Hostname: page-component-76fb5796d-2lccl Total loading time: 0 Render date: 2024-04-27T07:37:07.032Z Has data issue: false hasContentIssue false

Subjects suffering from bipolar disorder taking lithium are less likely to report physical pain: a FACE-BD study

Published online by Cambridge University Press:  13 December 2023

Nathan Risch*
Affiliation:
Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France Department of Emergency Psychiatry and Post-Acute Care, CHU Montpellier, Montpellier, France Clinique de la Lironde, Clinea Psychiatrie, Saint-Clément-de-Rivière, France
Jonathan Dubois
Affiliation:
Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France Department of Emergency Psychiatry and Post-Acute Care, CHU Montpellier, Montpellier, France
Bruno Etain
Affiliation:
Fondation FondaMental, Créteil, France Département de Psychiatrie et de Médecine Addictologique, AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, DMU Neurosciences, Hôpital Fernand Widal, Paris, France Optimisation Thérapeutique en Neuropsychopharmacologie OTeN, Université Paris Cité, INSERM UMR-S 1144, Paris, France
Bruno Aouizerate
Affiliation:
Fondation FondaMental, Créteil, France Centre Hospitalier Charles Perrens, Bordeaux, France Laboratoire NutriNeuro (UMR INRA 1286), Université de Bordeaux, Bordeaux, France
Frank Bellivier
Affiliation:
Fondation FondaMental, Créteil, France Département de Psychiatrie et de Médecine Addictologique, AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, DMU Neurosciences, Hôpital Fernand Widal, Paris, France Optimisation Thérapeutique en Neuropsychopharmacologie OTeN, Université Paris Cité, INSERM UMR-S 1144, Paris, France
Raoul Belzeaux
Affiliation:
Fondation FondaMental, Créteil, France Pôle Universitaire de Psychiatrie, CHU de Montpellier, Montpellier, France /INT-UMR7289, CNRS Aix-Marseille Université, France
Caroline Dubertret
Affiliation:
Fondation FondaMental, Créteil, France AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, DMU ESPRIT, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France Université de Paris, Inserm UMR1266, Sorbonne Paris Cité, Faculté de Médecine, Paris, France
Emmanuel Haffen
Affiliation:
Fondation FondaMental, Créteil, France Service de Psychiatrie de l’Adulte, CIC-1431 INSERM, CHU de Besançon, Laboratoire de Neurosciences, UFC, UBFC, Besançon, France
Dominique Januel
Affiliation:
Fondation FondaMental, Créteil, France Pôle universitaire 93G03 EPS ville Evrard, Neuilly-sur- Marne, France Université Sorbonne Paris Nord, Bobigny, France
Marion Leboyer
Affiliation:
Fondation FondaMental, Créteil, France Translational NeuroPsychiatry Laboratory, Univ Paris Est Créteil, INSERM U955, IMRB, Créteil, France AP-HP, Hôpitaux Universitaires Henri Mondor, Département Médico-Universitaire de Psychiatrie et d’Addictologie (DMU IMPACT), Fédération Hospitalo-Universitaire de Médecine de Précision en Psychiatrie (FHU ADAPT), Créteil, France
Antoine Lefrere
Affiliation:
Fondation FondaMental, Créteil, France Assistance Publique Hôpitaux de Marseille, Pôle de Psychiatrie, Marseille, France Institut de neurosciences de la Timone UMR 7289, Aix-Marseille Université & CNRS, Marseille, France
Ludovic Samalin
Affiliation:
Fondation FondaMental, Créteil, France University of Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut Pascal, CHU Clermont-Ferrand, Department of Psychiatry, Clermont-Ferrand, France
Mircea Polosan
Affiliation:
Fondation FondaMental, Créteil, France Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France
Romain Rey
Affiliation:
Fondation FondaMental, Créteil, France Centre Hospitalier Le Vinatier, INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, Centre de Recherche en Neurosciences de Lyon, Equipe PSYR2, Pole Est, 95 bd Pinel, BP 30039, Bron Cedex, France
Paul Roux
Affiliation:
Fondation FondaMental, Créteil, France Centre Hospitalier de Versailles, Service Universitaire de Psychiatrie d’Adultes et d’Addictologie, Le Chesnay, Université Paris-Saclay; Université de Versailles Saint-Quentin-En-Yvelines; DisAP-DevPsy-CESP, INSERM UMR1018, Villejuif, France
Raymund Schwan
Affiliation:
Fondation FondaMental, Créteil, France Centre Psychothérapique de Nancy, Inserm, Université de Lorraine, Nancy, France
Michel Walter
Affiliation:
Fondation FondaMental, Créteil, France Service Hospitalo-Universitaire de Psychiatrie Générale et de Réhabilitation Psycho Sociale 29G01 et 29G02, CHRU de Brest, Hôpital de Bohars, Brest, France
Philippe Courtet
Affiliation:
Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France Department of Emergency Psychiatry and Post-Acute Care, CHU Montpellier, Montpellier, France Fondation FondaMental, Créteil, France
Emilie Olié
Affiliation:
Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France Department of Emergency Psychiatry and Post-Acute Care, CHU Montpellier, Montpellier, France Fondation FondaMental, Créteil, France
*
Corresponding author: Nathan Risch; Email: risch.nathan@gmail.com

Abstract

Background

Physical pain is a common issue in people with bipolar disorder (BD). It worsens mental health and quality of life, negatively impacts treatment response, and increases the risk of suicide. Lithium, which is prescribed in BD as a mood stabilizer, has shown promising effects on pain.

Methods

This naturalistic study included 760 subjects with BD ( FACE-BD cohort) divided in two groups: with and without self-reported pain (evaluated with the EQ-5D-5L questionnaire). In this sample, 176 subjects were treated with lithium salts. The objectives of the study were to determine whether patients receiving lithium reported less pain, and whether this effect was associated with the recommended mood-stabilizing blood concentration of lithium.

Results

Subjects with lithium intake were less likely to report pain (odds ratio [OR] = 0.59, 95% confidence interval [CI], 0.35–0.95; p = 0.036) after controlling for sociodemographic variables, BD type, lifetime history of psychiatric disorders, suicide attempt, personality traits, current depression and anxiety levels, sleep quality, and psychomotor activity. Subjects taking lithium were even less likely to report pain when lithium concentration in blood was ≥0.5 mmol/l (OR = 0.45, 95% CI, 0.24–0.79; p = 0.008).

Conclusions

This is the first naturalistic study to show lithium’s promising effect on pain in subjects suffering from BD after controlling for many confounding variables. This analgesic effect seems independent of BD severity and comorbid conditions. Randomized controlled trials are needed to confirm the analgesic effect of lithium salts and to determine whether lithium decreases pain in other vulnerable populations.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is used to distribute the re-used or adapted article and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of European Psychiatric Association

Introduction

Physical pain is highly prevalent in subjects suffering from bipolar disorder (BD) (~30%) [Reference Stubbs, Eggermont, Mitchell, De Hert, Correll and Soundy1]. Pain experienced by subjects suffering from BD seems to be mainly idiopathic (e.g. headache or chronic back pain) [Reference Stubbs, Eggermont, Mitchell, De Hert, Correll and Soundy1]. Pain worsens mental health and quality of life [Reference Risch, Dubois, M’bailara, Cussac, Etain and Belzeaux2]. Indeed, subjects reporting pain have a longer time to remission [Reference Karp, Scott, Houck, Reynolds, Kupfer and Frank3], poorer treatment response [Reference Kroenke, Shen, Oxman, Williams and Dietrich4], and higher suicidal rates [Reference Calati, Laglaoui Bakhiyi, Artero, Ilgen and Courtet5]. Despite the large number of available pain-killer drugs, many subjects still report pain and experience high disability levels [Reference Rice, Smith and Blyth6]. Opioids are among the most efficient analgesic drugs, but they have important side effects: substance use disorder, mood-altering effects, and higher suicide mortality [Reference Bohnert7Reference Vowles, McEntee, Julnes, Frohe, Ney and van der Goes11].

Lithium is recommended and widely used in BD as a mood stabilizer. Some case reports show a promising effect of lithium on pain [Reference Tyber12Reference Sugawara, Sakamoto and Ishigooka14]. A randomized controlled trial (RCT) demonstrated that lithium reduces pain in subjects with spinal cord injury compared to placebo [Reference Yang, Li, So, Chen, Cheng and Wu15]. Moreover, lithium reduces pain in subjects with chronic cluster headaches [Reference Boiardi, Bussone, Merati, Tansini and Boeri16, Reference Bussone, Leone, Peccarisi, Micieli, Granella and Magri17] and is recommended as a prophylactic treatment in this pathology [Reference Leroux and Ducros18]. Animal studies also support the lithium analgesic effect. In neuropathic rat models, lithium decreases thermal hyperalgesia, and mechanical and cold allodynia [Reference Shimizu, Shibata, Wakisaka, Inoue, Mashimo and Yoshiya19Reference Pourmohammadi, Alimoradi, Mehr, Hassanzadeh, Hadian and Sharifzadeh22]. These effects are not observed when lithium is combined with naloxone, suggesting that it acts through the opioid system [Reference Banafshe, Mesdaghinia, Arani, Ramezani, Heydari and Hamidi20].

We hypothesized that (1) subjects suffering from BD and taking lithium are less likely to report physical pain (H1); and (2) subjects suffering from BD and with blood lithium concentration ≥ 0.5 mmol/l (that is the threshold recommended to observe the mood stabilizing effect) [Reference Sproule23] are even less likely to report pain (H2).

Materials and methods

Study population

Participants were recruited from the FACE-BD cohort. This is a French prospective, naturalistic cohort of outpatients with BD enrolled at the advanced Centers of Expertise in Bipolar Disorder (CEBD) and coordinated by the FondaMental Foundation [Reference Henry, Etain, Mathieu, Raust, Vibert and Scott24, Reference Henry, Godin, Courtet, Azorin, Gard and Bellivier25]. Subjects are referred by a general practitioner or a psychiatrist to the expert center where they are evaluated and followed. Participants had a diagnosis of BD type I, II, or not otherwise specified, according to the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), were older than 18 years, and without ongoing severe mood episode at evaluation.

From all the subjects included in the database (n = 2,835), subjects with exhaustive baseline data (that is first evaluation at the CEBD) on pain levels, sex, age, depression level, sleep quality, and affectivity, lability, and intensity, impulsivity and hostility levels were selected (n = 977). Then, subjects treated with lithium but without available blood lithium measurements were excluded (n = 217). Therefore, the final sample included 760 subjects among whom 176 were treated with lithium salts. As treatment at baseline was the one prescribed by the referring physician (that is, current treating physician), the small number of participants taking lithium salts at inclusion could be explained by the current decrease in lithium prescriptions [Reference Kessing, Vradi and Andersen26].

Assessments

From the database, the following data were extracted: sociodemographic variables (age, sex, marital status, education), current psychotropic medications, age at BD onset, number of thymic episodes, number of lifetime suicide attempts and psychiatric comorbidities (recorded by trained psychiatrists or psychologists using the SCID-I), quality of sleep (self-evaluated by the subjects with the Pittsburgh Sleep Quality Index), and potentially painful somatic comorbidities (e.g. multiple sclerosis, cancer, ulcer, rheumatoid arthritis).

Pain

Pain was self-evaluated with the EQ-5D-5L questionnaire [Reference Janssen, Pickard, Golicki, Gudex, Niewada and Scalone27, Reference Feng, Kohlmann, Janssen and Buchholz28]. The EQ-5D-5L is a standardized quality-of-life scale developed by the European EuroQol group. This questionnaire has been validated in several countries, including France [Reference Luo, Li, Chevalier, Lloyd and Herdman29, Reference Andrade, Ludwig, Goni, Oppe and de Pouvourville30]. It includes five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension is rated on a 5-point Likert scale: no problem, slight problems, moderate problems, severe problems, and extreme problems. The standard reference period for the response is the respondent’s “own health state today.”

Using the reported EQ-5D-5L scores, subjects were classified in two groups in function of the presence or absence of moderate or severe problems for the pain/discomfort dimension [Reference Fond, Boyer, Andrianarisoa, Godin, Bulzacka and Berna31]. The EQ-5D-5L pain dimension has good psychometric properties and has shown good responsiveness and discriminative validity in various diseases where pain is a major symptom [Reference Soer, Reneman, Speijer, Coppes and Vroomen32Reference Spronk, Bonsel, Polinder, van Baar, Janssen and Haagsma37]. It is correlated with the scores of specific pain measuring tools, such as pain visual analog scales and the Brief Pain Inventory [Reference Whynes, McCahon, Ravenscroft, Hodgkinson, Evley and Hardman34, Reference Garratt, Furunes, Hellum, Solberg, Brox and Storheim38].

Lithium

Lithium plasma levels (mmol/l) were extracted from the database. For all participants, blood samples were collected 12 hours after the last lithium intake and after fasting.

Affective state

The scores of the following tests were extracted from the database: Young Mania Rating Scale (YMRS; manic state assessment), Quick Inventory of Depressive Symptoms (QIDS) scale (depression level), and Spielberger Anxiety Inventory (STAI Y-A; self-evaluation of anxiety state). Subscales of the Multidimensional Assessment of Thymic States (MAThyS) for subjects suffering from BD were used to evaluate emotional reactivity, cognition, motivation, psychomotor activity, and sensory perception.

Personality traits

Affective traits were self-assessed with the Affective Lability Scale (ALS), the Affect Intensity Measure (AIM), the Barrat Impulsiveness Scale (BIS-10), and the Buss-Durkee Hostility Inventory (BDHI). Two dimensions, overt and covert aggressiveness, were derived from the BDHI because its construction produces these two distinct loaded factors [Reference Bushman, Cooper and Lemke39, Reference Fernandez, Day and Boyle40].

Ethical concerns

A web-based application, e-bipolar©, was developed and is used to collect data for clinical monitoring and research purposes [Reference Henry, Godin, Courtet, Azorin, Gard and Bellivier25]. Access to this web-based system is carefully regulated and the application was approved by the French body overseeing the safety of computerized databases (that is, Commission Nationale de l’Informatique et des Libertés, CNIL) [Reference Henry, Godin, Courtet, Azorin, Gard and Bellivier25]. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All procedures involving human subjects were approved by an ethics committee (CPP-Ile de France IX). All individuals provided written informed consent before entering the study.

Statistical analysis

Variables in the two groups (with and without pain) were compared by univariate analysis. Another univariate analysis was done to compare subjects with and without lithium intake. For quantitative variables, mean and standard deviation (SD) were used. For qualitative variables, number of occurrences and frequencies per class were used. Quantitative and quantitative variables were compared between groups with the t-test or Mann–Whitney test, and the chi-square or Fisher test, respectively.

To test whether pain was associated with lithium intake, two multivariate regression logistic models were used. Model 1 tested whether subjects with lithium intake were less likely to report pain compared with those without lithium intake. Model 2 tested whether subjects with blood lithium concentration ≥ 0.5 mmol/l were even less likely to report pain. To this aim, the sample was classified in three groups: (1) subjects without lithium intake, (2) subjects with blood lithium concentration < 0.5 mmol/l, (3) subjects with blood lithium concentration ≥ 0.5 mmol/l. All analyses were done with R, version 4.2.1 [41].

For each model, confounders were selected from the literature and from our univariate analysis (p < 0.15). The following variables were selected as potential confounders: age, sex, BD type, lifetime psychiatric disorders (anxiety, eating and substance use disorders), past history of suicide attempt, personality traits (affective lability and intensity, impulsivity, aggressiveness according to the ALS, AIM, BIS-10 and BDHI scores, respectively), depression and anxiety levels (QIDS and STAI Y-A scores), sleep quality (PSQI score), and MAThyS subscale scores. Their normal distribution was evaluated. The Box Cox transformation was used for the QIDS score to reduce the influence of positive skewness and of outliers. MAThyS sub-scores were categorized in three classes (that is terciles) because the relation between MAThyS sub-scores and pain was nonlinear [Reference Risch, Dubois, M’bailara, Cussac, Etain and Belzeaux2].

To avoid overfitting, an automatic stepwise forward and backward selection was performedwith the MASS package [Reference Venables, Ripley and Venables42]. Only variables with the best fit were retained, according to the Akaike information criterion (AIC). The odds ratios (OR) and their 95% confidence intervals (CI) were estimated. To discuss the risk accurately, odds ratios were transformed to averaged risk ratios according to Grant [Reference Grant43].

In sensitivity analyses, the following variables were added sequentially to the best model to test whether lithium intake was still associated with pain: psychotropic drugs (anticonvulsants, antipsychotics, anxiolytics, hypnotics, antidepressants) and variables associated in univariate analyses but with missing data (high-school diploma, single, age of first episode, number of depressive episodes, anxiety score, cancer, and ulcer). The number of observations without missing data are reported for each sensitivity analysis.

Results

Sample description

The sample included 463 (60.9%) women, and 339 (44.6%) subjects who had BD type 1. The mean age was 40.2 years (SD = 12.62), the mean QIDS score was 9.56 (SD = 5.75), suggesting a low level of depressive symptomatology, and the mean YMRS score was 2.34 (SD = 3.67), indicating the absence of hypomanic symptoms. According to the EQ-5D-5L score, 171 subjects (22.5%) reported pain. Depressive episodes, lifetime psychiatric comorbidities (anxiety, eating and substance abuse/dependence disorders), and history of suicide attempts were more frequent in subjects who reported pain than in those who did not. Moreover, the levels of depression and anxiety and also of affective lability and intensity, hostility, and impulsivity were higher, and sleep quality was lower in subjects who reported pain. The percentages of subjects taking anxiolytics and lithium salts were higher and lower, respectively, in the group who reported pain (Table 1). Few subjects had somatic comorbidities that were not associated with self-reported pain (Table 1).

Table 1. Sociodemographic and clinical characteristics of the groups with and without pain

Note: *p-values are not corrected for multiple comparison, nor adjusted for other variables.

Abbreviations: AIM, affect intensity measure; ALS, affective lability scale; BD, bipolar disorder; BDHI, Buss–Durkee Hostility Inventory; BIS-10, Barratt Impulsiveness Scale; MAThyS, multidimensional assessment of thymic states; NOS, not otherwise specified; PSQI, Pittsburgh Sleep Quality Index; QIDS-SR, quick inventory of depressive self-report; STAI Y-A, State–Trait Anxiety Inventory; YMRS, Young Mania Rating Scale.

Compared with subjects not treated with lithium salts, subjects taking lithium salts were more often men, with BD type I, had less frequent lifetime anxious and substance abuse/dependence disorders, took less often anticonvulsants, but reported a higher number of past psychiatric hospitalizations. They had lower levels of affective lability and intensity, hostility and impulsivity, and better sleep quality (Supplementary Table S1).

Multivariate analyses

In multivariate analysis (model 1), lithium intake was significantly and negatively associated with reporting pain, that is, subjects on lithium were significantly less likely to report pain (OR = 0.59, 95% CI, 0.35–0.95; p = 0.036) compared with the other subjects (Table 2). The risk of reporting pain was reduced by 36% in subjects on lithium (RR = 0.64, 95% CI, 0.41, 0.96). Model 1 with all confounding variables gave similar results (OR = 0.58, 95% CI, 0.34–0.95; p = 0.035) (Supplementary Table S2), as well as the sensitivity analyses (Supplementary Table S3).

Table 2. Odds ratios for the best model 1 selected based on the AIC

a The reference for comparison is no lithium intake.

b The reference for comparison is the score [0–15] of the MAThyS motivation subscale.

Abbreviations: BDH, Buss–Durkee Hostility Inventory; MAThyS, multidimensional assessment of thymic states; PSQI, Pittsburgh sleep quality index; QIDS-SR, quick inventory of depressive self-report.

Among the 176 subjects with lithium blood level data, 139 had a lithium concentration ≥ 0.5 mmol/l (that is therapeutic concentration). The multivariate analysis (model 2) showed a significant and negative association between lithium concentration and reporting pain (OR = 0.45, 95% CI, 0.24–0.79; p = 0.008), but not in subjects with lithium <0.5 mmol/l (OR = 1.15, 95% CI, 0.49–2.51: p = 0.73) (Table 3). The risk of reporting pain was halved in subjects with lithium ≥0.5 mmol/l (RR = 0.5. 95% CI, 0.28, 0.83). Model 2 with all confounding variables gave the same results (OR = 0.45, 95% CI, 0.23–0.81; p = 0.01), and also the sensitivity analyses (Supplementary Table S4).

Table 3. Odds ratios for the best model 2 selected based on the AIC

a The reference for comparison is no lithium intake.

b The reference for comparison is the score [0–15] of the MAThyS motivation subscale.

Abbreviations: BDHI, Buss–Durkee Hostility Inventory; MAThyS, multidimensional assessment of thymic states; PSQI, Pittsburgh Sleep Quality Index; QIDS-SR, quick inventory of depressive self-report.

Discussion

In our study, individuals treated with lithium were less likely to report physical pain. Moreover, they were two times less likely to report pain when they had the recommended lithium blood level. This indicates that the recommended threshold of lithium efficiency for mood stabilization [Reference Sproule23] is also effective for pain relief. These results remained significant after controlling for many variables, leading us to conclude that our results were not influenced by BD severity or emotional state. Subjects who reported pain also took more drugs, particularly antidepressants and anticonvulsants known to have analgesic effects. However, the intake of psychotropic medications (except lithium) was not associated with a reduced risk of reporting pain. Therefore, it is unlikely that the other psychotropic medications might explain lithium’s positive effect on pain. This negative result may be explained by the naturalistic design of our study. Generally, the analgesic effects of antidepressants and anticonvulsants are reduced in psychiatric patients [Reference Marchettini, Wilhelm, Petto, Tesfaye, Tölle and Bouhassira44]. Future studies should investigate the analgesic effect of antidepressants and anticonvulsants in subjects suffering from BD and reporting pain.

Lithium could be a promising strategy for subjects suffering from BD reporting pain and could also be tested in subjects with chronic pain, independently of mood disorders. Case reports and animal studies suggest that lithium is efficient for different painful pathologies, such as fibromyalgia and neuropathic pain [Reference Tyber12, Reference Fontrier13, Reference Banafshe, Mesdaghinia, Arani, Ramezani, Heydari and Hamidi20]. The current analgesic medications have limited efficiency [Reference Finnerup, Attal, Haroutounian, McNicol, Baron and Dworkin45Reference Jackson, Cogbill, Santana-Davila, Eldredge, Collier and Gradall48] and opioids have serious side effects [Reference Bohnert7, Reference Gomes, Mamdani, Dhalla, Paterson and Juurlink8, Reference Vowles, McEntee, Julnes, Frohe, Ney and van der Goes11]. Moreover, developing new drugs to alleviate pain with acceptable adverse effects is a complex and long process [Reference Percie du Sert and Rice49Reference Knezevic, Yekkirala and Yaksh51]. Lithium is a well-known drug, cheap, with monitorable adverse effects [Reference Volkmann, Bschor and Köhler52]. Lithium effect occurs through multiple mechanisms at different levels, but its blood concentration needs to be >0.5 mmol/l to observe its full mood-stabilizing effect [Reference Alda53]. Lithium prevents the reduction of gray matter volume in brain, restores the balance between excitatory and inhibitory neurotransmission in neurons, and promotes the synthesis of neuroprotective proteins [Reference Malhi, Tanious, Das, Coulston and Berk54]. All these mechanisms are impaired also in pain (e.g. neuropathic pain) [Reference Pan, Zhong, Shang, Zhu, Xiao and Dai55Reference Eaton, Blits, Ruitenberg, Verhaagen and Oudega57], and could be improved with lithium. For example, painful pathologies are associated with hyperalgesia due to N-methyl-D-aspartate (NMDA) receptor activity [Reference Basbaum, Bautista, Scherrer and Julius58]. Chronic lithium intake reduces NMDA receptor activity, promotes glutamate reuptake, and restores the normal excitatory activity [Reference Malhi, Tanious, Das, Coulston and Berk54].

Some limitations must be highlighted. First, the EQ-5D-5L questionnaire is a validated measure of pain intensity, but does not provide any useful information on pain location, duration, and frequency. Thus, we could not determine whether lithium was effective on chronic pain. Second, due to the database format, we could not determine whether the pain reported by patients was related to specific medical conditions or was idiopathic. We also could not assess the effect of lithium on specific painful pathologies. Fibromyalgia and headache are frequently reported by subjects suffering from BD, and lithium could be efficient particularly for these pathologies [Reference Fornaro and Stubbs59Reference Stubbs61]. Third, some variables could have confounded the effect of lithium on pain, such as opioid intake or other somatic comorbidities not recorded in the database. Fourth, the cross-sectional design of our study does not allow highlighting of causal relationships. Lithium could have been prescribed to people with lower depression levels and lower emotional instability, thus favoring the selection of individuals who were less likely to report pain. RCTs are necessary to rule out these potential confounding variables and to confirm our results.

The study has some strengths. We included many variables that could have confounded the effect of lithium on pain, particularly potential painful commodities, and we had the blood lithium concentration. Moreover, we assessed lithium’s effect on pain in naturalistic conditions and this gives an ecological validity to our results.

In conclusion, this is the first naturalistic study showing that lithium has a promising effect on pain in subjects suffering from BD. However, RCTs are necessary to confirm this result. It would be important to determine whether lithium could also decrease pain in subjects reporting chronic pain and in subjects vulnerable to pain.

Supplementary material

The supplementary material for this article can be found at http://doi.org/10.1192/j.eurpsy.2023.2476.

Data availability statement

The datasets generated and/or analyzed during the current study are not publicly available due to the sensitive and identifiable nature of health data but are available from the corresponding author upon reasonable request.

Acknowledgments

We thank the FondaMental Foundation (www-fondation-fondamental.org), a private foundation supporting research in mental health that develops a new model of translational research in psychiatry in France and supports the infrastructure of the Bipolar Expert Centers. We express all our thanks to the nurses, and to the individuals who were included in the present study. We thank Hakim Laouamri, and his team (Seif Ben Salem, Karmène Souyris, Victor Barteau, and Mohamed Laaidi) for the development of the FACE-BD computer interface, data management, quality control, and regulatory aspects. We would like to Elisabetta Andermarcher for the careful proofreading.

Author contribution

Olié E., Courtet Ph., Dubois J., and Risch N. formulated the hypotheses, designed the study, interpreted the results, and wrote the article. Dubois J and Risch N performed statistical analyses. Etain B, Aouizerate B, Bellivier F, Belzeaux R, Dubertret C, Haffen E, Januel D, Lefrere Antoine, Walter M, Rey R, Schwan R, Samalin L, Roux P, Polosan M, Leboyer M, Olié E and Courtet P and FACE BD collaborators participated in partcipants’ inclusion and assessment. All authors contributed to revise the final manuscript. All authors approved the submitted version of the article.

Financial support

This work was funded by Fondation FondaMental (RTRS Santé Mentale), by the Investissements d’Avenir program managed by ANR (references ANR-11-IDEX-0004-02 and ANR-10-COHO-10-01), and by INSERM (Institut National de la Santé et de la Recherche Médicale).

Competing interest

The authors and the FACE BD Collaborators declare none.

Ethical standard

The study was performed according to the Declaration of Helsinki. The protocol was approved by an ethics committee (CPP-Ile de France IX).

Transparency declaration

All of the authors declare that the manuscript is an honest, accurate, and transparent account of the study being reported; and that no important aspects of the study have been omitted.

Footnotes

*

List of FondaMental Advanced Centre of Expertise (FACE-BD) collaborators:1.

1. FACE-BD Clinical Coordinating Center (Fondation FondaMental): B. Etain, E. Olié, M. Leboyer, E. Haffen and PM Llorca;

2.

2. FACE-BD Data Coordinating Center (Fondation FondaMental): V. Barteau, S. Bensalem, O. Godin, H. Laouamri, and K. Souryis;

FACE-BD Clinical Sites and Principal Collaborators in France:3.

3. AP-HP, Département Médico-Universitaire de psychiatrie et d’addictologie, DMU IMPAACT, Hôpitaux Universitaires H Mondor, Créteil: S. Hotier, A. Pelletier, N. Drancourt, JP. Sanchez, E. Saliou, C. Hebbache, J. Petrucci, L. Willaume and E. Bourdin;

4.

4. AP-HP, GHU Paris Nord, DMU Neurosciences, Hôpital Fernand Widal: F. Bellivier, M. Carminati, B. Etain, E. Marlinge, J. Meheust, V. Hennion

5.

5. Hôpital C. Perrens, center Expert Trouble Bipolaire, Service de Psychiatrie Adulte, Pôle 3–4–7, Bordeaux: B. Antoniol, A. Desage, S. Gard, A. Jutant, K. Mbailara, I. Minois, and L. Zanouy;

6.

6. Département d’Urgence et Post Urgence Psychiatrique, CHRU Montpellier, Montpellier: L. Boukhobza, M. Benramdane, P. Courtet, B. Deffinis, S. Denat D. Ducasse, M. Gachet, F. Molière, L. Nass, E. Olié and G. Tarquini;

7.

7. Pôle de Psychiatrie, addictologie et pédopsychiatrie, Hôpital Sainte Marguerite, Marseille: A. Lefrere, L. Lescalier, F. Groppi, E. Moreau, I. Muraccioli, J. Pastol and H.Polomeni;

8.

8. Service de Psychiatrie et Psychologie Clinique, CHU de Nancy, Hôpitaux de Brabois, Vandoeuvre Les Nancy: T. Schwitzer, R. Cohen, M. Milazzo, and O. Wajsbrot-Elgrabli;

9.

9. Service Universitaire de Psychiatrie, CHU de Grenoble et des Alpes, Grenoble: T. Bougerol, B. Fredembach, A. Suisse, A. Pouchon, and M. Polosan;

10.

10. center Hospitalier de Versailles, Service Universitaire de Psychiatrie d’adultes, Le Chesnay; L Brehon, V. Feuga, A.M. Galliot, N. Kayser, C. Passerieux, and P. Roux;

11.

11. Service de Psychiatrie, center Hospitalier Princesse Grace, Monaco: V. Aubin, I. Cussac, M.A. Dupont, J. Loftus, and I. Medecin;

12.

12. Service de psychiatrie et addictologie, Hôpital Louis Mourier, Colombes, AHPH, Groupe Hospitalo-universitaire AP-HP Nord, DMU ESPRIT France: C. Dubertret, N. Mazer, C. Portalier, C. Scognamiglio, A. Bing;

13.

13. Service de Psychiatrie de l’adulte B, center Expert Trouble Bipolaire, CHU de Clermont-Ferrand, Clermont-Ferrand, France: P.M. Llorca, L. Samalin, L. Foures, D. Lacelle, S. Pires, C. Doriat and O. Blanc.

14.

14. Service Hospitalo-Universitaire de Psychiatrie Générale et de Réhabilitation Psycho Sociale 29G01 et 29G02, CHRU de Brest, Hôpital de Bohars, Brest, France: M Walter, V Le Moal

References

Stubbs, B, Eggermont, L, Mitchell, AJ, De Hert, M, Correll, CU, Soundy, A, et al. The prevalence of pain in bipolar disorder: a systematic review and large-scale meta-analysis. Acta Psychiatr Scand. 2015;131:7588. doi:10.1111/acps.12325.Google ScholarPubMed
Risch, N, Dubois, J, M’bailara, K, Cussac, I, Etain, B, Belzeaux, R, et al. Self-reported pain and emotional reactivity in bipolar disorder: a prospective FACE-BD study. J Clin Med. 2022;11:893. doi:10.3390/jcm11030893.Google ScholarPubMed
Karp, JF, Scott, J, Houck, P, Reynolds, CF, Kupfer, DJ, Frank, E. Pain predicts longer time to remission during treatment of recurrent depression. J Clin Psychiatry. 2005;66:591–7. doi:10.4088/JCP.v66n0508.Google ScholarPubMed
Kroenke, K, Shen, J, Oxman, TE, Williams, JW, Dietrich, AJ. Impact of pain on the outcomes of depression treatment: results from the RESPECT trial: Pain. 2008;134:209–15. doi:10.1016/j.pain.2007.09.021.Google ScholarPubMed
Calati, R, Laglaoui Bakhiyi, C, Artero, S, Ilgen, M, Courtet, P. The impact of physical pain on suicidal thoughts and behaviors: meta-analyses. J Psychiatr Res. 2015;71:1632. doi:10.1016/j.jpsychires.2015.09.004.Google ScholarPubMed
Rice, ASC, Smith, BH, Blyth, FM. Pain and the global burden of disease. Pain. 2016;157:791–6. doi:10.1097/j.pain.0000000000000454.Google ScholarPubMed
Bohnert, ASB. Association between opioid prescribing patterns and opioid overdose-related deaths. JAMA. 2011;305:1315. doi:10.1001/jama.2011.370.Google ScholarPubMed
Gomes, T, Mamdani, MM, Dhalla, IA, Paterson, JM, Juurlink, DN. Opioid dose and drug-related mortality in patients with nonmalignant pain. Arch Intern Med. 2011;171:686691. doi:10.1001/archinternmed.2011.117.Google ScholarPubMed
Schaffer, CB, Nordahl, TE, Schaffer, LC, Howe, J. Mood-elevating effects of opioid analgesics in patients with bipolar disorder. J Neuropsychiatry Clin Neurosci. 2007;19:449–52. doi:10.1176/jnp.2007.19.4.449.Google ScholarPubMed
Scherrer, JF, Svrakic, DM, Freedland, KE, Chrusciel, T, Balasubramanian, S, Bucholz, KK, et al. Prescription opioid analgesics increase the risk of depression. J Gen Intern Med. 2014;29:491–9. doi:10.1007/s11606-013-2648-1.Google ScholarPubMed
Vowles, KE, McEntee, ML, Julnes, PS, Frohe, T, Ney, JP, van der Goes, DN. Rates of opioid misuse, abuse, and addiction in chronic pain: a systematic review and data synthesis. Pain. 2015;156:569–76. doi:10.1097/01.j.pain.0000460357.01998.f1.Google ScholarPubMed
Tyber, MA. Lithium carbonate augmentation therapy in fibromyalgia. CMAJ Can Med Assoc J. 1990;143:902.Google ScholarPubMed
Fontrier, T. Lithium for fibromyalgia. Anesth Analg. 2004;98:1505. doi:10.1213/01.ANE.0000114584.16029.0D.Google ScholarPubMed
Sugawara, H, Sakamoto, K, Ishigooka, J. Lithium for bipolar depression with chronic pain. Clin Neuropsychopharmacol Ther. 2010;1:32–4. doi:10.5234/cnpt.1.32.Google Scholar
Yang, ML, Li, JJ, So, KF, Chen, JYH, Cheng, WS, Wu, J, et al. Efficacy and safety of lithium carbonate treatment of chronic spinal cord injuries: a double-blind, randomized, placebo-controlled clinical trial. Spinal Cord. 2012;50:141–6. doi:10.1038/sc.2011.126.Google ScholarPubMed
Boiardi, A, Bussone, G, Merati, B, Tansini, E, Boeri, R. Course of chronic cluster headache. Ital J Neurol Sci. 1983;4:75–7. doi:10.1007/BF02043441.CrossRefGoogle ScholarPubMed
Bussone, G, Leone, M, Peccarisi, C, Micieli, G, Granella, F, Magri, M, et al. Double blind comparison of lithium and verapamil in cluster headache prophylaxis. Headache J Head Face Pain 1990;30:411–7. doi:10.1111/j.1526-4610.1990.hed3007411.x.Google ScholarPubMed
Leroux, E, Ducros, A. Cluster headache. Orphanet J Rare Dis. 2008;3:20. doi:10.1186/1750-1172-3-20.Google ScholarPubMed
Shimizu, T, Shibata, M, Wakisaka, S, Inoue, T, Mashimo, T, Yoshiya, I. Intrathecal lithium reduces neuropathic pain responses in a rat model of peripheral neuropathy. Pain. 2000;85:5964. doi:10.1016/S0304-3959(99)00249-3.CrossRefGoogle Scholar
Banafshe, HR, Mesdaghinia, A, Arani, MN, Ramezani, MH, Heydari, A, Hamidi, GA. Lithium attenuates pain-related behavior in a rat model of neuropathic pain: possible involvement of opioid system. Pharmacol Biochem Behav. 2012;100:425–30. doi:10.1016/j.pbb.2011.10.004.CrossRefGoogle Scholar
Banafshe, HR, Hamidi, GA, Brahimipoor, M. The effect of lithium on painful diabetic neuropathy in streptozotocin-induced diabetic rats. J Neurol Sci. 2013;333:e527. doi:10.1016/j.jns.2013.07.1858.CrossRefGoogle Scholar
Pourmohammadi, N, Alimoradi, H, Mehr, SE, Hassanzadeh, G, Hadian, MR, Sharifzadeh, M, et al. Lithium attenuates peripheral neuropathy induced by paclitaxel in rats. Basic Clin Pharmacol Toxicol. 2012;110:231–7. doi:10.1111/j.1742-7843.2011.00795.x.Google ScholarPubMed
Sproule, B. Lithium in bipolar disorder: can drug concentrations predict therapeutic effect? Clin Pharmacokinet. 2002;41:639–60. doi:10.2165/00003088-200241090-00002.CrossRefGoogle ScholarPubMed
Henry, C, Etain, B, Mathieu, F, Raust, A, Vibert, J-F, Scott, J, et al. A French network of bipolar expert centres: a model to close the gap between evidence-based medicine and routine practice. J Affect Disord. 2011;131:358–63. doi:10.1016/j.jad.2010.11.013.CrossRefGoogle Scholar
Henry, C, Godin, O, Courtet, P, Azorin, J-M, Gard, S, Bellivier, F, et al. Outcomes for bipolar patients assessed in the French expert center network: a 2-year follow-up observational study (FondaMental advanced centers of expertise for bipolar disorder [FACE-BD]). Bipolar Disord. 2017;19:651–60. doi:10.1111/bdi.12539.CrossRefGoogle ScholarPubMed
Kessing, LV, Vradi, E, Andersen, PK. Nationwide and population-based prescription patterns in bipolar disorder. Bipolar Disord. 2016;18:174–82. doi:10.1111/bdi.12371.CrossRefGoogle ScholarPubMed
Janssen, MF, Pickard, AS, Golicki, D, Gudex, C, Niewada, M, Scalone, L, et al. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res. 2013;22:1717–27. doi:10.1007/s11136-012-0322-4.CrossRefGoogle Scholar
Feng, Y-S, Kohlmann, T, Janssen, MF, Buchholz, I. Psychometric properties of the EQ-5D-5L: a systematic review of the literature. Qual Life Res. 2021;30:647–73. doi:10.1007/s11136-020-02688-y.Google ScholarPubMed
Luo, N, Li, M, Chevalier, J, Lloyd, A, Herdman, M. A comparison of the scaling properties of the English, Spanish, French, and Chinese EQ-5D descriptive systems. Qual Life Res. 2013;22:2237–43. doi:10.1007/s11136-012-0342-0.CrossRefGoogle ScholarPubMed
Andrade, LF, Ludwig, K, Goni, JMR, Oppe, M, de Pouvourville, G. A French value set for the EQ-5D-5L. PharmacoEconomics. 2020;38:413–25. doi:10.1007/s40273-019-00876-4.CrossRefGoogle ScholarPubMed
Fond, G, Boyer, L, Andrianarisoa, M, Godin, O, Bulzacka, E, Berna, F, et al. Self-reported pain in patients with schizophrenia. Results from the national first-step FACE-SZ cohort. Prog Neuro-Psychopharmacol Biol Psychiatry. 2018;85:62–8. doi:10.1016/j.pnpbp.2018.04.007.Google ScholarPubMed
Soer, R, Reneman, MF, Speijer, BLGN, Coppes, MH, Vroomen, PCAJ. Clinimetric properties of the EuroQol-5D in patients with chronic low back pain. Spine J. 2012;12:1035–9. doi:10.1016/j.spinee.2012.10.030.Google ScholarPubMed
Obradovic, M, Lal, A, Liedgens, H. Validity and responsiveness of EuroQol-5 dimension (EQ-5D) versus short Form-6 dimension (SF-6D) questionnaire in chronic pain. Health Qual Life Outcomes. 2013;11:110. doi:10.1186/1477-7525-11-110.CrossRefGoogle ScholarPubMed
Whynes, DK, McCahon, RA, Ravenscroft, A, Hodgkinson, V, Evley, R, Hardman, JG. Responsiveness of the EQ-5D health-related quality-of-life instrument in assessing low back pain. Value Health. 2013;16:124–32. doi:10.1016/j.jval.2012.09.003.Google ScholarPubMed
Durham, J, Steele, JG, Breckons, M, Story, W, Vale, L. DEEP study: does EQ-5D-5L measure the impacts of persistent oro-facial pain? J Oral Rehabil. 2015;42:643–50. doi:10.1111/joor.12296.CrossRefGoogle ScholarPubMed
Tawiah, AK, Al Sayah, F, Ohinmaa, A, Johnson, JA. Discriminative validity of the EQ-5D-5 L and SF-12 in older adults with arthritis. Health Qual Life Outcomes. 2019;17:68. doi:https://doi.org/10.1186/s12955-019-1129-6.CrossRefGoogle ScholarPubMed
Spronk, I, Bonsel, GJ, Polinder, S, van Baar, ME, Janssen, MF, Haagsma, JA. Exploring the relation between the EQ-5D-5L pain/discomfort and pain and itching in a sample of burn patients. Health Qual Life Outcomes. 2020;18:144. doi:10.1186/s12955-020-01394-0.CrossRefGoogle Scholar
Garratt, AM, Furunes, H, Hellum, C, Solberg, T, Brox, JI, Storheim, K, et al. Evaluation of the EQ-5D-3L and 5L versions in low back pain patients. Health Qual Life Outcomes. 2021;19:155. doi:10.1186/s12955-021-01792-y.CrossRefGoogle ScholarPubMed
Bushman, BJ, Cooper, HM, Lemke, KM. Meta-analysis of factor analyses: an illustration using the buss-Durkee hostility inventory. Personal Soc Psychol Bull. 1991;17:344–9. doi:10.1177/0146167291173015.Google Scholar
Fernandez, E, Day, A, Boyle, GJ. Measures of anger and hostility in adults. In: Measures of personality and social psychological constructs. The Netherlands: Elsevier; 2015, p. 74100. doi:10.1016/B978-0-12-386915-9.00004-8.Google Scholar
R Core Team. R: a language and environment for statistical computing. Vienna: R foundation; 2022.Google Scholar
Venables, WN, Ripley, BD, Venables, WN. Modern applied statistics with S. 4th ed. New York: Springer; 2002.Google Scholar
Grant, RL. Converting an odds ratio to a range of plausible relative risks for better communication of research findings. BMJ. 2014;348:f7450. doi:10.1136/bmj.f7450.Google ScholarPubMed
Marchettini, P, Wilhelm, S, Petto, H, Tesfaye, S, Tölle, T, Bouhassira, D, et al. Are there different predictors of analgesic response between antidepressants and anticonvulsants in painful diabetic neuropathy? Eur J Pain. 2016;20:472–82. doi:10.1002/ejp.763.CrossRefGoogle ScholarPubMed
Finnerup, NB, Attal, N, Haroutounian, S, McNicol, E, Baron, R, Dworkin, RH, et al. Pharmacotherapy for neuropathic pain in adults: a systematic review and meta-analysis. Lancet Neurol. 2015;14:162–73. doi:10.1016/S1474-4422(14)70251-0.CrossRefGoogle ScholarPubMed
van de Laar, M. Pain treatment in arthritis-related pain: beyond NSAIDs. Open Rheumatol J. 2012;6:320–30. doi:10.2174/1874312901206010320.Google Scholar
Chou, R, Deyo, R, Friedly, J, Skelly, A, Weimer, M, Fu, R, et al. Systemic pharmacologic therapies for low back pain: a systematic review for an American College of Physicians Clinical Practice Guideline. Ann Intern Med. 2017;166:480. doi:10.7326/M16-2458.Google ScholarPubMed
Jackson, JL, Cogbill, E, Santana-Davila, R, Eldredge, C, Collier, W, Gradall, A, et al. A comparative effectiveness meta-analysis of drugs for the prophylaxis of migraine headache. PLoS One. 2015;10:e0130733. doi:10.1371/journal.pone.0130733.Google ScholarPubMed
Percie du Sert, N, Rice, ASC. Improving the translation of analgesic drugs to the clinic: animal models of neuropathic pain: Improving models of neuropathic pain. Br J Pharmacol. 2014;171:2951–63. doi:10.1111/bph.12645.CrossRefGoogle Scholar
Yaksh, TL, Woller, SA, Ramachandran, R, Sorkin, LS. The search for novel analgesics: targets and mechanisms. F1000Prime Rep. 2015;7:56. doi:10.12703/P7-56.Google ScholarPubMed
Knezevic, NN, Yekkirala, A, Yaksh, TL. Basic/translational development of forthcoming opioid- and nonopioid-targeted pain therapeutics. Anesth Analg. 2017;125:1714–32. doi:10.1213/ANE.0000000000002442.CrossRefGoogle ScholarPubMed
Volkmann, C, Bschor, T, Köhler, S. Lithium treatment over the lifespan in bipolar disorders. Front Psychiatry. 2020;11:377. doi:10.3389/fpsyt.2020.00377.Google ScholarPubMed
Alda, M. Lithium in the treatment of bipolar disorder: pharmacology and pharmacogenetics. Mol Psychiatry. 2015;20:661–70. doi:10.1038/mp.2015.4.Google ScholarPubMed
Malhi, GS, Tanious, M, Das, P, Coulston, CM, Berk, M. Potential mechanisms of action of lithium in bipolar disorder: current understanding. CNS Drugs. 2013;27:135–53. doi:10.1007/s40263-013-0039-0.Google ScholarPubMed
Pan, PL, Zhong, JG, Shang, HF, Zhu, YL, Xiao, PR, Dai, ZY, et al. Quantitative meta-analysis of grey matter anomalies in neuropathic pain. Eur J Pain. 2015;19:1224–31. doi:10.1002/ejp.670.Google ScholarPubMed
Petrou, M, Pop-Busui, R, Foerster, BR, Edden, RA, Callaghan, BC, Harte, SE, et al. Altered excitation-inhibition balance in the brain of patients with diabetic neuropathy. Acad Radiol. 2012;19:607–12. doi:10.1016/j.acra.2012.02.004.Google ScholarPubMed
Eaton, MJ, Blits, B, Ruitenberg, MJ, Verhaagen, J, Oudega, M. Amelioration of chronic neuropathic pain after partial nerve injury by adeno-associated viral (AAV) vector-mediated over-expression of BDNF in the rat spinal cord. Gene Ther. 2002;9:1387–95. doi:10.1038/sj.gt.3301814.Google ScholarPubMed
Basbaum, AI, Bautista, DM, Scherrer, G, Julius, D. Cellular and molecular mechanisms of pain. Cell. 2009;139:267–84. doi:10.1016/j.cell.2009.09.028.CrossRefGoogle ScholarPubMed
Fornaro, M, Stubbs, B. A meta-analysis investigating the prevalence and moderators of migraines among people with bipolar disorder. J Affect Disord. 2015;178:8897. doi:10.1016/j.jad.2015.02.032.CrossRefGoogle ScholarPubMed
Kudlow, PA, Rosenblat, JD, Weissman, CR, Cha, DS, Kakar, R, McIntyre, RS, et al. Prevalence of fibromyalgia and co-morbid bipolar disorder: a systematic review and meta-analysis. J Affect Disord. 2015;188:134–42. doi:10.1016/j.jad.2015.08.030.CrossRefGoogle ScholarPubMed
Stubbs, B. A random effects meta-analysis investigating the prevalence of bipolar disorder in people with fibromyalgia: an updated analysis. J Affect Disord. 2016;191:308–9. doi:10.1016/j.jad.2015.12.006.Google ScholarPubMed
Figure 0

Table 1. Sociodemographic and clinical characteristics of the groups with and without pain

Figure 1

Table 2. Odds ratios for the best model 1 selected based on the AIC

Figure 2

Table 3. Odds ratios for the best model 2 selected based on the AIC

Supplementary material: File

Risch et al. supplementary material

Risch et al. supplementary material
Download Risch et al. supplementary material(File)
File 37.3 KB
Submit a response

Comments

No Comments have been published for this article.