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People who are immune-suppressed have less ability to recover and possess weaker immune systems after dengue fever. Early diagnosis and treatment reduce the mortality. With the approval of the Ethical Committee, 70 dengue fever cases were selected from Balaji Medical College Hospital, Chennai, Tamil Nadu, India. Under aseptic precautions, venous blood was collected with minimal stasis using dry and sterile disposable syringe and needle. The analyzer followed the sheath fluid impedance principle to calculate total RBC counts and platelet counts. The laser flow cytometry principle was used to calculate the total WBC counts. Calculations were done using SPSS21 and Microsoft Excel. One-way analysis of variance (ANOVA) with post-hoc test, Tukey’s honest significance difference tests, Spearman’s rho correlation, and chi-square test of independence were used to compare more than two independent samples. A T-test for single samples was done. P of 0.05 (a = 0.05) was considered to be statistically significant. About 70 cases of fever of various causes were studied. Serum ferritin and platelet-derived parameters such as mean platelet volume (MPV), platelet distribution width (PDW), and platelet count were studied, and the significance in relation between diagnosis and age in years was found. Significant changes were observed in PWD. Patients who had low platelet counts commonly presented with high ferritin (p = .036). Trends in platelet indices have been of continuous interest as markers. The relationship between age, sex, diagnosis, serumferritin, platelet distribution width (PDW), and platelet count was studied in 70 cases of non-structural protein NS1serology positive dengue. Some variables showed statistically significant correlations.
Department of Pathology, Sree Balaji Medical College and Hospital, Chennai, India
Marry Lilly
Department of Pathology, Sree Balaji Medical College and Hospital, Chennai, India
*Address all correspondence to: drammoorthyvc@gmail.com
1. Introduction
Dengue fever, caused by the dengue virus, is the most common arboviral infection. The highest number of dengue cases was reported in 2023, affecting over 80 countries in all regions defined by the World Health Organization [1]. The presentation of dengue can be quite varied. Dengue can present as a febrile illness with or without warning signs or in the form of severe dengue (dengue with severe bleeding or organ failure).
Dengue is known to present with organ dysfunction causing hepatitis, neurological disease, kidney disease, myocarditis, or heart attack. The common domestic, passive feeder is Aedes aegypti. The active feeder is Aedes albopictus. The Aedes mosquito transmits its disease by feeding on a human in the first 5 days of the course of the disease. The immune-suppressant medicines are used during liver transplantation to reduce graft rejection.
1.1 Vaccine development
Currently, there is only one approved dengue vaccine available, which provides sub-optimal protection. However, several other dengue vaccines are under development to lower the infection burden and decrease dengue-related morbidities. Dengvaxia is the first vaccine for dengue approved in many countries. It is recommended only for those with prior dengue infection due to the risk of severe dengue in seronegative individuals.
1.2 Pathogenesis and clinical features of dengue
Pathogenesis of viral infection includes various mechanisms, including the following:
Integration of the nuclear material and replication of the virus (most commonly in macrophages)
Direct viral infection through skin
Cellular immune response brought on by host viral interaction
About 70 fever cases were examined from outpatient centers of departments of medicine, surgery, obstetrics and gynecology, and hematology as well as biochemistry labs of Sree Balaji Medical College, Chennai, during 2021–2022. Observational and analytical cross-sectional study was done with the approval of the institutional ethical committee.
2.1 Inclusion criteria
About 70 (29 males and 41 females) serologically confirmed dengue patients were selected for the study. Out of 70 patients, 11 patients had additional symptoms of joint pain, cough, constipation, and abnormal complete blood counts (CBC) per 2012 WHO criteria, while remaining patients had fever, weakness, and rashes. Both males and females were above 18 years. Serum ferritin and platelet were used as a variable. The severity of dengue fever was evaluated by these markers.
2.2 Exclusion criteria
Dengue cases not confirmed by the laboratory were not included. Hematological neoplasm was not considered. The critical and recovery phase dengue patients were eliminated. Less than 18 years of male and female dengue patients were excluded.
2.3 Methodology
Patients from selected population who presented to the outpatient service center were questioned about demographic details, duration of fever, and other history specific to other causes. History regarding bleeding and complications of dengue fever (e.g., petechiae, vomiting, abdominal pain, joint pain, maculopapular rashes, and shock) was elicited. Dengue hemorrhagic fever [DHF] and DSS were diagnosed based on the WHO revised criteria for dengue. NS1 serology was done, and seropositive dengue cases were identified. Laboratory tests for serum ferritin and CBC were done. Platelet count and values of platelet indices were collected.
2.4 Sample collection
Under aseptic precautions, venous blood was collected with minimal stasis using dry and sterile disposable syringe and needle.
Venous samples for CBC and serum ferritin were collected in Ethylemediamurelectra acidic acid [EDTA] tubes. Samples were labeled with patients’ name, age, sex, and identification number and stored at room temperature.
Samples were tested as soon as possible or within 1 hour of collection to reduce variations caused by sample changes associated with time.
Samples were run in a Mindray BC-6800 analyzer, and the values were collected.
2.5 Laboratory analysis
Complete blood count (CBC) was done using MINDRAY, a five-part analyzer. Platelet count and values of platelet indices were isolated from the CBC of each case. Serum ferritin was done separately. Standardization and calibration of the instrument and sample processing was done as per as instructions of manufacturers and lab quality control protocol. The analyzer followed the sheath fluid impedance principle to calculate total red blood cell (RBC) counts and platelet count. The laser flow cytometry principle was used to calculate the total white blood cell (WBC) count. Serum ferritin was calculated by an automated Beckman–Coulter analyzer. Clinical history was collected from the medical records department. After baseline investigations and review of clinical history, patients were classified into different categories of dengue according to the WHO classification of dengue: Undifferentiated fever/viral syndrome, dengue fever (with or without hemorrhage), dengue hemorrhagic fever, dengue shock syndrome, and isolated organopathy. Platelet parameters such as platelet count, mean platelet volume (MPV), and platelet distribution width (PDW) were collected for seropositive dengue cases.
2.6 Statistical analysis
Calculations were done using SPSS 21 and Microsoft Excel’s data analysis Tool Pak. Data are presented as mean along with SD. One-way analysis of variance (ANOVA) with post-hoc Tukey’s honest significant difference test, Spearman’s rho correlation, and chi-square test of independence were used to compare more than two independent samples for correlation and significance. T-tests for single samples were done p < 0.05 (α = 0.05) and considered to be statistically significant.
2.7 Results
About 70 cases of fever of various causes were studied. The study of age distribution, gender distribution, serum ferritin, and platelet parameters was done. Serum ferritin and platelet derived parameters such as MPV, PDW, and platelet count were studied in seropositive dengue cases, cases clinically diagnosed and confirmed as dengue fever or dengue hemorrhagic fever, and for identifying, if any, the relation and correlation between individual variable and multiple variables (of independent means) in the study sample (Figure 1 and Table 1).
Figure 1.
Age distribution.
Age (in years)
Number
Percentage (%)
<30
30
43
30–44
15
21
45–60
12
17
>60
13
19
Table 1.
Age distribution.
The most common ages affected were between 18 and 30 years (43%). About 21 % of cases were between 30 and 44 years of age. About 17% of cases were between 45 and 60 years of age. About 19% of cases were above 60 years of age. Mean age in years of population affected in the study is 18–30 years (Figure 2 and Table 2).
Figure 2.
Sex distribution.
Sex
Number
Percentage (%)
F
41
59
M
29
41
Table 2.
Sex distribution.
Female patients (59%) are more commonly affected than male patients (41%). The ratio is 1.44:1 (male: female) (Figure 3 and Table 3) [2].
Figure 3.
Platelet count.
Platelet count (*103/mL)
Number
Percentage (%)
0–49
29
41
50–99
15
21
100–150
26
37
Table 3.
Platelet count distribution.
Most patients presented with platelet counts between 0 and 50,000/μL (41%), followed by 100–150,000/μL (37%) and 50–100,000/μL (21%).
Mean platelet count was between 0 and 50,000/μL, which is significant (t(69) = 4.38, p = <.001) (Figure 4 and Table 4).
Patients most commonly presented with dengue fever (84%) followed by dengue hemorrhagic fever (16%) (Figure 5 and Table 5).
Most of the cases (90%) presented with MPV value less than 9 fl, which is significant (t(69) = −6.98, p = <.001). About 10% of cases had MPV values above 9 fl (Figure 6 and Table 6).
In the age groups of 30–45 and more than 60 years, patients commonly presentedwith low platelet count (0–50,000/μL). In the age groups of less than 30 and 45–60 years, patients commonly presented with higher platelet count (>50,000/μL) (Figure 7 and Table 7).
Most cases of DF were in the younger age group (<30 years).
Most cases of DHF were in the older age group (>30 years) (Figure 8 and Table 8).
Patients presenting with lower platelet count (0–50,000/μL) more commonly had lower MPV values (<9 fl) when compared to those with higher platelet count (>50,000/μL), who had higher MPV values (>9 fl) (Figure 9 and Table 9).
In this study sample, MPV and PDW were negatively correlated (r(138) = −0.34, p = .004). Low MPV is likely to present with high PDW values in seropositive dengue cases.
Figure 4.
Diagnosis.
Diagnosis
Number
Percentage (%)
DF
59
84
DHF
11
16
Table 4.
Diagnosis.
Figure 5.
Mean platelet volume.
Mean platelet volume (fL)
Number
Percentage (%)
<8
33
47
8–9
30
43
>9
7
10
Table 5.
Mean platelet volume.
Figure 6.
Age distribution of platelet count.
Age (in years)
Platelet count (*103/μL)
0–49
50–99
100–150
<30
8
8
14
30–44
9
1
5
45–60
4
1
7
>60
8
5
0
Table 6.
Age distribution of platelet count.
Figure 7.
Diagnosis versus age.
Diagnosis
Age (in years)
Total
<30
30–44
45–60
>60
DF
30
12
10
7
59
DHF
0
3
2
6
11
TOTAL
30
15
12
13
70
Table 7.
Diagnosis versus age.
Figure 8.
Platelet count versus MPV.
Platelet count (*103/ μL)
MPV (fl)
Total
<8
8–9
>9
0–49
20
8
1
29
50–99
6
9
0
15
100–149
7
13
6
26
TOTAL
33
30
7
70
Table 8.
Platelet count versus mean platelet volume (MPV).
Figure 9.
MPV versus PDW.
MPV (fl)
PDW (fl)
Mean
SD
<8
11
9
8–9
10
1
>9
2.33
1.53
P value = 0.004 (0.00392)
Spearman’s rho correlation
Table 9.
Mean platelet volume versus platelet distribution width.
Dengue fever is a febrile disease that resolves with supportive therapy. DHF is typified by thrombocytopenia, increased vascular permeability, and significant hemorrhagic symptoms. It is challenging to make a diagnosis of DHF, especially in the initial stages of the illness. Serum ferritin is increased in the setting of inflammation. By the first week of the illness, lab results like thrombocytopenia and an increasing hematocrit are typically seen in DHF cases. Uncertainty surrounds the intricate process of throm- bocytopenia in case of dengue. Direct bone marrow suppression by DENV may be a cause of thrombocytopenia. Platelet lysis is caused by anti-dengue antibodies, platelet consumption in the periphery, and isolated virus replication in the platelet. In this study of 70 serologically confirmed dengue cases, the following can be concluded. Most of the cases in this study were between 18 and 30 years of age, followed by older adults and the elderly. Several previous studies also report similar findings. Egger and Coleman [3] note a high incidence of dengue in the age group of 20–40 years age group. Rodriguez-Barraquer et al. [4] also report similar findings. Patients in this study predominantly presented with only fever, weakness, and rashes, thus categorizing them as dengue fever (as per WHO 2012 criteria). Of the 70 cases that were studied, 11 cases presented with additional symptoms of joint pain, vomiting, abdominal pain, cough, constipation, petechiae, and abnormal lab CBC counts. Such cases were clinically categorized as DHF (as per 2012 WHO criteria). In this study, patients underwent clinical management and supportive therapy and did not develop shock due to plasma leakage. Younger people (<30 years) more commonly presented with DF, and the older age group (>30 years) presented with DHF (p = .007). Trends in platelet indices have been of continuous interest as markers. Indices measuring platelet volume (MPV) and size distribution (PDW) can give the status of platelets in peripheral blood and bone marrow. In this study, most MPV values were below 9 fl, and PDW values were above 14 fl. Low MPV was correlated with low platelet count (p < .001) and high PDW values (p = .004) in this study. Chatterjee et al. [5] noted that among their cases of dengue with platelet counts less than 20,000/ μL, MPV was lowered and PDW was above 14 fl. Similar findings have been reported by Mukker Pand Kiran S [6], However, Sanz et al. [7] and Martínez-Ruíz et al. [8] report a high MPV values presenting along with low platelet count in their cohort. Patients who had high PDW values commonly presented with high serum ferritin (p = .003), low platelet count (p < .001), and low MPV values (p = .004). Similar findings were reported by Chatterjee et al. [1], Mukker and Kiran [6], and Tangpukdee et al. [9] could not find any statistically significant relation between the trends of platelet count, platelet crit, MPV, and PDW values after studying 219 dengue cases. In this study, MPV and PDW values were correlated (p = .004), that is, patients with low MPV commonly presented with high PDW values. Shahila and Jothilingam [10] showed similar positive correlation findings between MPV, PDW and P-LCR. They found, after studying 254 cases, that the aforementioned indices were elevated but could not find any significant change in other platelet indices.
The relation between age, sex, diagnosis, serum ferritin, and platelet-derived parameters such as mean platelet volume (MPV), platelet distribution width (PDW), and platelet count were studied in 70 cases of NS1 serology positive dengue. Some variables showed statistically significant correlations. It was found that:
Mean platelet count was between 0 and 50,000/μL.
Most of the cases have MPV of less than 9 fl.
Most of the cases show PDW values above 14 fl.
Relation between diagnosis and age in years was significant—cases less than 30 years commonly presented with DF, while cases older than 30 years commonly presented with DHF.
Platelet count and MPV were positively correlated—low platelet count is likely to present with low MPV values in seropositive dengue cases.
Platelet count and PDW were negatively correlated—low platelet count is likely to present with high PDW values in seropositive dengue cases.
MPV and PDW were negatively correlated—low MPV is likely to present with high PDW values in seropositive dengue cases.
These markers can be used as an indicator for diagnosis of dengue and in predicting complications of dengue vasculopathy such as dengue hemorrhagic fever and dengue shock syndrome. At the minimal state, these parameters and trends can be used as preclinical indicators of development of complications and warning signs of dengue.
The following practices will aid recovery from dengue virus.: vajrasana, paschimottanasana, bhramma mudra, kapalapathi kiriya. and anuloma viloma pranayama.
The authors would like to thank the management for allowing the use of labora-tories, instruments, and equipment for conducting various investigations. Special thanks to Dr. S. Jagathrakshagan (chairman), Prof. Dr. J. Sreenisha (managing trustee), Er. N. Elamaran (managing director), Prof. Dr. Veerabahu (advisor), and Prof. Dr. P. Sasikumar (Dean) for funding and guiding the research.
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Written By
M. Abishek Chakkaravarthi and Marry Lilly
Submitted: 03 July 2024Reviewed: 06 August 2024Published: 07 April 2025
Open access peer-reviewed chapter
