key: cord-0827944-dmd1el5y
authors: Chocron, Richard; Duceau, Baptiste; Gendron, Nicolas; Ezzouhairi, Nacim; Khider, Lina; Trimaille, Antonin; Goudot, Guillaume; Weizman, Orianne; Alsac, Jean Marc; Pommier, Thibault; Bory, Olivier; Cellier, Joffrey; Philippe, Aurélien; Geneste, Laura; Abdallah, Iannis Ben; Panagides, Vassili; Batti, Salma El; Marsou, Wassima; Juvin, Philippe; Deney, Antoine; Messas, Emmanuel; Attou, Sabir; Planquette, Benjamin; Mika, Delphine; Gaussem, Pascale; Fauvel, Charles; Diehl, Jean-Luc; Pezel, Theo; Mirault, Tristan; Sutter, Willy; Sanchez, Olivier; Bonnet, Guillaume; Cohen, Ariel; Smadja, David M.
title: D-dimers at hospital admission for COVID-19 are associated with in-hospital mortality, independent of venous thromboembolism: Insights from a French multicentre cohort study
date: 2021-03-09
journal: Arch Cardiovasc Dis
DOI: 10.1016/j.acvd.2021.02.003
sha: 5e3aaa8f53efd90cd6a31455968e9d9aa8075e28
doc_id: 827944
cord_uid: dmd1el5y

Background: Coronavirus disease 2019 (COVID-19) has been associated with coagulation disorders, in particular high concentrations of D-dimers, and increased frequency of venous thromboembolism. Aim: To explore the association between D-dimers at admission and in-hospital mortality in patients hospitalized for COVID-19, with or without symptomatic venous thromboembolism. Methods: From 26 February to 20 April 2020, D-dimer concentration at admission and outcomes (in-hospital mortality or venous thromboembolism) of patients hospitalized for COVID-19 in medical wards were analysed retrospectively in a multicentre study in 24 French hospitals. Results: Among 2878 patients enrolled in the study, 1154 (40.1%) patients had D-dimer measurement at admission. Receiver operating characteristic curve analysis identified a D-dimer concentration > 1128 ng/mL as the optimum cut-off value for in-hospital mortality (area under the curve 64.9%, 95% confidence interval [CI] 0.60–0.69), with a sensitivity of 71.1% (95% CI 0.62–0.78) and a specificity of 55.6% (95% CI 0.52–0.58), which did not differ in the subgroup of patients with venous thromboembolism during hospitalization. Among 545 (47.2%) patients with D-dimer concentration > 1128 ng/mL at admission, 86 (15.8%) deaths occurred during hospitalization. After adjustment, in Cox proportional hazards and logistic regression models, D-dimer concentration > 1128 ng/mL at admission was also associated with a worse prognosis, with an odds ratio of 3.07 (95% CI 2.05–4.69; P < 0.001) and an adjusted hazard ratio of 2.11 (95% CI 1.31–3.4; P < 0.01). Conclusions: D-dimer concentration > 1128 ng/mL is a relevant predictive factor for in-hospital mortality in patients hospitalized for COVID-19 in a medical ward, regardless of the occurrence of venous thromboembolism during hospitalization.

in patients hospitalized for COVID-19 in a medical ward, regardless of the occurrence of venous thromboembolism during hospitalization.

Contexte. -La COVID-19 a été associée à des troubles de la coagulation, en particulier des niveaux élevés de D-dimères, et une fréquence accrue d'évènement thromboembolique veineux (TEV). 

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with various clinical respiratory syndromes, ranging from mild upper airway symptoms to progressive life-threatening viral pneumopathy [1, 2] . Patients with severe coronavirus disease 2019 (COVID-19) have progressive hypoxaemia, inducing the need for mechanical ventilatory support. One specific feature of COVID-19 is induced vascular disease. Ackermann et al. recently examined the morphological and molecular features of lungs obtained during autopsies of patients who died from COVID-19, and evidenced an abnormal angiogenic process inside the lungs, in contrast to lungs from patients who died from influenza or agematched and uninfected control lungs [3] . COVID-19-induced vascular disease is also associated with an increased level of circulating endothelial cells [4] . Moreover, plasma biomarkers of endothelial lesions are also predictive factors for future referral to an intensive care unit (ICU), reinforcing the hypothesis of COVID-19-associated vascular injury [5] . The SARS-CoV-2 virus has been shown to infect blood vessels and to induce vascular damage [6] , and fibrin deposits have been found in vascular beds in the lungs, but also in the kidneys.

A high prevalence of venous thromboembolism (VTE)particularly pulmonary embolismhas been observed in patients hospitalized for COVID-19 [6] [7] [8] . However, more than these macrothrombotic events, microvascular thrombosis in the lungs has been reported following autopsies, suggesting acute respiratory distress syndrome in COVID-19 [9] [10] [11] . A thromboinflammatory process in the pulmonary capillary vessels is probably the main cause of microthrombosis in the lung capillaries, inducing COVID-19-associated coagulopathy [12] , which is characterized by an increase in procoagulant factors, such as fibrinogen, together with a strong increase in D-dimers at admission [2, 10] . D-dimer concentration at admission has been associated with in-hospital mortality in several studies [2, 10, 11] , although the cut-off allowing discrimination between patients with favourable and poor outcomes is still a matter of debate.

Using data from a large multicentre French case series, we aimed to identify a D-dimer cut-off at admission that could be a clear independent predictor of in-hospital mortality. [7] . Following World Health Organization criteria, SARS-CoV-2 infection was determined by positive results from real-time reverse transcriptase-polymerase chain reaction tests of nasal and pharyngeal swabs or lower respiratory tract aspirates (confirmed case), or by typical imaging characteristics on chest computed tomography scan when laboratory testing was inconclusive (probable case) [9] .

The Critical COVID-19 France study was declared and authorized by the French data protection committee (Authorization No. 2207326v0), and was conducted in accordance with the ethical standards established in the 1964 Declaration of Helsinki and its later amendments. Centre. Patient baseline information included demographic characteristics, co-existing medical conditions, cardiovascular co-morbidities and chronic medications. Clinical variables and biological findings were recorded at admission. On the chest computed tomography scan, the degree of pulmonary lesions with ground-glass opacities and areas of consolidation was categorized as low/moderate (< 50% involvement) or severe (> 50% involvement). The oral anticoagulation regimen at admission was categorized into two groups: (1) no anticoagulation; and (2) oral anticoagulant therapy with vitamin K antagonists or nonvitamin K antagonist oral anticoagulants. The occurrence of symptomatic VTE during hospitalization included pulmonary embolism and/or deep vein thrombosis.

The primary outcome was the time from diagnosis to death, to assess the predictive performance of Ddimer concentration at admission in patients with COVID-19. Outcomes were assessed using the electronic medical records.

Continuous data are expressed as means ± standard deviations and categorical data as proportions.

Continuous variables were compared using the Mann-Whitney test, and categorical variables were compared using Fisher's exact test [13] . We generated D-dimer concentration at admission receiver operating characteristic (ROC) curves for in-hospital mortality. We identified the optimal threshold of Ddimer concentration at admission using Youden's J statistic. In the univariate analysis, patients were compared according to the optimal threshold of D-dimers at admission. In the multivariable analysis, we used logistic regression to assess the association between the concentration of D-dimers (as a categorical dependent variable dichotomized according to the optimal threshold) and platelet count, leukocyte count or in-hospital mortality [14, 15] . The model included as covariates: sex; age; cardiovascular co-morbidities, such as history of high blood pressure; history of malignancy (cancer in remission or active cancer); plasma creatinine concentration (dichotomized according to the normal value of 107 µmol/L); C-reactive protein (mg/L); the degree of pulmonary lesions with ground-glass opacities and areas of consolidation (dichotomized < or > 50%); the use of oral anticoagulant therapy; and the occurrence of VTE during hospitalization. A Cox proportional hazards model with length of stay (in days) as a time scale was used to investigate the relationship between the concentration of D-dimers (as a categorical dependent variable dichotomized according to the optimal threshold) and in-hospital mortality. The model was adjusted for the same potential confounders included in the logistic regression model. The Kaplan-Meier method was used to represent the Cox proportional hazards model results according to the concentration of D-dimers (as a categorical dependent variable dichotomized according to the optimal threshold). We used the log-rank test to compare the survival distributions according to the optimal threshold of D-dimers. We performed three sensitivity analyses: (1) to take into account the retrospective design and to avoid bias caused by censored data (n = 268/1154, 23.2%), we performed the same multivariable analysis in the population of patients who were discharged alive from hospital or who died in hospital (total patients analysed, n = concentration at admission ROC curve only in the subgroup of patients with VTE during hospitalization (n = 127, and compared the area under the curve of the two ROC curves using Delong's test; (3) to adjust for bias caused by non-random allocation of potential covariates, we performed a propensity-matched analysis [16] of patients who had VTE during hospitalization for COVID-19 compared with those who did not have VTE, and repeated the Cox proportional hazards model adjusted only on plasma creatinine concentration (> 107 µmol/L), the use of oral anticoagulant therapy, VTE occurrence during hospitalization, fraction of inspired oxygen and the degree of pulmonary lesions with ground-glass opacities and areas of consolidation.

All analyses were two-sided, and a P value < 0.05 was considered statistically significant. Statistical analysis was performed using R studio software (R Development Core Team [2019]. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria).

During the study period, a total of 2878 consecutive patients who were hospitalized in a medical ward for SARS-CoV-2 infection were included. At admission, 1154/2878 (40.1%) patients had D-dimer measurement (mean age 64.35 ± 16.63 years; 59.8% (690/1154) male Table 1 ). The optimum cut-off value for D-dimers at admission with the best prognostic ability of in-hospital mortality was 1128 ng/mL according to the ROC curve ( Fig. 1) , with a sensitivity of 71.1% (95% confidence interval [CI] 0.62-0.78), a specificity of 55.6% (95% CI 0.52-0.58), a positive predictive value of 15.8% (95% CI 0.13-0.19) and a negative predictive value of 94.3% (95% CI 0.92-0.96). The area under the curve for in-hospital mortality was 64.9% (95% CI 0.60-0.69). Listed in Table 1 are the initial clinical, biological and radiological characteristics and outcomes of the patients above and beyond the D-dimer cut-off of 1128 ng/mL. We also explored the prognostic performance of D-dimer thresholds proposed previously, and a D-dimer concentration at admission > 1128 ng/mL remained the best threshold (Table 2 ). At admission, 609/1154 (52.8%) patients had D-dimer concentrations ≤ 1128 ng/mL and 545/1154 (47.2%) had D-dimer concentrations > 1128 ng/mL. Compared with patients with D-dimer concentrations ≤ 1128 ng/mL, patients with D-dimer concentrations > 1128 ng/mL were older, and more frequently had high blood pressure and chronic kidney disease. These patients had higher concentrations of creatinine, C-reactive protein and fibrinogen, higher platelet and leukocyte counts and a higher rate of severe parenchymal involvement on chest computed tomography scan. Moreover, those patients had a lower haemoglobin concentration and prothrombin ratio. The in-hospital mortality rate (15.8% vs 5.7%) and the mean duration of hospitalization (10.25 ± 6.47 days vs 8.75 ± 5.83 days) were significantly greater for patients with COVID-19 with a D-dimer concentration > 1128 ng/mL at admission (Table 1) .

We also evaluated D-dimer concentration at admission in the subgroup of patients who developed VTE during hospitalization (n = 127). In this subgroup, the optimum cut-off value for D-dimers at admission was 1202 ng/mL using the ROC curve, with a sensitivity of 61% (95% CI 0.17-0.92), a specificity of 25.3% (95% CI 0.12-0.58), a positive predictive value of 5.8% (95% CI 0.01-0.16) and a negative predictive value of 95.3% (95% CI 0.84-0.98). The area under the curve for in-hospital mortality was 63.7% (95% CI 0.37-0.90). This cut-off value of 1202 ng/mL did not differ significantly from that of the whole study population (P = 0.92).

Kaplan-Meier survival curves for D-dimer concentration showed that a concentration > 1128 ng/mL at admission was a significant predictor of in-hospital mortality (P < 0.001; Fig. 2A ). Statistical significance of separation between the two groups was achieved at 9 days. As shown in Table 3 , D-dimer concentration > 1128 ng/mL was significantly associated with higher in-hospital mortality (odds ratio 2.08, 95% CI 1.24-3.54; P = 0.006) in the logistic regression. In the same way, Cox proportional hazards analysis showed that D-dimer concentration > 1128 ng/ml at admission was also a significant determinant for worse prognosis (hazard ratio 2.11, 95% CI 1.31-3.4; P < 0.01) after adjustment ( Fig. 2A and 3A ).

In the sensitivity analysis, the D-dimer concentration at admission ROC curve for in-hospital mortality in the subgroup of patients with VTE during hospitalization (n = 127) was similar. Based on the matched and balanced dataset ( [9/127]; P = 0.72). Secondly, we repeated the same Cox proportional hazards model adjusted, and observed a significant association between concentration of D-dimer > 1128 ng/mL at admission and inhospital mortality, with a hazard ratio of 3.11 (95% CI 1.26-7.80; P = 0.014). According to the prediction 12 (hazard ratio) for in-hospital mortality, after adjustment, the best predictor remained > 1128 ng/mL, with the higher prognostic ability (Table A. 2). Moreover, when the analysis was restricted to patients without censored outcome (n = 1886) the level of association between D-dimer concentration > 1128 ng/mL and in-hospital mortality remained similar, with an odds ratio of 1.88 (95% CI 1.08-3.31; P = 0.02) and a hazard ratio of 2.20 (95% CI 1.25-3.3; P < 0.01) ( Table 4 and Fig. 3B ).

The main finding of this retrospective study is that D-dimer concentration at admission > 1128 ng/mL is an independent predictor of in-hospital mortality for patients with COVID-19. This multicentre French study of patients hospitalized for COVID-19 is the largest non-monocentric study to date of patients hospitalized in a medical ward to provide evidence that initial D-dimer concentration could be a valuable tool to predict further in-hospital mortality. Moreover, to the best of our knowledge, we show for the first time that VTE occurrence during hospitalization does not interfere with the predictive value of D-dimers for in-hospital mortality.

High D-dimer concentration has been widely reported to be one of the most common laboratory findings reported in patients with COVID-19 at hospital admission. We previously demonstrated that Ddimer measurement at admission is a discriminant factor during COVID-19 suspicion. Indeed, adding a Ddimer cut-off beyond 500 ng/mL to female sex and absence of pneumonia on computed tomography scan could exclude a COVID-19 diagnosis with high sensitivity and specificity [4] . Moreover, we and others showed that D-dimer concentration at admission was higher in patients who needed ICU referral compared with those who did not [5, 17] . Moreover, several reports have described that increased Ddimer concentrations were related to in-hospital mortality [10, 18, 19] . Only one study provided a well evaluated cut-off for D-dimers [11] (2000 ng/mL) for a relationship with in-hospital mortality in 343 patients. However, this study did not specify whether patients were hospitalized in a medical ward or if they were directly hospitalized in an ICU, making proper and accurate use of this cut-off difficult for clinicians. Our study only included patients with COVID-19 admitted to a medical ward; some were subsequently referred to an ICU, but none was directly hospitalized in an ICU. Our results propose COVID-19-increased D-dimer concentration as a clear consequence of respiratory disease through the J o u r n a l P r e -p r o o f 13 development of capillary microthrombosis, as observed in postmortem studies [20, 21] , and attributed to vascular thickening or vascular congestion [22] . Recently, we evidenced D-dimer involvement in the pathophysiology of COVID-19, and correlation with right ventricular dysfunction, which allows us to confirm pulmonary vascular obstruction as a site of coagulopathy and a source of circulating D-dimers [23] . Thus, in COVID-19, the hypothesis of microthrombosis is proposed in lung, but also in kidney, as the elevation of serum creatinine was associated with higher concentrations of D-dimers (> 500 ng/mL) [1, 2] .

The SARS-CoV-2 receptor (angiotensin-converting enzyme 2) is strongly expressed in endothelial cells [24] . Infection of endothelial cells could therefore induce endothelial lesions, triggering massive activation of coagulation and diffuse microthrombotic process, impairing renal function and respiratory gas exchanges. We previously described increased numbers of circulating endothelial cells in patients with COVID-19 [4] and an association between circulating biomarkers of endothelial activation in COVID-19 and ICU admission [5] . Angiopoietin-2 was also inversely correlated with respiratory system compliance in this study, paving the way for a relationship between endothelial dysfunction and pulmonary disease severity. Integrity of endothelial cells provides an antithrombotic environment that is reversed during COVID-19 upon the burst of inflammation related to interleukin-6. Therefore, SARS-CoV-2 infection induces a disruption of the endothelial thromboprotective barrier that leads to this coagulopathy and increased D-dimers. In the present cohort, patients were at the same stage of disease according to the time to onset of symptoms of disease, so endothelial-induced coagulopathy reflected by D-dimers could be a consequence of viral loading phase and severity of viral infection. The importance of the viral loading hypothesis needs to be confirmed, with association between D-dimers and viraemia quantified with sensitive tests.

A major confounding factor for D-dimer increase could be macrothrombosis, as a high incidence of VTE (pulmonary embolism or deep vein thrombosis) [7, 8, 25] has been described in COVID-19. In clinical practice, D-dimer measurements have been used only to exclude VTE. Indeed, no such D-dimer-based strategy has been described during COVID-19-associated coagulopathy in patients with a high concentration of D-dimers. Even if increased D-dimer concentrations at admission have been associated with VTE during follow-up in patients with COVID-19 [26] , no threshold is currently available to diagnose VTE. Furthermore, the International Society of Thrombosis and Haemostasis (ISTH) does not recommend J o u r n a l P r e -p r o o f 14 routine screening for VTE based on elevated D-dimer concentrations in patients with COVID-19 [27] .

However, we demonstrate here that a D-dimer cut-off of 1128 ng/mL at admission is independently correlated with in-hospital mortality, regardless of VTE occurrence during hospitalization. Moreover, we identified several other predictors of in-hospital mortality, such as renal function impairment, age and lung damage extent > 50%. Even after adjustment for those risk factors, D-dimer cut-off at admission remains independently correlated with in-hospital mortality. D-dimers might be used to monitor COVID-19 worsening [28] . Indeed, previous studies have observed that a progressive increase in D-dimers was observed in non-survivors of COVID-19 [11] .

Our study has several limitations. First, in this multicentre study, we could not identify the manufacturer or type of D-dimer assay used for all tested D-dimers, as suggested by ISTH [7] . It is well recognized by experts in the field that all D-dimer assays are not the samethey use different detection antibodies, different detection methods and often different calibrators [29] . Indeed, different D-dimer assays vary in their specificity against degradation products, resulting substantial variability between D-dimer assay kits.

This technical point is a limitation to multicentre studies. This limitation reduces the generalizability of the use of optimal D-dimer thresholds. Second, we did not have the delay from COVID-19 admission to VTE onset during hospitalization. Third, serial D-dimer monitoring has been suggested by ISTH [5, 30] as being helpful in determining prognosis in patients with COVID-19. Indeed, a peak of D-dimers has been found to be associated with VTE in COVID-19 [31, 32] , but in the present study, we only assessed D-dimers at admission. However, as VTE occurrence did not modify in-hospital mortality in the present study, this lack of continuous monitoring of D-dimers is unlikely to modify the results.

This multicentre retrospective study suggests that D-dimer concentration at admission could be a valuable biomarker to predict mortality related to COVID-19, independent of VTE occurrence during hospitalization.

The determined cut-off at 1128 ng/mL could be a valuable tool to guide anticoagulation intensity in patients with COVID-19. Further prospective studies are necessary to confirm whether this D-dimer threshold reflects COVID-19 worsening. 

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Data are expressed as % (95% confidence interval). NPV: negative predictive value; PPV: positive predictive value

A complete list of the Critical COVID-19 France Investigators is provided in the Appendix.

This research did not receive any specific grant from funding agencies in the public, commercial or not-forprofit sectors.