Dynamic Relationship Between High D-Dimer Levels and the In-Hospital Mortality Among COVID-19 Patients: A Moroccan Study

Abstract

This study included 221 patients with COVID-19 who were admitted to the emergency department of Avicenne Hospital in Rabat between August 2020 and August 2021. Patients were divided into three groups according to their D-dimer levels (<1, 1–2, and >2 µg/mL). Adjusted and unadjusted logistic regression analyses were performed to assess the association between elevated D-dimer levels and in-hospital mortality. Pearson’s correlation analysis was performed to explore the relationship between D-dimer levels and various biological and clinical parameters. The results revealed a statistically significant difference in the mean (SD) age among the three groups (p = 0.006). Analysis showed a statistically significant difference in the means (SD) of oxygen saturation, duration of hospital stay, and breathing rate among the three independent groups of COVID-19 patients. Patients with elevated D-dimer levels (greater than 2 µg/mL) experienced worse outcomes than those in the other groups, with severity, transfer to intensive care, and in-hospital mortality of 55 (40.7%), 35 (16%), and 24 (11%) patients, respectively, with p-values of 0.048, 0.002, and 0.002, respectively. Patients in the D-dimer > 2 µg/mL group had significantly higher C-reactive protein (CRP), lactate dehydrogenase, urea, cardiac troponin, B-type natriuretic peptide, and ferritin levels than those in the other two groups. The p-value was significant among the three groups (p = 0.044, p = 0.001, and p < 0.001). Age and elevated D-dimer levels (greater than 2 µg/mL) were associated with mortality in patients diagnosed with COVID-19. Correlation analysis indicated that D-dimer in COVID-19 patients is associated with worsening respiratory, hepatic, cardiac, and coagulation parameters, suggesting their utility as an integrative marker of disease severity. D-dimer levels > 2 µg/mL were identified as an independent risk factor for COVID-19 in-hospital mortality. Measuring and monitoring D-dimer levels can assist clinicians in taking timely actions and predicting the prognosis of patients with COVID-19.

1. Introduction

Since the beginning of 2020, the severity and mortality of the novel coronavirus disease (COVID-19) pandemic have been highlighted in several studies [1,2,3]. Other studies have demonstrated that coagulopathy is common among critically ill patients with severe acute respiratory syndrome caused by the novel coronavirus (SARS-CoV-2) [4,5]. Systemic microvascular thrombosis and venous thromboembolism have been observed in most cases, as substantiated by autopsy results [6]. As indicators of thrombosis risk, D-dimer levels, which are produced during the degradation of fibrin by the fibrinolytic system, which is activated during thrombus formation, were identified early in the pandemic as predictors of COVID-19 severity and death [7]. The evolving trend of D-dimer levels, especially at the beginning of hospitalization, could be a poor prognostic factor for this disease [5,8,9].

Several international studies have identified the optimal D-dimer threshold for predicting mortality in COVID-19 patients using statistical models such as the receiver operating characteristic curve (ROC), along with univariate and multivariate logistic regressions [4,10,11,12]. Research on D-dimers in Morocco remains limited in scope and is generally concentrated in specific areas. For instance, Oualim et al. conducted a study at Cheikh Khalifa Hospital in Casablanca that provided valuable insights using ROC curve analysis to assess the predictive value of D-dimers for mortality. While informative, the study’s relatively small sample size highlights the need for broader investigations involving larger and more diverse populations to strengthen the generalizability of the findings [13].

In the post-COVID-19 context, interest in biomarkers associated with disease severity and mortality remains topical, particularly because of the persistence of late complications and post-acute syndromes. D-dimers, indicators of coagulation activation and fibrinolysis, were identified early on as being strongly associated with severe forms and an increased risk of death in patients with COVID-19 infection. However, their clinical relevance in different geographical and demographic contexts remains unclear.

During the study period, Morocco experienced several waves of the novel coronavirus, shaped by the emergence and subsequent spread of various SARS-CoV-2 variants of concern. The Alpha variant (B.1.1.7) was predominant in early 2021, followed by the Delta variant (B.1.617.2), which became dominant by mid-2021 and was associated with increased disease severity and higher hospitalization rates. These variants are characterized by elevated viral loads, heightened inflammatory responses, and, in some cases, augmented coagulopathy, including elevated D-dimer levels. The Moroccan population also faced variability in access to healthcare and evolving treatment protocols during these waves of infection. It is imperative to comprehend the epidemiological context of the SARS-CoV-2 variants that were in circulation in Morocco during the period in which the data were collected. This is crucial for contextualizing the findings of the present study, particularly concerning biomarker profiles and clinical outcomes. Indeed, few studies have investigated the prognostic value of D-dimers in hospitalized COVID-19 patients, in relation to biological and clinical parameters and fatal outcomes. Understanding these associations is essential not only to inform medical practice during health crises but also to guide the long-term follow-up of at-risk patients in the post-pandemic era.

With this in mind, the present study was conducted to examine the role of elevated D-dimer levels as a potential marker associated with poor prognosis, identify correlations with other biological and clinical parameters, and investigate their potential risk in predicting mortality in the Moroccan population during the peak period of SARS-CoV-2 infection.

2. Materials and Methods

2.1. Study Design

This was a retrospective descriptive and analytical study of the medical records of patients admitted and hospitalized with COVID-19 in the acute medical unit (AMU) of Avicenne Hospital in Rabat from 1 August 2020 to 1 August 2021.

2.2. Study Population

The study population consisted of adult patients (>18 years old) admitted to the AMU of Avicenne Hospital in Rabat with a confirmed SARS-CoV-2 infection, determined by RT-PCR and/or thoracic computed tomography (CT), using the «CO-RADS» classification system. The exclusion criteria were pregnancy, cancer, hematologic malignancy, recent surgery or trauma within the preceding 30 days, and patients without D-dimer testing upon admission.

The present study included 221 patients who were enrolled between 1 August 2020 and 1 August 2021. Patients were divided into three groups based on their post-hospitalization D-dimer levels. The first group (N = 81) had D-dimer levels below 1 µg/mL. The second group (N = 54) included patients with D-dimer levels ranging from 1 to 2 µg/mL. The third group (N = 86) comprised patients with D-dimer levels greater than 2 µg/mL. Plasma D-dimer was measured using an immuno-turbidimetric method with the INNOVANCER reagent and the CS-2500 analyzer (SYSMEX), Norderstedt, Germany.

All patients received antiviral and supportive therapies following diagnosis. Low-molecular-weight heparin (LMWH) was administered prophylactically to all patients without contraindications. A minority of patients at high thrombotic risk or with confirmed thromboembolic events received therapeutic anticoagulation therapy.

Disease severity was classified according to the World Health Organization (WHO) guidelines. Patients with non-severe COVID-19 did not require supplemental oxygen. These patients had pneumonia but did not show signs of severe pneumonia. Patients with severe SARS-CoV-2 infection displayed at least one of the following: respiratory distress, respiratory rate > 30 breaths/min, or SpO2 level < 93% on ambient air.

2.3. Data Collection

A data sheet was created for each patient, and we retrospectively collected demographic characteristics (age and sex), clinical data such as oxygen saturation, breathing rate, laboratory parameters (hemoglobin, D-dimer, glycemia, urea, etc.), chest CT imaging, and the progression of SARS-CoV-2 infection.

Laboratory parameters and analysis results were extracted from the medical records of the biochemistry and hematology laboratories of Avicenne Hospital in Rabat, Morocco.

2.4. Statistical Analysis

The data were entered using Sphinx Plus² Logiciel software version 5 (V5). Statistical processing and analysis were conducted using Jamovi software (version 2.6.2). The initial step involved producing descriptive statistics to represent the variables being investigated. Continuous variables are presented as means and standard deviations or medians and interquartile ranges, as appropriate. Categorical variables are presented as numbers and percentages.

A post hoc power analysis was conducted using the observed mortality rates in the three D-dimer groups: 2.8% in group 1 (N = 81), 5.5% in group 2 (N = 54), and 11% in group 3 (N = 86). Using a Chi-square test for comparison of proportions with an alpha level of 0.05, the total sample size (N = 221) provided sufficient power (>80%) to detect a statistically significant difference between the groups. This supports the adequacy of our sample size for the primary outcome.

The associations between the variables were determined using the Chi-square test for qualitative variables and one-way analysis of variance (ANOVA) for quantitative variables with a symmetric distribution. The Kruskal–Wallis test for asymmetric distributions was used to compare more than two independent groups. Subsequently, simple and multiple logistic regression models were employed, considering the total number of deaths in our study, to evaluate the risk factors associated with mortality in patients with COVID-19. Pearson’s correlation was used to assess the relationships between quantitative variables. Statistical significance was set at p < 0.05.

2.5. Ethics Approval

The study was approved by the Ethics Committee of Biomedical Research (CERB) of the Faculty of Medicine and Pharmacy of Rabat. Its reference number was N/R n°L/21. No informed consent was obtained, as this study analyzed deidentified participant data for which formal consent was not required.

3. Results

3.1. Comparison of Demographic and Clinical Characteristics of the Study Population

As shown in

Table 1. Comparison of demographic and clinical characteristics between COVID-19 patients with normal and elevated D-dimers.

	D-Dimer < 1 N = 81	1 ≤ D-Dimer ≤ 2 N = 54	D-Dimer > 2 N = 86	p-Value
Age (years)	55.0 (±15)	62.3 (±15.9)	62.0 (±16.3)	0.006
Male gender (%)	49 (22.2%)	27 (12.2%)	56 (25.3%)	0.204
Underlying disease, N (%) Hypertension Diabetes mellitus Coronary artery disease Chronic kidney disease Chronic obstructive Pulmonary disease	19 (8.6%) 27 (12.1%) 9 (4.1%) 5 (2.3%) 11 (5.0%)	18 (8.1%) 24 (10.9%) 5 (2.3%) 7 (3.2%) 5 (2.3%)	30 (13.6%) 42 (19%) 15 (6.8%) 9 (4.1%) 8 (3.6%)	0.236 0.203 0.301 0.389 0.613
Time since symptom onset (days)	7 (±4)	8 (±5)	10 (±5)	0.073
Temperature (°C)	38 (±0.84)	38 (±2)	37.8 (±2)	0.560
Symptoms Cough Dyspnea Asthenia	36 (20.2%) 42 (23.6%) 47 (21.3%)	30 (16.9%) 31 (17.4%) 27 (31.0%)	42 (23.6%) 52 (29.2%) 41 (18.6%)	0.530 0.852 0.080
Oxygen saturation	88 (±9.9)	85.5 (±8.5)	81.8 (±15.2)	0.016
Length of hospital stay (days)	8 (±4)	12 (±9)	12.5 (±14)	0.002
Breathing rate	25.6 (±6.4)	28.5 (5.38±)	27.6 (±7.39)	0.025
CT or (scanner) <25% 25–50% 50–75% >75%	24 (14.8%) 17 (10.5%) 17 (10.5%) 2 (1.2%)	10 (6.2%) 12 (7.4%) 15 (9.3%) 5 (3.1%)	13 (8.0%) 16 (9.9%) 27 (16.7%) 4 (2.4%)	0.173
Oxygen therapy	61 (33.3%)	48 (26.2%)	74 (40.4%)	0.031
Anticoagulation therapy	76 (35.3%)	50 (23.3%)	82 (38.1%)	0.846
Recovery, n (%) Yes No	73 (33.0%) 8 (3.6%)	39 (17.6%) 15 (6.8%)	60 (27.1%) 26 (11.8%)	0.003
Severity n (%) Yes No	45 (33.3%) 29 (50.9%)	35 (25.9%) 8 (14%)	55 (40.7%) 20 (35.1%)	0.048
In-hospital mortality, n (%) Yes No	6 (2.8%) 74 (33.9%)	12 (5.5%) 42 (19.3%)	24 (11.0%) 60 (27.5%)	0.002
Transfer to ICU (%) Yes No	14 (6.4%) 66 (30.1%)	21 (9.6%) 33 (15.1%)	35 (16.0%) 50 (22.8%)	0.002

, a comparative analysis of the demographic and clinical features of patients with SARS-CoV-2 revealed notable differences across the three distinct groups. The first group included patients with D-dimer values less than 1 µg/mL, the second group included those with values between 1 and 2 µg/mL, and the third group included patients with values > 2 µg/mL. The study found a statistically significant difference in the mean (SD) age among the three groups (p = 0.006). However, there were no significant differences in sex, underlying conditions, time since symptoms appeared, or the percentage of pulmonary involvement. The p-value indicates no significant difference between the groups.

Statistical analysis was conducted using ANOVA for symmetrical distributions. This analysis revealed a statistically significant difference in the means (SD) of oxygen saturation, duration of hospital stay, and breathing rate among the three independent groups of COVID-19 patients. A very high D-dimer level, >2 µg/mL, was identified as a discriminating factor. The respective p-values were p = 0.016, p = 0.002, and p = 0.025, indicating statistical significance.

Conversely, the Chi-square test for qualitative variables showed that participants with elevated D-dimer levels (greater than 2 µg/mL) experienced worse outcomes than the other groups. This is indicated by a higher incidence of severity 55 (40.7%), transfer to intensive care 35 (16%), and in-hospital mortality 24 (11%), compared to the groups with d-dimer levels less than 1 µg/mL and between 1 and 2 µg/mL. The respective p-values were p = 0.048, p = 0.002, p = 0.002. In contrast, a favorable evolution was observed in the group with D-dimer levels below 1 µg/mL. The frequency of recovery was found to be significant at 33% in comparison with the other two groups (17.6% and 27.1%, respectively), with a statistically significant p-value of 0.003.

3.2. Comparison of Laboratory Parameters Between COVID-19 Patients

Table 2. Comparison of laboratory values between COVID-19 patients with normal and elevated D-dimers.

	D-Dimer < 1 N = 81	1 ≤ D-Dimer ≤ 2 N = 54	D-Dimer > 2 N = 86	Normal Range	p-Value
	Mean ± SD Median [25–75]	Mean ± SD Median [25–75]	Mean ± SD Median [25–75]
Lymphocyte count (/mm3)	1210 [250–14,020]	940 [40–9350]	803 [40–11,110]	1000–4000	0.001
Neutrophil count (/mm3)	7733 ± 5260	6833 ± 4163	10,818 ± 5801	1500–7000	<0.001
Hemoglobin (g/L)	13.1 ± 2.36	11.8 ± 2.33	12.1 ± 2.31	11.5–15.5	0.003
D-dimer level (µg/mL)	0.59 ± 0.23	1.37 ± 0.28	8.90 ± 13.6	<0.5	<0.001
C-reactive protein (mg/L)	116 ± 87.7	140 ± 101	153 ± 105	<5	0.044
Alanine aminotransferase (IU/L)	29 [19–57]	26.5 [16–47.8]	30.5 [20–67.5]	0–55	0.321
Aspartate aminotransferase (IU/L)	32 [21–57.8]	44 [27–60]	40.5 [28–73]	5–34	0.097
Alkaline phosphatase (IU/L)	69 [54–94]	69.5.5 [57–105]	92.5 [66–128]	40–129	0.010
Gamma-glutamyl Transferase (U/L)	40 [25–77]	48 [27–108]	51 [29–120]	9–36	0.517
Lactate dehydrogenase (IU/L)	419 ± 182	484 ± 162	674 ± 442	125–220	0.001
Serum creatinine (mg/L)	8.20 [7.53–9.38]	9.10 [7.50–14.1]	9.5 [7.60–17]	5.7–12.5	0.172
Urea (g/L)	0.33 [0.24–0.47]	0.41 [0.27–0.86]	0.60 [0.39–1.00]	0.15–0.55	<0.001
Blood glucose (g/L)	1.79 ± 1.04	2.05 ± 1.19	2.12 ± 1.34	0.7–1.10	0.167
Prothrombin rate (%)	92.6 ± 14.4	94.0 ± 10.4	80.1 ± 22.8	70–100	<0.001
Fibrinogen (g/L)	6.26 ± 2.08	6.82 ± 2.13	5.75 ± 2.25	2–4	0.026
Cardiac troponin hs (ng/mL)	0.006 [0.002–0.01]	0.010 [0.004–0.017]	0.032 [0.008–0.157]	<0.05	<0.001
B-type natriuretic peptide (pg/mL)	16.5 [9–64]	67.7 [29–130]	158 [86–705]	<100	<0.001
Ferritin (ng/mL)	475 [272–968]	781 [442–1374]	791 [549–1511]	21–274	<0.001

summarizes the basic comparison of laboratory values between COVID-19 patients with normal and elevated D-dimer levels. A comparison of the biological and biochemical parameters among the different patient groups showed significant differences in lymphocyte, neutrophil, hemoglobin, and D-dimer levels, with p-values of 0.001, <0.001, 0.003, and <0.001, respectively. Additionally, patients in the D-dimer > 2 µg/mL group had significantly higher levels of CRP, alkaline phosphatase, lactate dehydrogenase, urea, cardiac troponin, B-type natriuretic peptide, and ferritin than those in the other two groups. The p-values indicate significant differences among the three groups (p = 0.044, p = 0.010, and p = 0.001, p < 0.001). It was also observed that fibrinogen levels increased more in the group with D-dimer levels from 1 to 2 µg/mL, while prothrombin levels decreased more in the group with D-dimer levels > 2 µg/mL. A significant difference was found among the three groups for these parameters (p = 0.026, p < 0.001).

3.3. D-Dimer as a Risk Factor Associated with Mortality Among COVID-19 Patients

As shown in

Table 3. Risk factors associated with mortality among COVID-19 patients.

	Univariable OR (95% CI)	p-Value	Multivariable OR (95% CI)	p-Value
Age (years)	1.05 [1.02–1.08]	<0.001	1.05 [1.01–1.08]	0.005
Sex	1.15 [0.57–2.29]	0.689	0.90 [0.37–2.15]	0.819
Breathing rate	1.07 [1.01–1.13]	0.011	1.05 [0.98–1.12]	0.158
D-dimer (mg/L)
B-A	4.93 [1.89–12.84]	0.001	3.37 [1.16–10.35]	0.034
C-A	3.52 [1.23–10.07]	0.019	1.88 [0.54–6.55]	0.319
Oxygen saturation	0.96 [0.93–0.99]	0.006	0.99 [0.95–1.02]	0.565

A: D-dimer < 1 reference. B: D-dimer > 2. C: 1 < D-dimer < 2.

, a univariate and multivariate logistic regression study was conducted, which revealed that advanced age and elevated D-dimer levels (greater than 2 µg/mL) were factors associated with mortality in patients diagnosed with COVID-19. The respective odds ratios (ORs) were 1.05 (95% confidence interval [CI]: 1.01–1.08; p = 0.005) and 3.37 (95% CI: 1.16–10.35; p = 0.034). The analysis demonstrated that, in the context of univariate logistic regression, oxygen saturation acted as a protective factor against mortality (OR = 0.96; 95%: 0.93–0.99; p = 0.006). However, after adjusting for confounding variables, including age, sex, respiratory rate, and D-dimer level, the protective effect was not significant (OR = 0.99; 95% IC: 0.95–1.02; p = 0.565).

3.4. Pearson Correlation Between D-Dimer and Various Biological and Clinical Parameters

Pearson’s correlation analysis revealed that D-dimers were significantly and positively correlated with several clinical and biological parameters (

Table 4. Pearson correlation on D-dimer levels and various biological and clinical parameters in patients with COVID-19.

	D-Dimer	Respiratory Rate	Platelets	TP	APTT	FIB	CRP	BLO GLUCOSE	UREE	CREAT	ASAT	ALAT	LDH	FERRITIN	TROPONINE	BNP
D-Dimer	1
Respiratory rate	0.170 *	1
Platelets	−0.061	0.056	1
TP	−0.269 **	−0.083	0.014	1
APTT	0.156 *	0.091	−0.107	−0.312 **	1
FIB	−0.106	0.124	0.172 *	0.177 *	0.004	1
CRP	0.104	0.213 **	−0.027	−0.031	0.122	0.435 **	1
BLO GLUCOSE	0.086	0.098	0.001	0.069	0.017	−0.041	0.077	1
UREE	0.055	−0.03	−0.074	−0.266 **	0.349 **	−0.184 **	0.066	0.138 *	1
CREAT	−0.027	−0.099	−0.170 *	−0.083	0.222 **	−0.096	0.073	0.003	0.745 **	1
ASAT	0.422 **	0.146	−0.052	−0.310 **	0.200 **	−0.05	−0.029	−0.103	−0.059	−0.108	1
ALAT	0.313 **	0.169 *	−0.005	−0.287 **	0.108	−0.05	−0.051	−0.091	−0.071	−0.149	0.909 **	1
LDH	0.499 **	0.239 **	0.06	−0.321 **	0.134	−0.044	0.235 **	−0.047	0.123	−0.013	0.604 **	0.488 **	1
FERRITIN	−0.005	0.089	−0.045	−0.037	−0.01	0.031	0.053	−0.028	0.033	−0.018	0.220 **	0.215 **	0.419 **	1
TROPONINE	−0.015	−0.06	−0.041	−0.111	0.007	−0.044	0.102	0.006	0.072	0.03	0.007	−0.036	0.259 **	−0.016	1
BNP	0.313 **	0.059	−0.168	−0.701 **	0.499 **	−0.363 **	0.015	0.011	0.278 **	0.053	0.395 **	0.392 **	0.339 **	−0.028	0.167	1

* Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). PT: prothrombin time; APTT: activated partial thromboplastin time; FIB: fibrinogen; CRP: C-reactive protein; BLO GLUCOSE: blood glucose; CREAT: creatinine; ASAT: aspartate aminotransferase; ALT: alanine aminotransferase; LDH: lactate dehydrogenase; BNP: brain natrium peptide; TROPONIN HS: troponin high sensitivity. Green indicates a positive correlation, while red indicates a negative correlation. The higher the degree of correlation (in absolute value), the more intense the color.

). Notably, there was a significant positive correlation with respiratory rate (r = 0.170, p < 0.05), indicating that patients with higher D-dimer levels tend to have a faster respiratory rate. This suggests greater respiratory involvement in these patients, likely linked to infection severity or acute respiratory distress syndrome (ARDS). A moderate and significant correlation was also observed with liver enzymes, specifically ASAT (r = 0.422, p < 0.01) and ALAT (r = 0.313, p < 0.01), implying hepatocellular damage associated with elevated D-dimer levels. This indicates that patients with hypercoagulability may also experience hepatic distress, possibly due to hypoxia, systemic inflammation, or medication effects. The lactate dehydrogenase (LDH) level, a non-specific marker of cellular injury, exhibited the strongest correlation with D-dimer (r = 0.499, p < 0.01). This relationship emphasizes the association between coagulation activation (reflected by D-dimer levels) and the extent of tissue cell damage. It supports the role of D-dimers as a biomarker of COVID-19 severity. Furthermore, a significant positive correlation was observed between D-dimer and Brain Natriuretic Peptide (BNP) (r = 0.313, p < 0.01). This cardiac hormone is an indicator of left ventricular dysfunction and volume overload. This association suggests that patients with elevated D-dimer levels may also experience cardiac distress or cardiovascular decompensation, which is frequently encountered in severe COVID-19 cases. Conversely, there was a significant negative correlation with (prothrombin rate) (r =−0.269, p < 0.01), a marker of extrinsic clotting time. This reflects a tendency toward coagulopathy, with increased consumption of coagulation factors in patients with higher D-dimer levels. The activated partial thromboplastin time (APTT), another coagulation indicator, was positively correlated (r = 0.156, p < 0.05), further supporting the hypothesis of a disruption in the coagulation cascade among these patients.

Although biologically plausible, some variables showed no significant correlation with D-dimer levels in this cohort. These include platelets (r = −0.061), fibrinogen (r = −0.106), CRP (r = 0.104), ferritin (r = −0.005), troponin (r = −0.015), blood glucose (r = 0.086), urea (0.055), and creatinine (r = −0.027). The absence of significant correlations could be explained by the heterogeneity of inflammatory or metabolic responses between patients or by the variability of biological sampling times during the disease. For example, ferritin is a marker of inflammation, but its value can fluctuate independently of coagulation status. Similarly, troponin, while reflecting myocardial damage, did not appear to be associated with D-dimers, perhaps due to the low prevalence of myocarditis or infarction in the sample studied.

By extending the analysis, certain correlations between other variables provide a better understanding of the pathophysiological links. For example, there was a strong correlation between ASAT and ALAT (r = 0.909), which is expected given that these two enzymes are classic liver markers. LDH was also strongly correlated with ASAT (r = 0.604) and ALAT (r = 0.488), ** reinforcing the idea of systemic cellular damage. BNP correlated negatively with PT (r = −0.701) and positively with APTT (r = 0.499), suggesting coagulopathy in patients with cardiac damage, consistent with D-dimer observations. Urea correlated positively with APTT (r = 0.349) and BNP (r = 0.278), indicating that patients with impaired renal function may also present with coagulation disorders and signs of cardiac overload. Finally, fibrinogen (FIB) showed a positive correlation with platelets (r = 0.172) and PT (r = 0.177), underlining its central role in hemostasis, although its association with D-dimers was not significant.

4. Discussion

This study yielded several findings regarding elevated D-dimer levels. It was observed that patients infected with the SARS-CoV-2 virus who are aged 60 and over, and with blood oxygen saturation levels below 94% are more likely to have concurrent inadequate respiratory rates and insufficient oxygen saturation levels. These observations necessitate transfer to an intensive care unit or other facilities, depending on the severity of the disease and the necessity of emergency oxygen therapy. We found that a higher D-dimer value (>2 μg/mL) was significantly associated with in-hospital mortality in patients with COVID-19. A study conducted by Zhang et al. in China, involving 343 patients, concluded that D-dimer could serve as an early and useful marker for predicting in-hospital mortality. The optimal cutoff point for D-dimer was determined to be 2 μg/mL [10]. A subsequent study in China found that patients with D-dimer values greater than 2 μg/mL at the time of admission exhibited an elevated risk of mortality, with an odds ratio of 10.17 (95% CI 1.10–94.38) [7]. A systematic analysis published in August 2020 found that patients with confirmed SARS-CoV-2 infection who presented with elevated D-dimer values were at an increased risk of developing severe symptoms and mortality. The analysis noted that no consistent cutoff value had been defined to predict adverse events [11]. A study conducted at Cheick Khalifa International University Hospital, Mohammed VI (Casablanca, Morocco), showed that D-dimer levels on day 5 greater than 1.36 μg/mL were associated with higher odds of in-hospital death [14]. A study by Julien et al. [14] showed that very high D-dimer levels at admission or low levels with a rapid increase during hospitalization are important prognostic factors for the severity and mortality of COVID-19. Furthermore, Zhou et al. [15] conducted a retrospective study involving 191 patients with confirmed cases of the disease and found that elevated D-dimer levels at the time of admission were associated with an increased risk of mortality in adult patients. However, this conclusion is inconsistent with those of other studies. Xie et al. [16] found that D-dimer was not a risk factor after adjusting for age and sex by analyzing 140 patients with confirmed cases of severe acute respiratory syndrome coronavirus 2. This finding does not align with the results of the present study. However, as indicated by the findings of the study conducted by He et al. [17], our study showed that advanced age was identified as a factor contributing to elevated D-dimer levels, which has been shown to negatively impact the prognosis of patients infected with COVID-19 and often results in fatal outcomes. Moreover, prophylactic anticoagulation (typically low-molecular-weight heparin at standard doses) was routinely prescribed to hospitalized COVID-19 patients with moderate disease to prevent thrombotic complications. Therapeutic anticoagulation was reserved for patients with confirmed or strongly suspected thromboembolic events, markedly elevated D-dimer levels, and clinical signs of severe disease.

The precise mechanism underlying the association between elevated D-dimer levels and COVID-19-related mortality is unclear. Wang et al. previously reported that markedly increased D-dimer levels, along with hypoxemia, could promote pulmonary microthrombus formation during the 2009 influenza A (H1N1) pandemic [18]. More recently, Klok et al. demonstrated that approximately 31% of critically ill COVID-19 patients admitted to intensive care units experienced thrombotic complications [19]. Moreover, D-dimer levels have been proposed as a biomarker for identifying deep vein thrombosis in COVID-19 patients with pre-existing cardiovascular conditions [20]. These findings suggest that elevated D-dimer levels, a marker of thrombogenesis, may directly contribute to adverse outcomes in COVID-19.

Conversely, other studies suggest that elevated D-dimer levels may result from disease progression rather than being a causal factor of it. SARS-CoV-2 infection is frequently associated with an exaggerated inflammatory response, including cytokine storms and elevated markers of inflammation, such as CRP, LDH, Ferritin, and D-dimer, which can result in endothelial injury and dysfunction. This endothelial disruption may lead to increased thrombin generation and D-dimer levels [11,21,22]. Despite evidence from numerous studies associating elevated D-dimer levels with markers of inflammation and cardiac injury, our analysis did not demonstrate a statistically significant correlation between D-dimer levels and troponin or ferritin values. This absence of a substantial correlation may be ascribed to the comparatively modest sample size of the present study, which may have curtailed the statistical potency to discern such associations. Furthermore, variations in the timing of biomarker sampling could have influenced the results, as the levels of these parameters may fluctuate depending on disease progression and the timing of blood collection. Further studies with larger cohorts and standardized sampling protocols are required to facilitate a more comprehensive evaluation of these potential associations. Additionally, COVID-19-related organ damage and hypoxemia may contribute to a prothrombotic state by increasing blood viscosity and activating hypoxia-inducible transcription factor (HIF)-dependent signaling pathways [23,24]. Zhou et al. [15] demonstrated that multivariable regression analysis of 191 patients with COVID-19 had an odds ratio of 18.42 (2.64–128.55, p = 0.0033) for in-hospital mortality for patients with D-dimer > 1 μg/mL. In another study, Berger et al. concluded that D-dimer levels > 2 µg/mL were correlated with the highest risk of thrombotic complications, acute kidney injury, critical illness, and death [25]. This finding indicates that fibrinolytic activity may be elevated in patients with SARS-CoV-2 infection, concurrently with hypercoagulation. However, the underlying causes of elevated D-dimer levels in patients with severe disease remain unknown. The most probable hypothesis regarding the elevated D-dimer levels in patients diagnosed with SARS-CoV-2 is that the increase is attributable to the local extravascular activity of the fibrinolytic system within the affected lungs. This increase may not indicate the degree of activation of plasminogen and fibrinolysis in the tissues [1,26,27]. This assumption was partially confirmed by a comparative analysis of the activity of the blood coagulation and complement systems, as well as the composition of cytokines and chemokines in bronchoalveolar lavage fluid (BALF) and blood plasma samples from patients with severe SARS-CoV-2 infection [28,29]. Furthermore, Turagam et al. suggested that COVID-19-related mortality is frequently associated with pulseless electrical activity (PEA). Whether D-dimer-associated thrombotic events contribute to PEA and subsequent mortality remains unclear [30].

In Morocco, the Alpha and Delta variants predominated during the various waves of the pandemic. These variants have been linked to a variety of clinical presentations and inflammatory responses, which may affect D-dimer levels. Several international studies have reported an association between the Delta variant and a more severe clinical course, as well as an elevated thrombotic risk, which may result in increased D-dimer levels [31,32]. However, local longitudinal data on D-dimer trends in Morocco by variant type are limited. In addition, selection bias, a consequence of the retrospective nature of the investigation, is acknowledged to be one of the principal limitations of the present study. Longitudinal D-dimer data were not available for all patients, limiting trend analysis, particularly in deceased cases. The absence of information on SARS-CoV-2 variants (such as Alpha or Delta) makes it impossible to assess their potential impact on D-dimer levels and clinical outcomes. Furthermore, although the use of anticoagulants was described, detailed data on the doses and timing of administration were lacking, limiting the analysis of their prognostic effects.

5. Conclusions

This study aimed to ascertain whether elevated D-dimer levels at admission and during hospitalization were associated with poor prognosis and increased in-hospital mortality in patients with confirmed cases of Coronavirus Disease 2019 (COVID-19) during the Alpha and Delta waves in Morocco. The results showed that D-dimer levels and advanced age were related to the clinical classification of COVID-19 patients and could be used to evaluate the prognosis of patients. A D-dimer value > 2 μg/mL was a value that indicated a higher risk of death. Correlation analysis highlighted that elevated D-dimer levels were significantly associated with multi-organ alterations, particularly in the hepatic, cardiac, and respiratory systems, underscoring their importance as biomarkers of severity in patients with COVID-19.

The results of this study open up several interesting perspectives for the future clinical management of patients with COVID-19. The identification of significant correlations between D-dimers and certain hepatic (ASAT, ALAT), cardiac (BNP), and cell necrosis (LDH) biomarkers suggests that these markers could be incorporated into predictive models of clinical prognosis, notably to anticipate severe forms of the diseases. In the future, large-scale, multicenter prospective studies should validate these associations and assess the value of dynamic D-dimer monitoring as a complement to other biological indicators. Serial measurements could help determine whether elevated D-dimer levels are an independent predictor of mortality or a reflection of severe disease progression. Furthermore, incorporating detailed clinical data, including anticoagulant dosing and viral variant identification, would enhance the robustness of these analyses. In addition, the integration of these biomarkers into decision-support algorithms could contribute to better risk stratification and optimization of healthcare resources, particularly in situations of hospital overload or during new waves involving emerging SARS-CoV-2 variants.