Finding the vulnerable postoperative population: A two-step cluster analysis of the PAIN-OUT registry.
Journal
European journal of pain (London, England)
ISSN: 1532-2149
Titre abrégé: Eur J Pain
Pays: England
ID NLM: 9801774
Informations de publication
Date de publication:
09 2022
09 2022
Historique:
revised:
08
06
2022
received:
27
01
2022
accepted:
26
06
2022
pubmed:
29
6
2022
medline:
17
8
2022
entrez:
28
6
2022
Statut:
ppublish
Résumé
Identifying predictors of poor postoperative outcomes is crucial for planning personalized pain treatments. The aim of this study was to examine pain outcomes using cluster analysis in N = 2678 patients from the PAIN-OUT registry at first postoperative day. Indicator variables of the clustering analysis assessed multiple domains, such as clinical and surgical conditions, analgesic-anaesthetic variables, desire for more pain treatment and outcome variables of the International Pain Outcome Questionnaire (IPO) summarized as factor scores. Two-step cluster identified the three-cluster solution as the optimal. Two empirical groups (C1 and C2) included patients with good postoperative outcomes discriminated by peripheral nerve block use, while the other cluster (C3) grouped patients with the worst outcomes, where all patients desired more pain treatment. C3 comprised about 20% of the participants, mostly lower limb, abdominal and spine procedures. The best predictors of belonging to C3 included younger age, being male, preoperative opioid use, bone and fracture reduction procedures, institution, number of comorbidities and morphine equivalents in the recovery room. IPO factor scores can be used to select pain outcomes phenotypes in large clinical databases. Most of the predictors were present before the recovery period so perioperative planning should focus in the preoperative and intraoperative periods. Improvement of postoperative pain requires assessment methods that go beyond pain intensity scores. We perform a cluster analysis among PAIN-OUT patients that revealed a cluster of vulnerable postoperative patients, using a novel composite measure of postoperative outcomes: the factor scores of the International Pain Outcomes Questionnaire. By changing the focus from pain intensity to multidimensional pain outcomes, male gender and number of comorbidities appeared as new risk factors for worse postoperative outcomes. The study also identified procedures that require urgent quality improvements.
Sections du résumé
BACKGROUND
Identifying predictors of poor postoperative outcomes is crucial for planning personalized pain treatments. The aim of this study was to examine pain outcomes using cluster analysis in N = 2678 patients from the PAIN-OUT registry at first postoperative day.
METHODS
Indicator variables of the clustering analysis assessed multiple domains, such as clinical and surgical conditions, analgesic-anaesthetic variables, desire for more pain treatment and outcome variables of the International Pain Outcome Questionnaire (IPO) summarized as factor scores.
RESULTS
Two-step cluster identified the three-cluster solution as the optimal. Two empirical groups (C1 and C2) included patients with good postoperative outcomes discriminated by peripheral nerve block use, while the other cluster (C3) grouped patients with the worst outcomes, where all patients desired more pain treatment. C3 comprised about 20% of the participants, mostly lower limb, abdominal and spine procedures. The best predictors of belonging to C3 included younger age, being male, preoperative opioid use, bone and fracture reduction procedures, institution, number of comorbidities and morphine equivalents in the recovery room.
CONCLUSIONS
IPO factor scores can be used to select pain outcomes phenotypes in large clinical databases. Most of the predictors were present before the recovery period so perioperative planning should focus in the preoperative and intraoperative periods.
SIGNIFICANCE
Improvement of postoperative pain requires assessment methods that go beyond pain intensity scores. We perform a cluster analysis among PAIN-OUT patients that revealed a cluster of vulnerable postoperative patients, using a novel composite measure of postoperative outcomes: the factor scores of the International Pain Outcomes Questionnaire. By changing the focus from pain intensity to multidimensional pain outcomes, male gender and number of comorbidities appeared as new risk factors for worse postoperative outcomes. The study also identified procedures that require urgent quality improvements.
Substances chimiques
Analgesics, Opioid
0
Banques de données
ClinicalTrials.gov
['NCT02083835']
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1732-1745Informations de copyright
© 2022 European Pain Federation - EFIC ®.
Références
Andrew Moore, R., Derry, S., Wiffen, P. J., Banerjee, S., Karan, R., Glimm, E., Wiksten, A., Aldington, D., & Eccleston, C. (2018). Estimating relative efficacy in acute postoperative pain: Network meta-analysis is consistent with indirect comparison to placebo alone. Pain, 159, 2234-2244.
Baca, Q., Marti, F., Poblete, B., Gaudilliere, B., Aghaeepour, N., & Angst, M. S. (2021). Predicting acute pain after surgery: A multivariate analysis. Annals of Surgery, 273, 289-298.
Chapman, C. R., Stevens, D. A., & Lipman, A. G. (2013). Quality of postoperative pain management in American versus european institutions. Journal of Pain & Palliative Care Pharmacotherapy, 27, 350-358.
Chou, R., Gordon, D. B., De Leon-Casasola, O. A., Rosenberg, J. M., Bickler, S., Brennan, T., Carter, T., Cassidy, C. L., Chittenden, E. H., Degenhardt, E., Griffith, S., Manworren, R., McCarberg, B., Montgomery, R., Murphy, J., Perkal, M. F., Suresh, S., Sluka, K., Strassels, S., … Wu, C. L. (2016). Management of postoperative pain: A clinical practice guideline from the American pain society, the American society of regional anesthesia and pain medicine, and the American Society of Anesthesiologists' Committee on Regional Anesthesia, Executive Committee, and Administrative Council. The Journal of Pain, 17, 131-157.
Finner, H. (1993). On a monotonicity problem in step-down multiple test procedures. Journal of the American Statistical Association, 88, 920.
Fletcher, D., & Martinez, V. (2014). Opioid-induced hyperalgesia in patients after surgery: A systematic review and a meta-analysis. British Journal of Anaesthesia, 112, 991-1004.
Gan, T. J. (2017). Poorly controlled postoperative pain: Prevalence, consequences, and prevention. Journal of Pain Research, 10, 2287-2298.
Garduño-López, A. L., Nava, V. M. A., Garcés, L. C., Martínez, D. M. R., Cuellarguzmán, L. F., Villanueva, M. E. F., Villegassotelo, E., Carrillo-Torres, O., Vilchis-Sámano, H., Calderón-Vidal, M., Islaslagunas, G., Chapman, C. R., Komann, M., Meissner, W., Baumbach, P., & Zaslansky, R. (2021). Towards better perioperative pain management in Mexico: A study in a network of hospitals using quality improvement methods from pain out. Journal of Pain Research, 14, 415-430.
Gerbershagen, H. J., Aduckathil, S., van Wijck, A. J. M., Peelen, L. M., Kalkman, C. J., & Meissner, W. (2013). Pain intensity on the first day after surgery: A prospective cohort study comparing 179 surgical procedures. Anesthesiology, 118, 934-944.
Han, J., Kamber, M., & Pei, J. (2012). 10 - Cluster analysis: Basic concepts and methods. In J. Han, M. Kamber, & J. Pei (Eds.), The Morgan Kaufmann series in data management systems, data mining (3rd ed., pp. 443-495). Elsevier Inc. https://doi.org/10.1016/B978-0-12-381479-1.00010-1
Harbaugh, C. M., & Suwanabol, P. A. (2019). Optimizing pain control during the opioid epidemic. The Surgical Clinics of North America, 99(5), 867-883.
Helander, E. M., Billeaud, C. B., Kline, R. J., Emelife, P. I., Harmon, C. M., Prabhakar, A., Urman, R. D., & Kaye, A. D. (2017). Multimodal approaches to analgesia in enhanced recovery after surgery pathways. International Anesthesiology Clinics, 55, 51-69.
Kehlet, H. (2018). Postoperative pain, analgesia, and recovery-bedfellows that cannot be ignored. Pain, 159, S11-S16.
Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological Methods, 17, 137-152.
Khan, J. S., Margarido, C., Devereaux, P. J., Clarke, H., McLellan, A., & Choi, S. (2016). Preoperative celecoxib in noncardiac surgery. European Journal of Anaesthesiology, 33, 204-214.
Komann, M., Baumbach, P., Stamer, U. M., Weinmann, C., Arnold, C., Pogatzki-Zahn, E., & Meißner, W. (2021). Desire to receive more pain treatment - a relevant patient-reported outcome measure to assess quality of post-operative pain management? Results from 79,996 patients enrolled in the pain registry QUIPS from 2016 to 2019. The Journal of Pain, 22, 730-738.
Martinez, V., Beloeil, H., Marret, E., Fletcher, D., Ravaud, P., & Trinquart, L. (2017). Non-opioid analgesics in adults after major surgery: Systematic review with network meta-analysis of randomized trials. British Journal of Anaesthesia, 118, 22-31.
Montes, A., Roca, G., Cantillo, J., & Sabate, S. (2020). Presurgical risk model for chronic postsurgical pain based on 6 clinical predictors: A prospective external validation. Pain, 161, 2611-2618.
Montes, A., Roca, G., Sabate, S., Lao, J. I., Navarro, A., Cantillo, J., & Canet, J. (2015). Genetic and clinical factors associated with chronic postsurgical pain after hernia repair, hysterectomy, and thoracotomy: A two-year multicenter cohort study. Anesthesiology, 122, 1123-1141.
Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14, 535-569.
Pereira, J., Lawlor, P., Vigano, A., Dorgan, M., Bruera, E., & Chb, M. B. (2001). Equianalgesic dose ratios for opioids. A critical review and proposals for long-term dosing. Journal of Pain and Symptom Management, 22, 672-687.
Polanco-García, M., García-Lopez, J., Fàbregas, N., Meissner, W., & Puig, M. M. (2017). Postoperative pain Management in Spanish Hospitals. A cohort study using the PAIN-OUT registry. The Journal of Pain, 18, 1237-1252.
Polanco-García, M., Granero, R., Gallart, L., García-Lopez, J., & Montes, A. (2021). Confirmatory factor analysis of the international pain outcome questionnaire in surgery. PAIN Reports, 6, e903.
Polanco-García, M., Novoa, E., Blanco, N., Pisani, I., & Chamero, A. (2021). Using the factor scores of the international pain outcome questionnaire to evaluate quality improvement program in perioperative pain management [Poster Abstract]. IASP 2021 Virtual World Congress Pain.
Ramsay, M. A. (2019). Postoperative pain management: Is the surgical team approach finally getting it right? Annals of Surgery, 270, 209-210.
Rothaug, J., Zaslansky, R., Schwenkglenks, M., Komann, M., Allvin, R., Backström, R., Brill, S., Buchholz, I., Engel, C., Fletcher, D., Fodor, L., Funk, P., Gerbershagen, H. J., Gordon, D. B., Konrad, C., Kopf, A., Leykin, Y., Pogatzki-Zahn, E., Puig, M., … Meissner, W. (2013). Patients' perception of postoperative pain management: Validation of the international pain outcomes (IPO) questionnaire. The Journal of Pain, 14, 1361-1370.
Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53-65.
Sanfilippo, F., Conticello, C., Santonocito, C., Minardi, C., Palermo, F., Bernardini, R., Gullo, A., & Astuto, M. (2016). Remifentanil and worse patient-reported outcomes regarding postoperative pain management after thyroidectomy. Journal of Clinical Anesthesia, 31, 27-33.
Sen, S., Arulkumar, S., Cornett, E. M., Gayle, J. A., Flower, R. R., Fox, C. J., & Kaye, A. D. (2016). New pain management options for the surgical patient on methadone and buprenorphine. Current Pain and Headache Reports, 20, 1-8.
Shanthanna, H., Ladha, K. S., Kehlet, H., & Joshi, G. P. (2021). Perioperative opioid administration: A critical review of opioid-free versus opioid-sparing approaches. Anesthesiology, 134, 645-659.
Sommer, M., De Rijke, J. M., Van Kleef, M., Kessels, A. G. H., Peters, M. L., Geurts, J. W. J. M., Gramke, H. F., & Marcus, M. A. E. (2008). The prevalence of postoperative pain in a sample of 1490 surgical inpatients. European Journal of Anaesthesiology, 25, 267-274.
Stamer, U. M., Liguori, G. A., & Rawal, N. (2020). Thirty-five years of acute pain services: Where do we go from here? Anesthesia and Analgesia, 131, 650-656.
van Boekel, R. L. M., Bronkhorst, E. M., Vloet, L., Steegers, M. A. M., & Vissers, K. C. P. (2021). Identification of preoperative predictors for acute postsurgical pain and for pain at three months after surgery: A prospective observational study. Scientific Reports, 11, 16459.
van Boekel, R. L. M., Vissers, K. C. P., van der Sande, R., Bronkhorst, E., Lerou, J. G. C., & Steegers, M. A. H. (2017). Moving beyond pain scores: Multidimensional pain assessment is essential for adequate pain management after surgery. PLoS ONE, 12(5), e0177345. https://doi.org/10.1371/journal.pone.0177345
Zaslansky, R., Chapman, C. R., Rothaug, J., Bäckström, R., Brill, S., Davidson, E., Elessi, K., Fletcher, D., Fodor, L., Karanja, E., Konrad, C., Kopf, a., Leykin, Y., Lipman, a., Puig, M., Rawal, N., Schug, S., Ullrich, K., Volk, T., & Meissner, W. (2012). Feasibility of international data collection and feedback on post-operative pain data: Proof of concept. European Journal of Pain, 16, 430-438.
Zaslansky, R., Meissner, W., & Chapman, C. R. (2018). Pain after orthopaedic surgery: Differences in patient reported outcomes in the United States vs internationally. An observational study from the PAIN OUT dataset. British Journal of Anaesthesia, 120, 790-797.