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Clinico-laboratory spectrum of dengue viral infection and risk factors associated with dengue hemorrhagic fever: a retrospective study.

Mallhi TH, Khan AH, Adnan AS, Sarriff A, Khan YH, Jummaat F - BMC Infect. Dis. (2015)

Bottom Line: Skin rash, dehydration, shortness of breath, pleural effusion and thick gall bladder were more significantly (P < 0.05) associated with DHF than DF.Current study demonstrated that DF and DHF present significantly different clinico-laboratory profile.Older age, secondary infection, diabetes mellitus, lethargy, thick gallbladder and delayed hospitalization significantly predict DHF.

View Article: PubMed Central - PubMed

Affiliation: Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, University Sains Malaysia, Penang, 11800, Malaysia. tauqeer.hussain.mallhi@hotmail.com.

ABSTRACT

Background: The incidence of dengue is rising steadily in Malaysia since the first major outbreak in 1973. Despite aggressive measures taken by the relevant authorities, Malaysia is still facing worsening dengue crisis over the past few years. There is an urgent need to evaluate dengue cases for better understanding of clinic-laboratory spectrum in order to combat this disease.

Methods: A retrospective analysis of dengue patients admitted to a tertiary care teaching hospital during the period of six years (2008 - 2013) was performed. Patient's demographics, clinical and laboratory findings were recorded via structured data collection form. Patients were categorized into dengue fever (DF) and dengue hemorrhagic fever (DHF). Appropriate statistical methods were used to compare these two groups in order to determine difference in clinico-laboratory characteristics and to identify independent risk factors of DHF.

Results: A total 667 dengue patients (30.69 ± 16.13 years; Male: 56.7 %) were reviewed. Typical manifestations of dengue like fever, myalgia, arthralgia, headache, vomiting, abdominal pain and skin rash were observed in more than 40 % patients. DHF was observed in 79 (11.8 %) cases. Skin rash, dehydration, shortness of breath, pleural effusion and thick gall bladder were more significantly (P < 0.05) associated with DHF than DF. Multivariate regression analysis demonstrated presence of age > 40 years (OR: 4.1, P < 0.001), secondary infection (OR: 2.7, P = 0.042), diabetes mellitus (OR: 2.8, P = 0.041), lethargy (OR: 3.1, P = 0.005), thick gallbladder (OR: 1.7, P = 0.029) and delayed hospitalization (OR: 2.3, P = 0.037) as independent predictors of DHF. Overall mortality was 1.2 % in our study.

Conclusions: Current study demonstrated that DF and DHF present significantly different clinico-laboratory profile. Older age, secondary infection, diabetes mellitus, lethargy, thick gallbladder and delayed hospitalization significantly predict DHF. Prior knowledge of expected clinical profile and predictors of DHF/DSS development would provide information to identify individuals at higher risk and on the other hand, give sufficient time to clinicians for reducing dengue related morbidity and mortality.

No MeSH data available.


Related in: MedlinePlus

ROC Curve analysis of logistic regression model to predict DHF
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Fig4: ROC Curve analysis of logistic regression model to predict DHF

Mentions: To identify possible risk factors of DHF among dengue patients, logistic regression analysis was performed for clinically relevant and statistically tested variables. Out of five tested signs/symptoms, lethargy (OR: 3.1, P = 0.005) and thick gallbladder (OR: 1.7, P = 0.029) were two symptoms with a higher likelihood of presenting DHF. Patients with age greater than 40 years, secondary infection and diabetes mellitus presented a higher risk of DHF in our study (Table 4). It was also observed that patients who were admitted after 3 days of onset of illness (delayed hospitalization), were associated with a higher risk (OR: 2.3, P = 0.037) of having DHF than patients who were admitted within three days (Fig. 3b). ROC curve analysis of logistic model is shown in Fig. 4.Table 4


Clinico-laboratory spectrum of dengue viral infection and risk factors associated with dengue hemorrhagic fever: a retrospective study.

Mallhi TH, Khan AH, Adnan AS, Sarriff A, Khan YH, Jummaat F - BMC Infect. Dis. (2015)

ROC Curve analysis of logistic regression model to predict DHF
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4590689&req=5

Fig4: ROC Curve analysis of logistic regression model to predict DHF
Mentions: To identify possible risk factors of DHF among dengue patients, logistic regression analysis was performed for clinically relevant and statistically tested variables. Out of five tested signs/symptoms, lethargy (OR: 3.1, P = 0.005) and thick gallbladder (OR: 1.7, P = 0.029) were two symptoms with a higher likelihood of presenting DHF. Patients with age greater than 40 years, secondary infection and diabetes mellitus presented a higher risk of DHF in our study (Table 4). It was also observed that patients who were admitted after 3 days of onset of illness (delayed hospitalization), were associated with a higher risk (OR: 2.3, P = 0.037) of having DHF than patients who were admitted within three days (Fig. 3b). ROC curve analysis of logistic model is shown in Fig. 4.Table 4

Bottom Line: Skin rash, dehydration, shortness of breath, pleural effusion and thick gall bladder were more significantly (P < 0.05) associated with DHF than DF.Current study demonstrated that DF and DHF present significantly different clinico-laboratory profile.Older age, secondary infection, diabetes mellitus, lethargy, thick gallbladder and delayed hospitalization significantly predict DHF.

View Article: PubMed Central - PubMed

Affiliation: Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, University Sains Malaysia, Penang, 11800, Malaysia. tauqeer.hussain.mallhi@hotmail.com.

ABSTRACT

Background: The incidence of dengue is rising steadily in Malaysia since the first major outbreak in 1973. Despite aggressive measures taken by the relevant authorities, Malaysia is still facing worsening dengue crisis over the past few years. There is an urgent need to evaluate dengue cases for better understanding of clinic-laboratory spectrum in order to combat this disease.

Methods: A retrospective analysis of dengue patients admitted to a tertiary care teaching hospital during the period of six years (2008 - 2013) was performed. Patient's demographics, clinical and laboratory findings were recorded via structured data collection form. Patients were categorized into dengue fever (DF) and dengue hemorrhagic fever (DHF). Appropriate statistical methods were used to compare these two groups in order to determine difference in clinico-laboratory characteristics and to identify independent risk factors of DHF.

Results: A total 667 dengue patients (30.69 ± 16.13 years; Male: 56.7 %) were reviewed. Typical manifestations of dengue like fever, myalgia, arthralgia, headache, vomiting, abdominal pain and skin rash were observed in more than 40 % patients. DHF was observed in 79 (11.8 %) cases. Skin rash, dehydration, shortness of breath, pleural effusion and thick gall bladder were more significantly (P < 0.05) associated with DHF than DF. Multivariate regression analysis demonstrated presence of age > 40 years (OR: 4.1, P < 0.001), secondary infection (OR: 2.7, P = 0.042), diabetes mellitus (OR: 2.8, P = 0.041), lethargy (OR: 3.1, P = 0.005), thick gallbladder (OR: 1.7, P = 0.029) and delayed hospitalization (OR: 2.3, P = 0.037) as independent predictors of DHF. Overall mortality was 1.2 % in our study.

Conclusions: Current study demonstrated that DF and DHF present significantly different clinico-laboratory profile. Older age, secondary infection, diabetes mellitus, lethargy, thick gallbladder and delayed hospitalization significantly predict DHF. Prior knowledge of expected clinical profile and predictors of DHF/DSS development would provide information to identify individuals at higher risk and on the other hand, give sufficient time to clinicians for reducing dengue related morbidity and mortality.

No MeSH data available.


Related in: MedlinePlus