| Literature DB >> 35626288 |
Eleonora Galosi1, Andrea Truini1, Giulia Di Stefano1.
Abstract
Converging evidence shows that patients with fibromyalgia syndrome have signs of small fibre impairment, possibly leading to pain and autonomic symptoms, with a frequency that has not yet been systematically evaluated. To fill this gap, our review aims to define the frequency of somatic and autonomic small fibre damage in patients with fibromyalgia syndrome, as assessed by objective small fibre-related testing. We found 360 articles on somatic and autonomic small fibre assessment in patients with fibromyalgia. Out of the 88 articles assessed for eligibility, 20 were included in the meta-analysis, involving 903 patients with fibromyalgia. The estimated prevalence of somatic small fibre impairment, as assessed with skin biopsy, corneal confocal microscopy, and microneurography, was 49% (95% confidence interval (CI): 39-60%, I2 = 89%), whereas the estimated prevalence of autonomic small fibre impairment, as assessed with heart rate variability, sympathetic skin response, skin conductance, and tilt testing, was 45% (95% CI: 25-65%, I2 = 91%). Our study shows that a considerable proportion of patients with fibromyalgia have somatic and autonomic small fibre impairment, as assessed by extensive small fibre-related testing. Nevertheless, the heterogeneity and inconsistencies across studies challenge the exact role of small fibre impairment in fibromyalgia symptoms.Entities:
Keywords: fibromyalgia; neuropathic pain; skin biopsy; small fibre pathology
Year: 2022 PMID: 35626288 PMCID: PMC9139885 DOI: 10.3390/diagnostics12051135
Source DB: PubMed Journal: Diagnostics (Basel) ISSN: 2075-4418
Figure 1Flow chart of the search process of papers included in the meta-analysis.
Studies dealing with somatic small fibre impairment included in the meta-analysis.
| Reference | Sample Size | Fibromyalgia | Control Group | Prevalence Number | Prevalence Estimate (%) |
|---|---|---|---|---|---|
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| Boneparth 2021 [ | 38 | 15 | 23 | 8 | 53 |
| Fasolino 2020 [ | 57 | 57 | - | 18 | 32 |
| Vecchio 2020 [ | 81 | 81 | - | 69 | 85 |
| Evdokimov 2019 [ | 128 | 117 | 11 | 74 | 63 |
| Lawson 2018 [ | 155 | 155 | - | 62 | 40 |
| Leinders 2016 [ | 116 | 28 | 88 | 14 | 50 |
| De Tommaso 2014 [ | 81 | 21 | 60 | 16 | 76 |
| Giannoccaro 2014 [ | 52 | 20 | 32 | 6 | 30 |
| Kosmidis 2014 [ | 80 | 46 | 34 | 16 | 35 |
| Oaklander 2013 [ | 57 | 27 | 30 | 11 | 41 |
| Uceyler 2013 [ | 155 | 24 | 131 | 10 | 42 |
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| Oudejans 2016 [ | * | 39 | * | 20 | 51 |
| Ramirez 2015 [ | 34 | 17 | 17 | 12 | 71 |
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| Evdokimov 2019 [ | 41 | 27 | 14 | 11 | 41 |
| Serra 2014 [ | 56 | 30 | 26 | 9 | 30 |
* Information not available.
Figure 2Forest plot showing overall pooled prevalence estimates of small fibre impairment in fibromyalgia.
Figure 3Forest plot showing pooled prevalence estimates of small fibre impairment in studies using skin biopsy.
Figure 4Forest plot showing pooled prevalence estimates of small fibre impairment in studies using corneal confocal 165 microscopy.
Figure 5Forest plot showing pooled prevalence estimates of small fibre impairment in studies using microneurography.
Studies dealing with autonomic small fibre impairment included in the meta-analysis.
| Sample Size | Fibromyalgia | Control Group | Prevalence Number | Prevalence Estimate (%) | |
|---|---|---|---|---|---|
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| Furlan 2005 [ | 32 | 16 | 16 | 7 | 44 |
| Raj 2000 [ | 31 | 17 | 14 | 11 | 65 |
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| Singh 2021 [ | 60 | 30 | 30 | 12 | 40 |
| Lee 2016 [ | 60 | 35 | 25 | 29 | 83 |
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| Pickering 2020 [ | 100 | 50 | 50 | 14 | 28 |
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| De Tommaso 2017 [ | 80 | 50 | 30 | 9 | 18 |
| Ünlü 2006 [ | 46 | 28 | 18 | 11 | 39 |
Figure 6Forest plot showing pooled prevalence estimates of autonomic disfunction.