British Journal of Haematology
John Wiley and Sons Inc.
Changes in blood coagulation in patients with severe coronavirus disease 2019 (COVID‐19): a meta‐analysis
Doi: 10.1111/bjh.16725

Table of Contents



Xiong, Liang, and Wei: Changes in blood coagulation in patients with severe coronavirus disease 2019 (COVID‐19): a meta‐analysis

To the Editor:

Coronavirus disease 2019 (COVID‐19) is widely spread and poses a critical threat to global health.1 Prominent changes in coagulation function in severe patients of COVID‐19 have been reported in a recent study.2 Therefore, we conducted this quantitative meta‐analysis to explore the difference in blood coagulation parameters between severe and mild cases of COVID‐19.

Literature published from December 1, 2019 to March 30, 2020 was searched systematically using PubMed and Embase without language limits. The keywords were: coronavirus, laboratory, clinical manifestations, clinical characteristics, and clinical features. All documents comparing information on coagulation parameters between mild and severe cases of COVID‐19 patients were finally referred to in our meta‐analysis. The pooled standardised mean difference (SMD) and 95% confidence interval (CI) were computed by applying the random‐effect model using Stata software (STATA 14.0, Stata Corp, College Station, TX, USA). The study quality was measured by adopting an 11‐item checklist, which was suggested by the Agency for Healthcare Research and Quality (AHRQ).

Table I displays the main characteristics of the included studies. Nine studies, including one study from medRxiv, with 1105 patients were eventually included for detailed evaluation. Platelet count (PLT), activated partial thromboplastin time (APTT), prothrombin time (PT) and D‐dimer (D‐D) levels were available in five, six, six and eight studies, respectively. All the studies were conducted in China. Quality score varied from 3 to 7 points, with a mean of 5·4 (Table I). All the studies were of moderate quality, except one of low quality.

Table 1
Study characteristics.
StudyN (male %)nAge (years)Severity criteriaQSCoagulation parameters*
PLT (109/l)APTT (s)PT (s)D‐D (mg/l)
Han et al.294 (51·0)45NATrail version 55NA29·5 (3·2)/28·6 (2·7)12·7 (1·1)/12·2 (0·9)19·3 (34·5)/2·1 ( 2·9)
Huang et al.441 (73·0)1349·0 (12·6)ICU and non‐ICU6196·0 (72·6)/149·0 (97·8)26·2 (8·4)/27·7 (6·9)12·2 (1·6)/10·7 (1·7)2·4 (10·2)/0·5 (0·4)
Liu et al.530 (33·3)435·0 (8·0)Trail version 55NANANA1·5 (1·2)/0·3 (0·1)
Mao et al.6214 (40·7)8852·7 (15·5)WHO interim guideline5204·5 (413·3)/219·0 (400·7)NANA0·9 (14·7)/0·4 (6·3)
Peng et al.7112 (47·3)1662·0 (8·9)Standard version6NA36·5 (8·4)/35·8 (6·2)13·9 (1·6)/13·0 (1·2)NA
Wan et al.8135 (53·3)4047·0 (14·1)Trail version 56147·0 (70·4)/170·0 (72·6)29·7 (9·8)/26·6 (3·2)11·3 (0·8)/10·8 (0·7)0·6 (0·5)/0·3 (0·2)
Wang et al.9138 (54·3)3656·0 (19·2)ICU and non‐ICU7142·0 (61·5)/165·0 (46·7)30·4 (4·1)/31·7 (2·9)13·2 (1·6)/12·9 (0·8)0·4 (0·8)/0·2 (0·1)
Wu et al.10201 (63·7)8451·0 (12·3)With and without ARDS6187·0 (94·1)/178·0 (73·7)26·0 (9·2)/29·5 (5·4)11·7 (1·0)/10·6 (1·1)1·2 (3·6)/0·5 (0·4)
Zhang et al.1140 (50·7)5857·0 (45·9)Trail version 53NANANA0·4 (1·6)/0·2 (0·1)
N, number of included patients; n, number of severe patients; QS, quality score; NA, not available; PLT, platelet, reference interval 125–350 × 109/l; APTT, activated partial thromboplastin time, reference interval 25·1–36·5 s; PT, prothrombin time, reference interval 9·4–12·5 s; D‐D, D‐dimer, reference interval 0–0·5 mg/l; ICU, intensive care unit; ARDS, acute respiratory distress syndrome.*Data presented as severe/mild COVID‐19 patients; data as given as mean (standard derivation).

The main difference in coagulation function between severe and mild COVID‐19 patients is shown in Fig 1. Pooled results revealed that PT and D‐D levels were significantly higher in patients with severe COVID‐19 (0·68, 95% CI = 0·43–0·93, I2 = 53·7%; 0·53, 95% CI = 0·22–0·84, I2 = 78·9%, respectively). However, no significant difference in PLT and APTT values between severe and mild patients was observed (−0·08, 95% CI = −0·34 to 0·18, I2 = 60·5%; −0·03, 95% CI = −0·40 to 0·34, I2  = 79·5%, respectively). Increasing values of D‐D and PT support the notion that disseminated intravascular coagulation (DIC) may be common in COVID‐19 patients.2 In addition, the rise of D‐D level also indicates secondary fibrinolysis conditions in these patients. According to Berri et al. ,3 fibrin clot formation helps people to fight against influenza virus infections. Hence, fibrinolysis may potentially induce following severe COVID‐19 infection. Future studies should aim to discover more biomarkers of severe cases of COVID‐19, and studies exploring the underlying mechanism of deranged coagulation function in COVID‐19 are urgently needed. The haemostatic system might be explored for underlying treatment against coronavirus.

Forest plot of PLT, APTT, PT and D‐D levels in severe COVID‐19 patients versus mild COVID‐19 patients.
Fig 1
Forest plot of PLT, APTT, PT and D‐D levels in severe COVID‐19 patients versus mild COVID‐19 patients.

Due to the lack of sufficient study data, we cannot perform a more thorough analysis to prove beneficial screening parameters for PLT, APTT, PT and D‐D for prediction of severity of COVID‐19. However, we suggest that clinical practitioners pay attention to the changes in coagulation function in COVID‐19 patients on a daily basis.



ZhangJJ, DongX, CaoYY, YuanYD, YangYB, YanYQ. . Clinical characteristics of 140 patients infected with SARS‐CoV‐2 in Wuhan, China. Allergy. 2020, doi: 10.1111/all.14238


HanH, YangL, LiuR, LiuF, WuKL, LiJ, et al. . Prominent changes in blood coagulation of patients with SARS‐CoV‐2 infection. Clin Chem Lab Med. 2020, doi: 10.1515/cclm-2020-0188


BerriF, RimmelzwaanGF, HanssM, AlbinaE, Foucault‐GrunenwaldML, LêVB, et al. . Plasminogen controls inflammation and pathogenesis of influenza virus infections via fibrinolysis. PLoS Pathog. 2013;9:e1003229.


HuangC, WangY, LiX, RenL, ZhaoJ, HuY, et al. . Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:, pp.497–506.


LiuM, HeP, LiuHG, WangXJ, LiFJ, ChenS, et al. . Clinical characteristics of 30 medical workers infected with new coronavirus pneumonia. Zhonghua Jie He He Hu Xi Za Zhi. 2020;43:, pp.E016.


MaoL, WangM, ChenS, HeQ, ChangJ, HongC, et al. . Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China. JAMA Neurol.2020, doi: 10.1001/jamaneurol.2020.1127.


PengYD, MengK, GuanHQ, LengL, ZhuRR, WangBY, et al. . Clinical characteristics and outcomes of 112 cardiovascular disease patients infected by 2019‐nCoV. Zhonghua xin xue guan bing za zhi. 2020;48:, pp.E004.


WanS, XiangY, FangW, ZhengY, LiB, HuY, et al. . Clinical features and treatment of COVID‐19 patients in Northeast Chongqing. J Med Virol. 2020, doi: 10.1002/jmv.25783


WangD, HuB, HuC, ZhuF, LiuX, ZhangJ, et al. . Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus‐infected pneumonia in Wuhan, China. JAMA. 2020;323(11):, pp.1061.


WuC, ChenX, CaiY, XiaJ, ZhouX, XuS. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020, doi: 10.1001/jamainternmed.2020.0994 in blood coagulation in patients with severe coronavirus disease 2019 (COVID‐19): a meta‐analysis&author=Mi Xiong,Xue Liang,You‐Dong Wei,&keyword=COVID‐19,coronavirus,coagulation,laboratory,meta‐analysis,&subject=Correspondence,Correspondence,