| Literature DB >> 33531833 |
Lin-Man Weng1, Xuan Su1, Xue-Qiang Wang1,2.
Abstract
PURPOSE: On 11 March, 2020, the coronavirus disease (COVID-19) outbreak was declared as a global pandemic by the World Health Organization. It brought substantial physical and psychological burden on individuals and financial loss across countries. Patients with COVID-19 may exhibit various symptoms, such as fever, cough, dyspnea, muscle pain, sore throat, headache, chest pain, and abdominal pain, at 2-14 days after exposure to the novel coronavirus (severe acute respiratory syndrome [SARS]-CoV-2). Pain symptoms present important challenge to clinicians' diagnosis when treating COVID-19 patients with mild symptoms. Considering the increasing number of confirmed COVID-19 cases, the pain symptoms should be systematically summarized.Entities:
Keywords: COVID-19; SARS-CoV-2; pain; symptom
Year: 2021 PMID: 33531833 PMCID: PMC7847371 DOI: 10.2147/JPR.S269206
Source DB: PubMed Journal: J Pain Res ISSN: 1178-7090 Impact factor: 3.133
The Incidence Rate of Pain Symptoms for Patients with COVID-19 in Different Studies
| Ranking | Author | Recruited Time | Country | Number of COVID-19 Patients | Number of Headache (Incidence, %) | Number of Sore Throat (Incidence, %) | Number of Chest Pain (Incidence, %) | Number of Myalgia or Arthralgia Pain (Incidence, %) | Number of Abdominal Pain (Incidence, %) |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Tian | 2020.01.20–2020.02.10 | China | 262 | 6.5% | NR | NR | NR | NR |
| 2 | Xu | 2020.01–2020.02 | China | 50 | 10.0% | 8.0% | NR | 16.0% | NR |
| 3 | Yang | 2020.01.17–2020.02.10 | China | 149 | 8.7% | 14.1% | 3.4% | 3.4% | NR |
| 4 | Wang | 2020.01.01–2020.01.28 | China | 138 | 6.5% | 17.4% | NR | 34.8% | 2.2% |
| 5 | Zhang | 2020.01.16–2020.02.03 | China | 140 | NR | NR | NR | NR | 5.8% |
| 6 | Guan | 2019.12.11–2020.01.29 | China | 1099 | 13.6% | 13.9% | NR | 14.9% | NR |
| 7 | Wu | 2020.01.22–2020.02.14 | China | 80 | NR | 13.8% | 3.8% | 22.5% | NR |
| 8 | Huang | 2019.12–2020.01 | China | 34 | 5.9% | NR | NR | NR | NR |
| 9 | Liu | 2019.12.30–2020.01.24 | China | 137 | 9.5% | NR | NR | NR | NR |
| 10 | Mo | 2020.01.01–2020.02.05 | China | 155 | 9.8% | NR | 3.7% | 61.0% | 1.9% |
| 11 | Zhou | 2019.12.29–2020.01.31 | China | 191 | NR | NR | NR | 15.2% | NR |
| 12 | Xu | 2020.01.23–2020.02.18 | China | 51 | NR | 5.9% | NR | 15.7% | NR |
| 13 | Wan | 2020.01.23–2020.02.08 | China | 135 | 32.5% | 17.7% | NR | NR | NR |
| 14 | Huang | Up to 2020.01.02 | China | 41 | 7.9% | NR | NR | NR | NR |
| 15 | Xu | 2020.01.10–2020.01.26 | China | 62 | 33.9% | NR | NR | NR | NR |
| 16 | Chen | 2020.01.20–2020.02.06 | China | 249 | NR | 6.4% | NR | NR | NR |
| 17 | COVID-19 National Incident Room Surveillance Team | Up to 2020.03.14 | Australia | 295 | 19.9% | 46.2% | 5.8% | 14.7% | 3.9% |
| 18 | Zhou | 2020.01.16–2020.01.30 | China | 62 | NR | NR | NR | 32.3% | NR |
| 19 | Qin | 2020.01.10–2020.02.12 | China | 452 | 11.4% | 4.8% | NR | 21.4% | 5.0% |
| 20 | Han | 2020.01.04–2020.02.03 | China | 108 | 13.0% | 13.0% | NR | 11.1% | NR |
| 21 | Song | 2020.01.20–2020.01.27 | China | 51 | NR | 5.9% | NR | NR | NR |
| 22 | Qian | 2020.01.20–2020.02.11 | China | 91 | 7.7% | NR | NR | 5.5% | NR |
| 23 | Chen | 2020.01.01–2020.01.20 | China | 99 | 8.1% | 5.1% | 2.0% | 11.1% | NR |
| 24 | Spiteri | up to 2020.02.21 | WHO European Region | 38 | 19.4% | 6.5% | NR | NR | NR |
| 25 | Xu | 2020.01.23–2020.02.04 | China | 90 | 4.4% | 25.6% | NR | 27.8% | NR |
| 26 | Zhu | 2020.01.24–2020.02.20 | China | 32 | 3.1% | NR | NR | NR | NR |
| 27 | Pung | Up to 2020.02.15 | Singapore | 36 | NR | 47.1% | 17.7% | 29.4% | NR |
| 28 | Shi | 2020.12.20–2020.01.23 | China | 81 | 6.2% | NR | NR | NR | NR |
| 29 | Zhao | NR | China | 101 | NR | 11.9% | NR | NR | NR |
| 30 | Wu | 2020.12.25–2020.01.26 | China | 201 | NR | NR | NR | 32.3% | NR |
| 31 | Wang | 2020.01.16–2020.02.27 | China | 90 | 4.4% | 7.8% | NR | 4.4% | 2.2% |
| 32 | Li | 2020.01–2020.02 | China | 83 | 10.8% | NR | 6.0% | 18.1% | NR |
| 33 | Mao | 2020.01.16–2020.02.19 | China | 214 | 13.1% | 14.5% | NR | NR | 4.7% |
| 34 | Shi | 2020.01.20–2020.02.10 | China | 416 | 2.2% | 2.9% | 3.4% | 4.6% | NR |
| 35 | Daily Situation Report on Coronavirus disease (COVID-19) in Iran | Up to 2020.03.13 | Iran | 11,364 | NR | NR | NR | 22.0% | NR |
| 36 | Guan | 2019.12.11–2020.01.31 | China | 1590 | 15.4% | 14.7% | NR | 17.5% | NR |
| 37 | Wang | 2020.01.25–2020.02.09 | China | 114 | NR | 5.3% | NR | NR | NR |
| 38 | Cao | 2020.01.03–2020.02.01 | China | 102 | NR | NR | NR | 34.3% | NR |
| 39 | Zhang | 2020.01.20–2020.02.10 | China | 120 | 23.3% | 16% | NR | NR | NR |
| 40 | Barrasa | 2020.03.04–2020.03.31 | Spain | 48 | NR | NR | NR | 4.2% | NR |
| 41 | Tang | 2020.12.24–2020.02.07 | China | 73 | NR | NR | NR | 34.2% | NR |
| 42 | Sun | 2020.01.26–2020.02.16 | Multi-country | 54 | NR | 33.3% | NR | NR | NR |
| 43 | Chen | 2020.01.20–2020.02.17 | China | 98 | NR | 8.2% | NR | NR | NR |
| 44 | Cai | 2020.01.11–2020.02.06 | China | 298 | 1.7% | 0.7% | NR | NR | NR |
| 45 | Chen | 2020.01.20–2020.02.09 | China | 42 | NR | 14.3% | NR | 23.8% | 11.9% |
| 46 | Wang | 2020.02.07–2020.02.12 | China | 1012 | 15.0% | 14.2% | NR | 16.8% | 3.7% |
| 47 | Shao | 2020.01.15–2020.02.25 | China | 136 | NR | NR | NR | 60.3% | 5.9% |
| 48 | Wang | 2020.01.20–2020.02.09 | China | 125 | NR | 13.6% | 1.6% | 3.2% | NR |
| 49 | Du | 2019.12.25–2020.02.15 | China | 109 | 7.3% | NR | NR | 17.4% | NR |
| 50 | Jia | 2020.01.29–2020.02.23 | China | 44 | 11.4% | 9.1% | NR | 15.9% | NR |
| 51 | Li | 2020.12.28–2020.02.10 | China | 131 | NR | NR | NR | 1.5% | NR |
| 52 | Feng | 2020.01.01–2020.02.15 | China | 476 | NR | 8.1% | 4.8% | 12.6% | NR |
| 53 | Zheng | 2020.01.17–2020.02.07 | China | 161 | 7.5% | NR | NR | 11.2% | NR |
| 54 | Du | 2020.01.09–2020.02.15 | China | 85 | 4.7% | 2.4% | 2.4% | 16.5% | 3.5% |
Figure 1The incidence rate of pain symptoms for patients with COVID-19.