ABSTRACT
Background and Aims
Down syndrome (DS) is a genetic condition caused by the triplication of chromosome 21. Currently, there is no available published data on hematological parameters among Sudanese children with Down syndrome. Therefore, this study aimed to investigate these parameters among this population.
Methods
Blood samples were collected from children at Farouk Center and Al‐Sababi Hospital in Khartoum State from July to December 2022. The samples were analyzed using a hematological analyzer, and the data were entered into a computer, examined, verified, and analyzed using the GraphPad Prism program.
Results
No statistically significant differences were observed between patients and controls concerning age and gender (p > 0.05). However, significant differences were found between the Down syndrome group and the control group in WBC, RBC, Hb, HCT, MCV, MCH, MCHC, and platelet count (p < 0.05). Differences were also observed in PLT, MPV, PDW, PCT, PLCC, PLCR, and platelet count between the groups (p < 0.05). There were no significant differences in the international normalized ratio (INR), partial thromboplastin time (APTT), and prothrombin time (PT) (p > 0.05). There were positive statistically significant correlations of Hb (p < 0.001), and RDWS (p = 0.016) with age in the children with Down syndrome only.
Conclusion
The study showed that Down syndrome has a clear effect on certain blood parameters, including lower platelet levels and MCHC. A significant difference was observed between the Down syndrome group and the control group in complete blood count (CBC) and coagulation parameters. The study recommends conducting similar studies for further insights and improvements in understanding the hematological effects of Down syndrome.
1. Introduction
Down syndrome (DS), a genetic disorder resulting from the triplication of chromosome 21, was first identified by John Langdon Down in 1866. It is one of the most frequently diagnosed genetic conditions. In the United States, approximately 210,000 individuals have DS, with a prevalence of 8.27 per 10,000 people [1, 2, 3, 4]. DS is the most prevalent chromosomal anomaly, affecting roughly one in 700 live births. The American College of Obstetrics and Gynecology (ACOG) and the American College of Medical Genetics recommend offering prenatal testing for DS to all pregnant women, regardless of age [5, 6, 7]. However, a significant proportion of diagnoses continue to be confirmed postnatally, and in developing regions like Sudan, epidemiological data and standardized clinical statistics regarding prevalence remain critically scarce. This lack of localized data hinders the development of targeted healthcare strategies for this vulnerable population. The syndrome is characterized by features such as muscle hypotonia, congenital heart defects, and changes in hormonal and enzymatic metabolism, which can lead to overweight and obesity. Chromosomal alterations causing neurochemical imbalances in enzymes like phosphofructokinase and superoxide dismutase may disrupt the body's antioxidative processes, potentially leading to premature aging [4, 8, 9, 10, 11, 12, 13]. Crucially, both accelerated aging and obesity are well‐established drivers of chronic, low‐grade systemic inflammation and altered immune responses. The persistent state of oxidative stress and adipose tissue dysfunction in DS leads to a dysregulated cytokine profile, which directly modulates the hematopoietic microenvironment [5, 9, 13, 14, 15]. These systemic stressors heavily influence bone marrow dynamics, peripheral immune cell distribution, and baseline endothelial function. Consequently, they are major underlying factors that directly alter baseline complete blood count (CBC) parameters and shift the homeostasis of baseline coagulation mechanisms. Understanding these hematological baselines is vital, as individuals with DS exhibit a unique susceptibility to both transient hematopoietic disorders and severe myeloid malignancies. Despite the clinical significance of these hematological variations, research exploring these physiological interactions remains heavily skewed toward Western studies [16, 17, 18, 19, 20, 21, 22].
In Sudan, research focusing on the biological and hematological profiles of individuals with Down syndrome remains scarce. Given that systemic genetic conditions profoundly dictate immune responses, oxygen‐carrying capacities, and hemostasis, it is vital to establish baseline clinical data for this population. The present study seeks to investigate the impact of Down syndrome on core hematological parameters, aiming to comprehensively analyze and evaluate complete blood counts and coagulation profiles among Sudanese children with Down syndrome.
2. Materials and Methods
2.1. Study Design and Population
This study was a cross‐sectional case‐control study conducted among children with Down syndrome at Farouk Center and Al‐Sababi Hospital in Khartoum State, Sudan, from July to December 2022.
2.2. Sample Collection and Processing
A total of 300 blood samples were collected, with 150 samples from children with Down syndrome (case group) and 150 samples from healthy children (control group). Information regarding participant identification numbers and residence areas was collected. A simple structured questionnaire, explained in Arabic, was used to gather this information.
Blood samples were collected using aseptic techniques. Approximately 5 mL of venous blood was obtained from each participant: 2.5 mL in a blood container with EDTA for complete blood count analysis and 2.5 mL in a blood container with tri‐sodium citrate for coagulation profile analysis. The samples were then transported to the clinical laboratory.
All samples were clearly labeled with the participant's identifying unique code number, and date and time of collection. Hematological analyses were performed using a hematological analyzer.
2.3. Data Analysis
Data were recorded in an Excel spreadsheet, and a t‐test was used to analyze differences in hematological parameters between the two groups, and a Pearson coefficient was performed to assess the correlation between continuous variables, employing the GraphPad Prism (version 6) program. A p‐value of less than 0.05 was considered statistically significant.
2.4. Ethical Considerations
The purpose and objectives of the study were explained to all participants, and written informed consent was obtained before their enrollment in the study. The study was approved by the Institutional Ethics Committee of the Faculty of Medical Laboratory Sciences, White Nile University (Approval code no.: WNU.FMLS.E.2022A1, date: January 6, 2022).
3. Results
3.1. Characteristics of Studied Participants
The mean age of children with Down syndrome was 11.9 years (±1.5), while the control group had a mean age of 13.2 years (±4.6). The age difference was not statistically significant (p = 0.248). In the Down syndrome group, 52.7% were male, and 47.3% were female. In the control group, 46.0% were male, and 54.0% were female, showing a significant gender distribution difference (p = 0.001), as showed in Table 1.
Table 1.
Characteristics of the studied participants.
| Down syndrome | Control group | ||||
|---|---|---|---|---|---|
| Variable | N | % | N | % | p‐value |
| Age in years (mean ± SD) | 11.9 ± 1.5 | 13.2 ± 4.6 | 0.248 | ||
| Gender | |||||
| Male | 79 | 52.7 | 69 | 46.0 | < 0.001 |
| Female | 71 | 47.3 | 81 | 54.0 | |
3.2. Hematological Parameters
The mean Hb in the Down syndrome group was 12.22 g/dL (±2.17) compared to 11.57 g/dL (±1.48) in the control group (p = 0.002). RBC count: The Down syndrome group had a mean RBC count of 4.02 (±0.67), significantly lower than the control group's 5.11 (±0.74) (p < 0.001). Hematocrit (HCT): The mean HCT was 35.10% (±5.53) in the Down syndrome group and 40.62% (±5.40) in the control group (p < 0.001). Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin (MCH), and Mean Corpuscular Hemoglobin Concentration (MCHC) were significantly higher in the Down syndrome group (p < 0.001 for all). Red Cell Distribution Width–Coefficient of Variation (RDWC) and Red Cell Distribution Width–Standard Deviation (RDWS) showed significant differences (p = 0.002 and p < 0.001, respectively). The Down syndrome group had a mean PLT of 199.23 (±85.31) compared to 285.46 (±125.22) in the control group (p = 0.000). Mean Platelet Volume (MPV) and Platelet Distribution Width (PDW) differed significantly, with lower MPV (p = 0.000) and higher PDW (p < 0.001) in the Down syndrome group, as explained in Table 2.
Table 2.
RBCs indices among children with Down and children without Down syndrome.
| RBCs indices | Case (mean ± SD) | Control (mean ± SD) | p‐value |
|---|---|---|---|
| Hb (g/dL) | 12.22 ± 2.17 | 11.57 ± 1.48 | 0.002 |
| RBCs | 4.02 ± 0.67 | 5.11 ± 0.74 | < 0.001 |
| HTC | 35.10 ± 5.53 | 40.62 ± 5.40 | < 0.001 |
| MCV (fL) | 86.74 ± 8.81 | 79.95 ± 6.87 | < 0.001 |
| MCH (pg) | 30.25 ± 2.69 | 22.77 ± 2.60 | < 0.001 |
| MCHC (g/dL) | 34.60 ± 1.39 | 28.43 ± 1.43 | < 0.001 |
| RDWC | 12.65 ± 1.87 | 13.71 ± 3.59 | 0.002 |
| RDWS | 46.58 ± 7.73 | 38.29 ± 5.49 | < 0.001 |
| PLT | 199.23 ± 85.31 | 285.46 ± 125.22 | < 0.001 |
| MPV | 8.32 ± 0.84 | 9.50 ± 1.32 | < 0.001 |
| PDW | 15.71 ± 0.80 | 12.09 ± 3.37 | < 0.001 |
| PCT (103/mL) | 0.27 ± 1.28 | 0.74 ± 5.78 | 0.328 |
The Down syndrome group had a significantly lower mean WBC count of 4.09 (±4.11) compared to 7.72 (±3.12) in the control group (p < 0.001). Lymphocytes, granulocytes, and monocytes were significantly lower in the Down syndrome group (p < 0.001 for all), as expressed in Table 3.
Table 3.
WBCs indices among children with Down and children without Down syndrome.
| WBCs indices | Case (mean ± SD) | Control (mean ± SD) | p‐value |
|---|---|---|---|
| WBCs | 4.09 ± 4.11 | 7.72 ± 3.12 | < 0.001 |
| Lymphocytes | 1.45 ± 0.69 | 2.55 ± 1.32 | < 0.001 |
| Granulocytes | 1.93 ± 0.78 | 4.42 ± 2.81 | < 0.001 |
| Monocytes | 0.24 ± 0.12 | 0.88 ± 1.10 | < 0.001 |
3.3. Coagulation Profile
Platelet Large Cell Count (PLCC) and Platelet Large Cell Ratio (PLCR) were significantly lower in the Down syndrome group (p < 0.001 for both). Prothrombin Time (PT), International Normalized Ratio (INR), and Activated Partial Thromboplastin Time (APTT) showed no significant differences between the groups (p = 0.963, p = 0.959, and p = 0.680, respectively), as explained in Table 4.
Table 4.
Coagulation profile among children with Down and children without Down syndrome.
| Coagulation profile | Case (mean ± SD) | Control (mean ± SD) | p‐value |
|---|---|---|---|
| PLCC | 33.14 ± 14.84 | 69.13 ± 28.34 | < 0.001 |
| PLCR | 18.10 ± 6.90 | 25.81 ± 7.87 | < 0.001 |
| PT | 17.81 ± 5.15 | 17.85 ± 5.27 | 0.963 |
| INR | 4.69 ± 16.01 | 4.57 ± 16.00 | 0.959 |
| APPT | 34.61 ± 2.66 | 34.45 ± 2.54 | 0.680 |
3.4. Correlation Between Hematological Parameters and Age
The statistically significant correlations with age were found only in the Down syndrome group for Hb (r = 0.288, p < 0.001), and RDWS (r = 0.197, p = 0.016). There are no statistically significant correlations between age and any of the hematological parameters in the Control group (children without Down syndrome), as showed in Table 5.
Table 5.
Correlation between hematological parameters and age among children with Down and children without Down syndrome.
| Parameters | Case group | Control group | ||
|---|---|---|---|---|
| r | p‐value | r | p‐value | |
| Hb (g/dL) | 0.288 | < 0.001 | 0.076 | 0.359 |
| RBCs | −0.021 | 0.797 | 0.000 | 0.997 |
| HCT | 0.015 | 0.854 | −0.089 | 0.283 |
| MCV (fL) | 0.106 | 0.197 | 0.078 | 0.345 |
| MCH (pg) | 0.067 | 0.416 | 0.128 | 0.120 |
| MCHC (g/dL) | −0.066 | 0.419 | 0.143 | 0.082 |
| RDWC | 0.143 | 0.082 | 0.000 | 0.997 |
| RDWS | 0.197 | 0.016 | 0.032 | 0.700 |
| PLT | 0.158 | 0.053 | 0.060 | 0.469 |
| MPV | −0.081 | 0.324 | 0.160 | 0.052 |
| PDW | −0.044 | 0.598 | 0.097 | 0.237 |
| PCT (103/mL) | −0.083 | 0.312 | 0.010 | 0.907 |
| WBCs | −0.088 | 0.286 | −0.142 | 0.083 |
| Lymphocytes | 0.138 | 0.092 | −0.127 | 0.125 |
| Granulocytes | 0.017 | 0.840 | −0.104 | 0.208 |
| Monocytes | 0.147 | 0.072 | −0.045 | 0.588 |
| PLCC | 0.096 | 0.241 | 0.094 | 0.256 |
| PLCR | 0.034 | 0.681 | 0.065 | 0.434 |
| PT | 0.169 | 0.123 | 0.035 | 0.747 |
| INR | −0.183 | 0.094 | 0.041 | 0.721 |
| APPT | 0.166 | 0.129 | 0.067 | 0.540 |
4. Discussion
In Sudan, few studies have evaluated the hematological profile of individuals with Down syndrome, and comprehensive assessments of both complete blood count (CBC) and coagulation profile parameters are lacking. Furthermore, differences in genetic background, environmental exposures, nutritional status, and healthcare access may influence hematological findings, limiting the applicability of evidence from other populations. Therefore, the present study aimed to evaluate complete blood count and coagulation profile parameters among Sudanese individuals with Down syndrome, providing baseline data that may facilitate the early detection and management of hematological abnormalities and inform future research in Sudan.
In the present study, the lack of statistical significance in age difference (p = 0.248) suggests that age may not be a confounding factor in the analysis of hematological parameters. This finding is consistent with previous studies that have reported similar age distributions in cohorts of children with Down syndrome, indicating that age‐related factors do not significantly influence the hematological profiles observed in this population [23]. Gender distribution showed a significant differences in males compared to females between the two groups. This aligns with existing literature that indicates a higher prevalence of Down syndrome in males, which may be attributed to biological and genetic factors influencing sex ratios at birth [24]. The hematological parameters revealed significant differences between the Down syndrome group and the control group. The mean hemoglobin (Hb) level in the Down syndrome group was significantly higher than the control groups. This finding is consistent with previous research that has documented elevated hemoglobin levels in children with Down syndrome, often attributed to compensatory mechanisms in response to chronic hypoxia or other underlying conditions [25]. The RBC count was significantly lower in the Down syndrome group compared to the control group, which corroborates findings from other studies that have reported reduced RBC counts in this population [26]. Hematocrit (HTC) levels were also significantly lower in the Down syndrome group compared to the control group. These findings suggest a potential predisposition to anemia in children with Down syndrome, which has been documented in various studies [27]. Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin (MCH), and Mean Corpuscular Hemoglobin Concentration (MCHC) were significantly higher in the Down syndrome, indicating macrocytic anemia, a common hematological trait in this population [28]. The Red Cell Distribution Width–Coefficient of Variation (RDWC) and Red Cell Distribution Width–Standard Deviation (RDWS) also showed significant differences, suggesting variability in red blood cell size, which can be indicative of underlying hematological disorders [29].
The Down syndrome group exhibited a mean platelet count (PLT) significantly lower than the control groups. This finding aligns with previous studies that have reported thrombocytopenia in individuals with Down syndrome, highlighting the need for careful monitoring of platelet levels in this population. Additionally, the mean Platelet Volume (MPV) was lower, while the Platelet Distribution Width (PDW) was higher in the Down syndrome group, indicating altered platelet production or function. The mean WBC count was significantly lower in the Down syndrome group compared to the control group. This reduction in WBC count, along with significantly lower lymphocyte, granulocyte, and monocyte counts, suggests potential immunological vulnerabilities in children with Down syndrome, as supported by previous studies that have documented altered immune profiles in this population. The coagulation profile revealed that the Platelet Large Cell Count (PLCC) and Platelet Large Cell Ratio (PLCR) were significantly lower in the Down syndrome group. However, no significant differences were observed in coagulation parameters such as prothrombin time (PT), international normalized ratio (INR), and activated partial thromboplastin time (APTT). The correlation analysis between hematological parameters with age revealed significant developmental patterns occurring exclusively in the Down syndrome group, notably a positive correlation between hemoglobin levels and age. Additionally, red cell distribution width standard deviation (RDWS) increased significantly with the age only in children with Down syndrome group, indicating that anisocytosis becomes more pronounced over time.
5. Conclusion
In conclusion, this study highlights significant hematological differences between Sudanese children with Down syndrome and their healthy counterparts. The findings underscore the importance of routine hematological assessments in this population to monitor for potential complications and guide clinical management. Further research is warranted to explore the underlying mechanisms driving these hematological changes and their implications for health outcomes in children with Down syndrome.
Author Contributions
Manasik Elghali: conceptualization, investigation, funding acquisition, methodology, software, project administration, data curation, resources, writing – original draft, visualization. Abdelhakam G. Tamomh: conceptualization, investigation, funding acquisition, writing – original draft, visualization, validation, methodology, software, formal analysis, project administration, data curation, supervision, resources, writing – review and editing. Rooa Alhaj Ahmed: conceptualization, investigation, funding acquisition, methodology, writing – review and editing, software, resources, data curation. Tibyan Hassan Abdalmalik: conceptualization, investigation, methodology, validation, visualization, writing – review and editing, software, resources. Howida Hajhamd Ibrahim: conceptualization, investigation, methodology, visualization, writing – review and editing, software, resources. Ibrahim K. Ibrahim: conceptualization, investigation, methodology, visualization, software, resources, writing – review and editing, formal analysis.
Funding
The authors have nothing to report.
Ethics Statement
The institutional ethics committee of the Faculty of Medical Laboratory, White Nile University approved the study (Approval code no.: WNU.FMLS.E.2022A1). Written informed consent was obtained from all parents of the children and the center manager who participated in the study after explaining the purpose of the study. All procedures were performed in accordance with the Declaration of Helsinki.
Consent
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflicts of interest.
Transparency Statement
The author, Abdelhakam G. Tamomh, 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.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
- 1. Ali R. I. K., Abdallah E. I., ELmobark M., Omer A. E., and Eltayeb L. B., “Abnormal Hematological Characteristics among Sudanese Children with Down Syndrome,” Journal of Biochemical Technology 12, no 3 (2021): 74–77, 10.51847/2OB9WmvN5N. [DOI] [Google Scholar]
- 2. Gensous N., Bacalini M. G., Franceschi C., and Garagnani P., “Down Syndrome, Accelerated Aging and Immunosenescence,” Seminars in Immunopathology 42 (2020): 635–645, 10.1007/s00281-020-00804-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Illouz T., Biragyn A., Iulita M. F., et al., “Immune Dysregulation and the Increased Risk of Complications and Mortality Following Respiratory Tract Infections in Adults With Down Syndrome,” Frontiers in Immunology 12 (2021): 2375, 10.3389/fimmu.2021.621440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Mang N., Vizitiu A. C., and Anghel A., “Changes in the Peripheral Blood Cell Count in Pediatric Patients With Down Syndrome,” Journal of International Medical Research 47 (2019): 3757–3762, 10.1177/0300060519850397. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Manna C., Officioso A., Trojsi F., et al., “Increased Non‐Protein Bound Iron in Down Syndrome: Contribution to Lipid Peroxidation and Cognitive Decline,” Free Radical Research 50 (2016): 1422–1431, 10.1080/10715762.2016.1253833. [DOI] [PubMed] [Google Scholar]
- 6. Nisihara R., Souza A. S. C., Finatti L. R., and Palmieri N. O., “Hematological Parameters in Children With Down Syndrome,” Jornal Brasileiro de Patologia e Medicina Laboratorial 51 (2015): 85–90, 10.5935/1676-2444.20150015. [DOI] [Google Scholar]
- 7. Roberts I., O'Connor D., Roy A., Cowan G., and Vyas P., “The Impact of Trisomy 21 on Foetal Haematopoiesis,” Blood Cells, Molecules, and Diseases 51 (2013): 277–281, 10.1016/j.bcmd.2013.07.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Chen D., Zhang Y., Tian Y., et al., “Relationship Between Risk of Childhood Acute Leukemia and Children's and Parents' Lifestyles and Household Environment Exposure,” Zhonghua Yu Fang Yi Xue Za Zhi[Chinese Journal of Preventive Medicine] 49 (2015): 792–799. [PubMed] [Google Scholar]
- 9. Lagan N., Huggard D., Mc Grane F., et al., “Multiorgan Involvement and Management in Children With Down Syndrome,” Acta Paediatrica 109, no. 6 (2020. June): 1096–1111. Epub January 24, 2020. PMID: 31899550. 2020, Accessed: June 109, 10.1111/apa.15153. [DOI] [PubMed] [Google Scholar]
- 10. Barroeta I., Nan M. N., Rives J., et al., “Evaluation of Biochemical and Hematological Parameters in Adults With Down Syndrome,” Scientific Reports 10, no. 1 (2020): 13755, 10.1038/s41598-020-70719-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Schmidt M. P., Colita A., Ivanov A. V., et al., “Outcomes of Patients With Down Syndrome and Acute Leukemia: A Retrospective Observational Study,” Medicine (Baltimore) 8 (2021): 27459. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. van den Bos H., Spierings D. C., Taudt A. S., et al., “Single‐Cell Whole Genome Sequencing Reveals No Evidence for Common Aneuploidy in Normal and Alzheimer's Disease Neurons,” Journal of the American Society of Hematology: 201631, 10.1097/MD.0000000000027459. [DOI] [Google Scholar]
- 13. Karakurt N., Uslu İ., Aygün C., and Albayrak C., “Hematological Disturbances in Down Syndrome: Single Centre Experience of Thirteen Years and Review of the Literature,” Turkish Journal of Pediatrics 61 (2019): 664–670, 10.24953/turkjped.2019.05.004. [DOI] [PubMed] [Google Scholar]
- 14. Sobey C. G., Judkins C. P., Sundararajan V., Phan T. G., Drummond G. R., and Srikanth V. K., “Risk of Major Cardiovascular Events in People With Down Syndrome,” PLoS One 10 (2015): e0137093, 10.1371/journal.pone.0137093. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Wiseman F. K., Al‐Janabi T., Hardy J., et al., “A Genetic Cause of Alzheimer Disease: Mechanistic Insights From Down Syndrome,” Nature Reviews Neuroscience 16 (2015): 564–574, 10.1038/nrn3983. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. McCann J. C. and Ames B. N., “The Pattern of Malignancies in Down Syndrome and Its Potential Context With the Immune System,” American Journal of Clinical Nutrition 85 (2018): 931–945, 10.3389/fimmu.2018.03058. [DOI] [Google Scholar]
- 17. Yang Q., Rasmussen S. A., and Friedman J., “Mortality Associated With Down's Syndrome in the USA From 1983 to 1997: A Population‐Based Study,” Lancet 359 (2002): 1019–1025, 10.1016/S0140-6736(02)08092-3. [DOI] [PubMed] [Google Scholar]
- 18. Gensous N. and Bacalini M. G., “Mortality Associated With Down's Syndrome in the USA, a Population‐Based Study,” Lancet 359 (2020): 1019–1025. [DOI] [PubMed] [Google Scholar]
- 19. Tenenbaum A., Malkiel S., Wexler I. D., Levy‐Khademi F., Revel‐Vilk S., and Stepensky P., “Anemia in Children With Down Syndrome,” International Journal of Pediatrics 2011 (2011): 813541, 10.1155/2011/813541. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Roizen N. J. and Patterson D., “Down's Syndrome,” Lancet 361 (2003): 1281–1289, 10.1016/S0140-6736(03)12987-X. [DOI] [PubMed] [Google Scholar]
- 21. Parker S. E., Mai C. T., Canfield M. A., et al., “Updated National Birth Prevalence Estimates for Selected Birth Defects in the United States 2004–2006,” Birth Defects Research Part A: Clinical and Molecular Teratology 88 (2010): 1008–1016, 10.1002/bdra.20735. [DOI] [PubMed] [Google Scholar]
- 22. Webb D., Roberts I., and Vyas P., “Haematology of Down Syndrome,” Archives 92, no. 38 (2018): 10.1136/adc.2006.104638. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Almeida E. W. and Greguol M., “Lipid Profile in People With Down Syndrome: A Literature Review,” Journal of Human Growth and Development 30, no. 2 (2020): 197–208, 10.7322/jhgd.v30.996. [DOI] [Google Scholar]
- 24. Cebeci Ayşe N., Ayla G., and Metin Y., “Profile of Hypothyroidism in Down's Syndrome,” Journal of Clinical Research in Pediatric Endocrinology 5, no. 2 (2013): 116–120, 10.4274/jcrpe.884. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Nkambule B. B., Mxinwa V., Nyambuya T. M., and Dludla P. V., “The Mean Platelet Volume and Atherosclerotic Cardiovascular‐Risk Factors in Adults With Obesity: A Systematic Review and Meta‐Analysis of Observational Studies,” BMC Nutrition 8, no. 1 (2022): 47, 10.1186/s40795-022-00541-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Wagner J., Langlois F., Lim D., McCartney S., and Fleseriu M., “Hypercoagulability and Risk of Venous Thromboembolic Events in Endogenous Cushing's Syndrome: A Systematic Meta‐Analysis,” Frontiers in Endocrinology 9 (2019): 805, 10.3389/fendo.2018.00805. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Gulleroglu K., Yazar B., Sakalli H., Ozdemir H., and Baskin E., “Clinical Importance of Mean Platelet Volume in Children With Nephrotic Syndrome,” Renal Failure 36, no. 5 (2014): 663–665, 10.3109/0886022X.2014.883931. [DOI] [PubMed] [Google Scholar]
- 28. Da'dara A. A., de Laforcade A. M., and Skelly P. J., “The Impact of Schistosomes and Schistosomiasis on Murine Blood Coagulation and Fibrinolysis as Determined by Thromboelastography (TEG),” Journal of Thrombosis and Thrombolysis 41, no. 4 (2016): 671–677, 10.1007/s11239-015-1298-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Chen J., Jiang T. T., Yi W., et al., “A Group of Serum Proteins as Potential Diagnostic Biomarkers for Yin‐Deficiency‐Heat Syndrome,” Anatomical Record 303, no. 8 (2020): 2086–2094, 10.1002/ar.24351. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.