Establishing Central Sensitization-Related Symptom Severity Subgroups: A Multicountry Study Using the Central Sensitization Inventory

被引：26

作者：

Cuesta-Vargas, Antonio, I ^{[1
,2
]}

Neblett, Randy ^{[3
]}

Nijs, Jo ^{[4
,5
]}

Chiarotto, Alessandro ^{[6
,7
]}

Kregel, Jeroen ^{[8
,9
]}

van Wilgen, C. Paul ^{[4
,5
,10
]}

Pitance, Laurent ^{[11
,12
]}

Knezevic, Aleksandar ^{[13
,14
]}

Gatchel, Robert J. ^{[9
,15
]}

Mayer, Tom G. ^{[16
]}

Viti, Carlotta ^{[17
,18
,19
]}

Roldan-Jimenez, Cristina ^{[1
]}

Testa, Marco ^{[20
]}

Caumo, Wolnei ^{[21
,22
,23
]}

Jeremic-Knezevic, Milica ^{[13
]}

Nishigami, Tomohiko ^{[24
]}

Feliu-Soler, Albert ^{[25
,26
]}

Perez-Aranda, Adrian ^{[25
,26
]}

Luciano, Juan, V ^{[25
,26
]}

机构：

[1] Univ Malaga, Dept Physiotherapy, IBIMA, Fac Hlth Sci, Malaga, Spain

[2] Queensland Univ Technol, Fac Hlth, Brisbane, Qld, Australia

[3] PRIDE Res Fdn, Dallas, TX USA

[4] Vrije Univ Brussel, Fac Phys Educ & Physiotherapy, Dept Physiotherapy Human Physiol & Anat, Pain Mot Int Res Grp, Brussels, Belgium

[5] Univ Hosp Brussels, Dept Phys Med & Physiotherapy, Brussels, Belgium

[6] Vrije Univ Amsterdam, Amsterdam Movement Sci Res Inst, Dept Hlth Sci, Amsterdam, Netherlands

[7] Erasmus MC, Dept Gen Practice, Univ Med Ctr, Rotterdam, Netherlands

[8] Univ Ghent, Fac Med & Hlth Sci, Dept Rehabil Sci & Physiotherapy, Ghent, Belgium

[9] Vrije Univ, Pain Mot Int Res Grp, Brussels, Belgium

[10] Transcare, Transdisciplinary Pain Ctr, Transcare, Netherlands

[11] Catholic Univ Louvain, Inst Clin Res IREC, Neuro Musculoskeletal Lab, Brussels, Belgium

[12] Clin Univ St Luc, Dept Oral & Maxillofacial Surg, Brussels, Belgium

[13] Univ Novi Sad, Fac Med, Novi Sad, Serbia

[14] Clin Ctr Vojvodina, Med Rehabil Clin, Novi Sad, Serbia

[15] Univ Texas Arlington, Coll Sci, Dept Psychol, Arlington, TX 76019 USA

[16] Univ Texas Southwestern Med Ctr Dallas, Dept Orthoped Surg, Dallas, TX 75390 USA

[17] Italian Assoc Integrated Therapy Cervicocranio Fa, FACEit, Barlassina, Italy

[18] Univ Padua, Dept Biomed Sci, Padua, Italy

[19] Fisioterap Viti, Bologna, Italy

[20] Univ Genoa, Dept Neurosci Rehabil Ophthalmol Genet Maternal &, Campus Savona, Savona, Italy

[21] Univ Fed Rio Grande do Sul UFRGS, Sch Med, Postgrad Program Med Sci, Porto Alegre, RS, Brazil

[22] Univ Fed Rio Grande do Sul, Lab Pain & Neuromodulat, Hosp Clin Porto Alegre HCPA, Pain & Palliat Care Serv, Porto Alegre, RS, Brazil

[23] Univ Fed Rio Grande do Sul, Pain & Anesthesia Surg Dept, Sch Med, Porto Alegre, RS, Brazil

[24] Prefectural Univ Hiroshima, Fac Hlth & Welf, Dept Phys Therapy, Hiroshima, Japan

[25] Inst Recerca St Joan de Deu, Esplugas de Llobregat, Spain

[26] Parc Sanitari St Joan de Deu, Teaching Res & Innovat Unit, C Dr Antoni Pujadas 42, St Boi De Llobregat 08830, Spain

来源：

PAIN MEDICINE | 2020年 / 21卷 / 10期

关键词：

Central Sensitization Inventory; Central Sensitization; Central Sensitivity Syndrome; Chronic Pain; Hierarchical Cluster Analysis; Latent Profile Analysis; CHRONIC PAIN PATIENTS; LOW-BACK-PAIN; CROSS-CULTURAL ADAPTATION; PATIENT MMPI SUBGROUPS; ACCEPTANCE QUESTIONNAIRE; PSYCHOMETRIC VALIDATION; POSTOPERATIVE PAIN; CLINICAL-PRACTICE; PROFILE CLUSTERS; IDENTIFICATION;

D O I：

10.1093/pm/pnaa210

中图分类号：

R614 [麻醉学];

学科分类号：

100217 ;

摘要：

Objectives. The goal of this study was to identify central sensitization-related symptom severity subgroups in a large multicountry sample composed of patients with chronic pain and pain-free individuals using the Central Sensitization Inventory (CSI). Methods. A large, pooled international (N =8 countries) sample of chronic pain patients plus healthy subjects (total N = 2,620) was randomly divided into two subsamples for cross-validation purposes. First, a hierarchical cluster analysis (HCA) was performed using CSI item-level data as clustering variables (test sample; N = 1,312). Second, a latent profile analysis (LPA) was conducted to confirm the optimal number of CSI clusters (validation sample; N = 1,308). Finally, to promote implementation in real-world clinical practice, we built a free online Central Sensitization Inventory Symptom Severity Calculator. Results. In both HCA (N = 1,219 valid cases) and LPA (N = 1,245 valid cases) analyses, a three-cluster and three-profile solution, respectively, emerged as the most statistically optimal and clinically meaningful. Clusters were labeled as follows: (i) Low Level of CS-Related Symptom Severity, (ii) Medium Level of CS-Related Symptom Severity, and (iii) High Level of CS-Related Symptom Severity. Conclusions. Our results indicated that a three-cluster solution clearly captured the heterogeneity of the CSI data. The calculator might provide an efficient way of classifying subjects into the cluster groups. Future studies should analyze the extent to which the CSI cluster classification correlates with other patient-reported and objective signs and symptoms of CS in patients with chronic pain, their associations with clinical outcomes, health-related costs, biomarkers, (etc.), and responsiveness to treatment.

引用

页码：2430 / 2440

页数：11

共 60 条

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