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BMC Musculoskeletal Disorders

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Neuropathic pain in patients with rotator cuff tears

  • Tatsuki Karasugi1,
  • Junji Ide2Email author,
  • Toshio Kitamura3,
  • Nobukazu Okamoto1,
  • Takuya Tokunaga1 and
  • Hiroshi Mizuta1
BMC Musculoskeletal DisordersBMC series – open, inclusive and trusted201617:451

https://doi.org/10.1186/s12891-016-1311-5

Received: 12 April 2016

Accepted: 26 October 2016

Published: 2 November 2016

Abstract

Background

Recent studies have confirmed the existence of neuropathic pain (NeP) components in patients with musculoskeletal disorders. However, the presence of NeP in patients with rotator cuff tears has not been investigated thus far. Therefore, we studied the prevalence of NeP and the prognostic factors for NeP in patients with rotator cuff tears.

Methods

Data were collected from 110 patients with rotator cuff tears, diagnosed by physical examination and magnetic resonance imaging, who attended an outpatient clinic between August 2013 and August 2014. The measured parameters included visual analog scale (VAS) pain scores, painDETECT questionnaire (PDQ) responses, a physical examination, and magnetic resonance imaging. To evaluate the factors associated with NeP, we performed a two-stage analysis. For univariate analysis, we used the Mann-Whitney U test. For multivariate analysis, forward stepwise regression was performed using factors that demonstrated statistical significance in the univariate analysis.

Results

Patients were classified into three groups according to their PDQ score: an NeP group (n = 12; 10.9 %), possible NeP group (n = 33; 30.0 %), and a nociceptive pain (NoP) group (n = 65; 59.1 %). In the univariate analysis between the NeP group and NoP group, NeP was affected by sex (p = 0.034), VAS score (average pain during the past 4 weeks; p = 0.013), and positive Neer and Hawkins impingement signs (p = 0.039). In the multivariate analysis, VAS score (p = 0.031) was an independent prognostic factor for NeP.

Conclusions

Using the PDQ, we found that 10.9 % of patients with rotator cuff tears may have NeP. The VAS score (average pain during the past 4 weeks) was a prognostic factor for NeP. Clinicians should remain vigilant for heterogeneous etiologies of pain in patients with rotator cuff tears.

Keywords

Neuropathic painNociceptive painpainDETECT questionnaireRotator cuff tear

Background

Rotator cuff tear is one of the major causes of pain and dysfunction of the shoulder in the middle-aged population. According to a recent epidemiological study, the prevalence of rotator cuff tears was found to be 20.7 % in the general population, with a mean age of 58 years (range, 22–87 years), and increased with age [1]. Rotator cuff tear can lead to persistent shoulder pain and considerable disability. Although the pain caused by rotator cuff tears is generally classified as nociceptive pain (NoP), occasionally, it does not improve with anti-inflammatory medication, and continued pain becomes the main surgical indication.

The primary etiology of pain in musculoskeletal disorders is mechanical stimulation and inflammation [2]. However, recent studies have shown the clear existence of neuropathic pain (NeP) components in patients with chronic low back pain and knee osteoarthritis based on responses to the painDETECT questionnaire (PDQ) [3, 4]. Recently, Gwilym et al. used the PDQ to detect NeP in patients with impingement syndrome of the shoulder [5]. Correct identification of NeP in musculoskeletal disorders enables the introduction of the appropriate treatment for musculoskeletal pain. The PDQ is not only a simple and efficient screening tool to identify the likelihood of NeP, but also demonstrates higher sensitivity and specificity than that of other screening tools for NeP [3, 6]. Clinicians are strongly recommended to use the PDQ to assess for the presence of NeP [7]. However, the existence of NeP in patients with rotator cuff tears has not been investigated thus far. Therefore, the aim of this study was to examine the prevalence of NeP in patients with rotator cuff tears using the PDQ, and to elucidate the factors associated with NeP. We hypothesized that the etiology of shoulder pain in patients with rotator cuff tears may be multifactorial, with a mixture of nociceptive and neuropathic components.

Methods

This study was conducted in accordance with applicable laws and regulations, including the guidelines of the Declaration of Helsinki for human experimentation. All patients provided written informed consent and the protocol and informed consent forms were approved by the local institutional review board (approval number: 1889). Two hospitals (KUH, KOH) participated in this study and used the same protocol.

Inclusion and exclusion criteria

The inclusion criteria were as follows: patients with (1) shoulder pain, and (2) rotator cuff tear on magnetic resonance imaging (MRI) scan. The exclusion criteria were as follows: (1) moderate or severe joint degeneration according to the radiographic classification established by Samilson and Prieto [8] and musculoskeletal abnormalities including calcifying tendinitis on plain radiographs, (2) pain with cervical motion and positive results on a Spurling test or Jackson’s test during cervical spine examination [9, 10], (3) history of central or peripheral nervous system lesions, (4) diabetes mellitus, (5) prior surgery to the affected shoulder, (6) duration of symptoms less than 1 month or longer than 60 months, (7) a workers’ compensation claim, and (8) a history of medication use for NeP.

Patients who enrolled in this study were selected from a source population of outpatients who attended one of the two participating hospitals for the treatment of shoulder pain between August 2013 and August 2014. Clinical assessment consisted of a structured interview, completion of the PDQ, a visual analog scale (VAS) for pain, a detailed physical examination, plain radiographs, and MRI scans. Among the 133 patients who met the inclusion criteria, 23 patients were excluded, leaving 110 patients enrolled in the study (Fig. 1). Demographic data and clinical features of the subjects, including age, sex, history of trauma, duration of symptoms, and VAS pain scores, are summarized in Table 1. All data were collected prospectively and analyzed retrospectively.
Fig. 1

Flow chart showing the number of patients enrolled, according to our inclusion and exclusion criteria

Table 1

Demographic data and clinical features of the subjects a(n = 110)

Age (y)

65.7 ± 8.5 (46–88)

Sex (male/female)b

60 (54.5)/50 (45.5)

History of traumab

47 (42.7)

Duration of symptoms (months)

9.9 ± 14.2 (1–60)

Visual analog scale score

 Pain at the initial visit (points)

5.3 ± 2.8 (0–10)

 Most severe pain during the past 4 weeks (points)

7.4 ± 2.6 (0–10)

 Average pain during the past 4 weeks (points)

5.6 ± 2.6 (0–10)

aValues are expressed as mean ± SD (range)

bValues are expressed as number of patients (%)

PainDETECT questionnaire (PDQ)

The PDQ established by Freynhagen et al. [3, 11] was used to identify the presence of NeP. The self-administered questionnaire consists of 9 questions that address the quality of NeP symptoms; no physical examination is required. The first 7 questions address the gradation of pain, and are scored from 0 to 5 (0 = never to 5 = very strongly). Question 8 addresses the pain course pattern, scored from –1 to 1, depending on which pain course pattern diagram is selected. Question 9, for which the response is “yes” or “no”, is scored as 2 or 0, respectively, and addresses radiating pain (Table 2). The final score is between –1 and 38 and indicates the likelihood of a neuropathic component. A score of ≤ 12 indicates a low likelihood of a neuropathic component (NoP group), while a score of ≥ 19 suggests a high likelihood of a neuropathic component (NeP group). A score between these values indicates the possibility of a neuropathic component.
Table 2

The painDETECT questionnaire

Item

Score

Gradation of paina

 Do you suffer from a burning sensation (e.g. stinging nettles) in the marked areas?

0–5

 Do you have a tingling or prickling sensation in the area of your pain (like crawling ants or electrical tingling)?

0–5

 Is light touching (clothing, a blanket) in this area painful?

0–5

 Do you have sudden pain attacks in the area of your pain, like electric shocks?

0–5

 Is cold or heat (bath water) in this area occasionally painful?

0–5

 Do you suffer from a sensation of numbness in the areas that you marked?

0–5

 Does slight pressure in this area, e.g. with a finger, trigger pain?

0–5

Pain course pattern

 Please select the picture that best describes the course of your pain:

 

 Persistent pain with slight fluctuations

0

 Persistent pain with pain attacks

–1

 Pain attacks without pain between them

+1

 Pain attacks with pain between them

+1

Radiating pain

 Does your pain radiate to other regions of your body? Yes/No

+2/0

aFor each question: never, 0; hardly noticed, 1; slightly, 2; moderately, 3; strongly, 4; very strongly, 5

The Japanese version of the PDQ has been validated, and has good reliability and validity according to a study by Matsubayashi et al. [7]. The study included patients with neuropathic pain related to the following pathologies: brachial plexus injury (12 patients), radiculopathy (12 patients), herpes zoster (11 patients), spinal cord injury (10 patients), diabetic or alcoholic polyneuropathies (7 patients), phantom pain (5 patients), complex regional pain syndrome (CRPS; 2 patients), carpal tunnel syndrome (1 patient), and thalamic pain (1 patient) [7]. The intraclass correlation coefficient for test–retest reliability was 0.94, and Cronbach’s alpha for the total score and main component were 0.78 and 0.80, respectively [7].

VAS for pain

The VAS, with a range from 0 to 10 (0 = no pain to 10 = worst possible pain), was used to evaluate the current pain experienced at the initial visit, the most severe pain experienced during the past 4 weeks, and the average pain experienced during the past 4 weeks.

Physical examination

Range-of-motion assessment included the measurement of forward elevation, lateral/scapular elevation, external rotation with the arm at the patient’s side, and internal rotation behind the back, which was recorded as the highest vertebral spinous process attained. Manual muscle tests for strength and Neer and Hawkins impingement tests were performed, as well as supraspinatus [12], infraspinatus [13], lift-off [14, 15], belly-press [14, 15], and Speed tests to evaluate the rotator cuff and biceps. All patients were evaluated at the initial visit.

Radiographic evaluation

Anteroposterior and axillary (West Point) radiographs and MRI scans were obtained for all symptomatic shoulders.

The size of the rotator cuff tear was established based on the extent of the tear in the anteroposterior direction as measured in a sagittal oblique plane on T2-weighted MRI. Tears were then classified into 5 grades: partial (articular-sided, bursal-sided, and intratendinous tears), small (<1 cm), medium (≥ 1 cm and < 3 cm), large (≥ 3 cm and < 5 cm), and massive (≥ 5 cm). When a fluid-equivalent signal was visible or when the tendon could not be visualized in at least one section of a fluid-sensitive sequence, a full-thickness rotator cuff tear was diagnosed. MRI studies were also evaluated to assess the specific location of the rotator cuff tear. The presence of fluid in the glenohumeral joint and subacromial space was also evaluated in the coronal oblique plane on T2-weighted MRI to detect hydrarthrosis.

Statistical analysis

To assess the association between pairs of qualitative variables, we used the Mann-Whitney U test for univariate analysis. For multivariate analysis, logistic regression with a forward stepwise technique was performed using factors that demonstrated statistical significance in the univariate analysis. A P value of < 0.05 was considered statistically significant. Power analyses were performed with EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan) [16], which is a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria).

Results

PainDETECT score

Twelve patients (10.9 %) were classified into the NeP group (score ≥ 19), 33 patients (30.0 %) into the possible NeP group (score 13 to 18), and 65 patients (59.1 %) into the NoP group (score ≤ 12) (Table 3).
Table 3

PainDETECT scores

Score

Number of patients (%)

−1–12

65 (59.1)

13–18

33 (30.0)

19–38

12 (10.9)

On the basis of the responses to the painDETECT questionnaire, neuropathic pain is likely with a score ≥ 19, possible with a score from 13 to 18, and unlikely if the score is ≤ 12

Demographic data and clinical features

In the univariate analysis between the NeP group and NoP group, the female-to-male ratio was significantly higher in the NeP group than in the NoP group (p = 0.034), and the mean VAS score (average pain during the past 4 weeks) was significantly higher in the NeP group than in the NoP group (p = 0.013). Other demographic data, including age, history of trauma, and duration of symptoms, did not differ significantly between the groups (Table 4).
Table 4

Clinical factors associated with neuropathic pain according to univariate analysisa (n = 77)

 

PainDETECT questionnaire

p-value

Neuropathic pain

(n = 12)

Nociceptive pain

(n = 65)

 

Age (y)

70.3 ± 8.9 (58–88)

65.5 ± 8.1 (46–83)

0.117

Sex (male/female)b

3 (25.0)/9 (75.0)

38 (58.5)/27 (41.5)

0.034*

History of traumab

5 (41.7)

30 (46.2)

0.776

Duration of symptoms (months)

11.3 ± 16.5 (1–60)

9.7 ± 13.5 (1–60)

0.439

Visual analog scale score

 Pain at the initial visit (points)

6.5 ± 2.1 (3–9)

4.6 ± 3.0 (0–10)

0.051

 Most severe pain during the past 4 weeks (points)

8.2 ± 1.9 (5–10)

6.8 ± 3.0 (0–10)

0.161

 Average pain during the past 4 weeks (points)

6.8 ± 1.2 (5–9)

4.8 ± 2.6 (0–10)

0.013*

Positive Neer and/or Hawkins impingement testsb

12 (100)

47 (71.2)

0.039*

Positive supraspinatus testb

11 (91.7)

51 (78.5)

0.292

Positive infraspinatus testb

3 (25.0)

14 (21.5)

0.792

Positive lift-off and/or belly-press testsb

2 (16.7)

9 (13.8)

0.562

Hydrarthrosisb

8 (66.7)

39 (60.0)

0.666

Size of rotator cuff tearb

 Partial

  articular-sided

2 (16.7)

2 (3.1)

0.053

  bursal-sided

3 (25.0)

6 (9.2)

0.121

  intratendinous

1 (8.3)

5 (7.7)

0.934

  Small (< 1 cm)

0 (0)

9 (13.8)

0.173

  Medium (≥ 1 cm, < 3 cm)

3 (25.0)

27 (41.5)

0.284

  Large (≥ 3 cm, < 5 cm)

3 (25.0)

10 (15.4)

0.417

  Massive (≥ 5 cm)

0 (0)

6 (9.2)

0.276

Tear locationb

 Supraspinatus

12 (100)

64 (98.5)

0.667

 Infraspinatus

4 (33.3)

21 (32.3)

0.945

 Subscapularis

3 (25.0)

14 (21.5)

0.792

*Statistically significant difference between the groups (p < 0.05)

aValues are expressed as mean ± SD (range)

bValues are expressed as number of patients (%)

Physical examination

In the univariate analysis, the number of positive results for the Neer and Hawkins impingement tests was significantly higher in the NeP group (100 % [12 of 12]) than in the NoP group (71.2 % [47 of 65]; p = 0.039). Other physical examination results, including the supraspinatus, infraspinatus, lift-off, and belly press tests, did not differ significantly between the groups (Table 4).

Radiographic evaluation

In the univariate analysis, radiographic findings, including hydrarthrosis, tear location, and rotator cuff tear size did not differ significantly between the groups (Table 4).

Multivariate analysis

In the multivariate analysis using logistic regression, we included variables that demonstrated statistical significance in the univariate analysis, specifically VAS score (average pain during the past 4 weeks), sex, and the results of the Neer and Hawkins impingement tests. The VAS score (average pain during the past 4 weeks) was found to be an independent prognostic factor for NeP (p = 0.031) whereas NeP was not affected by sex or the results of the Neer and Hawkins impingement tests (Table 5).
Table 5

Clinical factors associated with neuropathic pain according to multivariate analysis using logistic regression

Independent variable

Exp

95 % CI

p-value

Sex

3.871

0.853–17.569

0.079

Visual analog scale pain score

 Average pain during the past 4 weeks

0.674

0.471–0.964

0.031*

Positive Neer and/or Hawkins impingement tests

 

-

0.989

*Statistically significant difference (p < 0.05)

Discussion

To our knowledge, this is the first study to utilize the PDQ in patients with shoulder pain attributed to rotator cuff tears. We found that 10.9 % of patients with rotator cuff tears may have NeP. Multivariate analysis revealed that a higher VAS score for average pain during the past 4 weeks was significantly associated with the development of NeP. Therefore, clinicians should remain vigilant for heterogeneous etiologies of pain in patients with rotator cuff tears.

There are some pharmacotherapy guidelines for NeP [1720]. Antidepressants and calcium channel alpha 2-delta ligands are recommended as first-line therapy. Therefore, the diagnosis of NeP in patients with a rotator cuff tear is essential for optimal treatment. The clinical outcomes of pharmacotherapy for these patients needs to be elucidated.

Freynhagen et al. conducted a multicenter study and found that 37 % of 7772 patients with various forms of chronic low back pain exhibited pain that was predominantly related to an NeP component [3]. Subsequently, NeP has been reported to exist in 15 to 37.9 % of patients with low back pain on the basis of their PDQ responses [2125]. The pathology of NeP in patients with low back pain has been attributed to nerve tissue damage generated by mechanical compression or inflammation of the nerve root due to degenerative disc disease [11]. Results from studies in animal models have also suggested that factors such as notch signaling activation [26], transient receptor potential ankyrin 1 (TRPA1) [27], and Cdh1 [28] are involved in the pathogenesis of NeP.

The PDQ has also been used to identify NeP in patients with musculoskeletal disorders such as knee osteoarthritis. NeP has been reported to exist in 5.4 to 32 % of patients with knee osteoarthritis on the basis of their responses to the PDQ [4, 2932]. The mechanism of NeP in osteoarthritis remains unclear, but structural changes of the joint and changes in pain processing of the central nervous system have been implicated [33]. In a mono-iodoacetate-induced knee osteoarthritis study in rats, Orita et al. reported that the initial inflammatory pain state, induced by local inflammation, was followed by the gradual initiation of neuronal injury, which may have contributed to the development of NeP [34].

The pathogenesis of NeP in patients with rotator cuff tears remains unclear. There are neural mechanoreceptors such as Pacinian corpuscles, Ruffini endings, and Golgi tendon organs, as well as nociceptors such as free nerve endings in torn rotator cuff tissue and in the subacromial bursa. In the shoulder, these mechanoreceptors and nociceptors are mainly innervated by the suprascapular nerve (C5) [35]. Inflammation caused by rotator cuff tears may trigger injury of the neural mechanoreceptors and suprascapular nerve, thus leading to the gradual development of NeP. Further analysis of the interaction between rotator cuff tears and NeP is required to clarify the etiology of NeP in patients with rotator cuff tears.

This study has several limitations. First, the reliability of the PDQ for identifying NeP in patients with rotator cuff tears has not been assessed thus far. However, the original validation study included a large sample (n = 411) of patients with chronic pain who were recruited from 10 specialized pain centers [3]. The Japanese version of the PDQ has shown excellent test-retest reliability (intraclass correlation coefficient > 0.93) and good internal consistency (Cronbach’s alpha ≥ 0.78) [7]. Furthermore, the PDQ demonstrated excellent criterion validity when compared to an expert pain physician as the reference standard, as indicated by a high sensitivity, specificity, and positive predictive value (all > 80 %) [3]. Second, adequate statistical power to evaluate the outcomes was lacking because of the small number of patients in the study sample. According to the power analysis (type I error probability [a] = .05), the statistical power in this study was 0.703 (VAS score; average pain during the past 4 weeks), which is comparatively low. Therefore, the probability of a type I error is limited. Despite these limitations, we believe that the results of this study can be helpful to clinicians when treating patients with shoulder pain related to rotator cuff tears.

Conclusions

By using the PDQ, we found that 10.9 % of patients with rotator cuff tears may experience NeP. Furthermore, we found that VAS score (average pain during the past 4 weeks) was a prognostic factor for NeP in these patients. This is a novel approach to an important subject and will hopefully encourage future research on the topic of neuropathic shoulder pain in patients with rotator cuff tears, as there is currently a paucity of information. We believe that the creation of an animal model with NeP and rotator cuff tears is needed to clarify the etiology of NeP in patients with rotator cuff tears. Our results indicate that clinicians should remain vigilant for heterogeneous etiologies of pain in patients with rotator cuff tears.

Abbreviations

MRI: 

Magnetic resonance imaging

NeP: 

Neuropathic pain

NoP: 

Nociceptive pain

PDQ: 

painDETECT questionnaire

VAS: 

Visual analog scale

Declarations

Acknowledgments

The authors acknowledge Ken Kikuchi, PhD, for his help with the statistical analysis.

Funding

The authors declare that there were no sources of funding for the research.

Availability of data and materials

The dataset supporting the conclusions of this article is available through the corresponding author.

Authors’ contributions

TK and JI designed the study protocol. TK, JI, TK, and TT participated in the acquisition of data. TK performed the statistical analysis, managed the literature searches, summarized the previous related work, and wrote the first draft of the manuscript. JI, NO, and HM provided critical revision for intellectual content and final approval of the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

All patients provided written informed consent and the protocol and informed consent forms were approved by the local institutional review board (approval number: 1889).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Orthopaedic Surgery, Faculty of Life Sciences, Kumamoto University
(2)
Department of Advanced Joint Reconstructive Surgery, Kumamoto University Hospital, Kumamoto University
(3)
Kumamoto Orthopaedic Hospital

References

  1. Yamamoto A, Takagishi K, Osawa T, Yanagawa T, Nakajima D, Shitara H, et al. Prevalence and risk factors of a rotator cuff tear in the general population. J Shoulder Elbow Surg. 2010;19:116–20.View ArticlePubMedGoogle Scholar
  2. Clauw DJ. Diagnosing and treating chronic musculoskeletal pain based on the underlying mechanism(s). Best Pract Res Clin Rheumatol. 2015;29:6–19.View ArticlePubMedGoogle Scholar
  3. Freynhagen R, Baron R, Gockel U, Tölle TR. painDetect: a new screening questionnaire to identify neuropathic components in patients with back pain. Curr Med Res Opin. 2006;22:1911–20.View ArticlePubMedGoogle Scholar
  4. Ohtori S, Orita S, Yamashita M, Ishikawa T, Ito T, Shigemura T, et al. Existence of a neuropathic pain component in patients with osteoarthritis of the knee. Yonsei Med J. 2012;53:801–5.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Gwilym SE, Oag HC, Tracey I, Carr AJ. Evidence that central sensitisation is present in patients with shoulder impingement syndrome and influences the outcome after surgery. J Bone Joint Surg (Br). 2011;93:498–502.View ArticleGoogle Scholar
  6. Mathieson S, Lin C. painDETECT questionnaire. J Physiother. 2013;59:211.View ArticlePubMedGoogle Scholar
  7. Matsubayashi Y, Takeshita K, Sumitani M, Oshima Y, Tonosu J, Kato S, et al. Validity and reliability of the Japanese version of the painDETECT questionnaire: a multicenter observational study. PLoS One. 2013;8:e68013.View ArticlePubMedPubMed CentralGoogle Scholar
  8. Samilson RL, Prieto V. Dislocation arthropathy of the shoulder. J Bone Joint Surg Am. 1983;65:456–60.View ArticlePubMedGoogle Scholar
  9. Jackson R. The classic: the cervical syndrome. 1949. Clin Orthop Relat Res. 2010;468:1739–45.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Spurling RG, Scoville WB. Lateral rupture of the cervical intervertebral discs: a common cause of shoulder and arm pain. Surg Gynecol Obstet. 1944;78:350–8.Google Scholar
  11. Freynhagen R, Baron R. The evaluation of neuropathic components in low back pain. Curr Pain Headache Rep. 2009;13:185–90.View ArticlePubMedGoogle Scholar
  12. Jobe FW, Jobe CM. Painful athletic injuries of the shoulder. Clin Orthop Relat Res. 1983;173:117–24.Google Scholar
  13. Hama H, Morinaga T, Suzuki K, Kuroki H, Sunami M, Yamamuro T. The infraspinatus test: An early diagnostic sign of muscle weakness during external rotation of the shoulder in athletes. J Shoulder Elbow Surg. 1993;2:257–9.View ArticlePubMedGoogle Scholar
  14. Gerber C, Hersche O, Farron A. Isolated rupture of the subscapularis tendon. J Bone Joint Surg Am. 1996;78:1015–23.View ArticlePubMedGoogle Scholar
  15. Ide J, Tokiyoshi A, Hirose J, Mizuta H. Arthroscopic repair of traumatic combined rotator cuff tears involving the subscapularis tendon. J Bone Joint Surg Am. 2007;89:2378–88.PubMedGoogle Scholar
  16. Kanda Y. Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant. 2013;48:452–8.View ArticlePubMedGoogle Scholar
  17. Attal N, Cruccu G, Haanpää M, Hansson P, Jensen TS, Nurmikko T, et al. EFNS guidelines on pharmacological treatment of neuropathic pain. Eur J Neurol. 2006;13:1153–69.View ArticlePubMedGoogle Scholar
  18. Dworkin RH, O’Connor AB, Backonja M, Farrar JT, Finnerup NB, Jensen TS, et al. Pharmacologic management of neuropathic pain: evidence-based recommendations. Pain. 2007;132:237–51.View ArticlePubMedGoogle Scholar
  19. Tan T, Barry P, Reken S, Baker M. Guideline Development Group. Pharmacological management of neuropathic pain in non-specialist settings: summary of NICE guidance. BMJ. 2010;340:c1079.View ArticlePubMedGoogle Scholar
  20. Attal N, Cruccu G, Baron R, Haanpää M, Hansson P, Jensen TS, et al. EFNS guidelines on the pharmacological treatment of neuropathic pain: 2010 revision. Eur J Neurol. 2010;17:1113–e88.View ArticlePubMedGoogle Scholar
  21. Beith ID, Kemp A, Kenyon J, Prout M, Chestnut TJ. Identifying neuropathic back and leg pain: a cross-sectional study. Pain. 2011;152:1511–6.View ArticlePubMedGoogle Scholar
  22. Hiyama A, Watanabe M, Katoh H, Sato M, Sakai D, Mochida J. Evaluation of quality of life and neuropathic pain in patients with low back pain using the Japanese Orthopedic Association Back Pain Evaluation Questionnaire. Eur Spine J. 2015;24:503–12.View ArticlePubMedGoogle Scholar
  23. Morsø L, Kent PM, Albert HB. Are self-reported pain characteristics, classified using the PainDETECT questionnaire, predictive of outcome in people with low back pain and associated leg pain? Clin J Pain. 2011;27:535–41.View ArticlePubMedGoogle Scholar
  24. Schmidt CO, Schweikert B, Wenig CM, Schmidt U, Gockel U, Freynhagen R, et al. Modelling the prevalence and cost of back pain with neuropathic components in the general population. Eur J Pain. 2009;13:1030–5.View ArticlePubMedGoogle Scholar
  25. Sakai Y, Ito K, Hida T, Ito S, Harada A. Neuropathic pain in elderly patients with chronic low back pain and effects of pregabalin: a preliminary study. Asian Spine J. 2015;9:254–62.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Xie K, Qiao F, Sun Y, Wang G, Hou L. Notch signaling activation is critical to the development of neuropathic pain. BMC Anesthesiol. 2015;15:41.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Miyakawa T, Terashima Y, Takebayashi T, Tanimoto K, Iwase T, Ogon I, et al. Transient receptor potential ankyrin 1 in spinal cord dorsal horn is involved in neuropathic pain in nerve root constriction rats. Mol Pain. 2014;10:58.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Tan W, Yao WL, Hu R, Lv YY, Wan L, Zhang CH, et al. Alleviating neuropathic pain mechanical allodynia by increasing Cdh1 in the anterior cingulate cortex. Mol Pain. 2015;11:56.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Hochman JR, French MR, Bermingham SL, Hawker GA. The nerve of osteoarthritis pain. Arthritis Care Res (Hoboken). 2010;62:1019–23.View ArticleGoogle Scholar
  30. Hochman JR, Gagliese L, Davis AM, Hawker GA. Neuropathic pain symptoms in a community knee OA cohort. Osteoarthritis Cartilage. 2011;19:647–54.View ArticlePubMedGoogle Scholar
  31. das Moreton BJ, Tew V, Nair R, Wheeler M, Walsh DA, Lincoln NB. Pain phenotype in patients with knee osteoarthritis: classification and measurement properties of painDETECT and self-report Leeds assessment of neuropathic symptoms and signs scale in a cross-sectional study. Arthritis Care Res (Hoboken). 2015;67:519–28.View ArticleGoogle Scholar
  32. Roubille C, Raynauld JP, Abram F, Paiement P, Dorais M, Delorme P, et al. The presence of meniscal lesions is a strong predictor of neuropathic pain in symptomatic knee osteoarthritis: a cross-sectional pilot study. Arthritis Res Ther. 2014;16:507.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Sofat N, Ejindu V, Kiely P. What makes osteoarthritis painful? The evidence for local and central pain processing. Rheumatology (Oxford). 2011;50:2157–65.View ArticleGoogle Scholar
  34. Orita S, Ishikawa T, Miyagi M, Ochiai N, Inoue G, Eguchi Y, et al. Pain-related sensory innervation in monoiodoacetate-induced osteoarthritis in rat knees that gradually develops neuronal injury in addition to inflammatory pain. BMC Musculoskelet Disord. 2011;12:134.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Vangsness Jr CT, Ennis M, Taylor JG, Atkinson R. Neural anatomy of the glenohumeral ligaments, labrum, and subacromial bursa. Arthroscopy. 1995;11:180–4.View ArticlePubMedGoogle Scholar

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