016-9921-2

DO - 10.1208/s12248-016-9921-2

M3 - Journal article

C2 - 27116023

VL - 18

SP - 1013

EP - 1022

JO - A A P S Journal

JF - A A P S Journal

SN - 1550-7416

IS - 4

ER -

ID: 163755488