Diagnostic utility of fibrinolytic markers as indicators of pediatric Plasmodium falciparum malaria: a case-control study in the Offinso-North District, Ghana

Diagnostic utility of fibrinolytic markers as indicators of pediatric Plasmodium falciparum malaria: a case-control study in the Offinso-North District, Ghana | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Diagnostic utility of fibrinolytic markers as indicators of pediatric Plasmodium falciparum malaria: a case-control study in the Offinso-North District, Ghana Desmond Gyedu, Stephen Twumasi, Otchere Addai-Mensah, Lilian Antwi Boateng, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9418547/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Severe Plasmodium falciparum ( P. falciparum ) malaria is associated with life-threatening complications, potentially linked to disturbed fibrinolysis. This study evaluated the plasma levels of key fibrinolytic markers; plasminogen activator inhibitor-1 (PAI-1), tissue plasminogen activator (t-PA), and D-dimer to assess their diagnostic and prognostic values in children with malaria in Ghana. Methods: We conducted a case-control study in the Offinso-North District, Ghana, recruiting 120 children aged 1–13 years. Participants were divided into three groups: a control group (n=40), an uncomplicated malaria group (n=55), and a severe malaria group (n=25), as defined by WHO guidelines. Plasma levels of t-PA, PAI-1, and D-dimer were measured using the sandwich Enzyme-Linked Immunosorbent Assay (ELISA) technique, and their diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUROC). Results: Children with both uncomplicated and severe malaria had significantly higher plasma levels of PAI-1 and D-dimer, and significantly lower levels of t-PA, compared to the control group (p<0.05). D-dimer was identified as the strongest diagnostic marker for distinguishing all malaria cases from healthy controls (AUROC = 1.000, p<0.0001), demonstrating 98.8% (95% CI: 92.5–100) sensitivity and 100% (95% CI: 89.3–100) specificity. PAI-1 also demonstrated good diagnostic potential for both uncomplicated (AUROC = 0.752, p<0.0001) and severe malaria (AUROC = 0.811, p<0.0001) versus controls. For disease stratification, D-dimer significantly differentiated severe malaria from uncomplicated malaria (AUROC = 0.667, p=0.017). Conclusion: Malaria infection disrupts the balance between coagulation and fibrinolysis. Our findings establish D-dimer as an indicator of disease activity and a potentially valuable tool for risk stratification in pediatric malaria. We propose that integrating quantitative D-dimer and PAI-1 testing with standard microscopy could improve patient triage and risk stratification in resource-limited settings, enabling earlier identification of high-risk patients. Hematology Plasmodium falciparum Malaria Fibrinolysis Plasminogen Activator Inhibitor-1 Tissue Plasminogen Activator D-dimer Biomarker Pediatric Malaria Ghana Figures Figure 1 Figure 2 1. Introduction Plasmodium falciparum ( P. falciparum ) malaria remains a leading cause of childhood mortality in sub-Saharan Africa, where children under five bear the greatest burden [1–3]. According to the World Health Organization, of the 249 million malaria cases and 608,000 deaths worldwide in 2022, approximately 95% occurred in Africa [4,5]. In Ghana, this challenge is pronounced, with malaria prevalence varying from 2.6% to 41.9% across different ecological zones [6]. The pathophysiology of severe malaria is complex, driven largely by the cytoadherence of parasitized erythrocytes to vascular endothelium via P. falciparum erythrocyte membrane protein 1 (PfEMP-1) [7–10]. This process triggers widespread endothelial activation, sequestration of parasites in vital organs, and a systemic inflammatory response that critically disrupts hemostasis. A key consequence of these events is a dysregulation of the fibrinolytic system, which is responsible for dissolving fibrin clots. In malaria, endothelial activation and inflammation disrupt this balance, often leading to a state of hypofibrinolysis characterized by elevated levels of plasminogen activator inhibitor-1 (PAI-1), the primary inhibitor of fibrinolysis and decreased activity of its target, tissue plasminogen activator (t-PA) [11–14]. This prothrombotic state is further evidenced by the accumulation of D-dimer, a fibrin degradation product that serves as a marker for both coagulation activation and subsequent fibrinolysis [15–17]. While previous studies have documented hemostatic changes like thrombocytopenia and elevated fibrin degradation products in malaria [18–21], a comprehensive evaluation of multiple fibrinolytic markers in pediatric populations in West Africa remains limited. The specific diagnostic utility of PAI-1, t-PA, and D-dimer in distinguishing malaria from other febrile illnesses and in stratifying disease severity (uncomplicated vs. severe malaria) in Ghanaian children has not been adequately characterized. This study therefore aimed to address this gap through the following objectives: (1) determine the plasma levels of PAI-1, t-PA, and D-dimer in children with P. falciparum malaria; (2) compare hematological parameters between malaria cases and controls; (3) evaluate the diagnostic performance of these fibrinolytic markers in detecting malaria and distinguishing disease severity; and (4) assess the correlations between the fibrinolytic biomarkers and selected hematological parameters. 2. Materials and Methods 2.1 Study Design, Study Site and Study Duration This case-control study was conducted between April and October 2023 in the Offinso-North District, Ghana, a region with endemic, seasonal malaria transmission. Participants were recruited from three healthcare facilities: Janie Speaks A.M.E. Zion Hospital, Nkenkasu District Hospital, and Akumadan Polyclinic. 2.2 Ethical Clearance and Informed Consent The study protocol was approved by the Committee on Human Research, Publication and Ethics (CHRPE) of the Kwame Nkrumah University of Science and Technology (Ref: CHRPE/AP/218/23). The study was performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from parents or legal guardians, and assent was obtained from children aged 7-13 years. 2.3 Study Participants and Sample Size A total of 120 children aged 1–13 years were enrolled: 80 with microscopy-confirmed P. falciparum malaria (cases) and 40 healthy, afebrile, malaria-negative children (controls). The sample size was determined using Kelsey's formula, assuming a 25% prevalence of significant hemostatic disruption in severe malaria versus 5% in controls, based on previous reports of coagulopathy in pediatric malaria, with 95% confidence and 80% power (Gwacham-Anisiobi et al. 2024). Inclusion criteria for cases were: age 1–13 years, microscopy-confirmed P. falciparum infection, and symptoms consistent with malaria. Exclusion criteria for all participants included known chronic illnesses (e.g., sickle cell disease, HIV), recent antimalarial treatment (within 2 weeks), blood transfusion (within 3 months), or use of anticoagulant medications. Malaria cases were classified according to WHO criteria. Severe malaria (n=25) was defined by asexual parasitemia plus one or more of: prostration, impaired consciousness, respiratory distress, severe anemia (hemoglobin 100,000 parasites/μL). All other cases were classified as uncomplicated malaria (n=55). 2.4 Data and Sample Collection Clinical, demographic, and environmental data were collected through face-to-face interviews with parents/guardians and review of medical records using a standardized case report form. Approximately 5 mL of venous blood was collected from each participant into two tubes: a K₂EDTA tube for complete blood count and malaria microscopy, and a 3.2% sodium citrate tube for fibrinolytic assays. Blood for coagulation studies was immediately centrifuged at 2,000 × g for 15 minutes at 4°C. Platelet-poor plasma was aliquoted and stored at -80°C until analysis. 2.5 Laboratory Analyses Malaria diagnosis and parasitemia were determined by microscopic examination of Giemsa-stained blood smears by two independent expert microscopists. Parasite density was calculated using the formula: (number of parasites counted / 200 WBCs) × participant’s actual WBC count obtained from the hematology analyzer. Hematological parameters were measured using a Sysmex XE-5000 automated analyzer (Sysmex, Kobe, Japan). Plasma concentrations of D-dimer (Abcam, ab260076), PAI-1 (Abcam, ab108891), and t-PA (Abcam, ab108914) were quantified using commercial sandwich ELISA kits according to the manufacturer’s instructions. All samples were analyzed in duplicate, and quality control was maintained throughout the process. 2.6 Statistical Analysis Data were analyzed using IBM SPSS Statistics version 26.0. Continuous variables were assessed for normality using the Shapiro-Wilk test and are presented as median and interquartile range (IQR). Comparisons between the three groups were performed using the Kruskal-Wallis test, followed by Mann-Whitney U tests for pairwise comparisons. Categorical variables were compared using the Chi-squared or Fisher's exact test. Spearman's correlation was used to assess relationships between variables. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic and prognostic performance of D-dimer, PAI-1, and t-PA for malaria diagnosis and severity stratification. A p-value <0.05 was considered statistically significant. 3. Results 3.1 Participant Characteristics and Parasitological Findings A total of 120 children were enrolled: 80 with P. falciparum malaria (55 uncomplicated and 25 severe) and 40 healthy controls. Children with malaria were significantly younger than controls (median age 3.5 years vs. 8.0 years; p<0.001). Of the malaria cases, 56.2% (n=45/80) were children under 5 years, while 43.8% (n=35/80) were aged 5–13 years. There was no significant difference in sex distribution across groups (p=0.243), with female participants accounting for 43.3% (n=52/120) of the total population. Fever was the most common symptom (96.3%), and body temperature was significantly elevated in malaria cases (p<0.001) (Table1). Environmental risk factors were significantly associated with malaria, including the presence of stagnant water (p=0.009) and bushes near the home (p=0.001); however, these factors did not show a direct correlation with fibrinolytic biomarker levels. Among the malaria-positive cases, the median parasitemia was 50,400 (IQR: 18,250–185,600) parasites/µL. As expected, children with severe malaria had a significantly higher median parasitemia than those with uncomplicated malaria (210,900 [IQR: 100,471–293,794.5] parasites/µL vs. 36,820 [IQR: 9,240–79,805] parasites/µL; p<0.0001). Table 1. Demographic and Clinical Characteristics of Study Participants Characteristic Controls (n=40) Uncomplicated Malaria (n=55) Severe Malaria (n=25) P-value Age Age (years), Median (IQR) 8.0 (5.0–10.0) 4.0 (2.0–7.0) 3.0 (2.0–5.0) <0.001 Age < 5 years, n (%) 8 (20.0) 30 (54.5) 15 (60.0) <0.001 Age 5–13 years, n (%) 32 (80.0) 25 (45.5) 10 (40.0) <0.001 Sex Male, n (%) 25 (62.5) 28 (50.9) 13 (52.0) 0.459 Female, n (%) 15 (37.5) 27 (49.1) 12 (48.0) 0.459 Temperature,°C, Median (IQR) 36.5 (36.2–36.8) 37.8 (37.2–38.5) 38.2 (37.5–38.8) <0.001 Clinical Symptoms, n (%) Fever 0 (0.0) 52 (94.5) 25 (100.0) <0.001 Chills 0 (0.0) 35 (63.6) 17 (68.0) <0.001 Headache 0 (0.0) 32 (58.2) 16 (64.0) <0.001 Vomiting 0 (0.0) 20 (36.4) 12 (48.0) <0.001 Loss of appetite 0 (0.0) 28 (50.9) 15 (60.0) <0.001 Environmental Factors, n (%) Stagnant water near home 30 (75.0) 22 (40.0) 18 (72.0) 0.002 Bushes near home 40 (100.0) 42 (76.4) 20 (80.0) 0.003 Use of protective clothing 40 (100.0) 25 (45.5) 11 (44.0) <0.001 Insecticide-treated nets 38 (95.0) 48 (87.3) 20 (80.0) 0.146 Note: IQR, interquartile range. P-values from Kruskal-Wallis test (continuous variables) or Chi-square/Fisher's exact test (categorical variables). 3.2 Hematological Parameters Malaria cases exhibited significant hematological abnormalities compared to healthy controls. Both the uncomplicated and severe malaria groups had significantly lower hemoglobin levels, hematocrit, and platelet counts (p<0.0001). Anemia was a predominant finding among the cases. Specifically, the median hemoglobin was 9.7 (IQR: 8.0–11.1) g/dL in the uncomplicated group and 9.3 (IQR: 4.7–10.4) g/dL in the severe group, compared to 11.6 (IQR: 11.2–12.4) g/dL in controls. RBC indices, including mean cell hemoglobin (MCH) and mean cell hemoglobin concentration (MCHC), were also significantly lower in children with malaria (p=0.002 and p<0.0001, respectively). Conversely, the RDW-CV was significantly higher in the severe group (16.1%) compared to controls (13.9%) (p<0.0001). While total white blood cell (WBC) counts did not differ significantly between the three groups (p=0.299), differential counts revealed profound changes. Children with malaria showed significant neutrophilia (p<0.0001) and monocytosis (p=0.003), alongside marked lymphopenia (p<0.0001) compared to controls. Significant thrombocytopenia was observed in both the uncomplicated group (157.0 [IQR: 97.0–220.0] ×× 10⁹/L) and the severe malaria group (140.0 [IQR: 91.0–166.5] ×× 10⁹/L) relative to controls (334.5 [IQR: 274.3–400.0] × 10⁹/L) (p<0.0001). Table 2. Hematological Parameters of Study Participants Parameter Controls (n=40) Uncomplicated Malaria (n=55) Severe Malaria (n=25) P-value Hemoglobin (g/dL) 11.6 (11.2–12.4) 9.7 (8.0–11.1) 9.3 (4.7–10.4) <0.0001 Hematocrit (%) 33.2 (32.0–34.6) 28.4 (24.1–32.2) 28.4 (14.6–30.9) <0.0001 RBC (× 10¹²/L) 4.52 (4.20–4.85) 3.98 (3.55–4.35) 3.85 (3.20–4.10) <0.001 MCV (fL) 79.5 (76.0–82.0) 76.0 (72.0–79.0) 75.0 (70.0–78.0) 0.002 MCH (pg) 26.0 (24.5–27.5) 24.5 (23.0–26.0) 24.0 (22.0–25.5) 0.008 MCHC (g/dL) 35.4 (35.0–35.9) 33.7 (32.7–34.4) 33.8 (32.9–34.8) <0.0001 RDW-CV (%) 13.9 (12.9–14.4) 14.7 (13.2–16.0) 16.1 (14.6–18.5) <0.0001 WBC (× 10⁹/L) 6.3 (5.5–8.5) 8.1 (5.6–11.1) 8.0 (6.5–10.8) 0.299 Neutrophils (× 10⁹/L) 2.6 (2.0–3.8) 4.8 (3.5–7.1) 4.4 (3.8–7.7) <0.0001 Lymphocytes (× 10⁹/L) 3.2 (2.9–4.1) 1.8 (1.4–2.3) 2.0 (1.5–4.1) <0.0001 Monocytes (× 10⁹/L) 0.54 (0.41–0.62) 0.76 (0.50–1.15) 1.12 (0.33–1.53) 0.003 Eosinophils (× 10⁹/L) 0.25 (0.18–0.35) 0.15 (0.08–0.22) 0.12 (0.05–0.18) <0.001 Platelets (× 10⁹/L) 334.5 (274.3–400.0) 157.0 (97.0–220.0) 140.0 (91.0–166.5) <0.0001 MPV (fL) 8.5 (8.0–9.2) 9.2 (8.5–10.0) 9.5 (8.8–10.5) <0.001 Note: Data presented as median (IQR). RBC, red blood cell count; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; RDW-CV, red cell distribution width-coefficient of variation; WBC, white blood cell count; MPV, mean platelet volume. P-values from Kruskal-Wallis test. 3.3 Fibrinolytic Marker Levels Plasma levels of fibrinolytic markers were significantly dysregulated in malaria. Both uncomplicated and severe malaria groups showed significantly elevated levels of PAI-1 and D-dimer compared to controls (p<0.001). Conversely, t-PA levels were significantly lower in the uncomplicated malaria group than in controls (p=0.012). D-dimer levels demonstrated a stepwise increase with disease severity, being significantly higher in severe malaria than in uncomplicated malaria (p=0.004). The PAI-1/t-PA ratio was also significantly higher in children with uncomplicated (1.35) and severe malaria (1.32) compared to controls (1.00) (p<0.001), indicating a systemic hypofibrinolytic state (Figure 1, Table 3). Table 3. Plasma Levels of Fibrinolytic Markers in Study Participants Marker Controls (n=40) Uncomplicated Malaria (n=55) Severe Malaria (n=25) P-value PAI-1 (ng/mL) 27.5(24.0–30.5) 32.9 (29.5–36.8) 33.5(30.0–38.0) <0.001 t-PA (ng/mL) 27.7(25.0–31.0) 24.9 (22.0–27.5) 26.0(23.5–28.5) 0.042 D-dimer (pg/mL) 4485.2 (3850.0–5200.0) 7059.7 (6500.0–7800.0) 7852.5 (7200.0–8600.0) <0.001 PAI-1/t-PA ratio 1.00 (0.85–1.15) 1.35 (1.20–1.55) 1.32 (1.18–1.50) <0.001 Note: Data presented as median (IQR). PAI-1, plasminogen activator inhibitor-1; t-PA, tissue plasminogen activator. P-values from Kruskal-Wallis test. 3.4 Correlation Between the Fibrinolytic Markers In children under 5 years, D-dimer demonstrated a significant moderate positive correlation with parasitemia (r=0.546, p<0.001). However, it exhibited a weak positive relationship with hemoglobin (r=−0.179, p=0.241) and a weak negative relationship with platelets (r=−0.274, p=0.068), that was not statistically significant. Similarly, PAI-1 showed a significant positive trend with parasitemia in the under-5 group (r=0.311, p=0.038) ), and an insignificant weak correlation with hemoglobin and platelets respectively (r=0.103, p=0.503; r=-0.010 , p=0.948) . In the older age group, both D-dimer and PAI-1 showed statistically significant associations with parasitemia (r=0.351, p=0.039; r=0.354, p=0.037) (Table 4). Table 4. Correlations Between Fibrinolytic Markers and Selected Parameter Parameter D-dimer PAI-1 t-PA Children < 5 years (n=45) Parasitemia r=0.546,p<0.001 r=0.311,p=0.038 r=−0.005,p=0.976 Hemoglobin r =0.179, p =0.241 r =0.103, p =0.503 r =0.114, p =0.456 Platelets r =−0.274, p =0.068 r =−0.010, p =0.948 r =0.099, p =0.517 WBC r =−0.205, p =0.177 r =−0.011, p =0.941 r =−0.030, p =0.844 Neutrophils r =−0.005, p =0.974 r =−0.134, p =0.380 r =−0.001, p =0.992 Children 5–13 years (n=35) Parasitemia r =0.351, p =0.039 r =0.354, p =0.037 r =−0.045, p =0.799 Hemoglobin r =0.011, p =0.949 r =−0.094, p =0.591 r =0.133, p =0.446 Platelets r =0.366, p =0.031 r =−0.114, p =0.514 r =−0.143, p =0.414 RDW-CV r =0.449, p =0.007 r =−0.138, p =0.430 r =0.078, p =0.657 Note: WBC, white blood cell count; RDW-CV, red cell distribution width-coefficient of variation. 3.5 Diagnostic Performance of Fibrinolytic Markers Receiver operating characteristic (ROC) analysis showed that D-dimer had the strongest discriminatory power for malaria diagnosis (AUC = 1.000, p<0.0001), with a cutoff of ≥5609.6 pg/mL yielding 100% sensitivity and 97.5% specificity. PAI-1 followed with moderate performance (AUC = 0.770, p<0.0001), while t-PA exhibited the lowest diagnostic ability (AUC = 0.644, p=0.008) (Figure 2A). For predicting severe malaria, D-dimer again exhibited optimal performance (AUC = 1.000, p<0.0001) with perfect sensitivity and specificity at a cutoff of ≥5920.9 pg/mL. PAI-1 demonstrated good diagnostic accuracy for severe malaria (AUC = 0.811, p<0.0001), providing a sensitivity of 72.0% and a specificity of 85.0% at a threshold of ≥ 31.2 ng/mL. In contrast, t-PA performance for severity was marginal and did not reach high statistical significance (AUC = 0.649, p=0.057) (Figure 2B). Table 5: Diagnostic Performance of Biomarkers for Indicating Malaria Markers Cut-off Sensitivity (95% CI) Specificity (95% CI) PPV NPV AUC (95% CI) P-value D-dimer (pg/mL) ≥≥5609.6 100.0 (94.4–100.0) 97.5 (85.7–100.0) 98.8 100.0 1.000 (0.999–1.000) <0.0001 PAI-1 (ng/mL) ≥≥30.0 78.8 (68.4–86.3) 75.0 (59.6–85.9) 86.3 63.8 0.770 (0.685–0.855) <0.0001 t-PA (ng/mL) ≤≤ 29.8 87.0 (77.4–92.9) 35.0 (22.1–50.6) 72.0 58.3 0.644 (0.537–0.751) 0.008 PV = positive predictive value; NPV = negative predictive value; CI = confidence interval. Table 6: Diagnostic Performance of Biomarkers for Predicting Severe Malaria Markers Cut-off Sensitivity (95% CI) Specificity (95% CI) PPV NPV AUC (95% CI) P-value D-dimer (pg/mL) ≥≥ 5920.9 100.0 (83.9–100.0) 100.0 (89.3–100.0) 100.0 100.0 1.000 (1.000–1.000) <0.0001 PAI-1 (ng/mL) ≥≥ 31.2 72.0 (52.1–85.8) 85.0 (70.4–93.2) 75.0 82.9 0.811 (0.692–0.930) <0.0001 t-PA (ng/mL) ≤≤ 25.5 63.6 (42.8–80.2) 75.0 (59.6–85.9) 58.3 78.9 0.649 (0.496–0.802) 0.057 Note: PPV, positive predictive value; NPV, negative predictive value; AUC, area under the curve. 4. Discussion This study provided evidence that fibrinolytic dysregulation is a central feature of pediatric P. falciparum malaria in Ghana. The findings demonstrated that malaria-infected children exhibit a distinct hemostatic profile characterized by elevated PAI-1 and D-dimer, reduced t-PA, and significant hematological abnormalities. Most importantly, D-dimer was established as a strong indicator of disease activity, while PAI-1 served as a reliable marker of the systemic hypofibrinolytic response. Consistent with established epidemiology, the study found that severe malaria disproportionately affected younger children, who are also presented with higher parasitemia [22,23]. The predominant clinical and hematological findings; fever, anemia, and thrombocytopenia aligned with the known pathophysiology of malaria, which involves pyrogenic cytokine release, erythrocyte destruction, and platelet consumption [24–26]. The strong negative correlation observed between parasitemia and both hemoglobin and platelet count underscores the direct impact of parasite burden on these hematological disturbances [27,28]. The core findings of this study lie in the profound disruption of the fibrinolytic system. The significantly elevated PAI-1 and reduced t-PA levels in malaria cases confirmed the state of hypofibrinolysis, where the capacity to lyse clots is suppressed [13,19]. This imbalance is likely driven by the systemic inflammation characteristic of malaria, as pro-inflammatory cytokines like TNF-α are known to upregulate PAI-1 expression and downregulate t-PA [19,29–31]. This creates a prothrombotic environment that may contribute to the microvascular obstruction and organ damage observed in severe malaria [32–34]. Another key finding was the elevation of D-dimer with increasing disease severity. D-dimer reflects the net effect of both coagulation activation and subsequent (albeit impaired) fibrinolysis. Its strong positive correlation with parasitemia suggests that parasite load is a primary driver of this hemostatic activation [15,16]. D-dimer demonstrated excellent discriminatory performance (AUROC = 1.000) in the study cohort. This result likely reflects the clear physiological distinction between the well-defined, healthy afebrile control group and the acutely ill malaria cohort. It is crucial to contextualize this, however; in a real-world clinical setting, the primary challenge is often differentiating malaria from other common febrile illnesses, such as sepsis or viral infections, which are also known to elevate D-dimer levels. Therefore, while D-dimer's ability to distinguish malaria from a healthy state is remarkable, future validation studies are needed in undifferentiated febrile cohorts. Notably, PAI-1 also demonstrated good diagnostic accuracy for identifying severe malaria (AUC = 0.811), confirming that the degree of fibrinolytic suppression is closely linked to disease severity in these children. This finding matches the original thesis data and suggests that PAI-1 could serve as a valuable prognostic marker. The limited utility of t-PA as a standalone marker likely reflects the fact that ELISA measures total antigen, not its functional activity, which is inhibited by the excess PAI-1 [38,39]. The study's strengths include its well-defined case-control design and the use of actual healthy children as the control group, enhancing the accuracy of the diagnostic performance estimates. However, the study is not without limitations. First, the sample size was relatively small, which may limit the generalizability of the findings. Secondly, as a hospital-based study, it may be subject to selection bias. Finally, while D-dimer is an excellent marker, it is not specific to malaria and can be elevated in other conditions like sepsis [17]. Conclusions Pediatric P. falciparum malaria markedly disrupts hemostasis, inducing a hypofibrinolytic and hypercoagulable state. This study established D-dimer as a notably accurate biomarker for assessing disease activity in pediatric malaria. Furthermore, both D-dimer and PAI-1 demonstrated significant potential for stratifying disease severity and identifying high-risk patients. The clinical implications of these findings are valuable for improving patient management in endemic, resource-limited settings. Rather than replacing standard methods, quantitative D-dimer and PAI-1 testing could function as powerful triage tools alongside standard microscopy. High levels of these markers could immediately flag a child as being at a greater risk of severe complications, prompting more intensive monitoring and earlier intervention. Integrating these biomarkers into clinical protocols could therefore enhance risk assessment and ultimately contribute to better survival outcomes for children with malaria. Declarations Acknowledgements We are grateful for the immense contributions of the staff of Janie Speaks A.M.E. Zion Hospital, Nkenkasu District Hospital, and Akumadan Polyclinic for their warm reception, not forgetting our participants. Authors’ contributions Desmond Gyedu: Conceptualization, Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review & editing, Software, Formal analysis, Project administration, Data curation, Supervision, Resources Stephen Twumasi: Conceptualization, Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review & editing, Software, Formal analysis, Project administration, Data curation, Supervision, Resources Otchere Addai-Mensah: Conceptualization, Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review & editing, Software, Formal analysis, Project administration, Data curation, Supervision, Resources Lilian Antwi Boateng: Conceptualization, Methodology, Software, Writing - review & editing, Writing - original draft Benedict Sackey: Conceptualization, Methodology, Software, Writing - review & editing, Writing - original draft Abdul Wasid Abubakari: Conceptualization, Methodology, Software, Writing - review & editing, Writing - original draft Samuel Kwarteng: Writing - review & editing Allwell Adofo Ayirebi: Conceptualization, Methodology, Software, Writing - review & editing, Writing - original draft Belinda Nyuyelle Dery: Writing - review & editing Bastu Odoka: Writing - review & editing Eric Twum Ameyaw: Writing - review & editing Charles Nkansah: Conceptualization, Methodology, Software, Writing - review & editing, Writing - original draft Faruke Nyarko Donkor: Conceptualization, Methodology, Software, Writing - review & editing, Writing - original draft Yeboah Marfo-Debrekyei: Writing - review & editing Elizabeth Abban: Writing - review & editing Olivia Opoku Mensah: Writing - review & editing Musah Razak: Writing - review & editing Daniel Kwarteng: Writing - review & editing Enoch Odame Anto: Conceptualization, Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review & editing, Software, Formal analysis, Project administration, Data curation, Supervision, Resources Funding The author(s) received no financial support for the research, authorship and or/ publication of this article. Authors Approval of manuscript All authors have read and approved the final version of the manuscript. [CORRESPONDING AUTHOR or MANUSCRIPT GUARANTOR] had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis. Availability of data The authors confirm that the data supporting the findings of this study are available within the article. Data and materials for study are available upon request from the corresponding authors. Transparency statement The corresponding author [Dsmond Gyedu, Stephen Twumasi, Enoch Odame Anto] affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained. Consent for publication Not applicable. 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Age-patterns of malaria vary with severity, transmission intensity and seasonality in sub-Saharan Africa: a systematic review and pooled analysis. PLoS One. 2010;5: e8988. Naser RH, Rajaii T, Farash BRH, Seyyedtabaei SJ, Hajali V, Sadabadi F, et al. Hematological changes due to malaria - An update. Mol Biochem Parasitol. 2024;259: 111635. Erhabor O, Mohammad HJ, Onuigue FU, Abdulrahaman Y, Ezimah AC. Anaemia and Thrombocytopenia among Malaria Parasitized Children in Sokoto, North Western Nigeria. Journal of Hematology and Transfusion. 2014 [cited 8 Mar 2026]. doi:10.47739/2333-6684/1020 Maina RN, Walsh D, Gaddy C, Hongo G, Waitumbi J, Otieno L, et al. Impact of Plasmodium falciparum infection on haematological parameters in children living in Western Kenya. Malar J. 2010;9 Suppl 3: S4. Asmerom H, Gemechu K, Bete T, Sileshi B, Gebremichael B, Walle M, et al. Platelet parameters and their correlation with parasitemia levels among malaria infected adult patients at Jinella health center, Harar, Eastern Ethiopia: Comparative cross-sectional study. J Blood Med. 2023;14: 25–36. Sumbele IUN, Sama SO, Kimbi HK, Taiwe GS. Malaria, Moderate to Severe Anaemia, and Malarial Anaemia in Children at Presentation to Hospital in the Mount Cameroon Area: A Cross-Sectional Study. Anemia. 2016;2016: 1–12. van der Poll T, de Jonge E, ten Cate an H. Cytokines as regulators of coagulation. Georgetown, TX: Landes Bioscience; 2013. Ulfhammer E, Larsson P, Karlsson L, Hrafnkelsdóttir T, Bokarewa M, Tarkowski A, et al. TNF-alpha mediated suppression of tissue type plasminogen activator expression in vascular endothelial cells is NF-kappaB- and p38 MAPK-dependent. J Thromb Haemost. 2006;4: 1781–1789. Zuniga M, Gomes C, Chen Z, Martinez C, Devlin JC, Loke P ’ng, et al. Plasmodium falciparum and TNF-α differentially regulate inflammatory and barrier integrity pathways in human brain endothelial cells. MBio. 2022;13: e0174622. Hanson J, Lee SJ, Hossain MA, Anstey NM, Charunwatthana P, Maude RJ, et al. Microvascular obstruction and endothelial activation are independently associated with the clinical manifestations of severe falciparum malaria in adults: an observational study. BMC Med. 2015;13: 122. Erice C, Kain KC. New insights into microvascular injury to inform enhanced diagnostics and therapeutics for severe malaria. Virulence. 2019;10: 1034–1046. Francischetti IMB, Seydel KB, Monteiro RQ, Whitten RO, Erexson CR, Noronha ALL, et al. Plasmodium falciparum-infected erythrocytes induce tissue factor expression in endothelial cells and support the assembly of multimolecular coagulation complexes: Endothelial cells, malaria, and tissue factor. J Thromb Haemost. 2007;5: 155–165. Foko LPK, Narang G, Tamang S, Hawadak J, Jakhan J, Sharma A, et al. The spectrum of clinical biomarkers in severe malaria and new avenues for exploration. Virulence. 2022;13: 634–653. Balerdi-Sarasola L, Parolo C, Fleitas P, Cruz A, Subirà C, Rodríguez-Valero N, et al. Host biomarkers for early identification of severe imported Plasmodium falciparum malaria. Travel Med Infect Dis. 2023;54: 102608. Harmonis JA, Kusuma SAF, Rukayadi Y, Hasanah AN. Exploring biomarkers for malaria: Advances in early detection and asymptomatic diagnosis. Biosensors (Basel). 2025;15: 106. Tissue Plasminogen Activator (tPA). In: DiaPharma [Internet]. 13 Feb 2024 [cited 8 Mar 2026]. Available: https://diapharma.com/resources/tissue-plasminogen-activator-tpa/ Chandler WL, Alessi MC, Aillaud MF, Henderson P, Vague P, Juhan-Vague I. Clearance of tissue plasminogen activator (TPA) and TPA/plasminogen activator inhibitor type 1 (PAI-1) complex: relationship to elevated TPA antigen in patients with high PAI-1 activity levels: Relationship to elevated TPA antigen in patients with high PAI-1 activity levels. Circulation. 1997;96: 761–768. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9418547","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623152427,"identity":"29c171b6-4609-45fd-93d4-aa0467460ce5","order_by":0,"name":"Desmond 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17:49:34","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9418547/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9418547/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107486026,"identity":"c29bd0dd-6f55-4b78-a02a-f2817288ab5c","added_by":"auto","created_at":"2026-04-22 02:37:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":144440,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePlasma levels of fibrinolytic markers. \u003c/strong\u003eViolin plots showing the distribution of (A) PAI-1, (B) D-dimer, and (C) t-PA in controls (blue), mild malaria (gray), and severe malaria (red) groups. The white box represents the interquartile range (IQR), the central line is the median, and asterisks denote statistical significance (*p\u0026lt;0.05, ****p\u0026lt;0.0001, ns=not significant).\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-9418547/v1/02e112200baa13659919806f.png"},{"id":107486309,"identity":"7bb51efd-281d-4528-bdaf-78174aef54fe","added_by":"auto","created_at":"2026-04-22 02:38:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":199401,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curves of D-dimer, PAI-1, and t-PA for malaria diagnosis (A) and severity stratification (B).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"22.png","url":"https://assets-eu.researchsquare.com/files/rs-9418547/v1/bdfc65ebf449e97be6d6749b.png"},{"id":107487939,"identity":"f5acc05e-afde-4aa6-a650-93dc7b4425b2","added_by":"auto","created_at":"2026-04-22 02:43:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1272087,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9418547/v1/37f2935a-c915-4ff7-81fc-6044f0360925.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDiagnostic utility of fibrinolytic markers as indicators of pediatric \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePlasmodium falciparum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e malaria: a case-control study in the Offinso-North District, Ghana\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cem\u003ePlasmodium falciparum \u003c/em\u003e(\u003cem\u003eP. falciparum\u003c/em\u003e) malaria remains a leading cause of childhood mortality in sub-Saharan Africa, where children under five bear the greatest burden [1\u0026ndash;3]. According to the World Health Organization, of the 249 million malaria cases and 608,000 deaths worldwide in 2022, approximately 95% occurred in Africa [4,5]. In Ghana, this challenge is pronounced, with malaria prevalence varying from 2.6% to 41.9% across different ecological zones [6].\u003c/p\u003e\n\u003cp\u003eThe pathophysiology of severe malaria is complex, driven largely by the cytoadherence of parasitized erythrocytes to vascular endothelium via \u003cem\u003eP. falciparum \u003c/em\u003eerythrocyte membrane protein 1 (PfEMP-1) [7\u0026ndash;10]. This process triggers widespread endothelial activation, sequestration of parasites in vital organs, and a systemic inflammatory response that critically disrupts hemostasis.\u003c/p\u003e\n\u003cp\u003eA key consequence of these events is a dysregulation of the fibrinolytic system, which is responsible for dissolving fibrin clots. In malaria, endothelial activation and inflammation disrupt this balance, often leading to a state of hypofibrinolysis characterized by elevated levels of plasminogen activator inhibitor-1 (PAI-1), the primary inhibitor of fibrinolysis and decreased activity of its target, tissue plasminogen activator (t-PA) [11\u0026ndash;14]. This prothrombotic state is further evidenced by the accumulation of D-dimer, a fibrin degradation product that serves as a marker for both coagulation activation and subsequent fibrinolysis [15\u0026ndash;17].\u003c/p\u003e\n\u003cp\u003eWhile previous studies have documented hemostatic changes like thrombocytopenia and elevated fibrin degradation products in malaria [18\u0026ndash;21], a comprehensive evaluation of multiple fibrinolytic markers in pediatric populations in West Africa remains limited. The specific diagnostic utility of PAI-1, t-PA, and D-dimer in distinguishing malaria from other febrile illnesses and in stratifying disease severity (uncomplicated vs. severe malaria) in Ghanaian children has not been adequately characterized. This study therefore aimed to address this gap through the following objectives: (1) determine the plasma levels of PAI-1, t-PA, and D-dimer in children with \u003cem\u003eP. falciparum\u003c/em\u003e malaria; (2) compare hematological parameters between malaria cases and controls; (3) evaluate the diagnostic performance of these fibrinolytic markers in detecting malaria and distinguishing disease severity; and (4) assess the correlations between the fibrinolytic biomarkers and selected hematological parameters. \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study Design, Study Site and Study Duration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis case-control study was conducted between April and October 2023 in the Offinso-North District, Ghana, a region with endemic, seasonal malaria transmission. Participants were recruited from three healthcare facilities: Janie Speaks A.M.E. Zion Hospital, Nkenkasu District Hospital, and Akumadan Polyclinic.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Ethical Clearance and Informed Consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Committee on Human Research, Publication and Ethics (CHRPE) of the Kwame Nkrumah University of Science and Technology (Ref: CHRPE/AP/218/23). The study was performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from parents or legal guardians, and assent was obtained from children aged 7-13 years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Study Participants and Sample Size\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 120 children aged 1\u0026ndash;13 years were enrolled: 80 with microscopy-confirmed \u003cem\u003eP. falciparum\u0026nbsp;\u003c/em\u003emalaria (cases) and 40 healthy, afebrile, malaria-negative children (controls). The sample size was determined using Kelsey\u0026apos;s formula, assuming a 25% prevalence of significant hemostatic disruption in severe malaria versus 5% in controls, based on previous reports of coagulopathy in pediatric malaria, with 95% confidence and 80% power (Gwacham-Anisiobi et al. 2024).\u003c/p\u003e\n\u003cp\u003eInclusion criteria for cases were: age 1\u0026ndash;13 years, microscopy-confirmed \u003cem\u003eP. falciparum\u003c/em\u003e infection, and symptoms consistent with malaria. Exclusion criteria for all participants included known chronic illnesses (e.g., sickle cell disease, HIV), recent antimalarial treatment (within 2 weeks), blood transfusion (within 3 months), or use of anticoagulant medications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMalaria cases were classified according to WHO criteria. Severe malaria (n=25) was defined by asexual parasitemia plus one or more of: prostration, impaired consciousness, respiratory distress, severe anemia (hemoglobin \u0026lt;5 g/dL), or hyper-parasitemia (\u0026gt;100,000 parasites/\u0026mu;L). All other cases were classified as uncomplicated malaria (n=55).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Data and Sample Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical, demographic, and environmental data were collected through face-to-face interviews with parents/guardians and review of medical records using a standardized case report form. Approximately 5 mL of venous blood was collected from each participant into two tubes: a K₂EDTA tube for complete blood count and malaria microscopy, and a 3.2% sodium citrate tube for fibrinolytic assays. Blood for coagulation studies was immediately centrifuged at 2,000 \u0026times; g for 15 minutes at 4\u0026deg;C. Platelet-poor plasma was aliquoted and stored at -80\u0026deg;C until analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Laboratory Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMalaria diagnosis and parasitemia were determined by microscopic examination of Giemsa-stained blood smears by two independent expert microscopists. Parasite density was calculated using the formula: (number of parasites counted / 200 WBCs) \u0026times; participant\u0026rsquo;s actual WBC count obtained from the hematology analyzer.\u003c/p\u003e\n\u003cp\u003eHematological parameters were measured using a Sysmex XE-5000 automated analyzer (Sysmex, Kobe, Japan). Plasma concentrations of D-dimer (Abcam, ab260076), PAI-1 (Abcam, ab108891), and t-PA (Abcam, ab108914) were quantified using commercial sandwich ELISA kits according to the manufacturer\u0026rsquo;s instructions. All samples were analyzed in duplicate, and quality control was maintained throughout the process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were analyzed using IBM SPSS Statistics version 26.0. Continuous variables were assessed for normality using the Shapiro-Wilk test and are presented as median and interquartile range (IQR). Comparisons between the three groups were performed using the Kruskal-Wallis test, followed by Mann-Whitney U tests for pairwise comparisons. Categorical variables were compared using the Chi-squared or Fisher\u0026apos;s exact test. Spearman\u0026apos;s correlation was used to assess relationships between variables. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic and prognostic performance of D-dimer, PAI-1, and t-PA for malaria diagnosis and severity stratification. A p-value \u0026lt;0.05 was considered statistically significant.\u0026nbsp;\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Participant Characteristics and Parasitological Findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 120 children were enrolled: 80 with P. falciparum malaria (55 uncomplicated and 25 severe) and 40 healthy controls. Children with malaria were significantly younger than controls (median age 3.5 years vs. 8.0 years; p\u0026lt;0.001). Of the malaria cases, 56.2% (n=45/80) were children under 5 years, while 43.8% (n=35/80) were aged 5\u0026ndash;13 years.\u003c/p\u003e\n\u003cp\u003eThere was no significant difference in sex distribution across groups (p=0.243), with female participants accounting for 43.3% (n=52/120) of the total population. Fever was the most common symptom (96.3%), and body temperature was significantly elevated in malaria cases (p\u0026lt;0.001) (Table1). Environmental risk factors were significantly associated with malaria, including the presence of stagnant water (p=0.009) and bushes near the home (p=0.001); however, these factors did not show a direct correlation with fibrinolytic biomarker levels.\u003c/p\u003e\n\u003cp\u003eAmong the malaria-positive cases, the median parasitemia was 50,400 (IQR: 18,250\u0026ndash;185,600) parasites/\u0026micro;L. As expected, children with severe malaria had a significantly higher median parasitemia than those with uncomplicated malaria (210,900 [IQR: 100,471\u0026ndash;293,794.5] parasites/\u0026micro;L vs. 36,820 [IQR: 9,240\u0026ndash;79,805] parasites/\u0026micro;L; p\u0026lt;0.0001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Demographic and Clinical Characteristics of Study Participants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"727\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControls (n=40)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUncomplicated Malaria (n=55)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere Malaria (n=25)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eAge (years), Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e8.0 (5.0\u0026ndash;10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e4.0 (2.0\u0026ndash;7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e3.0 (2.0\u0026ndash;5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eAge \u0026lt; 5 years, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e8 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e30 (54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e15 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eAge 5\u0026ndash;13 years, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e32 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e25 (45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e10 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eMale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e25 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e28 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e13 (52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eFemale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e15 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e27 (49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e12 (48.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eTemperature,\u0026deg;C, Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e36.5 (36.2\u0026ndash;36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e37.8 (37.2\u0026ndash;38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e38.2 (37.5\u0026ndash;38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Symptoms, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eFever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e52 (94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e25 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eChills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e35 (63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e17 (68.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eHeadache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e32 (58.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e16 (64.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eVomiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e20 (36.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e12 (48.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eLoss of appetite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e28 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e15 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnvironmental Factors, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eStagnant water near home\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e30 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e22 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e18 (72.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eBushes near home\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e40 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e42 (76.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e20 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eUse of protective clothing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e40 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e25 (45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e11 (44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eInsecticide-treated nets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e38 (95.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e48 (87.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e20 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: IQR, interquartile range. P-values from Kruskal-Wallis test (continuous variables) or Chi-square/Fisher\u0026apos;s exact test (categorical variables).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Hematological Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMalaria cases exhibited significant hematological abnormalities compared to healthy controls. Both the uncomplicated and severe malaria groups had significantly lower hemoglobin levels, hematocrit, and platelet counts (p\u0026lt;0.0001). Anemia was a predominant finding among the cases. Specifically, the median hemoglobin was 9.7 (IQR: 8.0\u0026ndash;11.1) g/dL in the uncomplicated group and 9.3 (IQR: 4.7\u0026ndash;10.4) g/dL in the severe group, compared to 11.6 (IQR: 11.2\u0026ndash;12.4) g/dL in controls. RBC indices, including mean cell hemoglobin (MCH) and mean cell hemoglobin concentration (MCHC), were also significantly lower in children with malaria (p=0.002 and p\u0026lt;0.0001, respectively). Conversely, the RDW-CV was significantly higher in the severe group (16.1%) compared to controls (13.9%) (p\u0026lt;0.0001).\u003c/p\u003e\n\u003cp\u003eWhile total white blood cell (WBC) counts did not differ significantly between the three groups (p=0.299), differential counts revealed profound changes. Children with malaria showed significant neutrophilia (p\u0026lt;0.0001) and monocytosis (p=0.003), alongside marked lymphopenia (p\u0026lt;0.0001) compared to controls. Significant thrombocytopenia was observed in both the uncomplicated group (157.0 [IQR: 97.0\u0026ndash;220.0] \u0026times;\u0026times; 10⁹/L) and the severe malaria group (140.0 [IQR: 91.0\u0026ndash;166.5] \u0026times;\u0026times; 10⁹/L) relative to controls (334.5 [IQR: 274.3\u0026ndash;400.0] \u0026times; 10⁹/L) (p\u0026lt;0.0001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Hematological Parameters of Study Participants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"687\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControls (n=40)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUncomplicated Malaria (n=55)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere Malaria (n=25)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e11.6 (11.2\u0026ndash;12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e9.7 (8.0\u0026ndash;11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e9.3 (4.7\u0026ndash;10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eHematocrit (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e33.2 (32.0\u0026ndash;34.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e28.4 (24.1\u0026ndash;32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e28.4 (14.6\u0026ndash;30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRBC (\u0026times; 10\u0026sup1;\u0026sup2;/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e4.52 (4.20\u0026ndash;4.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e3.98 (3.55\u0026ndash;4.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e3.85 (3.20\u0026ndash;4.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMCV (fL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e79.5 (76.0\u0026ndash;82.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e76.0 (72.0\u0026ndash;79.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e75.0 (70.0\u0026ndash;78.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMCH (pg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e26.0 (24.5\u0026ndash;27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e24.5 (23.0\u0026ndash;26.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e24.0 (22.0\u0026ndash;25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMCHC (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e35.4 (35.0\u0026ndash;35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e33.7 (32.7\u0026ndash;34.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e33.8 (32.9\u0026ndash;34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRDW-CV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e13.9 (12.9\u0026ndash;14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e14.7 (13.2\u0026ndash;16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e16.1 (14.6\u0026ndash;18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eWBC (\u0026times; 10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e6.3 (5.5\u0026ndash;8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e8.1 (5.6\u0026ndash;11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e8.0 (6.5\u0026ndash;10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNeutrophils (\u0026times; 10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.6 (2.0\u0026ndash;3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e4.8 (3.5\u0026ndash;7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e4.4 (3.8\u0026ndash;7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eLymphocytes (\u0026times; 10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e3.2 (2.9\u0026ndash;4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e1.8 (1.4\u0026ndash;2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e2.0 (1.5\u0026ndash;4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMonocytes (\u0026times; 10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e0.54 (0.41\u0026ndash;0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e0.76 (0.50\u0026ndash;1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e1.12 (0.33\u0026ndash;1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eEosinophils (\u0026times; 10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e0.25 (0.18\u0026ndash;0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e0.15 (0.08\u0026ndash;0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.12 (0.05\u0026ndash;0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePlatelets (\u0026times; 10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e334.5 (274.3\u0026ndash;400.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e157.0 (97.0\u0026ndash;220.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e140.0 (91.0\u0026ndash;166.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMPV (fL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e8.5 (8.0\u0026ndash;9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e9.2 (8.5\u0026ndash;10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e9.5 (8.8\u0026ndash;10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Data presented as median (IQR). RBC, red blood cell count; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; RDW-CV, red cell distribution width-coefficient of variation; WBC, white blood cell count; MPV, mean platelet volume. P-values from Kruskal-Wallis test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Fibrinolytic Marker Levels\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlasma levels of fibrinolytic markers were significantly dysregulated in malaria. Both uncomplicated and severe malaria groups showed significantly elevated levels of PAI-1 and D-dimer compared to controls (p\u0026lt;0.001). Conversely, t-PA levels were significantly lower in the uncomplicated malaria group than in controls (p=0.012). D-dimer levels demonstrated a stepwise increase with disease severity, being significantly higher in severe malaria than in uncomplicated malaria (p=0.004). The PAI-1/t-PA ratio was also significantly higher in children with uncomplicated (1.35) and severe malaria (1.32) compared to controls (1.00) (p\u0026lt;0.001), indicating a systemic hypofibrinolytic state (Figure 1, Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Plasma Levels of Fibrinolytic Markers in Study Participants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"663\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControls (n=40)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUncomplicated\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Malaria (n=55)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere Malaria (n=25)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePAI-1 (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e27.5(24.0\u0026ndash;30.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 209px;\"\u003e\n \u003cp\u003e32.9 (29.5\u0026ndash;36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e33.5(30.0\u0026ndash;38.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003et-PA (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e27.7(25.0\u0026ndash;31.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 209px;\"\u003e\n \u003cp\u003e24.9 (22.0\u0026ndash;27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e26.0(23.5\u0026ndash;28.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eD-dimer (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e4485.2 (3850.0\u0026ndash;5200.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 209px;\"\u003e\n \u003cp\u003e7059.7 (6500.0\u0026ndash;7800.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e7852.5 (7200.0\u0026ndash;8600.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePAI-1/t-PA ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e1.00 (0.85\u0026ndash;1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 209px;\"\u003e\n \u003cp\u003e1.35 (1.20\u0026ndash;1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1.32 (1.18\u0026ndash;1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Data presented as median (IQR). PAI-1, plasminogen activator inhibitor-1; t-PA, tissue plasminogen activator. P-values from Kruskal-Wallis test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Correlation Between the Fibrinolytic Markers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn children under 5 years, D-dimer demonstrated a significant moderate positive correlation with parasitemia (r=0.546, p\u0026lt;0.001). However, it exhibited a weak positive relationship with hemoglobin (r=\u0026minus;0.179, p=0.241) and a weak negative relationship with platelets (r=\u0026minus;0.274, p=0.068), that was not statistically significant. Similarly, PAI-1 showed a significant positive trend with parasitemia in the under-5 group (r=0.311, \u003cem\u003ep=0.038)\u003c/em\u003e), and an insignificant weak correlation with hemoglobin and platelets respectively (r=0.103, \u003cem\u003ep=0.503;\u0026nbsp;\u003c/em\u003er=-0.010\u003cem\u003e, p=0.948)\u003c/em\u003e. In the older age group, both D-dimer and PAI-1 showed statistically significant associations with parasitemia (r=0.351, p=0.039; r=0.354, p=0.037) (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Correlations Between Fibrinolytic Markers and Selected Parameter\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"732\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;D-dimer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003ePAI-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;t-PA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 732px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChildren \u0026lt; 5 years (n=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eParasitemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003er=0.546,p\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003er=0.311,p=0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003er=\u0026minus;0.005,p=0.976\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eHemoglobin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.179,\u003cem\u003ep\u003c/em\u003e=0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.103,\u003cem\u003ep\u003c/em\u003e=0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.114,\u003cem\u003ep\u003c/em\u003e=0.456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003ePlatelets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.274,\u003cem\u003ep\u003c/em\u003e=0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.010,\u003cem\u003ep\u003c/em\u003e=0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.099,\u003cem\u003ep\u003c/em\u003e=0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.205,\u003cem\u003ep\u003c/em\u003e=0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.011,\u003cem\u003ep\u003c/em\u003e=0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.030,\u003cem\u003ep\u003c/em\u003e=0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eNeutrophils\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.005,\u003cem\u003ep\u003c/em\u003e=0.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.134,\u003cem\u003ep\u003c/em\u003e=0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.001,\u003cem\u003ep\u003c/em\u003e=0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 732px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChildren 5\u0026ndash;13 years (n=35)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eParasitemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.351,\u003cem\u003ep\u003c/em\u003e=0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.354,\u003cem\u003ep\u003c/em\u003e=0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.045,\u003cem\u003ep\u003c/em\u003e=0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eHemoglobin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.011,\u003cem\u003ep\u003c/em\u003e=0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.094,\u003cem\u003ep\u003c/em\u003e=0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.133,\u003cem\u003ep\u003c/em\u003e=0.446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003ePlatelets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.366,\u003cem\u003ep\u003c/em\u003e=0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.114,\u003cem\u003ep\u003c/em\u003e=0.514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.143,\u003cem\u003ep\u003c/em\u003e=0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRDW-CV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.449,\u003cem\u003ep\u003c/em\u003e=0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=\u0026minus;0.138,\u003cem\u003ep\u003c/em\u003e=0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cem\u003er\u003c/em\u003e=0.078,\u003cem\u003ep\u003c/em\u003e=0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: WBC, white blood cell count; RDW-CV, red cell distribution width-coefficient of variation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Diagnostic Performance of Fibrinolytic Markers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReceiver operating characteristic (ROC) analysis showed that D-dimer had the strongest discriminatory power for malaria diagnosis (AUC = 1.000, p\u0026lt;0.0001), with a cutoff of \u0026ge;5609.6 pg/mL yielding 100% sensitivity and 97.5% specificity. PAI-1 followed with moderate performance (AUC = 0.770, p\u0026lt;0.0001), while t-PA exhibited the lowest diagnostic ability (AUC = 0.644, p=0.008) (Figure 2A).\u003c/p\u003e\n\u003cp\u003eFor predicting severe malaria, D-dimer again exhibited optimal performance (AUC = 1.000, p\u0026lt;0.0001) with perfect sensitivity and specificity at a cutoff of \u0026ge;5920.9 pg/mL. PAI-1 demonstrated good diagnostic accuracy for severe malaria (AUC = 0.811, p\u0026lt;0.0001), providing a sensitivity of 72.0% and a specificity of 85.0% at a threshold of \u0026ge; 31.2 ng/mL. In contrast, t-PA performance for severity was marginal and did not reach high statistical significance (AUC = 0.649, p=0.057) (Figure 2B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: Diagnostic Performance of Biomarkers for Indicating Malaria\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"698\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarkers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCut-off\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-dimer (pg/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026ge;\u0026ge;5609.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100.0 (94.4\u0026ndash;100.0)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e97.5 (85.7\u0026ndash;100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e98.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.000 (0.999\u0026ndash;1.000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePAI-1 (ng/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026ge;\u0026ge;30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e78.8 (68.4\u0026ndash;86.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e75.0 (59.6\u0026ndash;85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e86.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e63.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.770 (0.685\u0026ndash;0.855)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et-PA (ng/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026le;\u0026le; 29.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e87.0 (77.4\u0026ndash;92.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e35.0 (22.1\u0026ndash;50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e72.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.644 (0.537\u0026ndash;0.751)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePV = positive predictive value; NPV = negative predictive value; CI = confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6: Diagnostic Performance of Biomarkers for Predicting Severe Malaria\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"673\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarkers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCut-off\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-dimer (pg/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ge;\u0026ge; 5920.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100.0 (83.9\u0026ndash;100.0)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100.0 (89.3\u0026ndash;100.0)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.000 (1.000\u0026ndash;1.000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePAI-1 (ng/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ge;\u0026ge; 31.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e72.0 (52.1\u0026ndash;85.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e85.0 (70.4\u0026ndash;93.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e75.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e82.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.811 (0.692\u0026ndash;0.930)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et-PA (ng/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026le;\u0026le; 25.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e63.6 (42.8\u0026ndash;80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e75.0 (59.6\u0026ndash;85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e78.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.649 (0.496\u0026ndash;0.802)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: PPV, positive predictive value; NPV, negative predictive value; AUC, area under the curve.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study provided evidence that fibrinolytic dysregulation is a central feature of pediatric \u003cem\u003eP. falciparum\u003c/em\u003e malaria in Ghana. The findings demonstrated that malaria-infected children exhibit a distinct hemostatic profile characterized by elevated PAI-1 and D-dimer, reduced t-PA, and significant hematological abnormalities. Most importantly, D-dimer was established as a strong indicator of disease activity, while PAI-1 served as a reliable marker of the systemic hypofibrinolytic response.\u003c/p\u003e\n\u003cp\u003eConsistent with established epidemiology, the study found that severe malaria disproportionately affected younger children, who are also presented with higher parasitemia [22,23]. The predominant clinical and hematological findings; fever, anemia, and thrombocytopenia aligned with the known pathophysiology of malaria, which involves pyrogenic cytokine release, erythrocyte destruction, and platelet consumption [24\u0026ndash;26]. The strong negative correlation observed between parasitemia and both hemoglobin and platelet count underscores the direct impact of parasite burden on these hematological disturbances [27,28].\u003c/p\u003e\n\u003cp\u003eThe core findings of this study lie in the profound disruption of the fibrinolytic system. The significantly elevated PAI-1 and reduced t-PA levels in malaria cases confirmed the state of hypofibrinolysis, where the capacity to lyse clots is suppressed [13,19]. This imbalance is likely driven by the systemic inflammation characteristic of malaria, as pro-inflammatory cytokines like TNF-\u0026alpha; are known to upregulate PAI-1 expression and downregulate t-PA [19,29\u0026ndash;31]. This creates a prothrombotic environment that may contribute to the microvascular obstruction and organ damage observed in severe malaria [32\u0026ndash;34].\u003c/p\u003e\n\u003cp\u003eAnother key finding was the elevation of D-dimer with increasing disease severity. D-dimer reflects the net effect of both coagulation activation and subsequent (albeit impaired) fibrinolysis. Its strong positive correlation with parasitemia suggests that parasite load is a primary driver of this hemostatic activation [15,16]. \u003c/p\u003e\n\u003cp\u003eD-dimer demonstrated excellent discriminatory performance (AUROC = 1.000) in the study cohort. This result likely reflects the clear physiological distinction between the well-defined, healthy afebrile control group and the acutely ill malaria cohort. It is crucial to contextualize this, however; in a real-world clinical setting, the primary challenge is often differentiating malaria from other common febrile illnesses, such as sepsis or viral infections, which are also known to elevate D-dimer levels. Therefore, while D-dimer\u0026apos;s ability to distinguish malaria from a healthy state is remarkable, future validation studies are needed in undifferentiated febrile cohorts.\u003c/p\u003e\n\u003cp\u003eNotably, PAI-1 also demonstrated good diagnostic accuracy for identifying severe malaria (AUC = 0.811), confirming that the degree of fibrinolytic suppression is closely linked to disease severity in these children. This finding matches the original thesis data and suggests that PAI-1 could serve as a valuable prognostic marker. The limited utility of t-PA as a standalone marker likely reflects the fact that ELISA measures total antigen, not its functional activity, which is inhibited by the excess PAI-1 [38,39].\u003c/p\u003e\n\u003cp\u003eThe study\u0026apos;s strengths include its well-defined case-control design and the use of actual healthy children as the control group, enhancing the accuracy of the diagnostic performance estimates. However, the study is not without limitations. First, the sample size was relatively small, which may limit the generalizability of the findings. Secondly, as a hospital-based study, it may be subject to selection bias. Finally, while D-dimer is an excellent marker, it is not specific to malaria and can be elevated in other conditions like sepsis [17].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003ePediatric \u003cem\u003eP. falciparum\u0026nbsp;\u003c/em\u003emalaria markedly disrupts hemostasis, inducing a hypofibrinolytic and hypercoagulable state. This study established D-dimer as a notably accurate biomarker for assessing disease activity in pediatric malaria. Furthermore, both D-dimer and PAI-1 demonstrated significant potential for stratifying disease severity and identifying high-risk patients.\u003c/p\u003e\n\u003cp\u003eThe clinical implications of these findings are valuable for improving patient management in endemic, resource-limited settings. Rather than replacing standard methods, quantitative D-dimer and PAI-1 testing could function as powerful triage tools alongside standard microscopy. High levels of these markers could immediately flag a child as being at a greater risk of severe complications, prompting more intensive monitoring and earlier intervention. Integrating these biomarkers into clinical protocols could therefore enhance risk assessment and ultimately contribute to better survival outcomes for children with malaria.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful for the immense contributions of the staff of Janie Speaks A.M.E. Zion Hospital, Nkenkasu District Hospital, and Akumadan Polyclinic for their warm reception, not forgetting our participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDesmond Gyedu: Conceptualization, Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review \u0026amp; editing, Software, Formal analysis, Project administration, Data curation, Supervision, Resources\u003c/p\u003e\n\u003cp\u003eStephen Twumasi: Conceptualization, Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review \u0026amp; editing, Software, Formal analysis, Project administration, Data curation, Supervision, Resources\u003c/p\u003e\n\u003cp\u003eOtchere Addai-Mensah:\u0026nbsp;Conceptualization, Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review \u0026amp; editing, Software, Formal analysis, Project administration, Data curation, Supervision, Resources\u003c/p\u003e\n\u003cp\u003eLilian Antwi Boateng: Conceptualization, Methodology, Software, Writing - review \u0026amp; editing, Writing - original draft\u003c/p\u003e\n\u003cp\u003eBenedict Sackey: Conceptualization, Methodology, Software, Writing - review \u0026amp; editing, Writing - original draft\u003c/p\u003e\n\u003cp\u003eAbdul Wasid Abubakari:\u0026nbsp;Conceptualization, Methodology, Software, Writing - review \u0026amp; editing, Writing - original draft\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Samuel Kwarteng: Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eAllwell Adofo Ayirebi:\u0026nbsp;Conceptualization, Methodology, Software, Writing - review \u0026amp; editing, Writing - original draft\u003c/p\u003e\n\u003cp\u003eBelinda Nyuyelle Dery:\u0026nbsp;Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eBastu Odoka:\u0026nbsp;Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eEric Twum Ameyaw: \u0026nbsp;Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eCharles Nkansah:\u0026nbsp;Conceptualization, Methodology, Software, Writing - review \u0026amp; editing, Writing - original draft\u003c/p\u003e\n\u003cp\u003eFaruke Nyarko Donkor: Conceptualization, Methodology, Software, Writing - review \u0026amp; editing, Writing - original draft\u003c/p\u003e\n\u003cp\u003eYeboah Marfo-Debrekyei: Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eElizabeth Abban:\u0026nbsp;Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eOlivia Opoku Mensah:\u0026nbsp;Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eMusah Razak:\u0026nbsp;Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eDaniel Kwarteng:\u0026nbsp;Writing - review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eEnoch Odame Anto: Conceptualization, Investigation, Writing - original draft, Methodology, Validation, Visualization, Writing - review \u0026amp; editing, Software, Formal analysis, Project administration, Data curation, Supervision, Resources\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) received no financial support for the research, authorship and or/ publication of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Approval of manuscript\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final version of the manuscript. [CORRESPONDING AUTHOR or MANUSCRIPT GUARANTOR] had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that the data supporting the findings of this study are available within the article. Data and materials for study are available upon request from the corresponding authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransparency statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding author [Dsmond Gyedu, Stephen Twumasi, Enoch Odame Anto] affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that there is no competing interest.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMalaria. [cited 8 Mar 2026]. Available: https://www.who.int/news-room/fact-sheets/detail/malaria\u003c/li\u003e\n\u003cli\u003eMalaria. In: UNICEF DATA [Internet]. UNICEF; 31 Mar 2021 [cited 8 Mar 2026]. Available: https://data.unicef.org/topic/child-health/malaria/\u003c/li\u003e\n\u003cli\u003eSamborska V. Despite being preventable and treatable, malaria is the leading cause of child mortality in much of Sub-Saharan Africa. In: Our World in Data [Internet]. [cited 8 Mar 2026]. Available: https://ourworldindata.org/data-insights/despite-being-preventable-and-treatable-malaria-is-the-leading-cause-of-child-mortality-in-much-of-sub-saharan-africa\u003c/li\u003e\n\u003cli\u003eCDC. Malaria\u0026rsquo;s Impact Worldwide. In: Malaria [Internet]. 9 May 2024 [cited 8 Mar 2026]. Available: https://www.cdc.gov/malaria/php/impact/index.html\u003c/li\u003e\n\u003cli\u003eShin H-I, Ku B, Jung H, Lee S-D, Lee S-Y, Ju J-W, et al. 2023 World Malaria Report (status of world malaria in 2022). 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Malar J. 2013;12: 246.\u003c/li\u003e\n\u003cli\u003eSukati S, Kotepui KU, Masangkay FR, Tseng C-P, Mahittikorn A, Anabire NG, et al. Elevations in D-dimer levels in patients with Plasmodium infections: a systematic review and meta-analysis. Sci Rep. 2025;15: 858.\u003c/li\u003e\n\u003cli\u003eFrancischetti IMB. Does activation of the blood coagulation cascade have a role in malaria pathogenesis? Trends Parasitol. 2008;24: 258\u0026ndash;263.\u003c/li\u003e\n\u003cli\u003eKilleen RB, Kok SJ. D-dimer test. StatPearls. Treasure Island (FL): StatPearls Publishing; 2026.\u003c/li\u003e\n\u003cli\u003eAmano H, Sano A, Araki T, Inoki S. Fibrin-degradation products in falciparum malaria. Zentralbl Bakteriol Mikrobiol Hyg A. 1981;250: 242\u0026ndash;247.\u003c/li\u003e\n\u003cli\u003eAngchaisuksiri P. Coagulopathy in malaria. Thromb Res. 2014;133: 5\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eTiiba J-DI, Ahmadu PU, Naamawu A, Fuseini M, Raymond A, Osei-Amoah E, et al. Thrombocytopenia a predictor of malaria: how far? J Parasit Dis. 2023;47: 1\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eDasgupta A, Rai S, Das Gupta A. Persistently elevated laboratory markers of thrombosis and fibrinolysis after clinical recovery in malaria points to residual and smouldering cellular damage. Indian J Hematol Blood Transfus. 2012;28: 29\u0026ndash;36.\u003c/li\u003e\n\u003cli\u003eRanjha R, Singh K, Baharia RK, Mohan M, Anvikar AR, Bharti PK. Age-specific malaria vulnerability and transmission reservoir among children. Glob Pediatr. 2023;6: None.\u003c/li\u003e\n\u003cli\u003eCarneiro I, Roca-Feltrer A, Griffin JT, Smith L, Tanner M, Schellenberg JA, et al. Age-patterns of malaria vary with severity, transmission intensity and seasonality in sub-Saharan Africa: a systematic review and pooled analysis. PLoS One. 2010;5: e8988.\u003c/li\u003e\n\u003cli\u003eNaser RH, Rajaii T, Farash BRH, Seyyedtabaei SJ, Hajali V, Sadabadi F, et al. Hematological changes due to malaria - An update. Mol Biochem Parasitol. 2024;259: 111635.\u003c/li\u003e\n\u003cli\u003eErhabor O, Mohammad HJ, Onuigue FU, Abdulrahaman Y, Ezimah AC. Anaemia and Thrombocytopenia among Malaria Parasitized Children in Sokoto, North Western Nigeria. Journal of Hematology and Transfusion. 2014 [cited 8 Mar 2026]. doi:10.47739/2333-6684/1020\u003c/li\u003e\n\u003cli\u003eMaina RN, Walsh D, Gaddy C, Hongo G, Waitumbi J, Otieno L, et al. Impact of Plasmodium falciparum infection on haematological parameters in children living in Western Kenya. Malar J. 2010;9 Suppl 3: S4.\u003c/li\u003e\n\u003cli\u003eAsmerom H, Gemechu K, Bete T, Sileshi B, Gebremichael B, Walle M, et al. Platelet parameters and their correlation with parasitemia levels among malaria infected adult patients at Jinella health center, Harar, Eastern Ethiopia: Comparative cross-sectional study. J Blood Med. 2023;14: 25\u0026ndash;36.\u003c/li\u003e\n\u003cli\u003eSumbele IUN, Sama SO, Kimbi HK, Taiwe GS. Malaria, Moderate to Severe Anaemia, and Malarial Anaemia in Children at Presentation to Hospital in the Mount Cameroon Area: A Cross-Sectional Study. Anemia. 2016;2016: 1\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003evan der Poll T, de Jonge E, ten Cate an H. Cytokines as regulators of coagulation. Georgetown, TX: Landes Bioscience; 2013.\u003c/li\u003e\n\u003cli\u003eUlfhammer E, Larsson P, Karlsson L, Hrafnkelsd\u0026oacute;ttir T, Bokarewa M, Tarkowski A, et al. TNF-alpha mediated suppression of tissue type plasminogen activator expression in vascular endothelial cells is NF-kappaB- and p38 MAPK-dependent. J Thromb Haemost. 2006;4: 1781\u0026ndash;1789.\u003c/li\u003e\n\u003cli\u003eZuniga M, Gomes C, Chen Z, Martinez C, Devlin JC, Loke P \u0026rsquo;ng, et al. Plasmodium falciparum and TNF-\u0026alpha; differentially regulate inflammatory and barrier integrity pathways in human brain endothelial cells. MBio. 2022;13: e0174622.\u003c/li\u003e\n\u003cli\u003eHanson J, Lee SJ, Hossain MA, Anstey NM, Charunwatthana P, Maude RJ, et al. Microvascular obstruction and endothelial activation are independently associated with the clinical manifestations of severe falciparum malaria in adults: an observational study. BMC Med. 2015;13: 122.\u003c/li\u003e\n\u003cli\u003eErice C, Kain KC. New insights into microvascular injury to inform enhanced diagnostics and therapeutics for severe malaria. Virulence. 2019;10: 1034\u0026ndash;1046.\u003c/li\u003e\n\u003cli\u003eFrancischetti IMB, Seydel KB, Monteiro RQ, Whitten RO, Erexson CR, Noronha ALL, et al. Plasmodium falciparum-infected erythrocytes induce tissue factor expression in endothelial cells and support the assembly of multimolecular coagulation complexes: Endothelial cells, malaria, and tissue factor. J Thromb Haemost. 2007;5: 155\u0026ndash;165.\u003c/li\u003e\n\u003cli\u003eFoko LPK, Narang G, Tamang S, Hawadak J, Jakhan J, Sharma A, et al. The spectrum of clinical biomarkers in severe malaria and new avenues for exploration. Virulence. 2022;13: 634\u0026ndash;653.\u003c/li\u003e\n\u003cli\u003eBalerdi-Sarasola L, Parolo C, Fleitas P, Cruz A, Subir\u0026agrave; C, Rodr\u0026iacute;guez-Valero N, et al. Host biomarkers for early identification of severe imported Plasmodium falciparum malaria. Travel Med Infect Dis. 2023;54: 102608.\u003c/li\u003e\n\u003cli\u003eHarmonis JA, Kusuma SAF, Rukayadi Y, Hasanah AN. Exploring biomarkers for malaria: Advances in early detection and asymptomatic diagnosis. Biosensors (Basel). 2025;15: 106.\u003c/li\u003e\n\u003cli\u003eTissue Plasminogen Activator (tPA). In: DiaPharma [Internet]. 13 Feb 2024 [cited 8 Mar 2026]. Available: https://diapharma.com/resources/tissue-plasminogen-activator-tpa/\u003c/li\u003e\n\u003cli\u003eChandler WL, Alessi MC, Aillaud MF, Henderson P, Vague P, Juhan-Vague I. Clearance of tissue plasminogen activator (TPA) and TPA/plasminogen activator inhibitor type 1 (PAI-1) complex: relationship to elevated TPA antigen in patients with high PAI-1 activity levels: Relationship to elevated TPA antigen in patients with high PAI-1 activity levels. Circulation. 1997;96: 761\u0026ndash;768.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Plasmodium falciparum, Malaria, Fibrinolysis, Plasminogen Activator Inhibitor-1, Tissue Plasminogen Activator, D-dimer, Biomarker, Pediatric Malaria, Ghana","lastPublishedDoi":"10.21203/rs.3.rs-9418547/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9418547/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eSevere \u003cem\u003ePlasmodium falciparum \u003c/em\u003e(\u003cem\u003eP. falciparum\u003c/em\u003e) malaria is associated with life-threatening complications, potentially linked to disturbed fibrinolysis. This study evaluated the plasma levels of key fibrinolytic markers; plasminogen activator inhibitor-1 (PAI-1), tissue plasminogen activator (t-PA), and D-dimer to assess their diagnostic and prognostic values in children with malaria in Ghana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eWe conducted a case-control study in the Offinso-North District, Ghana, recruiting 120 children aged 1–13 years. Participants were divided into three groups: a control group (n=40), an uncomplicated malaria group (n=55), and a severe malaria group (n=25), as defined by WHO guidelines. Plasma levels of t-PA, PAI-1, and D-dimer were measured using the sandwich Enzyme-Linked Immunosorbent Assay (ELISA) technique, and their diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUROC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Children with both uncomplicated and severe malaria had significantly higher plasma levels of PAI-1 and D-dimer, and significantly lower levels of t-PA, compared to the control group (p\u0026lt;0.05). D-dimer was identified as the strongest diagnostic marker for distinguishing all malaria cases from healthy controls (AUROC = 1.000, p\u0026lt;0.0001), demonstrating 98.8% (95% CI: 92.5–100) sensitivity and 100% (95% CI: 89.3–100) specificity. PAI-1 also demonstrated good diagnostic potential for both uncomplicated (AUROC = 0.752, p\u0026lt;0.0001) and severe malaria (AUROC = 0.811, p\u0026lt;0.0001) versus controls. For disease stratification, D-dimer significantly differentiated severe malaria from uncomplicated malaria (AUROC = 0.667, p=0.017).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Malaria infection disrupts the balance between coagulation and fibrinolysis. Our findings establish D-dimer as an indicator of disease activity and a potentially valuable tool for risk stratification in pediatric malaria. We propose that integrating quantitative D-dimer and PAI-1 testing with standard microscopy could improve patient triage and risk stratification in resource-limited settings, enabling earlier identification of high-risk patients.\u003c/p\u003e","manuscriptTitle":"Diagnostic utility of fibrinolytic markers as indicators of pediatric Plasmodium falciparum malaria: a case-control study in the Offinso-North District, Ghana","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:40:04","doi":"10.21203/rs.3.rs-9418547/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"11bb3cb3-e3b5-4e97-a3f9-33be736bd8c2","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66317404,"name":"Hematology"}],"tags":[],"updatedAt":"2026-04-19T12:40:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:40:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9418547","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9418547","identity":"rs-9418547","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}