key: cord-1007003-7w3djyqg authors: Gungor, Baris; Atici, Adem; Baycan, Omer Faruk; Alici, Gokhan; Ozturk, Fatih; Tugrul, Sevil; Asoglu, Ramazan; Cevik, Erdem; Sahin, Irfan; Barman, Hasan Ali title: Elevated D-dimer levels on admission are associated with severity and increased risk of mortality in COVID-19: A systematic review and meta-analysis date: 2020-09-14 journal: Am J Emerg Med DOI: 10.1016/j.ajem.2020.09.018 sha: 4b2776f1f0202468dd75f35239297a597958c511 doc_id: 1007003 cord_uid: 7w3djyqg BACKGROUND: In this systematic review and meta-analysis, we aimed to investigate the correlation of D-dimer levels measured on admission with disease severity and the risk of death in patients with coronavirus disease 2019 (COVID-19) pneumonia. MATERIALS AND METHODS: We performed a comprehensive literature search from several databases. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in abstracting data and assessing validity. Quality assessment was performed using the Newcastle-Ottawa quality assessment scale (NOS). D-dimer levels were pooled and compared between severe/non-severe and surviving/non-surviving patient groups. Weighted mean difference (WMD), risk ratios (RRs) and 95% confidence intervals (CIs) were analyzed. RESULTS: Thirty-nine studies reported on D-dimer levels in 5750 non-severe and 2063 severe patients and 16 studies reported on D-dimer levels in 2783 surviving and 697 non-surviving cases. D-dimer levels were significantly higher in patients with severe clinical status (WMD: 0.45 mg/L, 95% CI: 0.34–0.56; p < 0.0001). Non-surviving patients had significantly higher D-dimer levels compared to surviving patients (WMD: 5.32 mg/L, 95% CI: 3.90–6.73; p < 0.0001). D-dimer levels above the upper limit of normal (ULN) was associated with higher risk of severity (RR: 1.58, 95% CI: 1.25–2.00; p < 0.0001) and mortality (RR: 1.82, 95% CI: 1.40–2.37; p < 0.0001). CONCLUSION: Increased levels of D-dimer levels measured on admission are significantly correlated with the severity of COVID-19 pneumonia and may predict mortality in hospitalized patients. In December 2019, an outbreak of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei Province, China and severe acute respiratory syndrome coronavirus-2 (SARS-CoV -2) has been designated as the pathogen. COVID-19 has inflicted millions of people worldwide, but definite prognostic factors and treatment regimens could not been adequately defined (1) . COVID-19 manifests with enteric, hepatic, nephrotic, neurological and cardiac symptoms, causing multiple organ failure and a high risk of death (2) . Arterial have not been well described (3) (4) (5) (6) . In this systematic review and meta-analysis, we aimed to investigate the prognostic value of D-dimer levels measured on admission in COVID-19 patients. This analysis was planned based on the current MOOSE (Meta-analysis of Observational Studies in Epidemiology) and PRISMA (Preferred Reporting Items for Systematic Review and Meta-analysis) guidelines in order to perform a comprehensive systematic review and meta-analysis (7, 8) . As the study was a meta-analysis, no approval from the institutional review board was required. Severe patients were accepted to have any of the following criteria: (1) respiratory distress (respiratory rate ≥30 breaths per min); (2) oxygen saturation at rest ≤93%; (3) ratio of the partial pressure of arterial oxygen (PaO2) to the fractional concentration of oxygen inspired air (FiO2) (Pao2:FiO2, ≤300 mmHg); or (4) critical complication (respiratory failure and need for mechanical ventilation, septic shock, and/or multiple organ dysfunction/failure and intensive care unit admission requirement) (9) . Two independent investigators (B.G. and A.A.) searched the electronic databases including Medline, Google Scholar, and Scopus between December 12, 2019 and April 25, 2020 using the key words "coronavirus", "pneumonia", "nCoV", "SARS-CoV-2", "COVID*", "prognosis", "death", "mortality", "laboratory", "dimer" and "coagulation" either alone or in combinations. Moreover, medRxiv https://www.medrxiv.org), SSRN (https://www.ssrn.com) and the reference lists of all studies were identified. This search was restricted to adults (>18 years of age) and the English language. Reviews and reference lists of retrieved articles were hand searched for potentially relevant publication not previously identified in the database search. Retrieved studies were reviewed by two investigators (B.G. and H.A.B.) using a standardized data collection form. In case of disagreement, a consensus was reached by a third reviewer (AA). The title, abstract, and the full text of all these studies were analyzed. Among these studies, those reporting on the D-dimer values measured on admission in COVID-19 patients and those comparing non-severe and severe patients and surviving and non-surviving patients were included in the meta-analysis. Exclusion criteria included (1) case reports and case series, (2) unclear grouping of the study population (e.g. comparison according to presence of frailty, obesity, diabetes mellitus or comparison between different regions or countries), (3) laboratory parameters that were not measured during initial evaluation or on admission, and (4) the studies reporting only on the results of surviving, non-surviving, or ICU patients. Extracted data included age, sex, sample size, sample characteristics, D-dimer levels, odds ratio (OR) of D-dimer levels for the development of severe disease or mortality as well as the other study characteristics of the included studies. The country of origin, authors, and the enrollment periods of the studies were reviewed to exclude duplicate publications of the same cohort. Mean and standard deviation of D-dimer values were extrapolated from the sample size, median, and interquartile range (IQR) as previously defined (10,11). In the studies that J o u r n a l P r e -p r o o f presented the data using graphs only, GetData Graph Digitizer 2.24 (http://getdatagraphdigitizer.com/) software was used to digitize and extract the data. The methodological quality of retrospective studies was assessed by the modified Newcastle-Ottawa scale (NOS) which consists of three domains: (1) subject selection, (2) comparability of the study groups, and (3) the assessment of outcome(s) (12) . A score of 0-9 was allocated to each study except for randomized clinical trials. Observational studies with an NOS score ≥6 were accepted as high-quality. A meta-analysis was performed based on the calculation of weighted mean difference (WMD) and 95% confidence interval (95% CI) of D-dimer values in COVID-19 patients with or without severe disease and surviving and non-surviving patients. To determine heterogeneity across the studies, an a priori decision was made to select the random-effects model that could allow more conservative estimates in scenarios with heterogeneity. To investigate categorical variables, risk ratios (RRs) and 95% CIs were calculated from the number of cases in each group and the total sample size. In the studies reporting the outcomes using OR, the ORs were pooled using a random-effects model by the method of DerSimonian and Laird (13) . The Cochran's Q and Higgins's I2 statistics were used to estimate heterogeneity. Publication bias was estimated using funnel plots and Begg's rank correlation test and Egger's linear regression test (14, 15) . In order to define any source of heterogeneity, sensitivity analysis was performed by excluding each study and rerunning the meta-analysis. RevMan 5.3 (The Cochrane Collaboration) and MetaXL, software Version 5.3 (EpiGear International PtyLtd., Sunrise Beach, Australia) were used for performing this analysis. The study selection process was illustrated in Table 1 . Thirty-nine studies compared the D-dimer levels between a total of 5759 severe and 2063 non-severe patients . Sixteen studies compared the D-dimer levels between a total of 2783 surviving and 697 non-surviving patients (39, (55) (56) (57) (58) (59) (60) (61) (62) (63) (64) (65) (66) (67) (68) (69) . All the studies except for one were performed outside China (64) . Fourteen studies reported the number of cases with a D-dimer level above the upper limit of normal (ULN) in each group and analyzed the D-dimer levels as categorical variables (16, 20, (23) (24) (25) 33, 35, 39, 44, 46, 50, 51, 60, 67) . Thirteen studies reported on predictors of severity and eight other studies reported on predictors of mortality using logistic regression analysis; however, only four studies analyzed D-dimer levels using a multivariate regression model. The time from the onset of symptoms to hospital admission was longer in more severe and non-surviving patients. The In our study, the D-dimer levels were used as continuous variables in logistic regression analysis for the prediction of clinical outcomes in remarkably few studies. We pooled ORs from univariate and multivariate regression analyses for the prediction of clinical outcomes using admission D-dimer levels as continuous variables; however, the pooled ORs for each comparison did not reach statistical significance (Supplemental Figures 1-3) . We performed a meta-regression analysis to investigate the effect of the time from the onset of symptoms to hospital admission on D-dimer levels due to the fact that the patients in severe and non-surviving groups were admitted to hospital at a later period when compared to nonsevere and surviving groups (Supplemental Table 1 ). The ratio of the mean duration of this time period in severe/non-severe and surviving/non-surviving groups was accepted as the covariate for the meta-regression analysis. Eighteen studies compared the time from the onset of symptoms to hospital admission between severe and non-severe patients. In the meta-regression analysis, we did not find a significant correlation between symptom duration and D-dimer difference (β=0.248, p=0.075) (Supplemental Figure 4) . The same analysis was performed for six studies that reported time intervals in surviving and non-surviving patients. The admission time was found to have a significant effect on the D-dimer levels assessed on admission (β=27.646, p<0.01) (Supplemental Figure 5 ). The funnel-plot analysis showed a symmetrical shape for all outcomes, indicating a low risk of publication bias in severe and non-severe patients with no indication of small-study effects (Egger's test, p=0.987; Begg's test, p=0.953) (Supplemental Figure 6) . However, the funnelplot analysis showed an asymmetrical shape for the studies included, i.e. in the comparison of surviving and non-surviving patients with an indication of small-study effects (Egger's test, p=0.008; Begg's test, p=0.019) (Supplemental Figure 6 ). The present meta-analysis evaluated the clinical data of 11,054 COVID-19 patients and indicated that patients with more severe presenting symptoms and patients with a higher risk Although therapeutic anticoagulation seems to have clinical benefits in COVID-19 patients, routine anticoagulation is not recommended by international societies since there have been no randomized control trials to date (70, 72, 79) . Recently, Paranjpe et al. compared in-hospital mortality between 1987 patients without any anticoagulation and 786 patients with treatmentdose anticoagulation and found no significant difference between the two groups with regard to in-hospital mortality (22.8% and 22.5%, respectively). The authors also noted that only 1.9% of the anticoagulated patients developed bleeding events after the initiation of anticoagulation therapy, although there was no significant difference between the two groups with regard to the incidence of bleeding events (80) . In that study, however, the incidence of DIC, D-dimer levels, and the indications for anticoagulant therapy were not reported. The prognosis of COVID-19 is poor in some group of patients. Unfortunately, an effective, globally accepted treatment algorithm for the treatment of COVID- 19 has not yet been established. Additionally, the importance of anticoagulant therapy is increasing, as thrombotic events play a major role in mortality. This meta-analysis showed that elevated D-dimer levels are strongly associated with disease severity and increased mortality. Future studies are warranted to investigate whether anticoagulation treatment strategies reduce morbidity and mortality in COVID-19. Future studies are warranted to investigate the clinical benefit of ddimer directed anticoagulant treatment regimens in COVID-19. The authors received no financial support for the research, authorship, and/or publication of this article. Competing interests: None declared. A pneumonia outbreak associated with a new coronavirus of probable bat origin Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention Changes in Blood Coagulation in Patients with Severe Coronavirus Disease 2019 (COVID-19): a Meta-Analysis. British journal of haematology D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19 ISTH interim guidance on recognition and management of coagulopathy in COVID-19 Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis Metaanalysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range Newcastle-Ottawa quality assessment scale cohort studies Meta-analysis in clinical trials Operating characteristics of a rank correlation test for publication bias Bias in meta-analysis detected by a simple, graphical test ACP risk grade: a simple mortality index for patients with confirmed or suspected severe acute respiratory syndrome coronavirus 2 disease (COVID-19) during the early stage of outbreak in Wuhan Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease Characteristics and associations with severity in COVID-19 patients: a multicenter cohort study from Jiangsu province: China Clinical Characteristics and Laboratory Indicator Analysis of 69 COVID-19 Pneumonia Patients in Suzhou Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan Clinical characteristics of 145 patients with corona virus disease 2019 (COVID-19 Clinical Characteristics of Coronavirus Disease 2019 in China Clinical Characteristics of Coronavirus Disease Clinical characteristics of patients with 2019 coronavirus disease in a non-Wuhan area of Hubei Province, China: a retrospective study Clinical Characteristics of Patients with Severe Pneumonia Caused by the 2019 Novel Coronavirus in Wuhan, China Clinical characteristics of SARS-CoV-2 pneumonia compared to controls in Chinese Han population The clinical course and its correlated immune status in COVID-19 pneumonia Clinical Features and Risk Factors for the Severity of Inpatients with COVID-19: A Retrospective Cohort Study. Available at SSRN … Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan Clinical features and treatment of COVID-19 patients in northeast Chongqing Clinical features of patients infected with 2019 novel coronavirus in Wuhan Clinical Features of Patients Infected with the 2019 Novel Coronavirus (COVID-19 Clinical value of immuneinflammatory parameters to assess the severity of coronavirus disease 2019 A cohort study of 223 patients explores the clinical risk factors for the severity diagnosis of COVID-19. medRxiv COVID-19 in a designated infectious diseases hospital outside Hubei Province COVID-19 myocarditis and severity factors: an adult cohort study. medRxiv COVID-19 with Different Severity: A Multi-center Study of Clinical Features D-dimer as a biomarker for disease severity and mortality in COVID-19 patients: a case control study: europepmc.org A descriptive study of the impact of diseases control and prevention on the epidemics dynamics and clinical features of SARS-CoV-2 outbreak in Shanghai, lessons learned for metropolis epidemics prevention Diagnostic Utility of Clinical Laboratory Data Determinations for Patients with the Severe COVID-19 Early antiviral treatment contributes to alleviate the severity and improve the prognosis of patients with novel coronavirus disease (COVID-19) Epidemiologic and Clinical Characteristics of 91 Hospitalized Patients with COVID-19 in Zhejiang, China: A retrospective, multi-centre case series Epidemiological and clinical features of 291 cases with coronavirus disease 2019 in areas adjacent to Hubei Epidemiological characteristics and clinical features of 32 critical and 67 noncritical cases of COVID-19 in Chengdu The laboratory tests and host immunity of COVID-19 patients with different severity of illness A New Predictor of Disease Severity in Patients with COVID-19 in Wuhan, China. medRxiv Predicting COVID-19 malignant progression with AI techniques Renal Involvement and Early Prognosis in Patients with COVID-19 Pneumonia Retrospective study of risk factors for severe SARS-Cov-2 infections in hospitalized adult patients Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan2020 Cell Counts in COVID-19 Patients Revealed Initial Immune Status of Patients as a Major Determinant of Disease Severity: papers.ssrn.com Suspected myocardial injury in patients with COVID-19: Evidence from front-line clinical observation in Wuhan, China A Tool to Early Predict Severe Corona Virus Disease 2019 (COVID-19) : A Multicenter Study using the Risk Nomogram in Wuhan and Guangdong, China. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia Clinical and Laboratory Factors Predicting the Prognosis of Patients with COVID-19: An Analysis of 127 Patients in Wuhan Clinical and Laboratory Predictors of In-Hospital Mortality in 305 Patients with COVID-19: A Cohort Study in Wuhan Alteration of lipid profile and prognostic value of lipids on the length of hospital stay in COVID-19 pneumonia patients Admission biochemical test associated with the prognosis of COVID-19: a multi-centered retrospective cohort study: europepmc.org Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study Clinical Characteristics and Risk Factors for Mortality of COVID-19 Patients With Diabetes in Wuhan, China: A Two-Center Dynamic changes of D-Dimer and Neutrophil-Lymphocyte Count Ratio as prognostic biomarkers in COVID-19: europepmc.org Elevated serum IgM levels indicate poor outcome in patients with coronavirus disease 2019 pneumonia: A retrospective casecontrol study Laboratory predictors of death from coronavirus disease 2019 (COVID-19) in the area of Valcamonica Myocardial injury is associated with in-hospital mortality of confirmed or suspected COVID-19 in Wuhan Potential Predictors for Disease Progression and Medication Evaluation of 2019 Novel Coronavirus-Infected Pneumonia in Wuhan Predictors of Mortality for Patients with COVID-19 Pneumonia Caused by SARS-CoV-2: A Prospective Cohort Study. The European respiratory journal Short Term Outcomes and Risk Factors for Mortality in Patients with COVID-19 in Wuhan Suppressed T cellmediated immunity in patients with COVID-19: a clinical retrospective study in Wuhan Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic Potential Effects of Coronaviruses on the Cardiovascular System: A Review COVID-19 and Thrombotic or Thromboembolic Disease: Implications for Prevention, Antithrombotic Therapy, and Follow-up D-dimer levels and 15-day outcome in acute pulmonary embolism. Findings from the RIETE Registry Predicts Long-Term Cause-Specific Mortality, Cardiovascular Events, and Cancer in Patients With Stable Coronary Heart Disease: LIPID Study Laboratory abnormalities in patients with COVID-2019 infection D-dimer is Associated with Severity of Coronavirus Disease 2019: A Pooled Analysis Incidence of thrombotic complications in critically ill ICU patients with COVID-19 Anticoagulation in COVID-19 Association of Treatment Dose Anticoagulation with In-Hospital Survival Among Hospitalized Patients with COVID-19