Table 1.
Characteristics of included studies
| Study | Year (Online) | Country | Publication language | Recruitment time frame | Sample | Age, yearsa | Sex | NOS | |
|---|---|---|---|---|---|---|---|---|---|
| Male | Female | ||||||||
| Argenziano MG [17] | 2020 | USA | English | 2020.3.1–2020.4.15 | 1000 | 61.7 ± 17.5 | 596 | 404 | 8 |
| Cao JL [18] | 2020 | China | English | 2020.1.3–2020.2.1 | 102 | 54(37–67) | 53 | 49 | 6 |
| Chen T [19] | 2020 | China | English | 2020.1.13–2020.2.12 | 274 | 62(44–70) | 171 | 103 | 8 |
| Chen TL [20] | 2020 | China | English | 2020.1.1–2020.2.10 | 55 | 74(65–91) | 34 | 21 | 6 |
| Chen X [21] | 2020 | China | English | 2020.2.3–2020.2.20 | 73 | 66(59–72.3) | 42 | 31 | 8 |
| Chen XH [22] | 2020 | China | English | 2020.2.1–2020.2.19 | 48 | 64.6 ± 18.1 | 37 | 11 | 7 |
| Cheng AY [23] | 2020 | China | English | 2020.2.8–2020.3.11 | 305 | 65(52–71) | 184 | 121 | 7 |
| Cheng L [24] | 2020 | China | English | 2020.1.3–2020.2.26 | 89 | 59.74 ± 16.42 | 49 | 40 | 8 |
| Chon Y [25] | 2020 | Korea | English | 2020.2.22–2020.4.3 | 281 | 61.5 ± 5.5 | 75 | 206 | 5 |
| Colombi D [26] | 2020 | Italy | English | 2020.2.17–2020.3.10 | 236 | 68(95%CI:66–70) | 177 | 59 | 6 |
| d'Arminio Monforte A [27] | 2020 | Italy | English | 2020.2.24–2020.5.17 | 539 | 66(54–78) | 347 | 192 | 9 |
| Dupley L [28] | 2020 | UK | English | 2020.3.1–2020.4.26 | 64 | 83 ± 9 | 29 | 35 | 8 |
| Feng Y [29] | 2020 | China | English | 2020.1.1–2020.2.15 | 476 | 53(40–64) | 271 | 205 | 8 |
| Fu J [30] | 2020 | China | English | 2020.1.21–2020.3.4 | 35 | 47.94 ± 15 | 13 | 22 | 6 |
| Gao S [31] | 2020 | China | English | 2020.1.23–2020.2.29 | 210 | 71(67–77) | 101 | 109 | 7 |
| Gayam V [32] | 2020 | USA | English | 2020.3.1–2020.4.9 | 408 | 67(56–76) | 231 | 177 | 6 |
| Götzinger F [33] | 2020 | Austria | English | 2020.4.1–2020.4.24 | 582 | 5(0.5–12.0) | 311 | 271 | 9 |
| Guan WJ [34] | 2020 | China | English | 2019.12.11–2020.1.31 | 1590 | 48.9 ± 16.3 | 904 | 686 | 8 |
| Han MF [35] | 2020 | China | English | NR | 154 | 42.4 | 86 | 68 | 7 |
| Hu H [36] | 2020 | China | English | 2020.2.7–2020.3.7 | 105 | 60.82 ± 16.32 | 62 | 43 | 7 |
| Hu L [37] | 2020 | China | English | 2020.1.8–2020.2.20 | 323 | 61(23–91) | 166 | 157 | 8 |
| Huang HF [38] | 2020 | China | English | 2020.1.13–2020.3.10 | 64 | 47.8 ± 18.5 | 37 | 27 | 6 |
| Huang Q [39] | 2020 | China | English | 2020.1.17–2020.2.10 | 54 | 41(31–51) | 28 | 26 | 7 |
| Hwang JM [40] | 2020 | Korea | English | 2020.2.1–2020.3.25 | 103 | 67.62 ± 15.32 | 52 | 51 | 6 |
| Itelman E [41] | 2020 | Israel | English | 2020.2–2020.4.10 | 162 | 52 ± 20 | 105 | 57 | 6 |
| Javanian M [42] | 2020 | Iran | English | 2020.2.25–2020.3.12 | 100 | 60.12 ± 13.87 | 51 | 49 | 6 |
| Kutluhan MA [43] | 2020 | Turkey | English | 2020.3.11–2020.5.10 | 96 | 58 ± 18.5 | 57 | 39 | 7 |
| Lee JY [44] | 2020 | Korea | English | 2020.2.21–2020.4.2 | 694 | 52.1 ± 18.29 | 212 | 482 | 7 |
| Lei SQ [45] | 2020 | China | English | 2020.1.2–2020.2.5 | 34 | 55(43–63) | 14 | 20 | 7 |
| Li M [46] | 2020 | China | English | 2019.12.26–2020.2.25 | 245 | 54(37–64) | 118 | 127 | 8 |
| Li Q [47] | 2020 | China | English | 2020.1.20–2020.2.29 | 325 | 51(36–64) | 167 | 158 | 7 |
| Li T [48] | 2020 | China | English | 2020.2.1–2020.3.31 | 312 | 69.2 ± 7.3 | 187 | 125 | 6 |
| Liu Q [49] | 2020 | China | English | 2020.1.23–2020.2.29 | 84 | 51(37–59) | 45 | 39 | 8 |
| Liu SQ [50] | 2020 | China | English | 2020.1.10–2020.3.15 | 625 | 44.44 ± 17.19 | 329 | 296 | 7 |
| Lu L [51] | 2020 | China | English | 2020.1.18–2020.2.18 | 304 | 44(33–59.25) | 182 | 122 | 7 |
| Luo XM [52] | 2020 | China | English | 2020.1.30–2020.2.20 | 298 | 57(40–69) | 150 | 148 | 7 |
| Lyu PJ [53] | 2020 | China | English | 2020.1.15–2020.2.14 | 51 | 54 ± 17 | 29 | 22 | 7 |
| Maeda T [54] | 2020 | USA | English | 2020.3.13–2020.3.31 | 224 | 63 ± 17 | 127 | 97 | 7 |
| Pan L [55] | 2020 | China | English | 2020.1.18–2020.2.28 | 103 | 52.91 ± 15.98 | 55 | 48 | 9 |
| Qin C [56] | 2020 | China | English | 2020.1.10–2020.2.12 | 452 | 58(47–67) | 235 | 217 | 7 |
| Romero-Sánchez CM [57] | 2020 | Spain | English | 2020.3.1–2020.4.1 | 841 | 66.42 ± 14.96 | 473 | 368 | 6 |
| Shabrawishi M [58] | 2020 | Saudi Arabia | English | 2020.3.12–2020.3.31 | 150 | 46.1 ± 15.3 | 90 | 60 | 8 |
| Wang CZ [59] | 2020 | China | English | 2020.1.23–2020.2.13 | 45 | 39(16–62) | 23 | 22 | 6 |
| Wang D [60] | 2020 | China | English | 2020.1.15–2020.2.28 | 143 | 58(39–67) | 73 | 70 | 6 |
| Wang DW(a) [4] | 2020 | China | English | 2020.1.1–2020.1.28 | 138 | 56(42–68) | 75 | 63 | 8 |
| Wang DW(b) [61] | 2020 | China | English | −2020.2.10 | 107 | 51(36–65) | 57 | 50 | 8 |
| Wang F [62] | 2020 | China | English | 2020.1–2020.3 | 108 | Survivors 70.9 ± 10.6/non-survivors 71.1±10.1 | 72 | 36 | 7 |
| Wang L [63] | 2020 | China | English | 2020.1.1–2020.2.6 | 339 | 69(65–76) | 168 | 171 | 5 |
| Wang LW [64] | 2020 | China | English | 2020.1.14–2020.2.13 | 116 | 54(38–69) | 67 | 49 | 6 |
| Wang WL [65] | 2020 | China | English | 2020.2.10–2020.3.27 | 123 | 68(56.5–78) | 60 | 63 | 8 |
| Wang YF [66] | 2020 | China | English | 2020.1-2020.2.10 | 110 | NR | 48 | 62 | 7 |
| Wang YP [67] | 2020 | China | English | 2020.1.20–2020.2.10 | 275 | 49(34–62) | 128 | 147 | 8 |
| Wei YP [68] | 2020 | China | English | 2020.1.27–2020.3.11 | 276 | 51(41–58) | 155 | 121 | 9 |
| Wu GY [69] | 2020 | China | English | 2019.12.23–2020.2.13 | 299 | 50(35.5–63) | 137 | 162 | 8 |
| Wu J [70] | 2020 | China | English | 2020.1.20–2020.2.20 | 280 | 43.12 ± 19 | 151 | 129 | 7 |
| Wu SR [71] | 2020 | China | English | 2020.1.27–2020.2.26 | 270 | 62(50–69) | 139 | 131 | 6 |
| Xie JF [72] | 2020 | China | English | 2020.1.1–2020.2.29 | 733 | 65(56–73) | 477 | 256 | 7 |
| Yan XQ [73] | 2020 | China | English | 2020.1.21–2020.6.27 | 218 | 42.9(32–52.3) | 122 | 96 | 9 |
| Yan YL [74] | 2020 | China | English | 2020.1.10–2020.2.24 | 193 | 64(49–73) | 114 | 79 | 7 |
| Yang QX [75] | 2020 | China | English | 2020.1.28–2020.2.12 | 136 | 56(44–64) | 66 | 70 | 8 |
| Yang XB [76] | 2020 | China | English | 2019.12.24–2020.1.26 | 52 | 59.7 ± 13.3 | 35 | 17 | 8 |
| Yuan ML [77] | 2020 | China | English | 2020.1.1–2020.1.25 | 27 | 60(47–69) | 12 | 15 | 6 |
| Zhang GQ [78] | 2020 | China | English | 2020.1.2–2020.2.10 | 221 | 55(39–66.5) | 108 | 113 | 7 |
| Zhang HM [79] | 2020 | China | English | 2020.1.28–2020.2.24 | 88 | 55(22–89) | 45 | 43 | 7 |
| Zhang JJ [80] | 2020 | China | English | 2020.1.16–2020.2.3 | 140 | 57(25–87) | 71 | 69 | 7 |
| Zhang L [81] | 2020 | China | English | 2020.1.20–2020.2.29 | 409 | 65(56–71) | 234 | 175 | 6 |
| Zhao Y [82] | 2020 | China | English | 2020.1.13- 2020.3.4 | 539 | 58(43–69) | 255 | 284 | 6 |
| Zheng F [83] | 2020 | China | English | 2020.1.17–2020.2.7 | 161 | 45(33.5–57) | 80 | 81 | 6 |
| Zou WB [84] | 2020 | China | Chinese | 2020.2.1–2020.2.29 | 63 | Severe 52 ± 16/non-severe 43±16 | 32 | 31 | 6 |
a
Age data presented as median (IQR) or mean ± s.d.. NR, not reported.